Results 211 to 220 of about 8,007 (257)
Review ofPerformance of snow density measurement systems in snow stratigraphies
, 2020 openaire +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.This study develops a method to identify the source areas of precipitation events, as illustrated for the western part of the Netherlands. Radar‐based precipitation data are traced back to their source areas and machine‐learning techniques are used to identify hypothesized causes: urban heat, surface roughness, and air pollution. We find that urban and
Jelmer van der Graaff +1 more
wiley +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.Daily time series of zonal‐mean zonal wind (m·s−1) at 10 hPa and 60° N from 1950 to 2021 from the ERA5 reanalysis. This shows huge variability in some seasons and very little in others. We provide evidence that high‐level observations, radiosonde and satellite, are more important during the extended winter season with its very large variability ...
Bruce Ingleby, Inna Polichtchouk
wiley +1 more source
An opportunity index to anticipate when subseasonal predictions are useful
Quarterly Journal of the Royal Meteorological Society, EarlyView.Simultaneously active subseasonal windows of forecast opportunity can be combined into a single opportunity index, which can be used operationally to anticipate enhanced or reduced subseasonal prediction skill. For predictions of temperature anomalies in Switzerland during summer—a region and season with particularly low predictability—skill can nearly
Dominik Büeler +4 more
wiley +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.We document the protocol and first results from the first ever coordinated multimodel variable‐resolution experiment set with refinement over the polar regions. We find that the refinement generally yields model‐dependent effects. The most consistent improvement is an amelioration of the upper‐level cold bias in the polar regions that translates into ...
Lise Seland Graff +8 more
wiley +1 more source
Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning
Quarterly Journal of the Royal Meteorological Society, EarlyView.Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis +7 more
wiley +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.Abstract The presence of Arctic clouds plays a crucial role in the evolution of the surface temperature of Arctic sea ice. However, large biases in cloud representation remain in state‐of‐the‐art weather and climate models. In this study, we use observational data from the one‐year Arctic ship campaign Multi‐disciplinary drifting Observatory for the ...
Luise Schulte +5 more
wiley +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.The climatological‐error covariance matrix used in three‐dimensional variational data assimilation (3DVar) provides smooth and isotropic increments spread to long distances. In contrast, three‐dimensional ensemble variational data assimilation (3DEnVar) with a purely ensemble‐error covariance matrix provides inhomogeneous increments and contains the ...
Kaushambi Jyoti +3 more
wiley +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie +3 more
wiley +1 more source
Forecast‐Error Diagnostics in Neural Weather Models
Quarterly Journal of the Royal Meteorological Society, EarlyView.Deep learning weather prediction models enable efficient forecast‐error diagnostics through auto‐differentiation and low computational cost. We apply grid‐point relaxation and gradient‐based error sensitivity to identify key forecast‐error sources. Results show that medium‐range forecasts in the midlatitudes benefit most from relaxing the stratosphere ...
Uroš Perkan +2 more
wiley +1 more source