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Key Study: “The Sweaty T-shirt Study” (Wedekind et al. 1995)

Travis Dixon November 19, 2019 Biological Psychology , Human Relationships , Key Studies

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Updated June, 2020

Can we smell someone’s genes? Not their trousers, but their genetics. The Swiss Biological Researcher Claus Wedekind and his colleagues conducted a famous study to see if our preference for smells is linked with our genetics. In other words, they wanted to see if we prefer the smell of someone who has genes that would be a good match with ours. 

Background Information

Studies have shown that even fish have preferences for MHC genes (Olsen et al. 1998).

MHC Genes are a large group of genes responsible for the development of the immune system. Different genes protect against different infections, so the healthiest individuals would have the largest range of MHC genes because this would mean their immune systems would be able to fight a wider range of diseases. This makes them healthier and more likely to survive and pass on genes (which is the purpose of life on this planet). It therefore makes sense then that we would want to procreate with someone who has very dissimilar (i.e. different) MHC Genes to us, so our offspring are well-protected against an array of diseases.

Yamazaki et al. (1976) showed this to be the case for male mice, who show such a preference for females with different MHC genes. Studies on fish have also shown that they show preferences for waters depending on MHC scents (Olsen et al. 1998). So while these animal studies show MHC genes can influence behaviour, can we say the same for humans?

• Key Study: Evolution of Gender Differences in Sexual Behaviour (Clark and Hatfield, 1989)
• What is a pheromone?
• Key Study: Buss’ cross-cultural study on mate preference (1989)

The Sweaty T-Shirt Study Methods

Wedekind’s study is often known as the “sweaty t-shirt study”. The researcher (Wedekind) assembled volunteers, 49 women and 44 men selected for their variety of MHC gene types.

The women were asked to record whether or not they were taking oral contraceptives (e.g. the pill) as this would affect the results because it affects levels of hormones.

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The men were given a clean cotton t-shirt and were asked to keep it in an open plastic bag when not wearing it. They wore the same t-shirt for 2 nights when they were sleeping. They were also asked to abstain from spicy foods and other activities that may affect the smell of the T-shirts (e.g. smoking or sleeping with someone else in their bed). They were also given odour free deodorants. They kept the shirts in open plastic bags when they weren’t wearing them.

Starting the day after the men wore the shirts, they were then put into identical boxes equipped with a smelling hole and invited the women volunteers to come in, one at a time, and sniff the boxes. Their task was to sample the odor of six boxes and to rate each t-shirt on a scale of 1-10 in terms of its intensity, pleasantness, and sexiness. There were three t-shirts that were similar MHC Genes, and three that were from men with dissimilar MHC Genes. Where possible, the timings of the smells were times for the second week of the women’s menstrual cycle.

A Note On Pheromones:  If you are using this study for your IB Psychology exams, be careful with using it for a demonstration of how pheromones can influence behaviour. While the effect on smell preference could be a result of pheromones, personally I prefer using studies focusing on putative human pheromones, like androstadienone or androstenone. In Wedekind et al.’s original paper, pheromones aren’t mentioned at all. 

Results and Conclusions

Overall, the women who were not on the pill preferred the scents of T-shirts worn by men whose MHC genes were different from their own. Another interesting finding was that the “….odours of MHC-dissimilar men remind the test women more often of their own actual or former mates than do the odours of MHC-similar men.” This suggests that it’s not just in the lab that the women preferred these smells but they might be reflective of what happens in the real world, too.

The researchers concluded that MHC genes and their associated smells influence mate preference.

Critical Thinking Considerations:

• How and why have we evolved to find some people’s smells more attractive than others?
• How does this study show the influence of genes on behaviour?
• Could this study be used as evidence for the existence of human pheromones? Why?
• What are the limitations of this

References Claus Wedekind; Thomas Seebeck; Florence Bettens; Alexander J. Paepke. MHC-Dependent Mate Preferences in: Biological Sciences, Vol. 260, No. 1359. (Jun. 22, 1995), pp. 245-249. ( Link )

OlsÉn KH, Grahn M, Lohm J, Langefors Å. MHC and kin discrimination in juvenile Arctic charr, Salvelinus alpinus (L.).  Anim Behav . 1998;56(2):319-327. doi:10.1006/anbe.1998.0837 ( Link )

Travis Dixon is an IB Psychology teacher, author, workshop leader, examiner and IA moderator.

Case Study: How to Turn an Event Poster into a T-shirt That Sells

Professional designer shares secrets on how to design event t-shirts with a color count and make the t-shirt look as good as the poster.

Raven Wilson

Read more posts by this author.

Live events are back.

It's no secret live events suffered last year. Especially community festivals featuring food as a major draw—AKA half of why people attend Chomp & Stomp. The bluegrass festival with a chili contest has been the sole fundraiser for the Cabbagetown Initiative Community Development Corporation, the non-profit responsible for public community spaces in the Cabbagetown neighborhood of Atlanta.

Another big revenue driver for the festival was the 5k walk/run. Something else snuffed out thanks to a once-in-a-lifetime-global pandemic.

All aspects of the event—contest judges, volunteers, runners, attendees—require shirts. This year, the event organizers went big to make up for lost time.

With a lot at stake, organizers chose UberPrints to print large bulk quantities of customized shirts. With 405 shirts needed for all events, organizers depended on UberPrints to be fast on the turnaround times and be top-notch quality so sales can make up for a lost year.

Events like no other call for designs like no other

The organizers partnered with graphic designer Gary O-Bryan for the event design, initially to be put on posters to advertise the event around Atlanta.

In a non-pandemic year, Chomp & Stomp brings in over 10,000 people, and that’s not counting the 5K runners. A tiny neighborhood non-profit can pull off a massive event but they rely on many hands to complete the work.

Each year’s event is funded by the previous year’s success—meaning 2021 was working on a tight budget. Gary, along with event planners, worked with UberPrints to keep shirt costs low by modifying the original design.

Making this shift eliminated 5 colors on the shirt, saving over $420 on the order overall.

Already making excellent choices, Gary made another brilliant design move: He used the t-shirt color as a third color element in the design.

Tips from Designer Gary O’Bryan on designing to reduce color costs

1. spend more time researching than you do designing.

Writers say their worst fear is a blank page. The same is the case for designing custom t-shirts: You might know what you want it to look like, but you don’t know how to make it. By collecting inspiration images from t-shirts you like (or already have), you’ll start further in the design process by knowing what you like and where you want to go.

Gary’s advice is to doodle, sketch, and look at what other t-shirts you like to get inspiration. Then when you begin designing, you already know what you want. The more time you spend thinking about what you want the final shirt to look like, the easier it will be to make it happen. Especially with tools like our Design Studio with pre-loaded clip art and design templates, you have many tools at your disposal to create and edit the design you need for your next t-shirt.

Start collecting your t-shirt inspiration on our Pinterest.

2. Pick a palette

Start with a color palette to work with. If the poster has three main colors, start there.

Before designing, Gary found his palette combo: Green, orange, and cream. Personally, Gary just likes dark colors. He delivered brown, dark blue, and black colors with his final design as options, but the Chomp & Stomp team decided on his original pick: Olive green. If you need to keep your color count low for cost, pick one color for the majority of the shirt design, a second color for the accent, and use your t-shirt color as your third. Once you know how many colors you want in your design, next you need to select your elements.

3. Know your main elements

Once you have your colors in place, take the main two to three elements from your poster and use those as the main focus for the shirt. Slowly add other elements to the shirt as they fit.

Before he jumped into the design, Gary decided the banjo and the chili pot lid were going to be his main two elements in the design. As he developed the concept around those two fused elements, if they cluttered the design or competed with the main elements, they had to go.

4. Edit out fine details

Here’s a secret from our screen printers: Fine lines are NOT your friend.

When you go to edit your design, try to remove any fine lines or too small details. Removing fine details will also create more white space for your design to stand out and be bold.

In the final iterations, Gary continued to remove elements from the initial design. “Some little design elements aren’t planned. When I look at a design so long, some things just start to bother me—so I get rid of them.” This is how the final shirt design looks so clean with plenty of white space.

5. Change your perspective

Once you’re comfortable with your design, take a step back.

During his editing process, Gary knew he needed to visualize the design differently. So using his Photoshop skills, he created a mockup of how the design would look on a t-shirt. “I like putting my designs on mockups to change my perspective. Then I see things that need to be changed I wouldn’t have seen otherwise,” Gary said. He also relies on his fellow designer friends for outside feedback on his designs (even though he doesn’t always go with their advice).

If you’re logged in to your UberPrints Account , you can save your design and come back later. Since the Design Studio creates designs directly on the shirt, your mock up is automatically created.

How’d it go?

Let’s get down to the meat and potatoes: Did the shirt SELL?

For attendees, t-shirts are more than repping a cool event or shirt. Participants look forward to collecting shirts from year to year.

"Shirts are always an iconic part of the festival. People collect them and seek them out, even if they're unable to make it to the festival," 2021 Chomp & Stomp Chair Lauren Appel said. " Last year, UberPrints helped us make money when there was not a festival to be had."

This year was important for event planners to prove a safe, successful fundraiser was possible again. And it worked, the event was a total success. Chili was a hit once again, hundreds shopped the pop-up markets, and over 10,000 people came out to listen to the bluegrass in the renowned Atlanta neighborhood. T-shirt sales made 5% of funds raised, selling over 150 shirts.

Not only is designing with a color count in mind helpful on the front-end, but it reaps rewards when it comes to increasing your profit margins during sales.

Your next live event t-shirt is gonna be great

Live events may have restrictions or virtual options not offered previously. One way event planners can ensure it will be a success is t-shirts that make it real. You’ll boost sales and give your attendees that warm-and-fuzzy feeling when they get a quality shirt they get to show off in their wardrobe.

Snag the same shirt Chomp & Stomp chose for its event this year.

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Levi’s Case Study: Transforming the Apparel Industry

• Written by 440 Industries
• Case Study , Levi's
• June 16, 2023

Picture this: a legendary brand, synonymous with denim and an integral part of fashion history . Yes, we’re talking about Levi Strauss & Co., the subject of our fascinating levi’s case study.

But even legends need to adapt in order to thrive in today’s fast-paced world. In this comprehensive levi’s case study, you’ll discover how the iconic apparel company has successfully reinvented itself through strategic leadership changes, innovative product development, and savvy marketing campaigns.

Dive into the transformation of their women’s denim line and learn about groundbreaking technologies such as Deepika’s Lookbook – an augmented reality wardrobe application that is revolutionizing customer engagement. Explore how Levi’s diversified its offerings beyond the iconic 501 jeans model by introducing new fits and advertising efforts for non-501 models.

We’ll also delve into global expansion strategies including production facilities around the world and a focus on menswear with Dockers catering to casual wear market demands. And finally, witness how investing in employee growth and talent development contributes significantly to Levi’s ongoing success story.

Ready for a captivating journey through one of fashion’s most storied brands? Let us begin!

Table of Contents:

Levi’s new strategy and leadership: a fresh approach to success, cost-cutting measures leading to innovation investments, successes from eureka innovation lab, targeted promotions for increased sales conversions, social media campaigns with human touchpoints, virtual try-on feature improving customer engagement, innovative technology integration into fashion retail, advertising efforts for non-501 jeans models, global expansion and production facilities: a world of opportunities, investing in employee growth and talent development, what is levi’s main message, what is the strategy of levi’s brand, what was the problem of levi strauss & company.

Let’s take a trip back in time, shall we?

In the late 1990s, Levi Strauss , once a market leader in the apparel industry, faced a decline due to its own success.

But then, a new CEO stepped in with an ambitious plan.

• Developing a new strategy for growth and innovation
• Allocating funds for investment in Levi’s Eureka Innovation Lab
• Focusing on employee growth and development
• Replacing nine out of eleven direct reports – talk about shaking things up.

The importance of leadership change cannot be overstated here. This shift not only revitalized the company but also positioned it as an innovative force within the fashion and lifestyle space today.

So, what exactly did Levi’s do to turn things around? Well, for starters, they recognized the need for change and took bold steps to implement it. Levi’s invested in their Eureka Innovation Lab, a move that enabled them to craft unique offerings and technologies that set them apart from other firms.

But beyond that, they also recognized the importance of their people. Levi’s also focused on their employees, recognizing that they were the key to the company’s success. By providing opportunities for growth and development, they were able to build a strong, motivated team that was committed to the company’s vision.

And of course, the leadership change was a crucial factor. By bringing in new blood and fresh ideas, Levi’s was able to break free from the old ways of doing things and chart a new course for the future.

Levi’s has managed to regain its position as a major player in the apparel industry, competing with top brands such as Calvin Klein, due to their willingness to embrace change and take risks. And it’s all thanks to their willingness to embrace change and take risks.

So, what can we learn from Levi’s case study? Simply put, that innovation and leadership are key to success in any industry. By staying ahead of the curve and taking bold steps to implement change, companies can position themselves as leaders and stay relevant in an ever-changing market.

And that’s a lesson that we can all take to heart.

Key Takeaway: 

Levi’s faced a decline in the late 1990s, but their new CEO implemented a fresh approach to success by investing in innovation, focusing on employee growth and development, and replacing direct reports. Their willingness to embrace change and take risks has positioned them as leaders in the apparel industry once again, teaching us that innovation and leadership are key to success.

Revamping Women’s Denim Line: A Game-Changer for Levi’s

Levi’s realized they needed to make a change when their market share in women’s clothing was suffering. To turn things around, the company adopted a more data-driven and financially disciplined approach, which allowed them to invest in their Eureka Innovation Lab.

So, what happened next?

The cost-cutting measures implemented by Levi’s were crucial in driving cash flow improvements and freeing up funds for innovation investments. This financial discipline enabled the brand to focus on creating groundbreaking products that would resonate with female consumers.

