One of the things I am proud of the most at our work here at Tomorrow.io: the most accurate GLOBAL precipitation data in real time. Below you can see a pretty cool animation showing Hurricane Helene as captured by our ML trained layer, which combines all sources of public data and our satellites, vs the US MRMS network. With such reliable global synthetic radar picture, you can drive nowcasting, flood forecasts, tropical storms forecasts and more. It is a key ingredient in our Resilience Platform and a global asset for Climate Adaptation.
Great animation! Curious, how do you measure the accuracy for precipitation? Any public benchmarks on this?
Excellent !!! and seems more information for our region in Central America where lack of Radars is an issue. will this be available as an API?
Can we get historical periods across US West in Raw Geotiff georef ... JSON formats ? How is it priced, or would you like to contribute to an active NOAA SBIR :) Round 1 :)
Nice comparison! Space-based microwave sounders are a valuable tool for precipitation estimation, providing essential data for a wide range of applications. Microwave sounders can directly measure the intensity of precipitation, providing quantitative data that is essential for hydrological modeling, weather forecasting, and climate studies. Of course to train and fine tune these AI algorithms, high-quality training data is essential. This typically includes ground-based precipitation observations, such as radar and rain gauge data, that can be compared with the microwave sounder measurements.
That’s seriously impressive! Having access to such accurate, real-time global precipitation data is a game-changer for climate adaptation and disaster preparedness. At Greenseedz, we understand the importance of reliable data in driving sustainability efforts. Exciting to see how technology like this can help build a more resilient future!
Impressive work on capturing such vital data! It's great to see how innovation in technology can make a real impact, especially in addressing climate adaptation challenges. How do you see this evolving in the future?
As far as data goes, how far back in time can we go ?
Senior Research Scientist at Google
2moSerious question: How can you actually verify that your product is doing well outside of the MRMS radar domain (e.g. compared to existing global products like IMERG)?