A Unified Ensemble Soil Moisture Dataset Across the Continental United States

A unified ensemble soil moisture (SM) package has been developed over the Continental United States (CONUS). The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. All datasets are unified to a 0.25-degree and monthly spatiotemporal resolution, covering various temporal spans and providing a comprehensive view of surface SM dynamics. The statistical analysis of the datasets leverages the Koppen-Geiger Climate Classification to explore surface SM’s spatiotemporal variabilities. The extracted SM characteristics highlight distinct patterns, with the western CONUS showing larger coefficient of variation values and the eastern CONUS exhibiting higher SM values. Remote sensing datasets tend to be drier, while reanalysis products present wetter conditions. In-situ SM observations serve as the basis for wavelet power spectrum analyses to explain discrepancies with respect to temporal scales across the 16 datasets facilitating daily SM records. This study provides a comprehensive soil moisture data package and an analysis framework that can be used for Earth system model evaluations and uncertainty quantification, quantifying drought impacts and land–atmosphere interactions, and making recommendations for drought response planning.

Data details: 1. scripts: 1) process data from original spatial resolution to 0.25 degree; 2) process data from original temporal resolution to monthly; 3) process the monthly data to seasonal mean analysis; 4) wavelet analysis. 2. data: 1) monthly 0.25deg data processed from raw datasets; 2) monthly and seasonal climatology data for comparison; 3) site data for wavelet analysis.

Reference: The data manuscript is under review now and will add it here later.

Contact: Mingjie Shi <mingjie.shi@pnnl.gov>; Lingcheng Li <lingcheng.li@pnnl.gov>