Results 11 to 20 of about 6,035 (266)
Earth and Space Science, 2022 Downscaling techniques are effective to bridge the scale gap between global circulation models and regional studies. Statistical downscaling methods are prevalent due to their advantages in high computational efficiency and accuracy. However, an implicit
Xintong Li +2 more
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Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0) [PDF]
Geoscientific Model Development, 2019 In this paper I present new methods for bias adjustment and statistical downscaling that are tailored to the requirements of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).
S. Lange
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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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Interrogating empirical-statistical downscaling [PDF]
Climatic Change, 2013 The delivery of downscaled climate information is increasingly seen as a vehicle of climate services, a driver for impacts studies and adaptation decisions, and for informing policy development. Empirical-statistical downscaling (ESD) is widely used; however, the accompanying responsibility is significant, and predicated on effective understanding of ...
Hewitson, Bruce +4 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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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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Statistical downscaling for precipitation projections in West Africa
Theoretical and Applied Climatology, 2023 Abstract The West Africa region (5to 20N and 10E to 20W) is particularly vulnerable to climate change due to a combination of unique geographic features, meteorological conditions, and socio-economic factors. Drastic changes in precipitation (e.g., droughts or floods) in the region can have dramatic impacts on rain-fed agriculture, water ...
Andrew Polasky +2 more
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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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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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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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