Statistical downscaling based on dynamically downscaled predictors: Application to monthly precipitation in Sweden [PDF]
Advances in Atmospheric Sciences, 2003 A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors.
Cecilia Hellström, Deliang Chen
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Climate Services, 2018 This work describes the results of a comprehensive intercomparison experiment of dynamical and statistical downscaling methods performed in the framework of the SPECS (http://www.specs-fp7.eu) and EUPORIAS (http://www.euporias.eu) projects for seasonal ...
R. Manzanas +7 more
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Testing Reanalyses in Constraining Dynamical Downscaling
Journal of the Meteorological Society of Japan. Ser. II, 2016 Reanalysis data sets have been widely used in regional climate dynamical downscaling studies. In this study, we test the use of various reanalysis data sets in constraining dynamical downscaling by assessing the reconstruction skill of the Yellow Sea coastal winds using the COSMO model in Climate Mode (CCLM) with 7-km resolution.
Li, D., Storch, H.v., Geyer, B.
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Review of Downscaling Methodologies for Africa Climate Applications [PDF]
, 2008 Downscaling is the term used to describe the various methods used to translate the climate projections from coarse resolution GCMs to finer resolutions deemed more useful for assessing impacts.
Block, Paul J. +3 more
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Efficient dynamical downscaling of general circulation models using continuous data assimilation [PDF]
, 2019 Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dynamical downscaling of a global atmospheric reanalysis.
Biswas A. +10 more
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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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Projected Changes in Temperature and Precipitation over Kashafrood Basin Based on Statistical and Dynamical Downscaling Methods [PDF]
مخاطرات محیط طبیعی, 2021 It is well-known that climate is changing continuously under the intricate influences of natural and artificial factors at global and regional scales. The global Coupled Model Intercomparison Project (CMIP) already provides multi model data resources in ...
Hooshmand Ataei +3 more
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Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction [PDF]
, 2013 When correcting for biases in general circulation model (GCM) output, for example when statistically downscaling for regional and local impacts studies, a common assumption is that the GCM biases can be characterized by comparing model simulations and ...
Cayan, Daniel R. +2 more
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A frailty-contagion model for multi-site hourly precipitation driven by atmospheric covariates [PDF]
, 2014 Accurate stochastic simulations of hourly precipitation are needed for impact studies at local spatial scales. Statistically, hourly precipitation data represent a difficult challenge.
Koch, Erwan, Naveau, Philippe
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Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies [PDF]
, 2016 Statistical downscaling is a commonly used technique for translating large-scale climate model output to a scale appropriate for assessing impacts. To ensure downscaled meteorology can be used in climate impact studies, downscaling must correct biases in
Ficklin, Darren L. +2 more
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