Learning skillful medium-range global weather forecasting
Global medium-range weather forecasting is critical to decision-making across many social
and economic domains. Traditional numerical weather prediction uses increased compute …
and economic domains. Traditional numerical weather prediction uses increased compute …
WeatherBench 2: A benchmark for the next generation of data‐driven global weather models
WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting
benchmark proposed by (Rasp et al., 2020, https://doi. org/10.1029/2020ms002203) …
benchmark proposed by (Rasp et al., 2020, https://doi. org/10.1029/2020ms002203) …
A machine learning model that outperforms conventional global subseasonal forecast models
Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand
scientific challenge. Recently, machine learning-based weather forecasting models …
scientific challenge. Recently, machine learning-based weather forecasting models …
Climatelearn: Benchmarking machine learning for weather and climate modeling
Modeling weather and climate is an essential endeavor to understand the near-and long-
term impacts of climate change, as well as to inform technology and policymaking for …
term impacts of climate change, as well as to inform technology and policymaking for …
The South American monsoon approaches a critical transition in response to deforestation
The Amazon rainforest is threatened by land-use change and increasing drought and fire
frequency. Studies suggest an abrupt dieback of large parts of the rainforest after partial …
frequency. Studies suggest an abrupt dieback of large parts of the rainforest after partial …
Challenges in the attribution of river flood events
P Scussolini, LN Luu, S Philip… - Wiley …, 2024 - Wiley Online Library
Advances in the field of extreme event attribution allow to estimate how anthropogenic
global warming affects the odds of individual climate disasters, such as river floods. Extreme …
global warming affects the odds of individual climate disasters, such as river floods. Extreme …
Generative emulation of weather forecast ensembles with diffusion models
Uncertainty quantification is crucial to decision-making. A prominent example is probabilistic
forecasting in numerical weather prediction. The dominant approach to representing …
forecasting in numerical weather prediction. The dominant approach to representing …
Global hydrological reanalyses: The value of river discharge information for world‐wide downstream applications–The example of the Global Flood Awareness …
C Prudhomme, E Zsótér, G Matthews… - Meteorological …, 2024 - Wiley Online Library
Global hydrological reanalyses are modelled datasets providing information on river
discharge evolution everywhere in the world. With multi‐decadal daily timeseries, they …
discharge evolution everywhere in the world. With multi‐decadal daily timeseries, they …
Evaluation of ERA5 precipitation and 10‐m wind speed associated with extratropical cyclones using station data over North America
While the ERA5 reanalysis is commonly utilized in climate studies on extratropical cyclones
(ETCs), only a few studies have quantified its ability in the representation of ETCs over land …
(ETCs), only a few studies have quantified its ability in the representation of ETCs over land …
[HTML][HTML] Where does the link between atmospheric moisture transport and extreme precipitation matter?
L Gimeno-Sotelo, L Gimeno - Weather and Climate Extremes, 2023 - Elsevier
Atmospheric moisture transport is the primary component of the atmospheric branch of the
water cycle, and its anomalies strongly influence drought and precipitation extremes. We …
water cycle, and its anomalies strongly influence drought and precipitation extremes. We …