The investment paid off as the Eureka Innovation Lab played an essential role in revamping Levi’s women’s denim line. New styles were introduced catering specifically to different body types and preferences of female customers. A shift towards using sustainable materials made the brand more eco-friendly. Innovative marketing campaigns helped create buzz around new product launches. And guess what? It worked. The revamped women’s denim line gained traction among consumers, and Levi’s saw a significant increase in sales.

Now that’s what we call a denim revolution.

Discover how Levi’s revolutionized the fashion industry with their innovative denim line by reading this insightful article from 440 Industries.  Check out this insightful article from 440 Industries.

In conclusion, revamping the women’s denim line was a game-changer for Levi’s, proving that with strategic cost-cutting measures and innovative investments, even an iconic brand can reinvent itself successfully.

Multi-Channel Marketing Campaign Strategies: Boost Your Sales and Engagement

To make the most of your marketing efforts, you need to embrace multi-channel strategies. Why? Because it allows you to reach a wider audience and increase sales conversions.

Step #1: Identify your target audience and their preferences.

Step #2: Create tailored promotions that resonate with them.

Step #3: Distribute these promotions across multiple channels like email, social media, and even SMS messaging.

Social media is a goldmine for engaging customers on a personal level. To create successful campaigns:

• Add human touchpoints by showcasing real people using your products or sharing testimonials from satisfied customers.
• Promote user-generated content (UGC) – encourage followers to share their experiences with your brand using specific hashtags or mentions.
• Incorporate influencers into your strategy – partner up with relevant personalities who can authentically promote your products while reaching new audiences.

To maximize the effectiveness of your marketing campaign, ensure that you are consistent and personalize each channel. By combining targeted promotions with engaging social media content, you’ll be on your way to boosting sales conversions and building lasting relationships with your customers.

Embrace multi-channel strategies to make the most of your marketing efforts. It allows you to reach a wider audience and increase sales conversions. Target your audience and create tailored promotions that resonate with them. Distribute these promotions across multiple channels like email, social media, and even SMS messaging. Social media is a goldmine for engaging customers on a personal level. Add human touchpoints, promote user-generated content (UGC), and incorporate influencers into your strategy. Staying regular and tailored to the customer is essential for a successful multi-channel marketing strategy. Combine targeted promotions with engaging social media content to boost sales conversions and build lasting relationships with your customers.

To boost sales conversions and engage with customers on a personal level, Levi’s recommends embracing multi-channel marketing strategies. This involves targeting your audience, creating tailored promotions that resonate with them, distributing these promotions across multiple channels like email and social media, adding human touchpoints to social media campaigns by showcasing real people using your products or sharing testimonials from satisfied customers, promoting user-generated content (UGC), and incorporating influencers into your strategy. Consistency and personalization are key to success in this approach.

Deepika’s Lookbook – Augmented Reality Wardrobe Application

With Deepika’s Lookbook, you no longer have to wonder if that trendy pair of jeans will suit your style or not – simply try them on virtually using the augmented reality wardrobe application. That’s where Deepika’s Lookbook comes in. This innovative augmented reality wardrobe application was proposed by a team of creative students to solve this very dilemma.

The Concept: By using advanced technology, the app allows users to virtually try on different outfits from their favorite brand collections before making a purchase decision. The aim is to make the shopping process more interactive and tailored for each customer, thus boosting their overall experience.

No more guessing games. With the virtual try-on feature, customers can have an immersive experience where they can see how various garments would fit them in real-time without ever stepping foot inside a physical store or dressing room.

Incorporating augmented reality (AR) into fashion retail is no small feat, but its potential benefits are immense. Beyond just improving customer satisfaction rates, AR integration has been shown to boost sales and revenue for brands that adopt this cutting-edge technology.

So, are you ready to revolutionize your shopping experience with Deepika’s Lookbook? Stay tuned as we keep you updated on the latest developments in augmented reality wardrobe applications.

Diversifying Product Offerings Beyond the Iconic 501 Jeans Model

Alright, let’s dive into the denim world.

Levi Strauss realized that relying solely on their iconic 501 jeans model wasn’t enough to keep up with the ever-changing fashion trends and customer preferences.

The solution? Introducing Red Tab fits.

However, the non-501 options initially underperformed in the marketplace due to consumer perception being strongly tied to Levi Strauss’ classic 501 jeans model.

Advertising must be leveraged to ensure that changes in product offerings are communicated effectively to the target audience, otherwise they may fail to gain traction.

Levi Strauss’ advertising campaigns for their non-501 jeans models were successful in shifting consumer perception and increasing sales. By highlighting the diversity and chicness of their novel items, they managed to gain the attention of those who are conscious about fashion and be a prominent player in the clothing industry with companies like Calvin Klein.

So go ahead, explore those new denim styles. Levi Strauss has proven that taking risks and diversifying your product offerings can pay off in a big way.

Levi Strauss, the iconic apparel industry brand, realized that focusing solely on menswear wasn’t enough to maintain their status as a market leader. They conducted a case study and found a solution – expanding globally and diversifying their product offerings.

This global expansion strategy not only allowed them to cater better to local markets but also helped increase efficiency by reducing shipping times for customers worldwide.

So, what can we learn from Levi’s case study on global expansion?

• Don’t be scared to branch out and provide services that appeal to diverse groups – it could possibly create new possibilities for development.
• Think big. Expanding globally can help you reach a wider audience and increase brand awareness in untapped markets.
• Investing in local production and customer service capabilities can both increase efficiency and provide a superior customer experience.

In short, don’t hesitate to explore new horizons – who knows where they might lead? If Levi Strauss, a brand that has been around for over 150 years, can do it, so can you.

Looking at the apparel industry, Levi’s has been a market leader for decades, but they faced stiff competition from other brands like Calvin Klein. By diversifying their product offerings and expanding globally, they were able to stay ahead of the game and maintain their position as a market leader.

Let’s talk about a crucial aspect of Levi Strauss’ turnaround strategy: employee growth and talent development.

Levi Strauss realized that the skills and dedication of their workforce are directly tied to their success. To address this, they created flexible benefits packages designed to reduce costs associated with workforce management.

These tailor-made programs allow employees to choose from various perks such as health insurance options, retirement plans, and even gym memberships.

• Flexible Benefits Packages for Employees
• Talent Development Contributing to Company Success

This focus on employee growth has been instrumental in repositioning Levi Strauss as a market leader within the apparel industry today.

To achieve this goal, Levi Strauss has implemented several initiatives such as training programs, mentorship opportunities, and career advancement paths tailored to individual needs. These initiatives pave the way for further skill enhancement among its employees.

Moreover, providing resources such as mental health support, financial planning assistance, and work-life balance tools empowers them not only professionally but also personally.

So, what’s the takeaway here?

Investing in your employee’s growth and development can lead to a more engaged, skilled workforce that ultimately drives company success. In Levi Strauss’ case, this approach has played a significant role in their impressive turnaround story.

FAQs in Relation to Levi’s Case Study

Levi’s primary message revolves around its commitment to creating high-quality, durable denim products that embody timeless style and sustainability. They focus on promoting a sense of individuality and self-expression through their iconic designs while maintaining responsible business practices. Learn more about Levi’s mission here .

The strategy of Levi’s brand is its continuous evolution as an iconic fashion label known for quality denim products and sustainable practices while adapting to changing market demands and consumer preferences. Through innovation, diversification, global expansion, and talent development strategies, they aim at remaining relevant in today’s competitive landscape. Explore more about their growth strategy here .

Levi Strauss & Company faced challenges in the past, including declining market share, competition from fast- fashion brands , and a lack of focus on women’s clothing. To address these issues, they revamped their strategy by investing in innovation, diversifying product offerings, expanding globally, and developing talent. Learn more about Levi’s turnaround here.

In conclusion, Levi’s successful revamp strategy involved new leadership, investment in innovation, addressing the women’s clothing market share, multi-channel marketing efforts, diversifying product offerings, and expanding operations globally. Their augmented reality wardrobe application, Deepika’s Lookbook, allowed customers to virtually try on clothes, while their talent development programs contributed to the business’s success.

Levi’s case study is a testament to how businesses can adapt and thrive by implementing strategic changes that resonate with their target audience. If you’re looking for expert guidance in fashion industry consulting or brand management strategies for your business, contact 440 Industries today!

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Case Study: How I Made $19,089 Selling Ugly T-Shirts On The Internet

I’ll just login to my Teespring admin area to quickly show you how much I’ve made so far selling t-shirts on the Internet using the Teespring platform.

Hey, I’m Verena Ho.

Let me introduce myself.

I’m a full time web designer .

That is my “day job”.

Now, I want to share with you my “part time” job, which is a little more interesting to talk about.

It’s selling t-shirts online using Teespring.

It makes me quite a bit of money as you’ve seen on the video above.

Before I show you the good stuff, let me share with you how it all got started.

Here is how it all started…

Back then, I used to run a Facebook fan page during my free time.

It was an inspirational quotes page: I posted images with inspirational quotes to my fan page during my free time.

I just did for fun…

But as you may know, hobbies like that don’t last long and I abandoned it after a few months.

My brother saw what I did and wanted a fan page in the military niche.

He’s always been a fan of military weapons: guns, aircraft, tanks, attack helicopters etc.

He wanted to start a Facebook page built around his passion.

I created a fan page for him and showed him how to post cool military weapons images to his page.

He’d find the images he wanted on Pinterest.com and upload them to his FaceBook page.

Sometimes, he’d post military quotes and memes if he stumbled ones he particularly liked.

He invited his buddies to show off his new “project”.

Over time, his page acquired a small number of likes, but nothing significant…

One day…

One day, I notice one of the military quotes on his page invited an exceptionally high number of likes and shares vs the rest of the posts.

It was obvious that viewers were drawn to it and I figured the message should resonate with Veterans too…

Why not make a t-shirt with the quote and sell it to Veterans?

I opened a free account with Teespring (a t-shirt fulfillment company), typed in the quote from my brother’s fan page, added in a small eagle icon,

…and launched a t-shirt campaign called “I AM A VETERAN”

This is what my first “ugly” t-shirt looked like

I posted the shirt image on my brother’s fan page and started a $60 daily budget ad campaign with Facebook.

I went to bed… 24 hours later, I had 14 sales.

The following day, I sold another 14 tees.

“This looks promising,” I thought to myself…

I increased my Facebook ad’s daily budget to $120.

1 day later, I sold another 46 tees.

This was making me a lot more money than I was spending on my ads.

I increased my daily ad budget every other day and let the ads run through the week.

My campaign ended, here are the stats

Another 7 days passed, I ended my 10-day campaign, here were my stats:

– Shirts sold: 349 – Revenue: $4388.47 – Ad spent: $2649.30

– Net profit: $1739.17

Here is the money Teespring sent me:

I netted $1739.17 in 10 days ($4,388.47 gross return less $2,649.30 in ad expenses).

I spent 30 minutes a day checking stats and making sure I was in the green.

That’s all I did.

Not bad for a side project.

Since I used my brother’s fan page for the campaign, I sent him $739.17 for allowing me to use his ‘real estate’.

The rest was mine 😉

He’s my brother… no problem.

What’s more important is…

I’ve found a proven model to sell t-shirts on the Internet

I’ve discovered a proven model to reach a very targeted audience (military veterans) using Facebook ads and sold t-shirts to them.

Since then, I’ve replicated the steps I took on my first campaign (and enhanced it A LOT), and now sell t-shirts in a variety of niches.

This isn’t rocket science; with a little guidance, anyone can definitely do this.

Best of all, you can do this part time and gradually grow yourself a t-shirt empire.

You only need 2 things to succeed:

Once you’ve decided on a niche, you only need two things to run a profitable t-shirt business.

1) A t-shirt design that will resonate with your target audience.

2) A campaign that reaches out to your targeted audience using Facebook ads.

And that’s it.

First, here is how I roll out t-shirt designs that almost always resonate with my audience.

I login to my Pinterest.com account, then punch in “[name of niche] quotes” on the search bar.

“[niche]” being the niche I’m targeting.

So it’s “veteran quotes” if I am searching the veteran niche.

I will spend some time studying the quotes in the search results, then pick the quote that I feel would be the best message that will resonate with my target audience.

As long as the message on the t-shirt resonates with my target audience, they will identify with the message.

They will tell themselves: “This is me!”

And they will buy the shirt.

It becomes an instant must-have.

Next, I login to my Teespring account (free to sign up) and start a t-shirt campaign.

I type the quote on the shirt, just like I did with the Veteran shirt I showed you.

It can be a simple text-based design with no graphics – you don’t need to be a designer to do this.

I’m not saying that you should only sell text-based designs.

What I’m saying is that the crucial factor to determine sales is the message on the tee, not the graphic.

If you have a budget to hire designers to create your shirt, go ahead; however, beautiful graphics are not the decisive factor.

Most of my “ugly” text-based t-shirts outsell a lot of other, graphically sophisticated designs used by my competitors.

My next step is to start running some traffic to a fan page using Facebook ads…

Here is my entire system

I’ve just put together something very special for you.

You’ve read my stories about how I built a profitable t-shirt business online.

You’ve seen my case study and you’re interested to know more.

The thing is, you need to have a complete system in place to build a sustainable t-shirt business like the one I have.

You’re at the right place now.

I’m going to show you my entire system… how to put my method to work for you.

In my private membership site, I show how I run my business THE RIGHT WAY.

I explain what’s involved from “A to Z.”

I give you a detailed step-by-step, “do-this”, “do-that” set of instructions.

I break it down to simple, doable steps so that even new t-shirt marketers can do it.

I put down everything in easy to follow steps, documented it with screen shots, and present to you a complete system on how to rake in big selling t-shirts on the Internet.

This is what I have for you…

Niche Market Selection:

– No idea of a profitable niche market? No worries, I show you the perfect niches that sell a lot of t-shirts.

– There are certain golden niche selection rules to follow; most newbies fail this stage and get nowhere.

– I show you the winning niche selection formula rich t-shirt marketers use.

T-shirt Design Ideas:

– I show you 5 powerful design inspiration sources (Pinterest is just one of them) so that you’ll never run out of design ideas.

