A Bayesian network inference model was developed to account for and predict the likelihood of floods of various durations using physics informed predictors.
A Bayesian network inference model was developed to account for and predict the likelihood of floods of various durations using physics informed predictors.
California precipitation is well forecast when the Arctic Oscillation phase is correctly captured by a state-of-the-art forecast system, GloSea5.
In two papers, Jin and coauthors investigated how decadal variations of subsurface ocean heat content (50–300 m) in the Indian Ocean respond to conditions in the Pacific region.
A new study shows that a simple linear model that accounts for changes in mean source distance, as well as the local drying ratio, can successfully replicate water isotopic variations in space and time.
Researchers have developed a complementary approach to creating ensembles for seasonal-average temperature and precipitation over land that can also be used to study internal variability.
A new Arctic and mid-latitude interaction study highlights the necessity to use stratosphere-resolving models when identifying the warm Arctic–cold Siberia pattern.
Observed Southern Hemisphere summer and fall trends of tropical expansion are well captured in model simulations of the late 20th and early 21st centuries, consistent with the roles of increasing greenhouse gases and stratospheric ozone depletion in driving poleward circulation shifts during these seasons.
To improve estimates of risks associated with megadroughts, researchers look at improving the understanding of ENSO/AMO behavior, their teleconnections, and their response to volcanic eruptions in climate models.
Researchers found that atmospheric rivers that impact the West Coast contain more tropical moisture than average, indicating that long-distance transport of tropical moisture does occur.
Using both observations and simulations from multiple models, researchers show that most models underestimate the amplitude of low-frequency AMOC variability.
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