Abstract
AbstractThe NASA Soil Moisture Active Passive (SMAP) mission Level‐4 Soil Moisture (L.4_SM) product provides global, 3‐hourly, 9‐km resolution estimates of surface (0–5 cm) and root zone (0–100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. In Version 4 of the L4_SM modeling system the upward recharge of surface soil moisture from below under nonequilibrium conditions was reduced, resulting in less bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation‐minus‐forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias‐adjusted root‐mean‐square error in Version 4 is 0.039 m3/m3 for surface and 0.026 m3/m3 for root zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01–0.02 m3/m3) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm/year) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.
Highlights
The Soil Moisture Ocean Salinity (SMOS; Kerr et al, 2010; Mecklenburg et al, 2016) and Soil Moisture Active Passive (SMAP; Entekhabi et al, 2010) satellite missions measure Earth's L‐band (1.4 GHz) passive microwave brightness temperature (Tb), which is highly sensitive to the water content in the top few centimeters of the soil and in the vegetation (Jackson & Schmugge, 1991; Schmugge et al, 1974)
Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates
Among the global soil moisture data sets partly based on L‐band observations is the SMAP Level‐4 Surface and Root Zone Soil Moisture (L4_SM) product (Reichle, De Lannoy, Liu, Ardizzone, et al, 2017; Reichle, De Lannoy, Liu, Koster, et al, 2017)
Summary
The Soil Moisture Ocean Salinity (SMOS; Kerr et al, 2010; Mecklenburg et al, 2016) and Soil Moisture Active Passive (SMAP; Entekhabi et al, 2010) satellite missions measure Earth's L‐band (1.4 GHz) passive microwave brightness temperature (Tb), which is highly sensitive to the water content in the top few centimeters of the soil and in the vegetation (Jackson & Schmugge, 1991; Schmugge et al, 1974). Among the global soil moisture data sets partly based on L‐band observations is the SMAP Level‐4 Surface and Root Zone Soil Moisture (L4_SM) product (Reichle, De Lannoy, Liu, Ardizzone, et al, 2017; Reichle, De Lannoy, Liu, Koster, et al, 2017). Validation with in situ measurements indicated that Version 2 of the L4_SM product met its soil moisture accuracy requirement, with a bias‐adjusted (or unbiased) root‐mean‐square error (ubRMSE, known as standard deviation of the error) of 0.038 m3/m3 (0.030 m3/m3) for surface (root zone) soil moisture at the 9‐km scale (Reichle, De Lannoy, Liu, Ardizzone, et al, 2017). When compared to in situ measurements across the globe, the L4_SM soil moisture estimates were more skillful than model‐only estimates that do not benefit from the assimilation of SMAP Tb observations (Reichle, De Lannoy, Liu, Ardizzone, et al, 2017). In effect, we quantify the performance of the Version 4 product relative to the documented performance of the Version 2 data (Reichle, De Lannoy, Liu, Ardizzone, et al, 2017; Reichle, De Lannoy, Liu, Koster, et al, 2017)
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