Abstract:
This report closely examines Version 7 of the NASA Soil Moisture Active Passive (SMAP) Level 4 Surface and Root Zone Soil Moisture (L4_SM) product, which was first released on 15 November 2022. The assessment includes comparisons of L4_SM soil moisture estimates with in situ measurements from SMAP core validation sites and sparse networks. Also provided is a quasi-global evaluation of the product’s anomaly correlation skill relative to the previous version and a model-only version, based on independent satellite radar soil moisture retrievals and an Instrumental Variable approach. The assessment further provides a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product, including observation-minus-forecast (O-F) brightness temperature (Tb) residuals and soil moisture analysis increments. The core validation site comparisons, the assessment of the anomaly correlation skill using independent radar soil moisture retrievals, and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to upscaling errors from their native point-scale to the grid-cell scale of the data product. The validation period is April 2015 to March 2022.

The two key changes in the Version 7 L4_SM product relative to earlier versions are (i) improved hydrological process modeling for peatlands (PEATCLSM) and an updated global distribution of peatlands and (ii) the use of climatological L-band soil roughness, scattering albedo, and (seasonally varying) vegetation opacity parameters derived from the SMAP Level 2 soil moisture retrieval product.

An analysis of the time-average surface and root zone soil moisture shows that the global pattern of arid and humid regions is well captured by the Version 7 L4_SM estimates. In peatlands, the Version 7 surface soil moisture is somewhat wetter on average with much increased variability compared to that of Version 6, and the root zone soil moisture is much wetter, owing to the new peatland hydrology module. These changes are also reflected in the surface turbulent fluxes and in the surface and soil temperatures. Because of these climatological differences, the Version 6 and Version 7 products should not be combined into a single dataset for use in applications that include peatlands.

Results from the core validation site comparisons indicate that the Version 7 L4_SM product meets its accuracy requirement, which is formulated in terms of the root-mean square (RMS) error after removal of the long-term mean error, i.e., ubRMSE≤0.04 m3 m-3, where the error is vs. the unknown true soil moisture. Computed directly against core site in situ measurements at the 9-km scale, the average unbiased RMS difference (ubRMSD) of the 3-hourly Version 7 L4_SM data is 0.041 m3 m 3 for surface soil moisture and 0.026 m3 m-3 for root zone soil moisture. When factoring in measurement and upscaling errors of the in situ data, the L4_SM product meets the 0.04 m3 m-3 ubRMSE requirement.

The ubRMSD values of the Version 7 soil moisture are essentially unchanged from those of Version 6. There is a small but consistent increase in the correlation skill of the Version 7 surface and root zone soil moisture, likely owing to the improved seasonal cycle amplitude and phasing of the L-band vegetation opacity parameters derived from the SMAP Level 2 retrieval product.

The Version 7 L4_SM estimates are an improvement compared to estimates from a model-only Open Loop (OL7000) simulation, which demonstrates the beneficial impact of the SMAP Tb data. Overall, L4_SM surface and root zone soil moisture estimates are more skillful than model-only simulation (OL7000) estimates, with statistically significant improvements for surface soil moisture R and anomaly R values (based on 95% confidence intervals). Results from comparisons of the L4_SM product to in situ measurements from more than 400 sparse network sites corroborate the core validation site results.

The new peatland water level output of the Version 7 L4_SM product provides reasonable estimates, as indicated by the validation of retrospective simulations with the L4_SM land model against historic in situ measurements.

The evaluation of the anomaly correlation skill based on independent radar soil moisture retrievals indicates that there is no net skill difference between the Version 6 and Version 7 L4_SM products. This is expected because the key changes in the Version 7 L4_SM algorithm are limited to peatlands and climatological model parameters.

The instantaneous soil moisture analysis increments lie within a reasonable range and result in spatially smooth soil moisture analyses. The long-term mean soil moisture analysis increments make up only a small fraction of the water budget. Regionally, the O-F Tb residuals exhibit only a modest bias (less than 3 K) between the (rescaled) SMAP Tb observations and the L4_SM model forecast, which indicates that the assimilation system is reasonably unbiased. The globally averaged time series standard deviation of the O-F Tb residuals is 5.0 K, which represents a reduction of ~0.1 K from that of the Version 6 product. The globally averaged time series standard deviation is 3.3 K for the observation-minus-analysis Tb residuals, reflecting the impact of the SMAP observations on the L4_SM system. The Tb simulation skill is most improved in peatlands, with average reductions in the typical magnitude of the O-F Tb residuals exceeding 1 K in northern peatlands.

Regionally, the time series standard deviation of the normalized O-F Tb residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm tends to over- or underestimate the total (model and observation) error present in the system. There is no net difference in this metric between the Version 6 and Version 7 L4_SM algorithms.

In summary, Version 7 of the L4_SM product is sufficiently mature and of suitable quality for distribution to, and use by, the larger science and application communities.