– Not only that, I reveal what to look for when deciding which design will work and which won’t…before you spend any money on advertising.

Outsource Your Design:

Mind you, beautiful graphics are not the decisive factor that makes shirts sell. It’s the message on the shirt, the text we put on it.

Still, graphics can be used to enhance the message.

I know that most of you are not designers. No idea how to use Photoshop? Hate to make your own design? No problem. You don’t need to be a designer to do it.

I show you how to outsource CHEAPLY. I show you where to hire a t-shirt designer at less than $10 per design. Rich t-shirt marketers outsource most of their designs here.

Pricing and Sales Goal:

– I show you the best price and sales goal strategies for your shirts to maximize profits with each campaign you run on Teespring.

Copy Writing:

– I reveal the time tested ad copy I put on my Teespring pages.

– I show you what ad copy outsells others by 300%. Literally copy my script, change a few words to fit your campaign, and reap the profits.

– Hint: When you’re selling t-shirts, don’t over-pitch. Instead, focus on building trust with your copy. Anything else is just superfluous!

Finding the Perfect Audience:

Targeting your audience is the most important thing you must do to be successful.

– Most newbies completely fail at targeting. Don’t let this happen to you. I reveal the only sure-fire method to find your perfect audience on Facebook.

– I show you the best tool I use (it’s free) so that you can locate laser targeted audiences for Facebook ad and generate revenue at will.

– This is perhaps the most important thing you must do to be successful.

Facebook Ads Creation:

– I show you my ad creation process to cut your learning curve by almost 90%.

– You’ll replicate the exact steps I use to create high performance ads.

Facebook Ads Optimization:

– I show you the 2-step process I use to identify winners and losers within 24 hours of running any ad campaign.

– I show you how I determine which ad sets are converting and which to kill…all in 24 hours.

Facebook Ads Scaling:

– You’ll pick up my brain for how and when to scale your campaigns… I show you the essential metrics in your ad report that you should analyze before making your decisions.

– I show you the RIGHT WAY to scale your ads. All Positive ROI from there…

These are real secrets… and I want to keep this stuff away from the public.

My coaching students paid $499 to access these lessons…

If you join today, here’s what I’m going to do:

I’ll offer you a 90%+ discount

You will only pay a small fee of $49 to access the lessons.

Just a one-time payment of $49. No monthly fees, no renewal… nothing.

You will receive a username and password when you go through the sign up process.

You can use that username and password to access the secure exclusive members’ area on my site.

Now, if you have a little more to invest on your education, I have something even more exciting lined up for you.

This information will catapult your t-shirt marketing into the stratosphere…

Here is the deal…

If you pay a little extra more than $49…

If you pay a little extra, you’ll be able to access the lessons + my t-shirt niche reports.

In the reports, you’ll get access to the exact profitable Teespring campaigns for huge, no brainer, copy and paste profits.

I’ll show you the exact niche markets and the exact Teespring campaigns that rake in huge profits.

I lay it all out in each of the niche reports that I’ll send you, one niche market per report.

In each niche report, I’ve documented 7-10 highly profitable campaigns on Teespring with screenshots so that you can see exactly what works, what sells in which markets, right down to the actual sales numbers, prices and what shirt styles to sell.

Here is a sneak peek at the sales numbers that you can expect to see in the reports (the full campaign details with screenshots are revealed in the reports).

838 were sold:

855 were sold:

877 were sold:

1029 were sold:

1455 were sold:

I don’t stop there; in the reports…

I’ll also show you how to locate the perfect audience on Facebook to sell your shirts to in any specific niche market.

To recap, in each niche report you will see:

1. Anywhere from 7-10 highly profitable campaigns on Teespring.

2. The exact steps needed to locate your best converting, t-shirt hungry audience using Facebook ads.

Others waste time creating campaigns out of thin air only to lose money.

You see what works, know exactly who buys, and run campaigns when you know exactly what works.

This is as close to copy & paste profits as you can get: copy the campaigns, slip in your own niche-specific words, and you’re good to go.

So if you’re serious about building a solid t-shirt business, pick one of the options below.

These are just one-time payment. No monthly fees, no renewal…nothing.

Ready to get started?

Choose your package below:

Ugly Shirt Fortune Course Only

USF Course + 3 Niche Reports

USF Course + 9 Niche Reports

You’re literally getting an insane offer!

I’m handing you the niche reports at a crazy bargain!

Let me show you the math:

Let’s say that you select the “Course + 9 Niche Reports” Package.

With that, you’re really paying less than $6.00 for each niche report.

Depending on the niches, I reveal 7-10 profitable campaigns in each report. That’s an insane number of campaigns for you to copy.

Let’s take 9 campaigns as an average.

You are investing $0.60 to access each campaign.

Each of these campaigns netted their sellers up to $12,000-$15,000 (yes, net profit, which means after deducting the Facebook ad spend).

Invest $0.60 to get access to the exact same, solidly profitable Teespring campaigns for huge, no-brainer, copy-paste profits straight to your pocket.

If this is not a crazy, insane bargain for you, I don’t know what is.

This could be the best investment you’ve ever made.

30 day money back guarantee

Try the course for 30 days, take the actions needed to map, create and implement what you learn from my training.

If you don’t see results, drop me a line ([email protected]) anytime within 30 days of purchase, send me proof of work you have done, and I’ll send you a full refund.

When you invest in this course, I genuinely want you to see results. if you really put in the effort but can’t get results, then I don’t deserve to keep your money.

I limited membership to just 200 lucky people.

I could easily charge a minimum $499 for this membership.

It’s more than worth the price.

In fact, memberships that produce money-makers raking in $1000’s and $1000’s in profits usually charge twice that annually.

These are real secrets I’m sharing with you… and I want to keep this stuff away from everyone out there.

So I set a limit.

Only 200 memberships are available.

When I first launched, I ended up selling out in under 24 hours. And that was with zero external promotion

For the past few months I’ve kept the doors closed, only opening them twice to accept new members, and that was for only a brief moment before slamming the doors shut again.

I’m accepting new members right now, but only for a very brief time.

If you want in, the time to pull the trigger is now. Choose your options below.

When you’ve paid, on the next page you’ll see the instruction to access your materials.

The membership is strictly limited to 200 new members and will not be opening up again anytime soon.

You have nothing to lose, and everything to gain. If you don’t see results, send me proof of work you have done, you get your money back.

Write a Comment

52 comments.

Finding a great idea, validating it, and expanding on it is no simple task. It’s even harder in the heavily saturated tshirt market. However, Verena’s course makes it easy. She delivers, in great deal, every step of developing a quality T-Shirt business. Being a newer entrepreneur I knew I needed to see the process up close. I felt a great deal of stress trying to figure it out on my own. For me it was a no brainier- I needed her content.

Some highlights include: -Discovering quality niche’s that can deliver profits multiple times. -How to develop a strong relationship with that target audience. -How to scale your business and function as a company would- making executive decisions that push you to the next level.

It’s worth your time to at least look at the course, especially at such a reasonable price point.

As an online ghost writer I’ve always looked for alternative ways to supplement my income after coming purchase Verena’s I know for a fact that I’ll be able to do this full time and have more free time to spend with my daughter. Thanks so much beloved. I swear the price you’re charging people isn’t nada for the price of dinner for me and my kid in NYC lmao you’ll be a dam fool to bypass this.

Verena’s Ugly T-shirt course has helped me discover a new way of making a side income. Her methods are outlined in great detail and can be implemented by novices and pros alike! I’m about to launch my first t-shirt campaign in a few days, and I feel confident that by using her methods, I will be successful. If you’re looking for a fun new business venture or an additional revenue stream, I highly recommend purchasing her course!

Verena’s Ugly T-shirt course has helped me in so many ways in making a side income. Her Teachings are very easy to follow step by step. When I first saw Verena’s course I was mesmerized buy the fact that it was actually possible to make a side income selling print on demand shirts I launch my first t-shirt campaign a few days after I finished the course and made a sale that same week! I feel confident enough that by following step by step on how she does it, you will be well on your way to your first sale too. If your on the edge to buy or not to buy, BUY because I assure you, you will not regret it. To much valuable information to pass up.

Making money online is hard!

It takes work, a lots of hard work! And the first thing that you have to do is to find “ONE” strategy and stick to it..

Verena is the real deal!

I have been looking for a step by step training to help me kick start a real online business – this was it!! Excellent value for the price – don’t hesitate – grab it now while you still can!! Her training is worth so much more in value, and I definitely recommend this to anyone who wants to get into making money online business and needs the steps to follow in an easy to follow step by step way that you can use over and over again.

I have purchased many other programs in the past and this one blows all the others away.

Making good money from home is something everyone can do… but you need to know the basic rules of game.

I met Verena a few years ago, her products are top notch quality products without the high price tag. This course is pure Gold, a very well structured step by step, newbie friendly and easy to implement course even for the technically challenged like me. The values she’s offering is insane, don’t overthink it, grab this offer quick before she comes to her senses and increase the price.

Great program. Lots of excellent ideas in easy bite size pieces. Lots of links to free resources.

Verena has a conversational style of writing. It feels like she is right there helping you succeed.

Just went through The Ugly T-shorts course and I am totally impressed. I have been online for over 6 years and have various income streams and have been through tons of courses. Verena has a way of simplifying the steps and making sure she doesn’t miss anything.

I was totally impressed with her knowledge of Facebook ads. Not only did I learn to sell t-shorts online but I learned some cool little tips to sell other products that I offer to different niches!

Definitely worth the money and time to go through this course!

Verena’s “Ugly T-shirt Fortune” course has given me the true confidence I have been praying for. My struggle to find a way to make serious money online has been a long rough road for years. I needed someone to provide me with a clear set direction, step by step instructions, and a proven path to keep moving focused forwards with. Most of all, I needed the process to feel totally 100% certain to me without any questions or doubts. (…and that’s asking for a lot in this world of internet marketeers with daily “new shiny objects” and false promises.) I can honestly say with all my heart and integrity that this course is the answer I have been waiting and wishing for. After reading all the instructions and most helpful step by step screenshots I knew for a fact that this was something I could totally do and achieve success with equally. Even though I am a newbie for both t-shirt selling and facebook ad’s, the confidence I feel within me now to take full time action with this process is an exciting, most encouraging reality. I also know that the more I do each step along the way the more I will Learn as I Earn. The trust I have knowing support is only an email away completes the reinforcement I need believe in myself and the most positive results I know I will attain. Thank you with my greatest energy, blessings and gratitude to you, Verena. I am honored to be one of your long term students.

Firstly, I do not know Verena at all. Not at all. Someone recommend me to her website – growthtext.com.

After reading of one of her posts on how a man from Australia made money online through setting an online cleaning business. And become successful at it. I like the business idea and thought of implementing in my own country.

But I am a newbie. I know the online business works. More success stories than scams! I want to try it myself! And I do not want to spend too much money on something I don’t know will work for me.

I came across her another post on how she made money through selling T-shirts online. That intrigues me and caught my attention.

Her course is inexpensive as compared to starting a business offline.

The best part is that the system is easy to use; step-by-step methods that can be implemented immediately. Not only that – her fast responses to my questions amazed me!

If I don’t succeed, it’s my fault not hers!

Look forward to you joining me – before the course is closed!

Thanks Verena for your great offer!

Verena has put together an excellent program. I have been learning POD for several months and finally came across a program that I have learned so much from. She does a great job with describing POD and an even better job with describing how to successful use Facebook Advertising.

This course rocks!!! This is the first time that I have full faith in a system that I have found online. This is a straight forward, no BS approach to generating some money online. With this course and the niche reports I am certain that I will create passive income for myself using it. Really really grateful to have found Verena.

Let me just start by saying that I love the course! I have bought many, many courses in my time and this one is by far the best investment I’ve made! Most courses promise step-by-step, showing exactly what to do, but they assume everyone knows the basics and I am fairly new to selling tshirts online, so I end up scratching my head and stuck once again. That’s definitely not the case with Verena’s course! Verena lays it all out for you, in which order to do things and even has screenshots to show you exactly what to do! Even a newbie can follow! I love it! If you are looking for a course to show you the ropes on exactly how to sell tshirts online, I absolutely recommend Verena’s ugly shirts fortune course!

Ugly Shirts Course is outstanding! I have had little success selling tee-shirts before, but now this takes the game to a new level. The training Verena provides is awesome! Unlike so many other products on how to make money online, this one is different from the crowd. This course teaches in exact steps what you need to do so you can earn a great amount of money using Facebook to promote the tee-shirts you create. I am implementing this now and already seeing results! Thank you so much Verena!

A very low key course full of golden nuggets . No big hoopla but it is solid and if you follow and take the time to understand each part, there is no doubt you will get results!

I just want to appreciation you on the wealth of knowledge you have given out to people like me in this course, You thought me not just how to design Tees but also how to market the T-shirt profitably. your Facebook Ads basics and scaling strategy are second to None. Thank you very much, and remain ever blessed.

I love Verena’s Ugly Shirts Fortune course. It is straight forward and easy to understand with step by step instructions. I’m confident that I will soon find my breakthrough on Teespring. Thank you, Verena!

I buy a lot of courses and most usually don’t work.

This One Does!

FINALY someone who is crystal clear and spells everything out thoroughly. Not many will have such an honest and transparent heart to do so. This Ugly T-shirt Course literally takes you step-by-step and holds you by the hand through the entire process of launching, growing, and profiting with your very own Teespring shirt business. The content just keeps getting better and better and words cannot explain how blessed I am to have found Verena guiding me through this process. I feel like a million bucks already. Grateful to have her as my mentor/coach.

You made a wonderful course – Uglyshirtscourse. I haven’t encountered any type of course that’s so detailed and step by step. The instructions are great. I have already created my FB page base on the recommendation. I bought 3-niches package and I am going to try one of the niche.

