Geophysical Research Letters
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Key Points

  • The Subseasonal-to-Seasonal prediction of summer precipitation over southern China is improved with a U-Net based deep learning method

  • The U-Net demonstrated promising performance in both general statistics and extreme events and shows superiority to the quantile mapping benchmark

  • The model skills arise from precipitation itself at the early stage, while atmospheric factors play important roles at longer lead times

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The Effects of a Microplate on Plume‐Ridge Interactions: Constraints From Comparing Easter and Juan Fernandez Microplates in the Eastern Pacific Ocean

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This study investigates the nature of plume‐ridge interactions near a tectonic microplate using mantle Bouguer anomaly (MBA) gravity calculations. The focus of this investigation...

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Kilometer‐scale (k‐scale) simulations, with explicit treatment of convection at sub‐grid scales, are useful for understanding precipitation characteristics. Such simulations...

Geophysical Research Letters VOL.53 ISSUE 15 | 1 August 2026

Subsurface Vertical Connectivity Shapes Solute Transport to Montane Streams: Insights From Watershed‐Scale Geophysics‐Informed Modeling

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Headwater catchments provide essential water and nutrients to downstream ecosystems. The timing and evolution of their transport is shaped in part by the “invisible” subsurface...

Geophysical Research Letters VOL.53 ISSUE 15 | 7 August 2026

Gamma Rays Signal the Vulnerability of Forest to Extreme Drought

Gavan S McGrath + Joseph B Fontaine + Richard Van Dongen ...

Extreme drought and heat are driving forest die‐off globally, yet regional‐scale mapping of subsurface water storage capacity, governing forest vulnerability, remains a major...