Results 231 to 240 of about 4,321,601 (325)
A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation. [PDF]
Schmidt J +4 more
europepmc +1 more source
Strategies for Statistical‐Dynamical Downscaling to Urban Climate Using Global Data
For the statistical part of statistical‐dynamical downscaling, a new formulation for the climate statistics is found. For the dynamical part of statistical‐dynamical downscaling, one‐way nesting with three nests (HH250) and one times nesting with a non‐uniform grid (HH6to250) are performed and evaluated.
Marita Boettcher +6 more
wiley +1 more source
Regional climate projections using a deep-learning-based model-ranking and downscaling framework: application to European climate zones. [PDF]
Loganathan P, Zea E, Vinuesa R, Otero E.
europepmc +1 more source
Statistical and dynamical downscaling methods are tested for their reproduction of compound dry‐hot events, using three representatives of each category. Statistical methods are found to better detect when they are produced, whereas dynamical downscaling better simulates their distribution over the whole period.
M. N. Legasa, A. Casanueva, R. Manzanas
wiley +1 more source
Fusion of multi-source precipitation records via coordinate-based generative models. [PDF]
Sun S +7 more
europepmc +1 more source
Google Earth Engine was utilised to assess snow cover area (SCA) across eight Upper Indus Basin (UIB) subbasins, employing ARIMA for prediction and comparing MODIS datasets using Dunn's test. Spatiotemporal changes were analysed using MK, Sen's slope, and other statistical tests.
Hafsa Muzammal +4 more
wiley +1 more source
Dynamical-generative downscaling of climate model ensembles. [PDF]
Lopez-Gomez I +5 more
europepmc +1 more source
To bridge the discrepancy between pre‐1997 sparse wind observations and post‐1997 high‐frequency data, we simulate historical daily wind observations from 10‐min data (1997–2023). These simulations enable spatially consistent wind speed estimations across Hungary using MASH homogenisation and MISH interpolation, with seasonal differences evaluated ...
Kinga Bokros +3 more
wiley +1 more source
Limitation of super-resolution machine learning approach to precipitation downscaling. [PDF]
Reddy PJ +3 more
europepmc +1 more source
Difference of monthly mean TC‐related precipitation (mm) during JAS over the EA between the SSP245 run and the CTL run in (a) TC core precipitation (TCP) + TC remote precipitation (TRP), (b) TCP and (c) TRP. ABSTRACT Climate change has fundamentally altered tropical cyclone (TC) characteristics globally, with TC‐related precipitation emerging as a ...
Jiwei Wu +3 more
wiley +1 more source

