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Journal of Hydrologic Engineering, 2015
AbstractDownscaling is a fundamental procedure in the assessment of the future climate change impact at regional and watershed scales. Hence, it is important to investigate the spatial variability of the climate conditions that are constructed by various downscaling methods to assess whether each method can properly model the climate conditions at ...
S. Jang, M. L. Kavvas
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AbstractDownscaling is a fundamental procedure in the assessment of the future climate change impact at regional and watershed scales. Hence, it is important to investigate the spatial variability of the climate conditions that are constructed by various downscaling methods to assess whether each method can properly model the climate conditions at ...
S. Jang, M. L. Kavvas
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Empirical-Statistical Downscaling: Nonlinear Statistical Downscaling
2021Empirical-statistical downscaling (ESD) models use statistical relationships to infer local climate information from large-scale climate information produced by global climate models (GCMs), as an alternative to the dynamical downscaling provided by regional climate models (RCMs).
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Deep Precipitation Downscaling
IEEE Geoscience and Remote Sensing Letters, 2022Precipitation downscaling, which is similar to the mechanism of single-image super-resolution (SR), aims to improve the spatial resolution of rain maps. It is of great practical value and theoretical significance. This letter presents a new deep precipitation downscaling (DPD) method, named auxiliary guided spatial distortion (AGSD) network, motivated ...
Tingzhao Yu +3 more
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Geoscientific Model Development
. Deep learning (DL) methods have recently garnered attention from the climate change community for being an innovative approach to downscaling climate variables from Earth system and global climate models (ESGCMs) with horizontal resolutions still too ...
P. Soares +5 more
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. Deep learning (DL) methods have recently garnered attention from the climate change community for being an innovative approach to downscaling climate variables from Earth system and global climate models (ESGCMs) with horizontal resolutions still too ...
P. Soares +5 more
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Science, 2017
Device Technology One option for extending the performance of complementary metal-oxide semiconductor (CMOS) devices based on silicon technology is to use semiconducting carbon nanotubes as the gates. Qiu et al. fabricated top-gated carbon nanotube field-effect transistors with a gate length of 5 nm. Thin graphene contacts helped maintain electrostatic
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Device Technology One option for extending the performance of complementary metal-oxide semiconductor (CMOS) devices based on silicon technology is to use semiconducting carbon nanotubes as the gates. Qiu et al. fabricated top-gated carbon nanotube field-effect transistors with a gate length of 5 nm. Thin graphene contacts helped maintain electrostatic
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Performance Preserving Network Downscaling
38th Annual Simulation Symposium, 2005The Internet is a large, complex, heterogeneous system operating at very high speeds and consisting of a large number of users. Researchers use a suite of tools and techniques in order to understand the performance of networks: measurements, simulations, and deployments on small to medium-scale testbeds.
Govindan, Ramesh +2 more
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2019
Winds within the atmospheric boundary layer (i.e., near to Earth’s surface) vary across a range of scales from a few meters and sub-second timescales (i.e., the scales of turbulent motions) to extremely large and long-period phenomena (i.e., the primary circulation patterns of the global atmosphere). Winds redistribute momentum and heat, and short- and
S.C. Pryor, A.N. Hahmann
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Winds within the atmospheric boundary layer (i.e., near to Earth’s surface) vary across a range of scales from a few meters and sub-second timescales (i.e., the scales of turbulent motions) to extremely large and long-period phenomena (i.e., the primary circulation patterns of the global atmosphere). Winds redistribute momentum and heat, and short- and
S.C. Pryor, A.N. Hahmann
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$L_{0}$ -Regularized Image Downscaling
IEEE Transactions on Image Processing, 2018In this paper, we propose a novel -regularized optimization framework for image downscaling. The optimization is driven by two -regularized priors. The first prior, gradient-ratio prior, is based on the observation that the number of edges in the downscaled image is approximately inverse square proportional to the downscaling factor.
Junjie Liu +2 more
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, 2021
The advent of Gravity Recovery and Climate Experiment (GRACE) has opened the doors for remote monitoring of gravitational changes and its derivatives across the globe, but received less attention due to poor spatial and temporal representation ...
P. J. Jyolsna +2 more
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The advent of Gravity Recovery and Climate Experiment (GRACE) has opened the doors for remote monitoring of gravitational changes and its derivatives across the globe, but received less attention due to poor spatial and temporal representation ...
P. J. Jyolsna +2 more
semanticscholar +1 more source
Remote Sensing of Environment, 2019
The Soil Moisture Active Passive (SMAP) satellite can no longer directly deliver high-resolution (9 km) soil moisture products with the failure of the onboard L-band radar. Thus, an appropriate replacement sensor and new algorithms are urgently needed to
Zushuai Wei +4 more
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The Soil Moisture Active Passive (SMAP) satellite can no longer directly deliver high-resolution (9 km) soil moisture products with the failure of the onboard L-band radar. Thus, an appropriate replacement sensor and new algorithms are urgently needed to
Zushuai Wei +4 more
semanticscholar +1 more source