I am a beginner in FB ads but your instructions are well put and easy to follow for beginner like me. Really appreciate it. This is a very valuable course for its price.

Thanks for putting up a great course.

Verena is the real deal! I have been looking for a step by step program to help my Tee biz off the ground – this was it!! Excellent value for the price – don’t hesitate – grab it now!!

I “met” Verena a couple of years ago when I purchased a couple of her affiliate websites. The quality was excellent; great graphics, excellent content, etc. When she contacted me regarding “ugly teeshirts” I read her promo piece, thought about it for about 10 seconds and signed up. I’m now going over the course for the second time and once again I’m amazed at the value she’s offering. I know this-if I don’t start making a bunch of money from her latest course, it’s my fault, not hers. Don’t wait for this course to sell out! Reserve your space now.

So far this course has been step by step as advertised. I have dealt with Verena in the past and trust her. If there are any questions she responds in less than a day.

After paying for the course, you’re taken to a webpage where you can find the different modules nicely organized. They are in the form of webpages and not downloadable material. That can either be good or bad according to you. For me, I would also have preferred a downloadable pdf so that I can easily read it offline. I actually ended up copying and pasting all the modules into a Word document and converting it to a pdf so that I could read it easily when relaxing.

Verena advises that you read through the course first, and then go through it to implement. That’s what I did. I have just finished reading through the course the first time, and I’m getting ready to implement.

There is absolutely NO FLUFF or filler in this course; Verena gets straight to the point, is focused on actionable information, and does not have any hype. That is a relief!

She includes step-by-step information, complete with screen captures to guide you through the process of actually implementing. She also uses actual examples and lessons from her own experience; she tells you what has worked or not worked for her so that you sort of have an idea of what to do and what to expect. The course is very realistic; Verena does not promise that all your campaigns will be successful. This sets a realist expectation.

Verena also shares actual scripts/words to use in our campaigns, which in my view, will make it very easy to copy and paste into your own campaigns. She also uses examples from her own campaigns which makes it easier to grasp/simplifies learning. That will definitely save a lot of time!

What could have added even more value to this course is a pdf version of the course, as well as a checklist of the steps to follow so that when you get to implementing you focus on action. That said, the course itself is about 50 pages, so it should not be difficult to skim through whenever one is implementing.

Should you get the course?

Definitely.

I hope to update my review as I implement and see results.

This Ugly Tee Shirt course is full of step by step content that is to the point, and not full of fluff. Easy to understand, simple to follow steps, written in an concise way that even if you have never sold on the internet before, you will easily be able to follow this.

I believe this course is worth so much more in value, and I do not hesitate to recommend this to anyone who wants to get into selling on the web and needs the steps to follow in a teachable way that you can use over and over again.

I have purchase other courses in the past and this Ugly T-shirt course that Verera design blows any others I have purchased away. I am so confident others will find the value in this course that I am writing my first review of any course and putting my name on it!

Verena also has quickly answered a question I had ,very promptly. I was so impressed with the quick response.

Thank you Verena for writing this course, you have given me a roadmap to t-shirt success!

Impressive from start to finish, Verena takes you by the hand and shows you step-by-step how to create successful marketing campaigns using facebook insights. Her style is clear, concise, easy to understand and ideal for newbies or veterans alike. I even had a question which she answered within 12 hours so you also have excellent support to back you up.

By far the best simple but most effected course I’ve purchased online period. I purchased this course for the facebook ads training alone. I firmly believe that once I master the ads training the income will follow. My first tee shirt campaign received 2.1K view seems like instant! I highly recommend YOU to take action while you have a chance. Thank you Verena for the REAL DEAL!

Easy to follow step-by-step approach from start to finish. No fluff. I bought the course and the niche reports. Her customer service is top notch too. Well worth my investment.

This course has so much content for the price. I am not sure why I waited so long. The course is drilled down step-by-step with screenshots of actual Facebook pages. Her niche reports have actual test cases that you can adapt to your own campaigns. If you have questions you will not receive a generic auto replay stating that you will be contacted within a few days. She answers her emails directly which is awesome! I am in the middle of my first campaign and could kick myself for not doing this sooner

Verena is the best i love purchasing from her because i know i’m going to get a straight up good product and service. i have bought several websites from her in the past and her customer service was always on point. So when she offered this new product ugly shirts fortune i jumped right on it. As expected this is an excellent course straight to the point step by step procedure that any one can execute. I highly recommend especially for those who are new or may have had difficulty produce an online income in the past in this course she has revealed some of her marketing secrets that i believe will help in the promoting of any product or service. Ugly Shirts Fortune a must buy.

Purchased the course and really happy with it. This course was well constructed and informative. It was easy to follow step by step, no guesswork and delivered exactly what was promised. I am always referring back to the guide as I setup my campaign. I would recommend this course to anyone who want to start their T-shirt selling online.

So I bought yet another course… I am really glad this one was different from the others. This course is step by step and very easy to follow, I had a money making campaign up and running very quickly. Course is very unique and leaves no secrets I also recommend getting a couple niche reports those are amazing!

Verena, I’m not sure how I got on your mailing list, but I’m glad I did. I received your email about signing up for your tshirt course. This was just days after me praying for a way to possibly generate 10k over the next 6 months.

Initially I was going to just delete the email but decided to click on the link. I like what I saw and was just planning to purchase and see what it was all about. I already had plans to ask for an immediate income because all too often once I purchase an online course of this sort in turns out to be a lot of fluff but no real substance. But much to my surprise, yours was the total opposite. I could not believe the information you were sharing and at the price you were sharing. I believe you are indeed the answer to that prayer I prayed earlier this week.

I am going to start your course this weekend and use this as my new business model. I believe I can be successful at the tshirt model and I think it can give me the full time income I have been looking for.

you are such a genuine person. I think I will start to model you from here out. because I notice in your course you provide actual steps. some others don’t. I think they purposely leave stuff out they only share enough to sell the course but not enough for someone to be successful like them.

thanks for sharing and i will start following your blog. If anyone is on the fence about purchasing this course, I can tell you she is the real deal. It is my intentions to reinvest in your content as much and as often as I can.

Many blessings to you Verana and thank you for all your awesomeness.

I have spent years looking for the right person with the right skill set to push my dreams forward of making money online. Verena knocked it out of the park on this one. I wanted someone to basically walk me through step by step on how to do what I’m passionate about. She delivered far above what I was expecting. If you’ve been anxious to find the right course for launching your dreams into reality, you are in the right place! Please don’t let fear get in your way. Verena will walk you through this process so you won’t have to worry about not getting all the information you need to make this happen. It’s all there! From start to finish!

I am a business professor at a USA university, I’m also a father of 6 children. It’s rare that I find entrepreneurship courses I can use in the classroom with my students and also teach to my children at home. However, Verena Ho’s course, does just that. Verena’s business philosophy of starting small to go big is rare in this day of guru teaching. Most courses I evaluate for my classes are too advanced for even the average marketer. However, this course helps you build the fundamentals without losing sight of making money. My 9 and 11 year old are loving going through her course and putting together their passion niches.

Verena is the real deal. No hype in her course, just good stuff. Her lessons are easy to put into action, trust me, just follow her teaching and good things will definitely happen.

Out of all of the programs I have purchased, I still have not found anyone that is as willing, and timely, with communication as they are. Every time I had even the slightest question, they would respond back quickly and answer any questions I had. What I received was spot on with what I ordered, and I couldn’t have been happier with it. The great customer support was an amazing bonus!

Just like you I was dabbling and wondering, stuck in the ‘wantrapreneur’ mode. Then I came across Verena and her course. Verena’s super simple-to-understand teaching style helps you to take baby steps and before you know it… you’ve made your first dollar on the internet. Pretty amazing. If you want a no BS way to start making money on the internet just by being yourself (no special talent required) then I encourage you to enrol in this course.

For a long time I have been looking for something to earn online. Finally I found Verena’s ‘Ugly T-Shirt Fortune” course. Her instructions are very clear with the step by step screenshots is really a plus. Even a newbie like me can follow through. I am confident that I will make it. Thank you for sharing your secret. I am looking forward to learn more from you, Verena. I have no regrets in my investment, and I highly recommend this course to those who really wants to earn some extra money online.

This course is very well put together. Each step is easy to understand and implement, it literally walks you through step by step what to do. No guesswork, no hard work, just follow the course and you’ll see how easy it is. I like how organized it is – it makes it easy for me to go back and review various topics as I’m implementing my campaigns. Overall, it’s a great course and I’m very happy I bought it!

If it is from Verena, it’s good and the Ugly Shirts Fortune course is no exception. This course is exactly what anyone who wants to sell T-shirts needs. It’s easy to understand and gives you up-to-date, information on how to run ads and build your own small t-shirt empire. If you’re sitting on the fence about whether or not to join this course; go ahead and pull the trigger. You won’t regret.

I have been really impressed with this very easy to follow course by Verena – its literally step by step. I purchased the upsell and boy am I glad I did as she gives you a series of pre researched niches to get started with – I am confidently starting my first campaign and am confident that what I have learnt especially about Facebook advertising can be used to drive seriously targeted traffic to not only this product but to any other.

This is a great program for people just starting out with t-shirts. Step-by-Step instructions and really clear visual screenshots to help in understanding the training. I’m still going through the training but think it will really help me grow my business. Hats off and my thanks to Verena!

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• women's health

Women are more likely to survive health issues with female doctors, new study finds

CHICAGO -- A new study suggests women are more likely to survive health issues when their doctors are also women.

The study, which was published in Annals of Internal Medicine , looked at Medicare patients over three years, and noted findings may be different for younger populations. The patients in the study had been hospitalized with medical conditions between 2016 and 2019 and were treated in the hospital.

Researchers also found that women are less likely to be re-admitted to the hospital under a female doctor's care.

The difference is just a quarter percent, but researchers said that even such a small difference is statistically significant and noteworthy.

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• Published: 22 April 2024

Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciarán

• Andrew J. Charlton-Perez   ORCID: orcid.org/0000-0001-8179-6220 1 ,
• Helen F. Dacre   ORCID: orcid.org/0000-0003-4328-9126 1 ,
• Simon Driscoll 1 , 2 ,
• Suzanne L. Gray   ORCID: orcid.org/0000-0001-8658-362X 1 ,
• Ben Harvey   ORCID: orcid.org/0000-0002-6510-8181 1 , 3 ,
• Natalie J. Harvey 1 ,
• Kieran M. R. Hunt   ORCID: orcid.org/0000-0003-1480-3755 1 , 3 ,
• Robert W. Lee   ORCID: orcid.org/0000-0002-1946-5559 1 ,
• Ranjini Swaminathan 1 , 2 ,
• Remy Vandaele 1 , 2 &
• Ambrogio Volonté   ORCID: orcid.org/0000-0003-0278-952X 1 , 3  

npj Climate and Atmospheric Science volume  7 , Article number:  93 ( 2024 ) Cite this article

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• Atmospheric dynamics
• Mathematics and computing

There has been huge recent interest in the potential of making operational weather forecasts using machine learning techniques. As they become a part of the weather forecasting toolbox, there is a pressing need to understand how well current machine learning models can simulate high-impact weather events. We compare short to medium-range forecasts of Storm Ciarán, a European windstorm that caused sixteen deaths and extensive damage in Northern Europe, made by machine learning and numerical weather prediction models. The four machine learning models considered (FourCastNet, Pangu-Weather, GraphCast and FourCastNet-v2) produce forecasts that accurately capture the synoptic-scale structure of the cyclone including the position of the cloud head, shape of the warm sector and location of the warm conveyor belt jet, and the large-scale dynamical drivers important for the rapid storm development such as the position of the storm relative to the upper-level jet exit. However, their ability to resolve the more detailed structures important for issuing weather warnings is more mixed. All of the machine learning models underestimate the peak amplitude of winds associated with the storm, only some machine learning models resolve the warm core seclusion and none of the machine learning models capture the sharp bent-back warm frontal gradient. Our study shows there is a great deal about the performance and properties of machine learning weather forecasts that can be derived from case studies of high-impact weather events such as Storm Ciarán.

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Introduction

During the 20th century and the first two decades of the 21st century, numerical weather prediction (NWP) transformed atmospheric science 1 . The combination of physical and mathematical understanding, the availability of high-performance computing and the expansion of the network of Earth system observation led to remarkable and continued progress in the skill and availability of weather forecasts. Numerical weather predictions are a ubiquitous part of modern life, with applications on many different timescales and in sectors as diverse as transport, agriculture, healthcare and recreation.

Over the last two years, machine learning (ML) techniques, a subset of the rapidly developing field of artificial intelligence (AI), have begun to be applied to the weather prediction problem in earnest. Whilst ML has had applications in climate science for many decades 2 , 3 , 4 , with these communities aware of its potential 5 , and is increasingly used for post-processing weather forecasts 6 , 7 , recent advances in ML and advancements in GPUs (Graphics Processing Units), have enabled the beginning of a ‘new dawn’ in the application of ML and AI techniques to weather and climate prediction 8 .

The publication of the WeatherBench dataset 9 and the 10-year roadmap for ML use by the European Centre for Medium-Range Weather Forecasts (ECMWF) 10 , amongst other developments, stimulated interest and investment in the development of ML models for weather forecasting. During 2022 and 2023, four ML models were developed by major technology companies to address the short to medium-range (0–10 day) forecasting problem. These models have all been shown to produce skillful 0–10 day forecasts of the 500 hPa geopotential height field, based on the widely used Anomaly Correlation Coefficient metric 11 . All four models use an encode-process-decode framework but with differing architectures:

FourCastNet 12 , developed by NVIDIA and based on Fourier Neural Operators (FNO) with a vision transformer architecture;

FourCastNet version 2 13 , which builds on FourCastNet by using spherical FNOs;

Pangu-Weather 14 , developed by Huawei and based on a three-dimensional Earth-specific transformer and hierarchical temporal aggregation; and

GraphCast 15 , developed by Google DeepMind and based on graph neural networks.

