Sensitivity of Mesoscale Convective System forecasting in the Sahel to synthetic sub-daily soil moisture observations using WRF

Master Thesis (2025)
Author(s)

N. Boscolo (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

S.C. Steele-Dunne – Mentor (TU Delft - Geoscience and Remote Sensing)

M.M. Messmer – Mentor (TU Delft - Atmospheric Remote Sensing)

C. M. Taylor – Mentor (UK Centre for Ecology & Hydrology)

R. Datta – Graduation committee member (TU Delft - Physical and Space Geodesy)

Faculty
Civil Engineering & Geosciences
More Info
expand_more
Publication Year
2025
Language
English
Coordinates
52.00667, 4.35556
Graduation Date
03-10-2025
Awarding Institution
Delft University of Technology
Programme
['Applied Earth Sciences']
Faculty
Civil Engineering & Geosciences
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

In semi-arid regions such as the Sahel surface soil moisture (SSM) strongly influences the partitioning between sensible and latent heat flux, with SSM anomalies on scales larger than 10 km favoring convection initiation. Mesoscale Convective Systems (MCSs) can be triggered as a result, which numerical weather prediction cannot accurately forecast with current available observational capabilities. This study investigates the sensitivity of MCS forecasting in the Sahel to synthetic sub-daily soil moisture observations using the Weather Research and Forecasting (WRF) model, in the context of the Sub-daily Land-Atmosphere INTEractions (SLAINTE) satellite mission concept. A high-resolution idealized case study was performed to assess the impact of SSM perturbations and data assimilation at different observation spatial resolutions (1 km, 5 km, 12 km) and observation times. Results indicate that synthetic observations three times per day at 5 km resolution would improve forecasting of precipitation intensity and timing. Finer resolution observations could improve forecasts only if observation noise is reduced, while 12 km resolution observations –representing the Advanced SCATterometer (ASCAT) satellite– tend to further disrupt them. The experiments highlight that at least one observation before 12:00 and an observation at 18:00 local time are necessary to constrain the forecasts sufficiently. These findings provide insight into the role of soil moisture observations for convective forecasting in semi-arid regions and contribute to defining requirements for future satellite missions such as SLAINTE.

Files

License info not available