Extensive ground temperature measurements complicate our understanding of how vegetation cover, snow duration, and microtopography influence the pace of permafrost thaw in a changing climate.
Editors’ Highlights
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More Accurately Modeling Rain Formation
Rain and cloud droplets are treated as distinct categories in most models yet lie on a continuous droplet size spectrum in nature. Representing them as part of a continuous spectrum improves models.
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Explaining Uncertainty in Estimates of Rain Response to Warming
Humidity increases with warming. Theory and observations about how increased humidity translates into more extreme rainfall can be reconciled if attention is paid to data and methods.
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Satellites Remotely Measure Ocean Waves and Sea Ice Interactions
A new method for using satellite observations from multiple sensors improves measurements of ocean waves as they propagate through and interact with sea ice.
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An Ocean Surface Layer with Potential
The depth of the ocean’s surface mixed layer is typically defined based on density thresholds. However, a more physically appealing definition can be constructed from potential energy considerations.
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Protecting Children’s Health Can Benefit the Economy
A new study presents an integrated approach to predicting the human health impacts, economic implications, and remediation solutions for using contaminated groundwater in Central Mexico.
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Comparing Methods for Analysis of Atmospheric Rivers
Results from the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) describe the similarity and difference of using eleven detection algorithms and three reanalysis products.
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Volcanic Creation and Destruction of Temporary Tephra Storage
Pyroclastic density currents (PDCs) are a major threat during an explosive volcanic eruption. A new study shows that loose tephra accumulations on volcanic slopes tend to re-mobilize rapidly.
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New Western Hemisphere Moisture Mode
A new study presents the first evidence of the existence of an intraseasonal westward-propagating moisture mode over the Western Hemisphere.
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Learning from Climate Simulations for Global Seasonal Forecast
A probabilistic deep learning methodology that learns from climate simulation big data offers advantageous seasonal forecasting skill and crucial climate model diagnosis information at a global scale.