Sensitivity of Soil Moisture Analyses to Contrasting Background and Observation Error Scenarios

Sensitivity of Soil Moisture Analyses to Contrasting Background and Observation Error Scenarios

Sensitivity of Soil Moisture Analyses to Contrasting Background and Observation Error Scenarios

Joaquín Muñoz-Sabater, Patricia de Rosnay, Clément Albergel and Lars Isaksen

Abstract

Soil moisture is a crucial variable for numerical weather prediction. Accurate, global initialization of soil moisture is obtained through data assimilation systems. However, analyses depend largely on the way observation and background errors are defined. In this study, a wide range of short experiments with contrasted specifications of the observation error and soil moisture background were conducted.

As observations, screen-level variables and brightness temperatures from the Soil Moisture and Ocean Salinity (SMOS) mission were used. The region of interest is North America, given the good availability of in situ observations and mixture of different climates, making it a good test for global applications. The impact of these experiments on soil moisture and the atmospheric layer near the surface were evaluated.

The results highlighted the importance of assimilating observations sensitive to soil moisture for air temperature and humidity forecasts. The benefits on predicting the soil water content were more noticeable with increasing the SMOS observation error, and with the introduction of soil texture dependency in the soil moisture background error.

Keywords : soil moisture; SMOS; data assimilation

Water   2018 10 (7), 890; https://doi.org/10.3390/w10070890 

Muñoz-Sabater, J.; de Rosnay, P.; Albergel, C.; Isaksen, L. Sensitivity of Soil Moisture Analyses to Contrasting Background and Observation Error Scenarios.  Water   2018 10 , 890. 

Source: MDPI