Similar techniques have been used to develop models for other forecast tasks (e.g., MetNet-3 for 12-h precipitation forecasts in the contiguous United States and 27 European countries 16 ). At the present time, ML models primarily produce deterministic forecasts, but rapid progress is being made in producing fully probabilistic forecasts 17 , 18 , 19 . All four ML models are extremely efficient when run on GPU or TPU (tensor processing unit) devices, typically producing 10-day forecasts in a few minutes.

Given the infancy of ML model weather prediction, to the author’s knowledge, there are no prior studies that compare how the four ML-models and NWP models capture individual, impactful weather events. Examination of individual weather events available from the papers that describe the ML models is limited to qualitative comparisons of the simulation of tropical cyclones and atmospheric rivers by FourCastNet 12 and quantitative assessment of the tracking error of tropical cyclones by Pangu-Weather 14 and GraphCast 15 . There are no published studies that examine ML model forecasts of extratropical windstorms 20 , despite their potential to cause multi-billion dollar damages 21 and increasing severity under climate and population change 22 .

In this study, we, therefore, seek to advance knowledge of the comparative performance of ML and NWP models by comparing their forecasts of Storm Ciarán, which affected several European countries during November 2023. This is a valuable out-of-sample test for the ML models because their training datasets all end before the beginning of 2023. We compare the ability of the models to capture the detailed physical structure of the storm and its impacts at two lead times over which operational weather forecasters were actively engaged in issuing weather warnings to the public. An accurate description of the physical structure of this, or any other, storm is a key component of forecasting its compound impact 23 and in constructing plausible storylines for end-users 24 .

Storm Ciarán and its associated impacts

Storm Ciarán was first seen as a low-pressure weather system south of Newfoundland at about 00 UTC on 31 October 2023. Based on surface analysis charts issued by the UK Met Office, it then tracked quickly across the North Atlantic, undergoing explosive deepening from 988 hPa at 00 UTC on 1 November to 954 hPa at 00 UTC on 2 November at which time it was located to the northeast of France. This deepening rate, 34 hPa in 24 h means that Ciarán was an extratropical cyclone “bomb” 25 . The lowest pressure recorded, 953 hPa at 06 UTC on 2 November, is a record low pressure for a November storm observed in England 26 . Figure 1 shows surface observations of the 10-m wind speed, cloud cover and mean sea level pressure (MSLP). The cyclonic circulation around the storm centre (with the lowest MSLP observed on the English south coast near the Isle of Wight) has a maximum wind speed of 65 knots on the Normandy coast in France.

The observations are shown as simplified station circles using conventional notation 54 . Circle shading indicates cloud cover in octas, wind barbs and feathers indicate wind speed in knots with the wind direction towards the circle, and numbers are the last three digits, including a decimal place, of the MSLP (in hPa) e.g., 543 equates to 954.3 hPa. Some thinning of observations has been performed for clarity and note that two ships both reported at 51.1 o N, 1.7 o E with different wind speeds and directions.

Although Storm Ciaran was not a classic Shapiro-Keyser cyclone 27 , clear banding in the vicinity of the tip of the cloud as it encircles the storm centre to the poleward side (called the cloud head) could be seen in satellite imagery before it made landfall in northern France. This banding suggests that a sting jet may have been present in Storm Ciarán 28 , however its identification requires methodologies beyond the scope of this study. Gusts of over 100 knots (51 m s -1 ) were reported in several locations in Brittany 29 , with a maximum of 111.7 knots (57.5 m s -1 ) recorded at Pointe du Raz at approximately 0200 UTC on 2 November 30 .

Across Northern Europe, at least 16 people were killed 31 . All flights were cancelled from Amsterdam Schiphol Airport and there were numerous cancellations from Spanish airports. An estimated 1.2 million households in northern France were left without electricity 32 and more than 1 million residents were cut off from the mobile telephone network. Brest and Quimper Airports were also shut and there was disruption to Eurostar operations 33 .

Approximately 10,000 homes in Cornwall were left without power, hundreds of schools were closed and many train services were disrupted by fallen trees. Gusts in Channel Islands ranged from 70-90 knots (36-46 m s -1 ) 32 with a maximum gust of 90 knots (46 ms -1 ) recorded in Alderney at approximately 08 UTC on 2 November 34 . Jersey also experienced a T6 tornado with estimated winds in the region of 161-186 mph (71–83 m s -1 ). Its 8-km track left a trail of destruction and tens of people needed to leave their homes. It is likely that this is the strongest tornado reported in the British Isles since the Gunnersbury tornado in December 1954 35 .

The 10-m wind speed and MSLP structure of Ciarán are shown in Fig. 2a, b at the times when it impacted the land: 00 and 06 UTC 2 November 2023. State-of-the-art model analyses, such as the IFS analysis used in this figure, represent the best three-dimensional estimates of the actual atmospheric state. The low-pressure centre of the storm tracked along the southern UK coast and the strongest winds (turning cyclonically) occurred in an arc in the southwest quadrant of the storm when the strong winds impacted Brittany and later more directly to the south of the low centre when they impacted the Channel Islands. The 10-m winds weakened significantly over land due to surface friction, no longer reaching the threshold for shading in the figure. They also weakened between the two times shown, with the peak winds falling by about 6 ms -1 , likely due to a combination of the storm making landfall and having already reached its mature stage. The observed wind speeds, shown by the overplotted colour-filled circles, are consistent with the analysed fields, away from the coastlines but exceed those analysed in some locations, notably some coastal locations and at the narrowest point of the English channel. The winds in these locations will be influenced by local mesoscale processes and so these exceedances are not unexpected given the resolution of the IFS model. The track of the storm, defined as the locations of its minimum MSLP according to IFS analyses, is shown by the black symbols joined by lines in panel (c). Ciarán had its genesis in the western North Atlantic around the time of the first track point shown (06 UTC 31 October) and travelled rapidly eastwards across the North Atlantic. The contours shown illustrate the MSLP and 250-hPa wind speed (i.e., the upper-level jet) at the start, middle and end times of the tracks and show how Ciarán evolved from a weak disturbance (with central MSLP exceeding 995 hPa) to a record-breaking deep storm as it crossed from the equatorward to the poleward side of the jet at about 06 UTC 1 November.

a , b Maps of 10-m wind speed (shading) and MSLP (contours) at a 00 UTC and b 06 UTC 2 November 2023 from the IFS analysis. Synoptic wind observations above 20 m s –1 are shown as coloured dots. c Six-hourly track points from the IFS analysis (blacks squares joined by lines) and the IFS HRES forecasts and AI models (coloured symbols as in Fig. 3a , b ) from 06 UTC 31 October to 06 UTC 06 UTC 2nd November 2023 (left to right) together with partial MSLP (grey contours in hPa) and 250-hPa wind speed (colour-filled contours) from the IFS analysis at 06 UTC on 31 October, 1 November and 2 November (left to right). The locations of the jet maxima at the longitude points of the MSLP minima at each time are indicated by the cyan squares connected by lines.

Track, intensification and wind impacts of Storm Ciarán

Ciarán’s track was well forecast by both the IFS HRES and ML-models (I. 2(c)) initialised at 00UTC on 31 October, although small differences in the location of the storm centre, and associated wind field, were critical for the accurate predictions of weather warnings along the southern English coast. Two days before Ciarán began to impact land and well before the start of its fast intensification, the spread in the position of the storm in ML models and NWP models is similar.

The evolution of the minimum mean sea pressure (MSLP) at the centre of the developing storm and its associated maximum 10-m wind speed are shown in Fig. 3 for the IFS analysis, IFS HRES forecast and ML model forecasts in panels (a, c), and for the ERA5 reanalysis, forecasts based on the ERA5 system, and the control (unperturbed) ensemble members of four NWP models in panels (b, d). Considering first the minimum (MSLP) evolution, all the forecasts closely follow both analysis products, capturing both the rapid deepening phase of the storm and its maximum intensity depth. The minimum MSLP at the end of the forecast (06 UTC 2 November) is 954 hPa in both the IFS analysis and ERA5. This value varies between 951 and 955 hPa for the ML models and between 950 and 953 hPa for the six NWP models (including the IFS HRES). In contrast, the spread in the maximum wind speed evolution is far greater. At the time of peak wind speed in both analyses, 00 UTC 2 November (48-h lead time), the value in the IFS analysis is 34 m s -1 . The IFS HRES forecast predicts this well (36 m s -1 ), while the other, generally slightly coarser resolution, NWP models mostly forecast slightly weaker winds (30-37 m s -1 ) with the NCEP model being a clear outlier, predicting winds of 40 m s -1 . The wind speeds forecast by the ML models are far too weak (25–26 m s -1 ), even in comparison with the analysis from ERA5 (30 m s -1 ). The ML models failed to capture the rapid intensification of the winds after about 06 UTC on 1 November (30-h lead time). Forecasts made using the ERA5 analysis system do not suffer from this low wind bias and so the underestimation is unlikely to be the result of training the ML models on the ERA5 data. The economic loss resulting from strong surface winds is often assumed to scale as the cube of normalised wind gust speed over a threshold (such as the 98 th percentile value) 36 , so even a small underestimation in predicted wind speed can be significant in terms of the subsequent losses.

a , c minimum MSLP and b , d maximum 10-m wind speed. a , b IFS analysis, IFS HRES forecast and forecasts from the four ML models. a , d ERA5, forecasts made from the ERA5 system and forecasts from control members of the ensemble forecasts from IFS (IFS ens_cntl), the Met Office (UKMO ens_cntl), the Japan Meteorological Agency (JMA ens_cntl) and National Centers for Environmental Prediction (NCEP ens_cntl). Note that the ECMWF HRES and IFS control members use the same model and resolution but are not bit-identical for technical computational reasons.

The differences in maximum 10-m wind speed are explored further in Fig. 4 which shows maps of the 10-m wind speed and MSLP for ERA5, the IFS HRES forecast and the four ML-models valid at 00 UTC 2 November, the time of peak wind speed in both analyses and when the strong winds made landfall in France. All the forecasts were initialised 48 h prior to this time (as for the data shown in Fig. 3 ). These maps can be compared directly with the IFS analysis fields shown in Fig. 2a . The region of strong winds is located in an arc in the region of the tight MSLP gradient in the southwest quadrant of the Ciarán in all seven maps. However, the ML models fail to predict the strongest winds in a band following the isobars (contours of constant MSLP) in the region of the tightest MSLP gradient, as is seen in the IFS HRES forecast, ERA5 and the IFS analysis. It is notable that, despite all the ML models being trained on ERA5, they fail to capture the structure and magnitude of the winds in ERA5 (including in forecasts made using the ERA5 system, as shown in Supp. Fig. 1a ) for this storm, implying that the far weaker winds found for the ML models compared to the NWP forecasts and IFS analysis are not simply a consequence of them being trained on a coarser resolution dataset. Note the NWP models used in Fig. 2 have a similar resolution to ERA5 (equivalent grid spacings of ERA5 ~ 31 km, Met Office ~20 km, JMA ~ 27 km, NCEP ~ 25 km) with the exception of the IFS ( ~ 9 km).

Maps of 10-m wind speed (shading) and MSLP (contours) from a ERA5 and b – f forecasts, initialised at 00 UTC 31 October 2023, from the b IFS HRES model and c – f ML models, as labelled.

Dynamical structure of Storm Ciarán

In this section, we evaluate the dynamics of Storm Ciarán during the final stage of its rapid development with a focus on the formation of strong winds at low altitudes. We compare the predictive capability of the ML models by comparing with the IFS HRES forecast and ERA5. The ML models are all trained on ERA5 and have the same resolution as the output provided for ERA5, allowing a fair comparison of model performance. The forecasts are all initialised at 00 UTC on 1 November, during the onset of Ciarán’s rapid intensification phase (Fig. 3a ). They were evaluated 18 h later (Fig. 5 ) and 24 h later (Fig. 6 ), when Storm Ciarán’s peak wind speeds were observed. By shifting the focus to these short lead times from the previous section, the aim is to highlight both the similarities in and differences between, the NWP and ML forecasts on timescales relevant for refining hazard warnings. To aid the reader, some key parts of the storm structure are labelled in Fig. 5a .

Maps show wind speed at 850 hPa (shading), wind speed at 250 hPa (65 ms –1 , cyan contour with high values in the bottom left of the panels), the wet-bulb potential temperature at 850 hPa (dark blue, light blue, light red and dark red contours indicating values increasing every 2.5 K from 280 K to 287.5 K), MSLP (thin grey contours), relative humidity with respect to water at 700 hPa (grey shading encircling regions above 80%, not shown for FourCastNet ( e ) as not available), the vertical component of relative vorticity at 850 hPa (light-to-dark green shading, from 3 × 10 −4 s –1 and then every 2 × 10 −4 s –1 ). a shows the structure in ERA5 while b – f show the structure from forecasts initialised at 00 UTC 1 November 2023. Note that the range of the wind speed colour bars in Figs. 5 and 6 is different to that in Figs. 2 and 4 . The main features of the cyclone described in the text are annotated in ( a ).

Contours of wind speed at 250 hPa and some of the contours of wet-bulb potential temperature at 850 hPa are not present as the associated values are not reached in the maps shown.

On 1 November 2023, Ciarán underwent significant intensification beneath the left exit region of an upper-level jet streak (Fig. 2c ). All the ML models captured the position and extent of the upper-level jet streak accurately with the minimum MSLP associated with Ciarán beneath the left exit region at 18 UTC (Fig. 5a–f ), a critical aspect of Storm Ciarán’s dynamics.

There is also consensus among the ML models concerning the general shape of the cyclone. Figure 5a–f shows the position of the selected moist isentropes, chosen to indicate the frontal locations and, by their separation, the frontal strengths. The position of the warm sector, identified as the region inside the 285 K moist isentrope, is characterised as a hooked feature in ERA5. The shape of the warm sector is well captured by all the ML models. The cloud head, represented by 700-hPa relative humidity above 80% (grey shading), is seen wrapping around the poleward side of the cyclone centre in ERA5. The IFS HRES, Graphcast and PanguWeather forecasts accurately depict the shape of the cloud head; however, the cloud head in FourCastNet v2 appears less curved than the other forecasts. FourCastNet forecast does not output a humidity variable at 700 hPa.

