Daily rainfall frequency distributions and their impacts on simulated hydrological fields in land-surface models
Abstract
Precipitation estimates using remotely-sensed products are a critical driver for land-surface models in regions where conventional observational data are sparse. The Famine Early Warning Systems Network (FEWS NET) land data assimilation system (FLDAS), which uses the NASA Land Information System (LIS) software framework, integrates remotely-sensed products and land surface models to simulate hydrological variables and aid in drought monitoring of food insecure regions in Africa. The accuracy of the precipitation data ingested by FLDAS is critical for reliable drought and food security monitoring. Total precipitation accumulation and daily distribution of rainfall varies between precipitation products. This study investigates the impact of daily rainfall distributions on FLDAS simulations of hydrological variables such as soil moisture, evapotranspiration, and runoff. This study compares two rainfall products: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS2) rainfall product and a derived product that was created by mapping the total accumulated rainfall of CHIRPS2 to a daily rainfall frequency matching that of the Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation product. Our study shows that changing the daily rainfall frequency distribution reduces the errors in the simulated surface soil moisture when compared to data retrieved by the Soil Moisture Active Passive (SMAP) mission over CONUS. Small improvements in simulated evapotranspiration were also seen in the winter when compared to the Simplified Surface Energy Balance (SSEBop) model data over CONUS. Our study indicates that modification of currently available precipitation products to incorporate different daily rainfall distributions while maintaining the total rainfall accumulation constant is a viable technique to improve land surface modeling efforts to support early warning systems in food insecure regions. Quantification of changes in hydrological variables caused by modifying the daily rainfall distribution can help guide future versions of remotely-sensed precipitation products.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMH194.0007S
- Keywords:
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- 1804 Catchment;
- HYDROLOGY;
- 1843 Land/atmosphere interactions;
- HYDROLOGY;
- 1846 Model calibration;
- HYDROLOGY;
- 1847 Modeling;
- HYDROLOGY