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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Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 Deep networks have achieved great success in image rescaling (IR) task that seeks to learn the optimal downscaled representations, i.e., low-resolution (LR) images, to reconstruct the original high-resolution (HR) images. Compared with super-resolution methods that consider a fixed downscaling scheme, e.g., bicubic, IR often achieves significantly ...
Bingna Xu +4 more
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Comparison of data-driven methods for downscaling ensemble weather forecasts [PDF]
Hydrology and Earth System Sciences, 2008 This study investigates dynamically different data-driven methods, specifically a statistical downscaling model (SDSM), a time lagged feedforward neural network (TLFN), and an evolutionary polynomial regression (EPR) technique for downscaling numerical ...
Xiaoli Liu, P. Coulibaly, N. Evora
doaj
ThumbNet: One Thumbnail Image Contains All You Need for Recognition
, 2020 Although deep convolutional neural networks (CNNs) have achieved great success in computer vision tasks, its real-world application is still impeded by its voracious demand of computational resources.
Abadi Mart'in +11 more
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An ensemble approach to assess hydrological models’ contribution to uncertainties in the analysis of climate change impact on water resources [PDF]
, 2012 Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic ...
Caya, D. +9 more
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Temporal stability of soil moisture and radar backscatter observed by the advanced Synthetic Aperture Radar (ASAR) [PDF]
, 2008 The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics.
Alexander Löw +58 more
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Impact of day/night time land surface temperature in soil moisture disaggregation algorithms [PDF]
, 2016 Since its launch in 2009, the ESA’s SMOS mission is providing global soil moisture (SM) maps at ~40 km, using the first L-band microwave radiometer on space.
Camps Carmona, Adriano José +5 more
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Nearshore wave forecasting and hindcasting by dynamical and statistical downscaling
, 2012 A high-resolution nested WAM/SWAN wave model suite aimed at rapidly establishing nearshore wave forecasts as well as a climatology and return values of the local wave conditions with Rapid Enviromental Assessment (REA) in mind is described. The system is
Birgitte R. Furevik +25 more
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Climate sensitivity to land use changes over the City of Brussels [PDF]
, 2019 Prompted with the ongoing and projected climate change, a wide range of cities have committed, not only to mitigate greenhouse gas emissions but also to implement different climate change adaptation measures.
Caluwaerts, Steven +7 more
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Detail-Preserving Pooling in Deep Networks
, 2018 Most convolutional neural networks use some method for gradually downscaling the size of the hidden layers. This is commonly referred to as pooling, and is applied to reduce the number of parameters, improve invariance to certain distortions, and ...
Goesele, Michael +3 more
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