Evaluating the NASA MERRA-2 climate reanalysis and ESA CCI satellite remote sensing soil moisture over the contiguous United States

ABSTRACT

 Accurate large-scale soil moisture (SM) retrievals using the daily NASA MERRA-2’ climate reanalysis and ESA’ Climate Change Initiative (CCI) remote sensing datasets are compromised by temporal and spatial ambiguities. To address this deficiency, we assess the accuracy of the above-mentioned datasets against the Soil Climate Analysis Network (SCAN) in-situ measurements at nine sites across the contiguous United States (CONUS) during 2014–2016. The sites are selected to represent different climate regions over the CONUS. SM dynamics from NASA MERRA-2 and ESA CCI are compared with those of SCAN, and an SM dataset is developed based on a spatiotemporal analysis. Our results show that the NASA MERRA-2 and ESA CCI SM datasets have different accuracies at the nine SCAN sites in different seasons. The MERRA-2 and CCI SM datasets have the highest accuracy at sites with the lowest number of extreme events, indicating that both datasets cannot robustly capture extremum soil moisture values. The highest (lowest) agreement between the MERRA-2/CCI and SCAN SM data is observed in April (February) with the nine-site average unbiased root-mean-square-difference (ubRMSD) of 0.0638 cm³/cm³ (0.0914 cm³/cm³). In all the nine sites, the CCI SM data are more accurate than those of MERRA-2 in April–October. The CCI SM data shows greater accuracy in the sites with lower SM values and/or higher SM variability. MERRA-2 and CCI SM datasets show higher and lower accuracy at the sites with pasture and agricultural vegetation, respectively. Finally, a new SM dataset is created by using the more accurate SM data from MERRA-2 and CCI in each site and season.

KEYWORDS:

• Soil moisture
• remote sensing retrievals
• NASA
• measurement
• climate reanalysis
• SCAN
• combining datasets
• CONUS

Acknowledgements

The authors tend to have special thanks to Dr. John Nieber, Professor at the University of Minnesota for his invaluable and constructive comments on the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

Conceptualization, M.V.; methodology, M.V.; software, M.V.; validation, M.V.; formal analysis, M.V.; investigation, M.V.; resources, M.V.; data curation, M.V.; writing – original draft preparation, M.V.; writing – review and editing, M.V., S.M.B., E.H., J.D., M.A.; All authors have read and agreed to the published version of the manuscript.

Data availability statement

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Additional information

Funding

Part of this research is funded under support from the Zumberge Research and Innovation Fund of the University of Southern California allocated to the Arid Climates and Water Research Center—AWARE.