Results 21 to 30 of about 2,660,815 (249)
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
doaj +1 more source
Meteorological Applications, 2023 This paper evaluated and compared the performance of a statistical downscaling method and a dynamical downscaling method to simulate the spatial–temporal rainfall distribution.
Raazia Attique +2 more
doaj +1 more source
Regridding uncertainty for statistical downscaling of solar radiation [PDF]
Advances in Statistical Climatology, Meteorology and Oceanography, 2023 Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM outputs from their native grids and at differing spatial resolutions to a common grid in
M. D. Bailey +6 more
doaj +1 more source
Advances in Meteorology, 2016 Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables to assess the hydrological impacts of climate change.
Jiaming Liu +4 more
doaj +1 more source
Atmosphere, 2011 When assessing the magnitude of climate signals in a regional scale, a host of optional approaches is feasible. This encompasses the use of regional climate models (RCM), nested into global climate models (GCM) for an area of interest as well as ...
Arne Spekat +3 more
doaj +1 more source
Impact of global atmospheric reanalyses on statistical precipitation downscaling [PDF]
, 2018 Statistical downscaling based on a perfect prognosis approach often relies on global reanalyses to infer the statistical relationship between synoptic predictors and the local variable of interest, here daily precipitation.
Horton, Pascal, Brönnimann, Stefan
core +4 more sources
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information [PDF]
Geoscientific Model Development, 2023 The nature and severity of climate change impacts vary significantly from region to region. Consequently, high-resolution climate information is needed for meaningful impact assessments and the design of mitigation strategies.
D. Boateng, S. G. Mutz, S. G. Mutz
doaj +1 more source
Remarks on the redefinition of system boundaries and model parameterization for downscaling experiments [PDF]
, 2009 The paper discusses problems encountered while implementing a downscaling experiment for testing the potential impacts of changes in temporal precipitation patterns on the biogeochemical properties of the lagoon of Venice.
Solidoro, C. +4 more
core +1 more source
Statistical Learning-Based Spatial Downscaling Models for Precipitation Distribution
Advances in Meteorology, 2022 The downscaling technique produces high spatial resolution precipitation distribution in order to analyze impacts of climate change in data-scarce regions or local scales.
Yichen Wu +3 more
doaj +1 more source
Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area
Italian Journal of Agronomy, 2012 In this paper we present and discuss a comparison between statistical and regional climate modeling techniques for downscaling GCM prediction . The comparison is carried out over the “Capitanata” region, an area of agricultural interest in south ...
Claudia Pizzigalli +5 more
doaj +1 more source