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Grillakis et al. (2021) Regionalizing Root‐Zone Soil Moisture Estimates From ESA CCI Soil Water Index Using Machine Learning and Information on Soil, Vegetation, and Climate
> ⚠️ **Warning:** This summary was generated from the **abstract only**, as the full text was not available. This study addresses the limitation of shallow sensing depth (2–5 cm) in the ESA CCI soil moisture dataset by developing a methodology to estimate root-zone soil moisture (RZSM). By calibrating the Soil Water Index (SWI) using in situ observations and leveraging machine learning techniques with global physical descriptors, the researchers successfully derived RZSM for the period 2001–2018, demonstrating good agreement with established reanalysis products like ERA5 Land, particularly over mid-latitudes....
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Massari et al. (2021) A Review of Irrigation Information Retrievals from Space and Their Utility for Users
This paper reviews existing Earth observation (EO) datasets, models, and algorithms used for mapping and quantifying irrigation water use, contrasting current monitoring capabilities with user requirements derived from a survey to identify shortcomings and propose guidelines for future satellite missions.
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Stefan et al. (2021) High-Resolution SMAP-Derived Root-Zone Soil Moisture Using an Exponential Filter Model Calibrated per Land Cover Type
This study tests a simple recursive exponential filter, calibrated by land cover type using ISBA-DIF data, to derive 1 km resolution Root-Zone Soil Moisture (RZSM) from downscaled SMAP Surface Soil Moisture (SSM), finding strong validation results over rainfed crop sites in Catalonia, NE Spain.
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Ward et al. (2021) Synoptic timescale linkage between midlatitude winter troughs Sahara temperature patterns and northern Congo rainfall: A building block of regional climate variability
This study identifies and characterizes a coherent synoptic sequence during November–March where upper-level midlatitude troughs over Iberia or the Central Mediterranean induce near-surface warming across the Sahara, which subsequently leads to statistically predictable rainfall events over Northern Congo (NC).
