Results 11 to 20 of about 2,660,815 (249)
Deep learning for statistical downscaling of sea states [PDF]
Advances in Statistical Climatology, Meteorology and Oceanography, 2022 Numerous marine applications require the prediction of medium- and long-term sea states. Climate models are mainly focused on the description of the atmosphere and global ocean variables, most often on a synoptic scale.
M. Michel +5 more
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A discussion of some aspects of statistical downscaling in climate impacts assessment
Shui kexue jinzhan, 2012 Global Climate Models(GCMs) are the primary tools for understanding how the global climate might change in the future.However,the relatively low spatial resolution of GCMs outputs is unsatisfactory for the local-scale climate impact assessments.Compared ...
LIU Chang-ming +3 more
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Application of Dynamical and Statistical Downscaling to East Asian Summer Precipitation for Finely Resolved Datasets [PDF]
Advances in Meteorology, 2017 Various downscaling approaches have been developed to overcome the limitation of the coarse spatial resolution of general circulation models (GCMs). Such techniques can be grouped into two approaches of dynamical and statistical downscaling.
Yoo-Bin Yhang, Soo-Jin Sohn, Il-Won Jung
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Spatial‐statistical downscaling with uncertainty quantification in biodiversity modelling
Methods in Ecology and EvolutionAccurate downscaling with uncertainty quantification and its inclusion in fitting biodiversity models to data are essential for accurate, valid inferences and predictions.
Xiaotian Zheng +4 more
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Statistical downscaling with artificial neural networks
, 2003 Statistical downscaling methods seek to model the relationship between large scale atmospheric circulation, on say a European scale, and climatic variables, such as temperature and precipitation, on a regional or sub-regional scale.
Dorling, SR +4 more
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Downscaling MODIS spectral bands using deep learning
GIScience & Remote Sensing, 2021 MODIS sensors are widely used in a broad range of environmental studies, many of which involve joint analysis of multiple MODIS spectral bands acquired at disparate spatial resolutions.
Rohit Mukherjee, Desheng Liu
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Progress in Earth and Planetary Science, 2018 The hybrid dynamical-statistical downscaling approach is an effort to combine the ability of dynamical downscaling to resolve fine-scale climate changes with the low computational cost of statistical downscaling.
Quan Tran Anh, Kenji Taniguchi
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Climate change and extreme wind speeds: An application of statistical downscaling to various climate scenarios in Northern Italy [PDF]
, 2023 openQuando parliamo di cambiamento climatico facciamo comunemente riferimento al riscaldamento globale, ma ci sono molti altri aspetti, o “sintomi”, meno evidenti. Considerando il sistema Terra nel suo insieme viene naturale ipotizzare che un cambiamento
BEVILACQUA, ARTURO
core
Advances in Climate Change Research, 2023 Extensive investigations on the projection of heat waves (HWs) were conducted on the basis of coarse-resolution global climate models (GCMs). However, these investigations still fail to characterise the future changes in HWs regionally over China. PRECIS
Ming Zhang +3 more
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Regional climate projections in two alpine river basins: Upper Danube and Upper Brahmaputra [PDF]
, 2011 Projections from coarse-grid global circulation models are not suitable for regional estimates of water balance or trends of extreme precipitation and temperature, especially not in complex terrain.
Yaoming, Ma +9 more
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