Modern climate models use both deterministic and stochastic parametrization schemes to represent uncertainties in their physics and inputs. This work considers the problem of …
The accuracy of initial conditions is an important driver of the forecast skill of numerical weather prediction models. Increases in the quantity of available measurements, in …
Floods caused by atmospheric rivers and wildfires fanned by Santa Ana winds are common occurrences in California with devastating societal impacts. In this work, we show that …
The effect of polar sea ice melt on low latitude climate is little known. To understand the response of the Indian summer monsoon (ISM) synoptic activity to the sea ice melt, we …
Deep-learning (DL) postprocessing methods are examined to obtain reliable and accurate probabilistic forecasts from single-member numerical weather predictions of integrated …
In oceanography, as in any scientific field, the goal is not to eliminate uncertainty in data, but instead to better quantify and clearly communicate its size and nature.
Quantifying uncertainty associated with our models is the only way we can express how much we know about any phenomenon. Incomplete consideration of model-based uncertainties …
Waves generated by tropical cyclones can have devastating effects on coastal regions. However, the role of ocean currents in modifying wave amplitudes, wavelengths, and …
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