Ever wondered how the future of weather forecasting could transform industries like energy, agriculture, and transportation? Join us for a captivating conversation with Brad from Mediomatics, where you'll discover their groundbreaking advancements in weather intelligence. Learn how their high-resolution data set and API can be tailored to meet specific industry needs, and gain insights into the transformative role of their Mediodrones. These autonomous drones soar up to 20,000 feet, tackling challenges like icing and battery optimization to deliver unparalleled forecast accuracy.
Travel with us to Berlin as we uncover the global impact of Mediomatics' innovative technology, originating from St. Gallen, Switzerland. Brad shares their ambitious plans to modernize weather measurement infrastructure through multimillion-dollar projects and collaborations with governments and industry leaders. Hear success stories that showcase how precise weather data enhances operational efficiency, particularly in energy trading. Get a glimpse into the future of autonomous drone networks and continuous advancements in weather modeling technology. Plus, enjoy a sneak peek into Brad’s upcoming summer travel plans across Europe. Don’t miss out on this engaging episode that highlights the transformative power of weather technology!
Ever wondered how the future of weather forecasting could transform industries like energy, agriculture, and transportation? Join us for a captivating conversation with Brad from Mediomatics, where you'll discover their groundbreaking advancements in weather intelligence. Learn how their high-resolution data set and API can be tailored to meet specific industry needs, and gain insights into the transformative role of their Mediodrones. These autonomous drones soar up to 20,000 feet, tackling challenges like icing and battery optimization to deliver unparalleled forecast accuracy.
Travel with us to Berlin as we uncover the global impact of Mediomatics' innovative technology, originating from St. Gallen, Switzerland. Brad shares their ambitious plans to modernize weather measurement infrastructure through multimillion-dollar projects and collaborations with governments and industry leaders. Hear success stories that showcase how precise weather data enhances operational efficiency, particularly in energy trading. Get a glimpse into the future of autonomous drone networks and continuous advancements in weather modeling technology. Plus, enjoy a sneak peek into Brad’s upcoming summer travel plans across Europe. Don’t miss out on this engaging episode that highlights the transformative power of weather technology!
More at https://linktr.ee/EvanKirstel
Speaker 1:
Hey everyone. Fascinating and important discussion today about the future of weather forecasting with Mediomatics. Brad, how are you hey?
Speaker 2:
doing well. Evan Great to be here.
Speaker 1:
Well, great to have you here, really intrigued by the amazing work you're doing. How do you describe Mediomatics these days and your mission in the weather intelligence space?
Speaker 2:
these days and your mission in the weather intelligence space. So, Mediamatics, our mission is to make weather forecasts better and to make them easier to consume and integrate. As we're seeing technology continue to advance in society. We're seeing greater autonomy with things like drones, self-driving cars, advanced air mobility All of that needs better weather data to function. Whether it's things like figuring out how much energy is going to be generated at our solar and wind power sites, whether your airplane might run into turbulence, A lot of the economy is dependent on good weather data. So at Mediomatics, we want to provide the best weather data and help to improve the way that weather observations are collected.
Speaker 1:
That's fantastic, and talk about the industries you serve. I imagine almost every industry can make use of weather data to some degree, but where are you really focused in serving customers?
Speaker 2:
Yeah, you're right, the breadth of inquiries that we get is massive. Pretty much you name a company or name an industry and we've probably had someone reach out and ask about an application for weather data. Biggest ones, I'd say, are energy, particularly in the renewable space, so optimizing how much energy can flow into the grid as well as how much electricity the grid can carry at any given time, figuring out how much demand there will be that's all very heavily weather dependent Transportation, insurance, agriculture, and then a bit in the water management space as well. I think those are probably the biggest ones that we work with.
Speaker 1:
Fantastic, and you know. Talk about your data set, your API. How are you different from the myriad of weather-related data sources that are out there private, public domain? There's a lot to look at, right.
