Statistical downscaling and projection of climatic extremes using machine learning algorithms-Reference-Cited by-同舟云学术

Statistical downscaling and projection of climatic extremes using machine learning algorithms

Published:2023-06-19 Issue:3-4 Volume:153 Page:1033-1047
ISSN:0177-798X
Container-title:Theoretical and Applied Climatology
language:en
Short-container-title:Theor Appl Climatol

Author:

Maqsood Junaid,Afzaal Hassan,Farooque Aitazaz A.^ORCID,Abbas Farhat,Wang Xander,Esau Travis

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

https://link.springer.com/content/pdf/10.1007/s00704-023-04532-y.pdf

Reference55 articles.

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2. Afzaal H, Farooque AA, Abbas F et al (2020) Computation of evapotranspiration with artificial intelligence for precision water resource management. Appl Sci 10:1621. https://doi.org/10.3390/app10051621

3. Ahmed K, Shahid S, Bin HS, Xiao-jun W (2015) Multilayer perceptron neural network for downscaling rainfall in arid region: A case study of Baluchistan, Pakistan. J Earth Syst Sci 124:1325–1341. https://doi.org/10.1007/S12040-015-0602-9

4. Alexander L, Herold N (2016) ClimPACT2: indices and software. The University of South Wales, Sydney, Australia. https://github.com/ARCCSS-extremes/climpact2

5. Bhatti AZ, Farooque AA, Krouglicof N et al (2021) Climate change impacts on precipitation and temperature in Prince Edward Island, Canada. World Water Policy 7:9–29. https://doi.org/10.1002/WWP2.12046

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