Despite capturing the general shape of Storm Ciarán, there are noticeable differences in the strength of frontal structures, indicated by the gradient in wet-bulb potential temperature (how close together moist isentropes are). This is true for the cold front, denoted by the 285-K and 287.5-K moist isentropes to the southeast of the cyclone centre and also for the “bent-back front”, i.e., the gradient between the 282.5-K and 285-K moist isentropes that wrap around the cyclone centre on its northwestern side. To the southwest of the low centre the moist isentropes indicate the bent-back front diverge, and this is known as the frontal-fracture region. While all the ML forecasts include a frontal-fracture region, they struggle to resolve the sharp across-front temperature gradient to the west and southwest of the low centre.

Cross-frontal wind shear is another indicator of frontal strength, and the values of the vertical component of 850-hPa relative vorticity (green shading in Fig. 5a–f ) near the bent-back front provide further evidence of the difficulties that the ML models have in simulating the frontal structures in the region. The hook-shaped narrow strip of high relative vorticity aligned with the bent-back warm front that is present in both IFS HRES and ERA5 (with maximum values up to 9 x 10 -4  s -1 and 7 x 10 -4  s -1 , respectively) becomes broader and weaker in the ML models. The discrepancy between the ERA5 (and also the forecasts based on the ERA5 system, see Supp. Fig. 1b ) and ML models in representing the sharpness of the bent-back front indicates that this shortcoming of the ML models is not solely due to model resolution.

This difference in frontal strength is particularly significant since it directly relates to the environment that can be conducive to the descent of a sting jet. Sting jets are coherent air flows that descend over a few hours from inside the tip of the cloud head at mid-tropospheric levels leading to a distinct mesoscale (perhaps 50–100 km across) region of near-surface stronger winds, and particularly gusts 37 . Among the models presented in this study, only the IFS forecasts and analysis have the necessary resolution to resolve a sting jet. It is crucial to recognise that the ML models, trained on coarse resolution data, are not equipped to discern features such as the presence of mesoscale jets. This limitation highlights the importance of using models with adequate resolution when predicting high-impact weather phenomena occurring at small spatial scales. However, our analysis suggests that the ML models struggle to represent frontal structures conducive to mesoscale high-impact features even when compared against NWP models with similar resolution, such as that used to generate ERA5.

The lack of sharpness of the bent-back warm front and cold front in the ML models impacts the strength of the wind speed maxima, as can be seen by turning the focus of evaluation to the region of strong winds. Figure 5a–f shows the 850-hPa wind speed (filled contours) to give an indication of the lower-tropospheric storm structure that is less influenced by the presence of land below than the 10-m winds shown previously; consequently, winds at this pressure level, roughly a km above the ground, are normally stronger than those nearer the surface. All the ML models consistently identify two regions of strong winds: one in the frontal-fracture region and another in the warm sector. The strong winds situated in the frontal-fracture region are associated with the tight pressure gradient near the tip of the bent-back warm front, the associated descent and acceleration where the moist isentropes spread out, and the alignment with the direction of propagation of the storm (with a possible local enhancement due to sting-jet descent in the IFS HRES, see the small-scale areas above 46 ms -1 ). The strong winds mostly in the core of the warm sector (enclosed by the 287.5-K moist isentropes) are associated with a broad jet, known as the warm conveyor belt jet, which ascends through the depth of the atmosphere from the top of the atmospheric boundary layer. The ability of the ML models to identify both the frontal-fracture and warm conveyor belt wind maxima (albeit with differences in the spatial structure and intensity of the latter) underscores their ability to accurately capture the general structure of extratropical cyclones. However, maximum wind speeds are weaker in the ML models than in ERA5, where they exceed 46 m s -1 (and even 48 m s -1 in the forecast based on the ERA5 system) in a broad region at the entrance of the frontal fracture. While Graphcast and FourCastNet display a small deficit of around 2 m s -1 , PanguWeather and FourCastNetv2 are roughly 4 m s -1 and 6 m s -1 lower, respectively.

We now turn our attention to the forecasts valid 6 h later, at 00UTC on 2 November 2023 (Fig. 6a–f ), the time of peak ERA5 wind speeds. At this stage of Ciarán’s evolution, analysis of the frontal-fracture region and the warm sector reveals several interesting features. ERA5 exhibits a region of warm air at the centre of the storm, which is separated from the main warm sector, a process known as warm core seclusion. Warm core seclusion occurs during the mature stage of extratropical cyclone development when cold air wraps around the low centre and cuts it off from the warm subtropical airmass. Relative vorticity starts decreasing along the bent-back front and generally increases near the cyclone centre as the front wraps around it. While the general evolution is captured by all models, the degree of clarity in the presence of a well-defined warm seclusion varies noticeably among the ML-models.

Focusing on the maximum winds in the frontal-fracture region, now compounded by the arrival of the cold conveyor belt (the main low-level jet in the cold sector, behind the cold front, of an extratropical cyclone), reveals that the ERA5, the forecast based on the ERA5 system (Supp. Fig. 1c ) and the IFS forecast all have peak 850-hPa wind speeds between 48-50 m s -1 . GraphCast and FourCastNet exhibit peak wind speeds 4–6 m s -1 lower. PanguWeather and FourCastNet-v2 have a larger weak bias, with wind speeds underestimated by 6-8 m s -1 . Wind maxima are consistently underestimated in the ML models when compared to the benchmarks provided by the ERA5 (and its forecast) and the IFS forecast. This discrepancy in predicting wind maxima at the time of peak winds and as they approach land is crucial for assessing the potential impact of Storm Ciaran’s surface winds and associated gusts.

By inspection, the structures of the MSLP fields in Figs. 5 and 6 are similar for the different models despite the differences in the wind speed structure and magnitude. This raises a further interesting question, is the discrepancy between the wind maxima in the conventional NWP and ML because the ML models do not reproduce the dynamical balances between the wind and pressure fields inherent in the conventional NWP models? This question is examined in detail in the Supplementary Material (and included Supp. Figs. 2 – 8 ) and a short summary is included here.

While the calculation of the geostrophic wind field (resulting from the balance of the pressure gradient and Coriolis forces) is relatively straightforward, calculating the more accurate gradient wind field (with the further inclusion of the centrifugal force associated with the curvature of a parcel trajectory) is more complex. Since both calculations require the evaluation of horizontal gradients in the geopotential field, an unphysical lack of smoothness on the smallest scales in all of the ML models becomes easily apparent and should be further investigated. Note that while the gradient wind should provide a better approximation to the frictionless large-scale flow (where that flow is curved) than the geostrophic wind, the flow can still differ from gradient wind balance due to unbalanced motions which may be physically realistic, particularly in high-resolution model output (and reality).

Smoothed geostrophic and gradient wind fields have physically plausible structures in both NWP and ML model outputs. While the strongest full winds are found in the NWP model outputs even after smoothing, the strongest gradient winds are not clearly different between the ML and NWP models. The differences between the smoothed full and gradient wind fields for the NWP and ML models have similar characteristic structures and magnitudes in strong wind regions of the storm. Within the limitations of the accuracy of our calculations, we cannot conclude that the weak winds in the ML model forecasts are the result of an inability to resolve the proper dynamical balances, but are likely to instead be related to inadequacies in the geopotential field, i.e., in the gradient and curvature of the geopotential contours.

In summary, the ML models represent the large-scale dynamical drivers key to the development of Storm Ciarán well, including the position of the storm relative to the upper-level jet exit. They also accurately capture the larger synoptic-scale structure of the cyclone such as the position of the cloud head, the shape of the warm sector and the location of the warm conveyor belt jet. The ability of the ML models to resolve the more detailed structure of the storm is more mixed. Only some ML models correctly resolve the warm core seclusion and none of them capture the sharp bent-back warm frontal gradient. ML models underestimate the magnitude of the strongest winds at the surface and in the free atmosphere (above the boundary layer), particularly in the frontal-fracture region near the end of the bent-back front. Note that this underestimation of the strongest wind speeds is not a consequence of the resolution of the output of the ML models or their training data, since it also applies when comparing against the ERA5 (and forecasts based on the ERA5 system) and NWP models with resolution similar to ERA5.

The contrasting ability of the four ML models considered to accurately forecast the large-scale dynamical properties of Storm Ciarán and its damaging winds serve to highlight the need for a more comprehensive assessment of this new and potentially transformative forecasting tool. More than 48 h before Storm Ciarán affected communities surrounding the English Channel, forecasts of the rapid MSLP deepening and track of the storms produced by the ML models were essentially indistinguishable from forecasts from an ensemble of conventional NWP models. Our analysis shows that the ML models were able to reproduce the upper-level flow that steered the developing storm into the left exit region of the jet and led to its rapid intensification. Many of the important dynamical features of the storm including the position of the cloud head, the shape of the warm sector and the location of cold and warm conveyor belt jets were also well captured by the ML models. The ML models do not seem to have been limited by the fact that a storm of comparable central pressure has never previously been observed over England during November. However, even in the relatively short ERA5 record, storms developing in a similar way with similar dynamical drivers (such as the upper-level jet) are common throughout winter and the ability of ML models to forecast more dynamically unusual storms, such as small-scale storms that develop rapidly from waves on pre-existing fronts, is an open question.

In contrast, when considering the damaging winds associated with Storm Ciarán in detail, forecasts from the ML models had significant errors and poorer performance than conventional NWP models. All four ML models failed to produce the narrow band of very strong winds at the surface that led to the most severe impacts, The ML models also failed to represent the strength of the cross-front thermal gradient in the bent-back front (a feature also dynamically linked to strong winds) and had variable success in producing the warm seclusion of air that formed in the centre of the storm in its mature stage.

Much further work, considering other storms, is needed to assess if the biases apparent in the simulation of Storm Ciarán are a systematic feature of this first generation of ML models. Increased scrutiny of the models is likely to lead to the identification of target areas for model improvement, as it has done for NWP models. Since the ML models are available to all through public repositories, this scrutiny is likely to enable rapid model improvement. Detailed documentation of the performance of ML models will also be critical to weather forecasters seeking to make greater use of the ML models as part of the forecasting process. Forecasting centres like ECMWF are already beginning to develop and test alpha versions of ML models that complement their existing capabilities 38 .

Based on a single case study, it would be premature to draw conclusions about the relative abilities of the four different approaches to ML weather forecasting exemplified by the different models. In particular, given we only had access to the ‘small’ version of the FourCastNet-v2 model it might be expected that this model would have a limited ability to produce the detailed properties of Storm Ciarán. Nonetheless, studies like ours are useful for identifying knowledge gaps in ML model development for forecasting, particularly in their ability to capture the structure of extreme weather patterns. This can be direct, such as the inclusion of necessary output variables (a 700-hPa humidity variable to identify the shape of the cloud head missing from the FourCastNet model), or through the formulation of more nuanced hypotheses for investigation. For instance, PanguWeather’s ability to capture the vertical component of the 850-hPa relative vorticity could be due to the model integrating height information across levels. Similarly, GraphCast’s ability to simulate the warm core seclusion better may be due to its multi-mesh representation rather than the spatial mixing used in the other models. All the ML models failed to capture the intense winds at the surface associated with Ciarán. As shown in the supplementary figures, wind errors in the lower troposphere are smaller. This may indicate that future models could benefit from including variables and the relationships across these variables that better characterise the planetary boundary layer in their training datasets. Most importantly, our analysis makes a strong case for a more robust evaluation of the forecasts from the ML models across all relevant spatio-temporal features of the physical phenomenon considered instead of isolated error metrics on individual variables.

The rapid acceleration of the forecasting capabilities of ML models as exemplified by our study of Storm Ciarán poses many new challenges and opportunities for atmospheric science 39 . Explainable AI (xAI) techniques 40 , 41 could be powerfully combined with the ML models we have considered to develop a deeper understanding of the reasons that they were able to produce skillful forecasts of Storm Ciarán in line with other attempts to unify ML and causal discovery methods 42 . The development of general-purpose, foundational models 43 could add further to the set of tools available to both forecast and understand high-impact weather events.

In this study, we compare forecasts produced by four different models based on machine learning methods. All are initialised from the same operational ECMWF analysis allowing a direct comparison with the current operational forecast of the ECMWF high-resolution model (CY48R1). The ML model forecasts are produced using the ai-models toolbox developed by ECMWF ( https://github.com/ecmwf-lab/ai-models ).

All four models considered are data-driven Deep Learning models and originally trained on a few ( ~ 4) decades worth of atmospheric and surface variables from the ERA5 dataset 44 at a resolution of 0.25°x 0.25° ( ~ 30 km resolution at the equator), which translates to 720 x 1440 grid cells. The ML models are all autoregressive, which means model output from a given time step can be used to predict output at the next time step. Model differences arise chiefly from the individual architectures, the selection of variables, parameterisations and training schemes briefly summarised in the technical details below:

FourCastNet 12 , uses the vision transformer (ViT) architecture with an Adaptive Fourier Neural Operator (AFNO) 45 . The AFNO enables dependencies across spatial and channel dimensions to be modelled efficiently at high resolutions where spatial token (feature) mixing occurs as a global convolution in the Fourier domain with FFTs. The model has a pre-training step where the AFNO is trained ahead on the ERA5 data with 20 different surface and atmospheric variables and then used for inference. The pre-training step learns mappings between X ( t ) and X ( t  + Δ t ) where t is a time step, Δ t is a time increment (set to 6 h) and X is a tensor of features called patches. In the second fine-tuning or inference step, the pre-trained model is used to produce inferences from a defined state X ( t ), first for X ( t + Δ t ) and this output from the models is itself then used to generate X ( t  + 2* Δ t ) or the output for the second time step. Thus, while the training of the model is resource intensive, it is a one-time cost and the inference step is very fast.