Speaker 2:
Yeah, so weather data is inherently a pretty messy topic.
Speaker 2:
The atmosphere is not all that easy to measure. It's not like we have a weather station at every location. We don't always know exactly what's happening at every single point, every single time. So at Mediamatics, what we try to do is provide the cleanest data, ensure that it has no gaps, that we can enhance it where possible, make sure that it's high resolution, and then we package that up in an API that delivers data for exactly the point, time and location that a user needs. That might be something like a wind forecast at 187 feet above ground for a turbine in Texas. It could be your turbulence or icing conditions at 37,000 feet over the Atlantic for an airline. Or maybe it's the average rainfall across a catchment that affects how a reservoir in Ohio that would be filled. So we do a lot with the data processing to make sure that industries can get the data in exactly the file format and exactly when they need it, so to help them a bit with digging through that mountain of data that's produced out there.
Speaker 1:
Oh, fantastic value you're delivering. And what's the role of technology? What new technologies are you leveraging and collecting atmospheric data? I see drones are a big part of your solution.
Speaker 2:
Yeah.
Speaker 2:
So the weather industry and weather forecasting technology has come a long way in the past 100 years, 50 years it's gone from we would get some observations by a telegraph and then figure out okay, it's raining in Chicago and then maybe there will be a storm coming up the east coast in a few days. Then the storm would inevitably miss because the understanding of the science was pretty limited. Now we have global measurement networks with ground stations, satellite, but the way that we measure a lot of the atmosphere is still very heavily based on weather balloons. You'll have two weather balloon launches a day. They're usually spaced a few hundred miles apart in the US.
Speaker 2:
But the new models that are coming onto the market now, such as ones that we're running here at Mediamatics, they're really data hungry and one of the biggest impacts in improving your model forecast is measuring those vertical profiles of the atmosphere. So to figure out not just what's happening at the surface but to get that column of everything that's going on all the way up to 20,000 feet and above. So at Mediamatics we're filling that gap with a technology we call Mediodrones.
Speaker 2:
It's a drone that's about two and a half feet across. So pretty tiny system, pretty lightweight just over 10 pounds, most of that weight being battery but they're super powerful. One of those drones that you're looking at right there can take off from an automated base system, so someone sitting on a computer or office clicks a button and that drone will rocket up to about about 20 000 feet straight on up at about 10 minutes time and then straight back down, landing at its base station. Then that data that it collects gets fed straight back to us and gets put into our model to help make the next forecast even better.
Speaker 1:
Fantastic and tell us about the development of that drone and deployment. How does that work from a business and technology standpoint? As a drone aficionado, I'd love to get a little more behind the scenes.
Speaker 2:
Yeah, it's a huge technological challenge, particularly because you need to have something that can fly a lot higher than you would usually see with a drone of this size, and you need something that can fly in almost all weather conditions. One of the biggest things that we run into is icing. During the initial test, maybe 10 years ago, you would find flights working great. Then you hit a cloud with some ice and then your propellers ice up and that's the end of that. So we developed a propeller heating system that's unique to enable the drone to fly through clouds, to fly in snowy conditions and collect data at pretty much all times. Then we also optimize the wind to get up to about 60 miles per hour though we see a chance to further improve that and working to optimize the battery as well, so you can get up as high as possible and as often as possible, and then the automation is a huge part as well.
Speaker 2:
So if we wanna have a dense network of drones like this, doesn't make sense to have a pilot out in the field. Maybe you want data as frequently as every hour, every half hour. That's where we developed a technology called Mediobasis. It's like a big box about, say, six feet by four feet that gets put out in the field. It's connected via Internet, so 5G or Wi-Fi or Ethernet, and then that allows a pilot and a control center to manage multiple drone flights, potentially even across multiple countries. So to get all of your drones up and flying without having to go out and work or maintain them directly.
