Impact of Surface Soil Moisture Retrieval Time Frequency on Land Surface Regime Detection Skill
Soil moisture (θ) thresholds associated with nonlinear changes in soil water loss rates can be used to detect transitions between land surface water flux regimes. Since such regimes are characterized by distinct soil water loss processes (e.g., energy- versus water-limited evapotranspiration), their identification is useful for applications reliant on the accurate parameterization of land surface water and energy fluxes. The most direct method for such regime detection is the time differencing of successive θ retrievals acquired from satellite-based, L-band microwave data records. The detection of regime transitions, and their associated θ thresholds, requires access to long-term historical θ data sets. As a result, traceable measurement requirements must be defined to ensure that future satellite missions can sample θ at temporal frequencies required for priority science applications reliant on the characterization of θ thresholds. Here, we perform a synthetic analysis to examine the impact of satellite θ temporal sampling frequency on water-flux regime detection skill based on the differencing of a retrieved θ time series. Globally, results suggest a sharp reduction in regime-detection skill when the inverse (τ) of this frequency exceeds a threshold value in the range of 2 to 4 days. Therefore, to directly contribute to land surface regime-detection applications, future satellite soil moisture missions must sample θ retrievals at τ ≤ 4 days.
Authors
- Rajat Bindlish (ORCID: https://orcid.org/0000-0002-1913-0353)
- Andrew F. Feldman (ORCID: https://orcid.org/0000-0003-1547-6995)
- Wade T. Crow (ORCID: https://orcid.org/0000-0002-8217-261X)
Institutions
- Goddard Space Flight Center (US)
- Agricultural Research Service (US)
Publication Details
- Journal
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/jstars.2025.3596474
- Citations
- 1
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.80