Improving Weather Forecasts: The Power of Soil Moisture Data

Scientists are looking at a new way to make weather and water predictions better. They're using something called coupled land–atmosphere data assimilation. This means they're combining information from the ground (like how wet the soil is) with information from the air (like temperature and wind speed). They used a special model called NICAM-LETKF to do this. In their tests, they tried two different ways to combine the data. One way was strong coupling, where they updated both soil moisture and air data at the same time. The other way was weak coupling, where they updated one before the other. They found that updating soil moisture using air data wasn't very helpful because it created some weird errors. But when they updated air data using soil moisture, it improved their forecasts! This was especially true in places like the Sahel and equatorial Africa during the rainy season. These areas have big changes in rainfall patterns, and soil moisture data helped them make better predictions. So, it turns out that soil moisture data can be really useful for weather and water forecasts. It can even help fix some problems with air temperature predictions.