Speaker 1:
Fantastic approach and talk about the impact you're having. I can imagine so many industries leveraging your platform, as we discussed, but agriculture and farming just the obvious ones. But tell me more about the industries and different verticals that you're seeing traction.
Speaker 2:
Sure. So one example is a project that we've been working on with our clients, grand Sky, up in North Dakota and in a town called Grand Forks. There is an Air Force base up there where they operate military drones, but then there's also a lot of commercial companies that go up there to test EV tall vehicles and then new drone technologies, so to help work on that future of flight.
Speaker 2:
Of course those systems are really sensitive to weather conditions. They can't fly if they're going to run into icing or winds that are too strong, and in the past they found that the weather was just pretty unpredictable. Where they're flying up there is pretty far from the nearest weather balloon measurement sites. The models often had trouble telling them exactly how strong the wind might be at a thousand feet or if they might run into some icing that would disrupt those flights. So, working with Grand Sky, we put in a video-based system, worked with them to get FAA approval to be able to fly, and then we commissioned a high-resolution model, which we call North Dakota 1K, over the region that takes in the drone observations and then helps them to get a better forecast out. So that's helping those drone operators to gain back more flight flying time, because they can be more certain about when they'll actually be inside or outside of their operating threshold, which of course helps to make the testing more effective and save them quite a bit of money in lost time.
Speaker 1:
Well done, great story. And once you collect all this data, how do you ensure the accuracy, reliability of the forecast? Do you have you know what's happening on the forecasting front, given we have machine learning and AI technologies being applied to weather and all kinds of scenarios?
Speaker 2:
Yeah, so it's important to validate the forecasts. We do routine checks of our models against weather stations on the ground, so to ensure that the performance is there, maybe we have to tweak something. It's important to always be validating those forecasts if you want to provide the best possible quality. With AI and machine learning, yeah, we see some potentially interesting applications there around things like data assimilation, so maybe it's decoding satellite images a little bit more effectively or filling in the gaps in the observations so that your model has good initial conditions to start from. However, we still believe that a solid, physics-based model is still the best way to get the most accurate forecast.
Speaker 1:
Fantastic. Now you're based in Berlin. Tell us about the team, where they're based and the great work they're doing.
Speaker 2:
So our company is based in Switzerland, founded in a town just to the east of Zurich called St Gallen, the company was started about.
Speaker 1:
I've been there on the train. It kind of goes by as you head to Zurich yeah.
Speaker 2:
Okay, that's probably the most of the reason, or most of some people's reasons, for visiting St Gallen, but it's a beautiful place to live and to work, so I always enjoy going down there to work with our colleagues. So that's where we do our software development, our model development and also the testing and manufacturing of our drones. But since then we've also expanded to have, of course, offices here in Germany, over in the US, where I'm from originally, and then we recently won a multimillion-dollar project with a research institution in Norway to help modernize Norway's weather measurement infrastructure. So the backbone of that will be a network of about 30 automated drone sites that we'll put in around the country.
Speaker 1:
Congratulations. What a fantastic opportunity. So the impacts are not just for private industry, obviously, but working with NGOs and governments of all sizes on environmental and, you know, economic issues, challenges.
Speaker 2:
Yeah, of course, governments have traditionally been responsible for collecting most of the weather observations out there, but we're starting to see a mindset shift where government wants to work more closely with industry to help improve the weather measurements that are made available. So, yeah, we're working with governments to find the right way to deliver that data so that they can also use it to help keep people safe and integrated into the national networks.
Speaker 1:
Yeah, great, great opportunity, and you work primarily through partners or direct with industries and enterprises, governments. You have a lot of logos on your website of partnerships and you know a lot of blue chip companies that you collaborate with. Tell us more about the business side business side.
