On the deep learning approach for improving the representation of urban climate: The Paris urban heat island and temperature extremes-Reference-Cited by-同舟云学术

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On the deep learning approach for improving the representation of urban climate: The Paris urban heat island and temperature extremes

Published:2024-07 Issue: Volume:56 Page:102039
ISSN:2212-0955
Container-title:Urban Climate
language:en
Short-container-title:Urban Climate

Author:

Johannsen Frederico,Soares Pedro M.M.,Langendijk Gaby S.

Publisher

Elsevier BV

Reference121 articles.

1. The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation;Ban;Clim. Dyn.,2021

2. Configuration and intercomparison of deep learning neural models for statistical downscaling;Baño-Medina;Geosci. Model Dev.,2020

3. Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44;Baño-Medina;Geosci. Model Dev.,2022

4. Machine learning in weather prediction and climate analyses-applications and perspectives;Bochenek;Atmosphere,2022

5. The concept of essential climate variables in support of climate research, applications, and policy;Bojinski;Bull. Am. Meteorol. Soc.,2014

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1. Heat exposure inequalities in Hong Kong from 1981 to 2021;Urban Climate;2024-07

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