Results 1 to 10 of about 2,888 (290)
Dynamical downscaling of GloSea5 over Ethiopia
Climate Services, 2018 We have implemented dynamical downscaling of the Met Office GloSea5 global seasonal forecasting system and analysed its ability to generate skilful forecasts of characteristics of the June-September rainy season in Ethiopia that are of societal relevance. The downscaling used a regional model with a resolution of 25 km, and the same atmosphere and land
S. Tucker +4 more
core +4 more sources
Verification of statistical-dynamical downscaling in the Alpine region [PDF]
Climate Research, 1996 A statistical-dynamical downscaling procedure for global climate sirnulations is verified for the greater Alpine region. This procedure links global and regional model simulations using frequencies of large-scale weather types in order to derive the regional climate corresponding to a given global climate. The results from multi-year global simulations
Fuentes, U., Heimann, D.
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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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Dynamical-generative downscaling of climate model ensembles. [PDF]
Proc Natl Acad Sci U S ARegional high-resolution climate projections are crucial for many applications, such as agriculture, hydrology, and natural hazard risk assessment. Dynamical downscaling, the state-of-the-art method to produce localized future climate information, involves running a regional climate model (RCM) driven by an Earth System Model (ESM), but it is too ...
Lopez-Gomez I +5 more
europepmc +4 more sources
Regional Dynamical Downscaling and the CORDEX Initiative [PDF]
Annual Review of Environment and Resources, 2015 We review the challenges and future perspectives of regional climate model (RCM), or dynamical downscaling, activities. Among the main technical issues in need of better understanding are those of selection and sensitivity to the model domain and resolution, techniques for providing lateral boundary conditions, and RCM internal variability.
Filippo Giorgi, William J Gutowski
exaly +3 more sources
Evaluating the utility of dynamical downscaling in agricultural impacts projections. [PDF]
Proc Natl Acad Sci U S A, 2014 SignificanceOne of the largest concerns about future climate change is its potential effect on food supply. Crop yield projections require climate inputs at higher resolution than typical for global climate models, and the computationally expensive technique of dynamical downscaling is widely used for this translation.
Glotter M +5 more
europepmc +5 more sources
The selective dynamical downscaling method for extreme‐wind atlases [PDF]
Wind Energy, 2012 ABSTRACTA selective dynamical downscaling method is developed to obtain extreme‐wind atlases for large areas. The method is general, efficient and flexible. The method consists of three steps: (i) identifying storm episodes for a particular area, (ii) downscaling of the storms using mesoscale modelling and (iii) post‐processing.
X.G. Larsén +3 more
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Optimal Spectral Nudging for Global Dynamic Downscaling [PDF]
Monthly Weather Review, 2017 This study analyzes a method of constructing a homogeneous, high-resolution global atmospheric hindcast. The method is the spectral nudging technique, which was applied to a state-of-the-art general circulation model (ECHAM6, T255L95). Large spatial scales of the global climate model prognostic variables were spectrally nudged toward a reanalysis ...
Schubert-Frisius, M. +3 more
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Fast and accurate learned multiresolution dynamical downscaling for precipitation [PDF]
Geoscientific Model Development, 2021 Abstract. This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computational cost. The key idea is to use combination of low- and high- resolution simulations to train a neural network to map from the former to the latter. Specifically,
Jiali Wang +5 more
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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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