Spatially coherent probabilistic precipitation downscaling with meteorological analogues
Studying past and present day precipitation and its link to large scale circulation increases our understanding of precipitation characteristics and helps to anticipate their future behaviour. Downscaling techniques are being developed to bridge the gap between large-scale climate information from global reanalyses or GCM global projections and local ...
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Attention-Enhanced CNN-LSTM with Spatial Downscaling for Day-Ahead Photovoltaic Power Forecasting. [PDF]
Peng F, Tang X, Xiao M.
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Fine-Scale Risk Mapping for Dengue Vector Using Spatial Downscaling in Intra-Urban Areas of Guangzhou, China. [PDF]
Shen Y +5 more
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Exploring super-resolution spatial downscaling of several meteorological variables and potential applications for photovoltaic power. [PDF]
Damiani A +4 more
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Benchmarking the geographic generalization of deep learning models for precipitation downscaling. [PDF]
Harder P +7 more
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Choice of Downscaled Climate Product Matters: Projections of Valley Fever Seasonality in a Warming Climate. [PDF]
Schollaert CL +7 more
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A global 400-m high-resolution soil moisture dataset derived from multi-sensor remote sensing observations. [PDF]
Fang B, Lakshmi V, Hain C, Mishra V.
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Spatial downscaling of alien species presences using machine learning
Summarization: Spatially explicit assessments of alien species environmental and socio-economic impacts, and subsequent management interventions for their mitigation, require large scale, high-resolution data on species presence distribution. However, these data are often unavailable.
Δαλιακοπουλος Ιωαννης(http://users.isc.tuc.gr/~gdaliakopoulos) +4 more
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An hourly climate projection and renewable energy generation dataset for power system modeling in China. [PDF]
Chen R +4 more
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Global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset (1950-2100). [PDF]
Lei X +6 more
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