Enhancing Regional Climate Downscaling through Advances in Machine Learning
Despite the sophistication of global climate models (GCMs), their coarse spatial resolution
limits their ability to resolve important aspects of climate variability and change at the local …
limits their ability to resolve important aspects of climate variability and change at the local …
Generative residual diffusion modeling for km-scale atmospheric downscaling
The state of the art for physical hazard prediction from weather and climate requires
expensive km-scale numerical simulations driven by coarser resolution global inputs. Here …
expensive km-scale numerical simulations driven by coarser resolution global inputs. Here …
A fusion-based framework for daily flood forecasting in multiple-step-ahead and near-future under climate change scenarios: a case study of the Kan River, Iran
This study proposes a novel fusion framework for flood forecasting based on machine-
learning, statistical, and geostatistical models for daily multiple-step-ahead and near-future …
learning, statistical, and geostatistical models for daily multiple-step-ahead and near-future …
Association of precipitation extremes and crops production and projecting future extremes using machine learning approaches with CMIP6 data
Precipitation extremes have surged in frequency and duration in recent decades,
significantly impacting various sectors, including agriculture, water resources, energy, and …
significantly impacting various sectors, including agriculture, water resources, energy, and …
Residual Diffusion Modeling for Km-scale Atmospheric Downscaling
Predictions of weather hazard require expensive km-scale simulations driven by coarser
global inputs. Here, a cost-effective stochastic downscaling model is trained from a high …
global inputs. Here, a cost-effective stochastic downscaling model is trained from a high …
On the Extrapolation of Generative Adversarial Networks for downscaling precipitation extremes in warmer climates
While deep-learning downscaling algorithms can generate fine-scale climate projections
cost-effectively, it is still unclear how well they will extrapolate to unobserved climates. We …
cost-effectively, it is still unclear how well they will extrapolate to unobserved climates. We …
[PDF][PDF] An LSTM-based downscaling framework for Australian precipitation projections
Understanding potential changes in future rainfall and their local impacts on Australian
communities can inform adaptation decisions worth billions of dollars in insurance …
communities can inform adaptation decisions worth billions of dollars in insurance …