Print Email Facebook Twitter Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data Title Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data Author Lu, Y. (TU Delft Water Resources) Steele-Dunne, S.C. (TU Delft Water Resources) Farhadi, Leila van de Giesen, N.C. (TU Delft Water Resources) Date 2017 Abstract Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large. To reference this document use: http://resolver.tudelft.nl/uuid:cc396287-0ff6-4c99-94d5-932fca38d766 DOI https://doi.org/10.1002/2017WR021415 ISSN 0043-1397 Source Water Resources Research, 53 (12), 10858–10877 Part of collection Institutional Repository Document type journal article Rights © 2017 Y. Lu, S.C. Steele-Dunne, Leila Farhadi, N.C. van de Giesen Files PDF Lu_et_al_2017_Water_Resou ... search.pdf 4.37 MB Close viewer /islandora/object/uuid:cc396287-0ff6-4c99-94d5-932fca38d766/datastream/OBJ/view