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Assimilation of SMAP Brightness Temperature Observations in the GEOS Land-Atmosphere Data Assimilation System
Rolf H Reichle1, Sara Q Zhang1, Qing Liu1
1Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
|November 25, 2021
Summary
Assimilation of Soil Moisture Active Passive (SMAP) mission data into the NASA Goddard Earth Observing System (GEOS) weakly coupled land-atmosphere data assimilation system (LADAS) significantly improves soil moisture and near-surface atmospheric condition modeling. This enhances land-atmosphere coupling accuracy in weather forecasting.
Area of Science:
- Earth Science
- Atmospheric Science
- Hydrology
Background:
- Errors in soil moisture modeling negatively impact land-atmosphere water and energy flux simulations within atmospheric data assimilation systems (ADAS).
- The NASA Goddard Earth Observing System (GEOS) ADAS currently lacks a land surface analysis component, potentially limiting accuracy.
- Integrating satellite observations can enhance the performance of coupled land-atmosphere data assimilation systems.
Purpose of the Study:
- To investigate the assimilation of L-band brightness temperature (Tb) observations from the Soil Moisture Active Passive (SMAP) mission.
- To evaluate the impact of SMAP Tb assimilation within the GEOS weakly coupled land-atmosphere data assimilation system (LADAS).
- To assess improvements in soil moisture and near-surface atmospheric conditions during boreal summer 2017.
Main Methods:
- Assimilation of L-band brightness temperature (Tb) observations from the Soil Moisture Active Passive (SMAP) mission.
- Utilized the GEOS weakly coupled land-atmosphere data assimilation system (LADAS) for boreal summer 2017.
- Compared LADAS results against GEOS ADAS estimates and in situ measurements.
Main Results:
- SMAP Tb assimilation improved soil moisture correlation with in situ data by ~0.1-0.26 and reduced unbiased root-mean-square error by 0.002-0.008 m3/m3.
- Global land average RMSE for specific humidity (q2m) and daily maximum temperature (T2mmax) decreased by 0.05 g/kg and 0.04 K, respectively.
- Regional RMSE improvements for q2m and T2mmax reached up to 0.4 g/kg and 0.3 K, with humidity improvements extending into the lower troposphere.
Conclusions:
- SMAP Tb assimilation in GEOS LADAS demonstrably enhances soil moisture and near-surface atmospheric variable accuracy.
- The assimilation positively impacts modeled land-atmosphere coupling, as evidenced by reduced Tb observation-minus-forecast residuals.
- This study highlights the benefit of incorporating satellite soil moisture observations into coupled land-atmosphere data assimilation systems.
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