Our Research

BLOSM: Boron-based Large scale Observation of Soil Moisture

Measuring soil moisture in the field at a scale comparable to that of satellite pixels or model raster cells is a central hydrological problem for calibration and validation. Using the standard gravimetric method, this involves taking many (100-1000) samples, which can only be achieved through expensive field campaigns. There is one way to measure soil moisture at a scale of about 30 hectares and that is, somewhat surprisingly, by measuring fast and slow neutrons at a point.

The GNSS navigation system for meteorology

GPS/GNSS sensors located at fixed positions can be exploited to derive measures of the atmospheric water vapor content with accuracies comparable to conventional instruments. Existing widespread networks of fixed GNSS stations could provide currently unavailable meteorological information to enhance the prediction of heavy rainfall. This innovative potential use of GNSS can be further boosted by the exploitation of low-cost sensors, made available thanks to technological advancements fostered by mass market applications of GPS/GNSS for navigation

New sensitivity studies for better heavy rainfall forecasts

Numerical Weather Prediction (NWP) models rely on numerous parameterizations to represent atmospheric processes that cannot be explicitly quantified because they happen on very small scales, such as droplet formation. However, these parameterizations are critical for a correct forecast of heavy rainfall. New sensitivity experiments have highlighted how important the mixing in the lower atmosphere is to correctly reproduce heavy rainfall dynamics

A fast and robust algorithm for the generation of SAR atmospheric water vapor maps

SAR images from the Copernicus Sentinel 1 satellite mission can be used to derive the distribution of atmospheric water vapor over large areas at a very high spatial resolution. A novel algorithm was developed and implemented to extract such snapshots for meteorological applications

Optimization tool for monitoring networks using satellite rainfall estimates

Monitoring networks set up by national weather services often follow generalized guidelines for instrument density. The World Meteorological Organization as well as the TAHMO initiative suggest station densities depending on the geographical setting. Especially in Africa, optimal densities are often not met, as a result of management issues but to a large degree in available resources required to install, operate and maintain dense monitoring networks. In such context of resource scarcity, knowledge of where and when additional monitoring adds the highest value not only improves data quality but also assists in planning networks more efficiently.