Speaker 2:
Yeah, it's a little bit all the above. We focus very much on just the weather data, so creating the highest quality data possible and then making it as easy to access by API as possible. So a lot of companies will have a data science team and they'll want to access our data directly and put it into, say, a dashboard that you're developing an internal software tool. Maybe they want to use it to manage their, say, fleet of ships or their network of wind and solar sites or anything like that. Then we provide direct data access. But other times companies will have software vendors that they work with. So maybe it's a flight planning tool that does a lot more besides weather. And then they want to see Mediomatics forecast via a tool they're already using. So we also work with partner companies who can integrate our data and then make it part of a larger product.
Speaker 1:
Fantastic, so good. Clean data is always welcome. But any sort of bigger picture success stories where you've made a difference in a business or operationally or an industry, anything you can share there on the big picture, yeah, the clean data is really, really important, I think, having data that you just don't really have to think about but it's always, always flowing in.
Speaker 2:
You don't have to worry about it being getting like anomalous or error values or something dropping out so that you have to spend a lot of time running around and fixing things. One example is an energy trading company. They have a desk of meteorologists who have to produce different forecasts for their traders so they can help make decisions on when to buy and sell commodities or when to place energy trades. Before working with us, they were spending a lot of time just on data entry, on finding the right source for something time just on data entry, on finding the right source for something, getting it into their dashboard and then getting the forecast out. Since we've started working with them, they've managed to cut their time spent on that in half. That's freed up a few extra hours for them to work on new techniques, for them to build new tools, and then that's helped them to become a lot more effective in working with their partners within the industry or within the company.
Speaker 1:
Fantastic, well done there. Maybe talk about the future. It feels like you're living in the future now, almost sci-fi kind of technology, but where do you see yourselves and the platform, maybe the roadmap going over the next couple of years? What's exciting that you can share?
Speaker 2:
drones, we see increasing levels of autonomy.
Speaker 2:
So as we start to roll out these networks to have the end goal of being able to have a really dense network of drones that can cover, say, a country, a region or eventually the whole world, and then with the ability to control those all remotely and to operate them from a central location.
Speaker 2:
It also helps us to be a lot more effective about the way that we collect us, to be a lot more effective about the way that we collect weather data and a lot more efficient.
Speaker 2:
Like it might not make sense every day to be flying every 20 minutes, but when you have, say, a hurricane coming up from the Gulf or you're getting ready for a potential tornado outbreak in Oklahoma, then to have that ability, with the flip of a switch, to start collecting really frequent measurements so that your meteorologists and your forecast models can get a better handle on what's going to happen and help you to warn people and help businesses to take action as well. That's a big piece of it. The other piece is the continued advancement of the weather modeling technology. So the supercomputers are getting better and better, the modeling techniques are getting better over time, so the forecast precision and the forecast accuracy is only continuing to improve, figuring out just how strong the winds in a hurricane might be, to try to get those impacts and the specific conditions at a location to be even more granular, which is what government and business are demanding these days.
Speaker 1:
Wow, that's a mic drop moment. Really important work indeed. Well, thanks for sharing Just a peek behind the curtain. Amazing progress. We're entering the summer season in Europe, so a little vacation might be on the radar. What else do you have coming up the next few weeks? Any travel or pretty much home-based.
Speaker 2:
Yeah, so I work a lot with our clients in aviation and government, so I spend a lot of my time on the road meeting with our partners. We'll be having a kickoff of our project out in Norway next week, so looking forward to visiting our new colleagues in Oslo then towards the end of the summer.
Speaker 1:
Better now than January. That's a good time for a kickoff.
Speaker 2:
Yes, because I always try to arrange these than January. That's a good time to kick off. I'd always try to arrange these things when the weather's a little bit nicer. Though when we did our scoping of our project out in North Dakota, that was, I think, the middle of January and, yeah, it was about minus 20. So it was, I guess, a good test of my own weather resilience, as well as that of the drones.
Speaker 1:
All right. Well, thanks so much for joining. Thanks for sharing. You know amazing work you guys are doing. Follow Mediomatics. Everyone Worth checking out the website. It looks amazing and take care. Thanks so much. Thanks, evan.