FourCastNet v2 13 is a development of the original FourCastNet model that uses Spherical Harmonics Neural Operators for modelling non-linear chaotic and dynamical systems on a sphere as opposed to flat Euclidean spaces. The model is trained with ERA5 data in a two-step process similar to FourCastNet—a single autoregressive step followed by fine-tuning. By learning global convolutions in computationally efficient manners, Fourier Neural Operators (such as those used in FourCastNet) are capable of accurately simulating long-range dependencies in spatio-temporal data. However, the Discrete Fourier Transform that FNOs rely on assumes a flat geometry, resulting in dissipation together with visual and spectral artefacts. The Spectral Fourier Neural Operators (SFNO), forming the basis for the FourCastNet v2 model architecture in its update from the FourCastNet model, in addition to having the desirable properties of FNOs also have translational or rotational equivariance. FourCastNet v2 is trained on a 73-channel subset of the ERA5 reanalysis dataset on single levels and pressure levels.

Pangu-Weather 14 consists of four deep neural networks with different lead times (time between input and output) of 1 h, 3 h, 6 h and 24 h. 5 upper atmosphere and 4 surface variables at 13 different pressure levels were used to train the model with a combined total of 256 million parameters. The overall deep network architecture is called 3DEST or 3D-Earth-specific Transformer that integrates height information into a new dimension thus capturing relationships between atmospheric variables across pressure levels, unlike similar transformer-based models such as FourCastNet. Data is fed into the neural network and a process called patch embedding is used to downsample the input data from individual grid cells into a 3D cube. This cube is then put through an encoder-decoder based on a ViT called the Swin transformer 25 with 16 blocks. The positional bias in the Swin transformer is replaced with an Earth-specific positional bias to reflect the fact that in a 2D projection of a sphere, distances between neighbouring points are not the same across all latitudes. The decoder is symmetric to the encoder. Although the transformer-based neural network has a large training time similar to FourCastNet, this is partially improved in Pangu-Weather by the use of a hierarchical temporal aggregation scheme that reduces cumulative forecast errors and also the forecast generation time. This is done by employing the neural network with the largest lead time iteratively for a forecast so that neural networks with shorter lead times are used closer to the forecast. The height integration and aggregated forecast schemes are also considered improvements over other transformer-based architectures.

GraphCast 15 is based on Graph Neural Networks (GNNs) 46 with around 36.7 million parameters. The model is trained with 5 surface and 6 atmospheric variables at 37 pressure levels resulting in 227 variables for every data point or grid cell. In the first step, the Encoder maps information from individual grid cells to nodes in a multi-mesh representation. The multi-mesh is derived as icosahedral meshes of increasing resolution from coarse (12 nodes) to fine (40,962 nodes). The second step has Processors using 16 GNN layers to propagate local and long-range information across the nodes on the multi-mesh through message passing. Finally, the decoder uses a single GNN layer to map the final processor layer’s multi-mesh representation back to the grid cells. GraphCast thus avoids the use of transformers and the associated scaling issues with higher resolutions that could result in large training times.

Numerical weather prediction model forecasts and analysis products

The ML model forecasts are compared to a set of forecasts from conventional numerical weather prediction (NWP) models to assess both systematic differences in the capabilities of the NWP and ML models and how the spread in the forecasts from the two architectures compare. Forecasts from the IFS HRES forecast and forecasts based on the ERA5 system (see below for a description of ERA5) were obtained from ECMWF and control (unperturbed) members of the ensemble forecasts for four models (the IFS 47 , the Met Office 48 , the Japan Meteorological Agency (JMA) 49 , and the National Centres for Environmental Prediction (NCEP) 50 ) were downloaded from the TIGGE archive 51 of operational global ensemble weather forecasts out to the medium range. The models chosen differ in their design and the resolution of the numerical model grid. Cycle 48r1 of the IFS was operational at the time of Storm Ciarán. Following the upgrade to this cycle in June 2023, the HRES and ensemble forecasts have the same resolution, equivalent to 9 km grid spacing. The Met Office, JMA and NCEP ensembles have grid spacings of approximately 20 km, 27 km and 25 km, respectively. The data for the four control ensemble members were all obtained regridded to a regular latitude-longitude grid of 0.5 degrees.

Analysis products

Both sets of models are compared to two analysis products (optimal blends of short-range forecasts and observations): the operational IFS analysis and ERA5 44 . The operational IFS analysis is produced using the IFS HRES forecast and has a resolution equivalent to 9 km grid spacing, ERA5 has a resolution equivalent to 31 km grid spacing. The IFS analysis and ERA5 were regridded to a regular latitude-longitude grid of 0.25 degrees.

ERA5 is used as an additional measure of forecasts ‘truth’ because the ML models all used ERA5 as their training data. Hence comparison with ERA5 indicates the skilfulness of these models relative to the best possible forecast given their training data. It is to be expected that the IFS analysis will include smaller-scale and higher amplitude weather features than ERA5 due to the use of a higher resolution model, despite being regridded to the same grid. It is also expected that the IFS analysis will be closer to the “truth” due to the use of higher resolution and an upgraded modelling system.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

Code availability

Apart from the Python packages referenced in the Acknowledgements, the underlying code for this study is not publicly available but may be made available to qualified researchers on reasonable request from the corresponding author.

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Acknowledgements

We thank the ECMWF labs team for building the publicly available ai-models library which enabled us to produce and compare forecasts from the four ML models. This library can be accessed at https://github.com/ecmwf-lab/ai-models . We also thank the modelling groups who made the code for the ML models publicly available through the following repositories: • FourCastNet https://github.com/NVlabs/FourCastNet . • PanguWeather https://github.com/198808xc/Pangu-Weather . • GraphCast https://github.com/google-deepmind/graphcast . This work is partly based on TIGGE data. TIGGE (The International Grand Global Ensemble) is an initiative of the World Weather Research Programme (WWRP). We are also grateful to ECMWF for providing access to operational analysis products to members of the research team through national research accounts held through the Met Office. The work is partly funded by the UKRI Natural Environment Research Council (UKRI-NERC) through several grants held by contributors and by the Schmidt Futures Foundation. BH is funded by the UKRI-NERC CANARI programme (NE/W004984/1). NJH is funded by UKRI-NERC UMBRELLA (NE/X018555/1). KMRH is funded by a UKRI-NERC Independent Research Fellowship (MITRE; NE/W007924/1). RS is funded by UKRI-NERC TerraFIRMA (NE/W004895/1). AV is funded by UKRI-NERC Arctic Summer-time cyclones (NE/T006773/1). SD is funded and supported by the Schmidt Futures Foundation.

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Contributions

A.J.C.P. conceived the analysis and produced ML forecasts and initial characterisation of their performance. S.D., K.M.R.H., R.S. and R.V. contributed to the analysis and description of the ML models. N.J.H. led analysis of the properties of Storm Ciarán and its impacts. H.D., S.G., B.H. and A.V. produced the detailed dynamical analysis of the properties of Storm Ciarán in the forecasts including collecting NWP data and producing all figures. All authors contributed to discussions, writing, proofreading and editing the manuscript. All authors should be considered co-first authors as the work was completed collaboratively. The funders played no role in the study design, data collection, analysis and interpretation of data, or the writing of this manuscript.

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Correspondence to Andrew J. Charlton-Perez .

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Want to start a business? 5 Florida cities deemed the best for entrepreneurs, says WalletHub

Sunday, April 28, kicks off National Small Business Week, with no shortages of businesses to support in the Sunshine State.

WalletHub released a new report on  2024′s Best Large Cities to Start a Business , with five Florida cities taking up the Top 10 slots.

“Starting a business can be very scary, considering one in every five startups doesn’t make it past the first year," Cassandra Happe, WalletHub analyst, said. "That’s why it’s especially important to live in a city that provides an environment where new businesses can thrive, with enough capital, workers and customers to keep it going long-term.”

What makes a city best for starting a business?

In order to determine the best cities for launching a business, WalletHub compared 100 cities, across three key dimensions:

• Business environment
• Access to resources
• Business costs

Its sample considers only the city proper in each case, excluding cities in the surrounding metro area.

What is the best U.S. city to start a business? Hint — it's found in Florida

WalletHub's study found that Orlando is the best large city to start a business in, due in part to the fact that the number of small businesses has grown faster than in most other cities.

"It’s also one of the top cities on the Kauffman Early-Stage Entrepreneurship Index, which means that in addition to Orlando having a lot of startups, those startups also have a high survival rate," WalletHub experts write. "One of the reasons why startups are so prevalent and successful in Orlando is that the city has a very high number of investors per capita, so new businesses are able to get the funding that they need to survive and thrive."

Starting a business in Orlando:

• 1st  – Growth in number of small businesses
• 42nd  – Labor costs
• 45th  – Cost of living
• 20th  – Length of average workweek (in hours)
• 31st  – Share of college-educated population
• 24th  – Industry variety

Although Orlando is known as a retirement haven, it has one of the highest growth rates for the working-age population, so businesses have plenty of potential new employees.

What are the Top 10 U.S. cities to start a business?

Within the Top 10 slots, Florida cities take up five. Here's all the cities that make up the top list:

• Charlotte, North Carolina
• Jacksonville
• Atlanta, Georgia
• Forth Worth, Texas
• Austin, Texas
• Durham, North Carolina
• St. Petersburg

WalletHub also dived deeper into the second best city for entrepreneurs, Tampa taking the title. The company highlighted its low corporate tax rate, allowing businesses to keep more of their revenue. It also has a high number of investors per capita, and the combination of low taxes and high capital gives businesses more resources to survive the difficult initial years.

"The monetary benefits of Tampa are evident in the fact that the city scores very high on the Entrepreneurial Activity Index, which indicates that there is a large number of startups in the city and those startups have a high survival rate."

What are the advantages and disadvantages of starting a business in a big city?

Talking with various business owners and experts, WalletHub collected some advice and wisdom for potential entrepreneurs. They asked their experts about the pros and cons of starting a business in a big city.

Miranda J. Welbourne Eleazar , assistant professor of management and entrepreneurship at the University of Iowa, shared that big g cities provide valuable opportunities in terms of networks, co-working spaces, and potential customers, co-founders, and employees. However, there's some down sides.

" … they come with greater costs and competition. It may be hard to get up and running if you cannot afford the basic necessities of your new business such as employees and real estate," Welbourne Eleazar said. "It may also be harder to stand out if many competitors are providing a similar product or service."

Felipe G. Massa , associate professor at the University of Vermont, addressed that while bigger cities are hubs for human and financial capital, smaller cities are often more supportive of homegrown entrepreneurial efforts.

"You are more likely to get support from mentors, have customers who care deeply about your success, and have better access to government and university support."

Want to start a business? WalletHub asks experts to give tips for aspiring entrepreneurs

In addition to general wisdom on starting a business in a large city, WalletHub's panel of experts also shared their tips to upcoming entrepreneurs.

Christopher E. Stevens , associate professor of entrepreneurship at Gonzaga University, advised those to "start small and realistic."

"Early-stage venture founding is a risky proposition, and it makes a difference if you approach it with realistic goals, a network of support and advice in place, and if you scale your goals around what is both realistic and manageable – especially if most of your resources will come from your personal savings or credit, as it does with most small businesses started in the US," Stevens said.

Dr. Briana Stenard , associate professor of management and entrepreneurship at Mercer University, recommended to start your business in the leanest way you can. She added if you start leanly, you can develop a customer base and collect feedback on your prices and products/services while saving up money for your potential business. 

"You will prove the model before you spend money on physical space. This would allow you to save up enough capital from your lean business to fund the growth/expansion of your business," Stenard said.

Brazilian Government Forced Censorship on X: New Report Reveals

• Two copies each of 28 orders, in Portuguese and in English translation, issued by Justice Alexandre de Moraes to X Corp.;
• An additional 23 orders issued by Justice Alexandre de Moraes for which X Corp. does not have an English translation; and
• 37 orders issued by the Superior Electoral Court of Brazil.
• Jair Messias Bolsonaro, 38th President of Brazil
• Marcos do Val, Current Member of the Federal Senate in Brazil 
• Paulo Figueiredo Filho, Brazilian journalist

A popular YouTuber's negative video of Humane's AI Pin raises questions about critical reviews in the age of innovation

• This post originally appeared in the Insider Today newsletter.
• You can sign up for Business Insider's daily newsletter here .

Hello there! If you're struggling to decide the foods worth buying organic, best-selling author Michael Pollan has some suggestions for the ones worth splurging on to avoid harmful chemicals .  

In today's big story, we're looking at a critical tech review that caused a bit of a stir on social media .

What's on deck:

Markets: Goldman Sachs quiets the haters with a monster earnings report .

Tech: Leaked docs show one of Prime Video's biggest issues, forcing customers to abandon shows .

Business: The best bet in business these days? Targeting young men who like to gamble .

But first, the review is in!

If this was forwarded to you, sign up here.

The big story

Up for review.

"The Worst Product I've Ever Reviewed… For Now"

Marques Brownlee, the YouTuber better known as MKBHD, didn't mince words with the title of his review of Humane's AI Pin .

In a 25-minute video , Brownlee details all the issues he encountered using the AI device. (Spoiler alert: There were a lot.)

Brownlee's review aligns with other criticisms of the device . But not all of those came from someone with as much sway. His YouTube channel has more than 18 million subscribers.

One user on X pointed that out , calling the review "almost unethical" for "potentially killing someone else's nascent project" in a post reposted over 2,000 times. 

Most of the internet disagreed, and a Humane exec even thanked Brownlee on X for the "fair and valid critiques." 

But it highlights the power of Brownlee's reviews. Earlier this year, a negative video of Fisker's Ocean SUV by Brownlee also made waves on social media . 

Critical reviews in the age of innovation raise some interesting questions.

