[HTML][HTML] ENSO analysis and prediction using deep learning: a review
Abstract El Niño/Southern Oscillation (ENSO) mainly occurs in the tropical Pacific Ocean
every a few years. But it affects the climate around the world and has a dramatic impact on …
every a few years. But it affects the climate around the world and has a dramatic impact on …
Training machine learning models on climate model output yields skillful interpretable seasonal precipitation forecasts
PB Gibson, WE Chapman, A Altinok… - … Earth & Environment, 2021 - nature.com
A barrier to utilizing machine learning in seasonal forecasting applications is the limited
sample size of observational data for model training. To circumvent this issue, here we …
sample size of observational data for model training. To circumvent this issue, here we …
Tree rings and observations suggest no stable cycles in Sierra Nevada cool‐season precipitation
AP Williams, KJ Anchukaitis… - Water Resources …, 2021 - Wiley Online Library
California's water resources rely heavily on cool‐season (November–March) precipitation in
the Sierra Nevada. Interannual variability is highly volatile and seasonal forecasting has little …
the Sierra Nevada. Interannual variability is highly volatile and seasonal forecasting has little …
Literature survey of subseasonal‐to‐seasonal predictions in the southern hemisphere
S Phakula, WA Landman… - Meteorological …, 2024 - Wiley Online Library
Abstract Subseasonal‐to‐seasonal (S2S) prediction has gained momentum in the recent
past as a need for predictions between the weather forecasting timescale and seasonal …
past as a need for predictions between the weather forecasting timescale and seasonal …
A joint approach combining correlation and mutual information to study land and ocean drivers of us droughts: Methodology
Normalized mutual information (NMI) is a nonparametric measure of the dependence
between two variables without assumptions about the shape of their bivariate data …
between two variables without assumptions about the shape of their bivariate data …
Introducing long‐term trends into subseasonal temperature forecasts through trend‐aware postprocessing
Skilful subseasonal forecasts are crucial for issuing early warnings of extreme weather
events, such as heatwaves and floods. Operational subseasonal climate forecasts are often …
events, such as heatwaves and floods. Operational subseasonal climate forecasts are often …
Sources of subseasonal predictability over CONUS during boreal summer
V Krishnamurthy, J Meixner, L Stefanova… - Journal of …, 2021 - journals.ametsoc.org
The predictability of the Unified Forecast System (UFS) Coupled Model Prototype 2
developed by the National Centers for Environmental Prediction is assessed for the boreal …
developed by the National Centers for Environmental Prediction is assessed for the boreal …
Oceanic meridional transports and their roles in warm water volume variability and ENSO in the tropical Pacific
The fluctuation of the subsurface ocean heat condition along the equatorial Pacific is
associated with the mass/heat exchanges between the equatorial and off-equatorial regions …
associated with the mass/heat exchanges between the equatorial and off-equatorial regions …
Sensitivity of US drought prediction skill to land initial states
In addition to remote SST forcing, realistic representation of land forcing (ie, soil moisture)
over the United States is critical for a prediction of US severe drought events approximately …
over the United States is critical for a prediction of US severe drought events approximately …
Improving the CFSv2 Seasonal Precipitation Forecasts across the United States by Combining Weather Regimes and Gaussian Mixture Models
Although seasonal climate forecasts have major socioeconomic impacts, current forecast
products, especially those for precipitation, are not yet reliable for forecasters and decision …
products, especially those for precipitation, are not yet reliable for forecasters and decision …