Despite the significant progress made in solar forecasting over the last decade, most of the
proposed models cannot be readily used by independent system operators (ISOs). This …

Existing machine learning models of weather variability are not formulated to enable
assessment of their response to varying external boundary conditions such as sea surface …

Solar energy integration into the power grid requires forecasting of solar power due to the
natural variability of solar irradiance, primarily due to clouds. Recently, rooftop solar …

Improved coastal stratocumulus (Sc) cloud forecasts are needed because traditional satellite
cloud motion vectors (CMV) do not accurately predict how Sc clouds move or dissipate in …

Earth system models are developed with a tight coupling to target hardware, often containing
specialized code predicated on processor characteristics. This coupling stems from using …

Can the current successes of global machine learning‐based weather simulators be
generalized beyond 2‐week forecasts to stable and accurate multiyear runs? The recently …

We examine the evidence for large‐scale tropical hydroclimate changes over the Common
Era based on a compilation of 67 tropical hydroclimate records from 55 sites and assess the …

On the Parameterization of Convective Downdrafts for Marine Stratocumulus Clouds in:
Monthly Weather Review Volume 148 Issue 5 (2020) Jump to Content Jump to Main Navigation …

Historical observations from radiosondes, buoys, and satellite images are used to generate
an analog ensemble (AnEn) solar forecast. In coastal California, Stratocumulus (Sc) clouds …

Progress in leveraging current and emerging high-performance computing infrastructures
using traditional weather and climate models has been slow. This has become known more …