To be clear, there was nothing wrong with Brownlee's review. Humane's AI Pin costs $700. Watering down his review to ease the blow would be a disservice to the millions of fans relying on his perspective before making such a significant purchase.

Too often, companies view potential customers as an extension of their research and development. They are happy to sell a product that is still a work in progress on the promise they'll fix it on the fly. ("Updates are coming!")

But in a world of instant gratification, it can be hard to appreciate that innovation takes time. 

Even Apple can run into this conundrum. Take the Apple Vision Pro. Reviewers are impressed with the technology behind the much-anticipated gadget — but are still struggling to figure out what they can do with it . Maybe, over time, that will get sorted out. It's also worth remembering how cool tech can be, as Business Insider's Peter Kafka wrote following a bunch of trips in Waymo's software-powered taxis in San Francisco . Sure, robotaxis have their issues, Peter said, but they also elicit that "golly-gee-can-you-believe-it" sense.

As for Humane, America loves a comeback story. Just look at "Cyberpunk 2077." The highly anticipated video game had a disastrous launch in 2020 , but redeemed itself three years later, ultimately winning a major award .

Still, Humane shouldn't get a pass for releasing a product that didn't seem ready for primetime, according to the reviews. 

And its issue could be bigger than glitchy tech. Humane's broader thesis about reducing screen time might not be as applicable. As BI's Katie Notopolous put it: " I love staring at my iPhone ."

3 things in markets

1. Goldman finally strikes gold. After a rough stretch, the vaunted investment bank crushed earnings expectations , sending its stock soaring. A big tailwind, according to CEO David Solomon, is AI spawning " enormous opportunities " for the bank. 

2. Buy the dip, Wedbush says. Last week's drop among tech stocks shouldn't scare away investors , according to Wedbush. A strong earnings report, buoyed by the ongoing AI craze, should keep them soaring, strategists said. But JPMorgan doesn't see it that way, saying prices are already stretched .   

3. China's economy beat analysts' expectations. The country's GDP grew 5.3% in the first quarter of 2024, according to data published by the National Bureau of Statistics on Tuesday. It's a welcome return to form for the world's second-largest economy, although below-par new home and retail sales remain a cause for concern .

3 things in tech

1. Amazon Prime Video viewers are giving up on its shows. Leaked documents show viewers are fed up with the streamer's error-ridden catalog system , which often has incomplete titles and missing episodes. In 2021, 60% of all content-related complaints were about Prime Video's catalog.

2. Eric Newcomer is bringing his Cerebral Valley AI Summit to New York. The conference, originally held in San Francisco, is famous for producing one of the largest generative AI acquisitions ever. Now, it's coming to New York in June .

3. OpenAI is plotting an expansion to NYC. Two people familiar with the plans told BI that the ChatGPT developer is looking to open a New York office next year. That would be the company's fifth office, alongside its current headquarters in San Francisco, a just-opened site in Tokyo, and spots in London and Dublin.

3 things in business

1. America's young men are spending their money like never before. From sports betting to meme coins, young men are more willing than ever to blow money in the hopes of making a fortune .

2. Investors are getting into women's sports. With women like Caitlin Clark dominating March Madness headlines, investors see a big opportunity. BI compiled a list of 13 investors and fund managers pouring money into the next big thing in sports.

3. Bad news for Live Nation. The Wall Street Journal reports that the Justice Department could hit the concert giant with an antitrust lawsuit as soon as next month. Live Nation, which owns Ticketmaster, has long faced criticism over its high fees.

In other news

Blackstone hires Walmart AI whiz to supercharge its portfolio companies .

Taylor Swift, Rihanna, Blackpink's Lisa: Celebrities spotted at Coachella 2024 . 

NYC's rat czar says stop feeding the pigeons if you want the vermin gone .

A major Tesla executive left after 18 years at the company amid mass layoffs .

Some Tesla factory workers realized they were laid off when security scanned their badges and sent them back on shuttles, sources say .

New York is in, San Francisco is very much out for tech workers relocating .

AI could split workers into 2: The ones whose jobs get better and the ones who lose them completely .

Oh look at that! Now Google is using AI to answer search queries .

A longtime banker gives a rare inside look at how he is thinking about his next career move, from compensation to WFH .

Clarence Thomas didn't show up for work today .

What's happening today

Today's earnings: United Airlines, Bank of America, Morgan Stanley, and others are reporting . 

It's Free Cone Day at participating Ben & Jerry's stores. 

The Insider Today team: Dan DeFrancesco , deputy editor and anchor, in New York. Jordan Parker Erb , editor, in New York. Hallam Bullock , senior editor, in London. George Glover , reporter, in London.

Watch: Nearly 50,000 tech workers have been laid off — but there's a hack to avoid layoffs

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Prospective Jurors Are Dismissed in Dozens as Trump’s Trial Begins

Jury selection began in the Manhattan criminal case, but many who might weigh Donald J. Trump’s fate told a judge that they could not be impartial.

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By Jonah E. Bromwich ,  Ben Protess ,  Maggie Haberman and Kate Christobek

Follow today’s live coverage of Trump’s hush money trial .

After years of investigation and weeks of delay, the criminal case known as the People of the State of New York v. Donald J. Trump went to trial Monday, with hundreds of citizens summoned to potentially join a jury that will decide the fate of the first American president to face prosecution.

But the ritual of choosing the jury got off to a slow start as more than half of the first group of 96 potential jurors raised their hands to say they could not be fair to Mr. Trump, demonstrating the challenges of picking an impartial panel in a city where the defendant is widely loathed. The judge immediately excused them.

One prospective juror, a woman in her 30s, was heard outside the courtroom saying, “I just couldn’t do it.”

The prospective jurors, who represented a cross-section of Manhattanites of various ages and demographics, filed past Mr. Trump and into the rows of a dingy courtroom. Some strained their necks for a glance at the former president. He stood and turned after the judge introduced him as the defendant, flashing them a tight-lipped smile.

The judge, Juan M. Merchan, welcomed the prospective jurors to his courtroom, and began to describe the case, which was brought by the Manhattan district attorney’s office and accused Mr. Trump of falsifying records to cover up a sex scandal. He is facing 34 felony counts, and, if convicted, could face up to four years in prison.

The trial was born from a long-running investigation that began when Mr. Trump was still president. He was a target of Manhattan prosecutors in fits and starts over five years, spanning the terms of two district attorneys and multiple grand juries. Not until last March did the current district attorney, Alvin L. Bragg, secure an indictment.

And the case only went to trial after a three-week postponement. In recent days, Mr. Trump continued to stall — as he does in all of his legal cases — but Justice Merchan rejected his 11th-hour effort to delay the landmark trial.

The Manhattan case, one of four indictments facing the former president and presumptive Republican presidential nominee, may be the only one to make it to trial before Election Day.

Mr. Trump is expected to attend much of the trial, bringing his rally-ready chaos to the sober environs of the criminal courthouse, testing the judge’s patience and the limits of the justice system as he goes.

Who Are Key Players in the Trump Manhattan Criminal Trial?

The first criminal trial of former President Donald J. Trump is underway. Take a closer look at central figures related to the case.

When Mr. Trump walked into the courtroom on Monday morning, he called the case “an assault on America,” adding, “that’s why I’m very proud to be here.”

Soon after, however, amid a dry exchange of arguments between the lawyers, he nodded off, his mouth slack and his head drooping onto his chest.

And for much of Monday afternoon, Mr. Trump was hunched over the defense table as Justice Merchan instructed the prospective jurors.

When the judge explained that if the case ended in a conviction, he would be responsible for imposing an appropriate sentence, Mr. Trump let out a sarcastic chuckle. He laughed again when Justice Merchan vowed to ensure a fair trial, as Mr. Bragg watched from the second row.

Then began the messy process of selecting a jury for a man who for the first time in the nation’s history will be judged by 12 people in a courtroom before he faces millions more at the polls.

The judge has ruled that the jurors, who could face threats to their privacy and safety, should remain anonymous, though lawyers for both sides will know their names and addresses.

The jury selection process pulled back a curtain on the lives of everyday New Yorkers, offering insights into their politics and hobbies alike. One potential juror, asked about her hobbies, said she liked to “go to the club” — drawing a big laugh from reporters. She was quickly excused after she acknowledged having strong opinions about the former president.

Jury selection will be crucial as both sides seek to weed out people harboring bias. Prosecutors arguably have the upper hand in one of the most Democratic counties in the country.

Of the 96 Manhattanites who entered the courtroom on Monday, about two thirds of them soon exited, either because they could not be fair, or for reasons they kept to themselves.

Those who remained answered a list of 42 questions that offered a sketch of their professional lives, media diets and political sensibilities.

Even before the selection process began, the day featured a flurry of legal developments, many of which favored the prosecution.

Soon after the clerk called the case, the judge announced his decision to remain on the trial, rejecting Mr. Trump’s latest effort to oust him .

He also ruled that prosecutors could introduce evidence regarding Mr. Trump’s involvement with coordinating negative and positive publicity with The National Enquirer, a tabloid newspaper, during the 2016 presidential campaign.

And Mr. Bragg’s office asked the judge to hold Mr. Trump in contempt and penalize him $3,000 for violating a gag order barring him from attacking witnesses, prosecutors, jurors and the judge’s family.

Mr. Trump has risked crossing the line a few times. He has reposted articles about the judge’s daughter, a Democratic political consultant, and, this past weekend, he assailed one of the prosecution’s key witnesses: Michael D. Cohen, his former fixer. Mr. Cohen paid $130,000 to the porn star Stormy Daniels during the 2016 campaign to keep quiet about a sexual encounter she said she had with Mr. Trump.

Justice Merchan, a former registered Republican who is now known as a moderate Democrat, is not expected to rule on the contempt request until later this month, and jury selection will not end soon. It could take two weeks or more, and the trial may spill into June.

Mr. Trump alternately seemed irritated and exhausted during pretrial arguments on Monday. At one point, he sat motionless while a prosecutor read his own comments from the infamous “Access Hollywood” tape, in which he bragged about grabbing women’s genitals.

The trial itself will be a remarkable spectacle: a former president will come face-to-face with part of his past that he has tried to bury. Mr. Trump, who might take the witness stand in his own defense, has denied the sexual encounter with Ms. Daniels ever took place.

But prosecutors say that, while serving as president, he allowed his company to falsify records to hide the reimbursements to Mr. Cohen for a 2016 hush-money payment that went to Ms. Daniels.

The 12 jurors, once selected, will have to judge Mr. Cohen’s story themselves: He is expected to be the prosecution’s star witness, confronting a boss he once idolized and now despises.

Prosecutors argue that his payment to Ms. Daniels was part of a pattern: Mr. Trump, faced with a swirl of damaging stories during the 2016 campaign, concealed them to influence the election.

In addition to the payment to Ms. Daniels, Mr. Bragg’s office is expected to highlight two other deals involving The National Enquirer, which has longstanding ties to Mr. Trump.

In one deal, the tabloid bought the silence of a man who had heard that Mr. Trump had fathered a child out of wedlock, a rumor that turned out to be false, and in the other, it paid Karen McDougal, a former Playboy model, who wanted to sell her story of an affair with Mr. Trump.

The prosecution’s witness list is expected to include Mr. Cohen, David Pecker, the former publisher of The National Enquirer, and Hope Hicks, a former aide to Mr. Trump. Ms. Daniels and Ms. McDougal could also testify.

And Justice Merchan on Monday rattled off a list of even more familiar people who could come up at trial, though they might not be witnesses. They included Mr. Trump’s former personal lawyer, Rudolph W. Giuliani, and his current wife, Melania Trump.

Mr. Trump has twice sought Justice Merchan’s recusal, citing his daughter’s work as a Democratic political consultant. Justice Merchan has declined to step aside, noting a ruling by an ethics commission that found his daughter’s work posed no conflict.

“There is no agenda here,” Justice Merchan said in court on Monday. “We want to follow the law,” he added. “We want justice to be done.”

Many of the prospective jurors offered yes or no answers to the 42 questions, but a few provided further detail, including a man who identified himself as a bookseller, who may draw skepticism from the defense, which still has an opportunity to excuse him.

“I feel that nobody is above the law, whether it be a former president or a sitting president or a janitor,” he said.

Wesley Parnell , Alan Feuer and Jesse McKinley contributed reporting.

Jonah E. Bromwich covers criminal justice in New York, with a focus on the Manhattan district attorney’s office and state criminal courts in Manhattan. More about Jonah E. Bromwich

Ben Protess is an investigative reporter at The Times, writing about public corruption. He has been covering the various criminal investigations into former President Trump and his allies. More about Ben Protess

Maggie Haberman is a senior political correspondent reporting on the 2024 presidential campaign, down ballot races across the country and the investigations into former President Donald J. Trump. More about Maggie Haberman

Kate Christobek is a reporter covering the civil and criminal cases against former president Donald J. Trump for The Times. More about Kate Christobek

Our Coverage of the Trump Hush-Money Trial

News and Analysis

Manhattan prosecutors delivered a raw recounting of Donald Trump’s seamy past  as they debuted their case  against him, reducing the former president to a co-conspirator in a plot to cover up three sex scandals that threatened his 2016 election win. Here are five takeaways .

Trump has assembled a team of defense lawyers with extensive experience representing people charged with white-collar crimes to defend him. Here’s a look at his defense team .

With support from demonstrators in Lower Manhattan spotty so far, Donald Trump issued a call to “rally behind MAGA,”  and suggested the poor turnout was a result of a plot against his supporters.

More on Trump’s Legal Troubles

Key Inquiries: Trump faces several investigations  at both the state and the federal levels, into matters related to his business and political careers.

Case Tracker:  Keep track of the developments in the criminal cases  involving the former president.

What if Trump Is Convicted?: Could he go to prison ? And will any of the proceedings hinder Trump’s presidential campaign? Here is what we know , and what we don’t know .

Trump on Trial Newsletter: Sign up here  to get the latest news and analysis  on the cases in New York, Florida, Georgia and Washington, D.C.