A Posteriori Random Forests for Stochastic Downscaling of Precipitation by Predicting Probability Distributions-Reference-Cited by-同舟云学术

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A Posteriori Random Forests for Stochastic Downscaling of Precipitation by Predicting Probability Distributions

Published:2022-03-29 Issue:4 Volume:58 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resources Research

Author:

Legasa M. N.¹^ORCID,Manzanas R.¹^ORCID,Calviño A.²^ORCID,Gutiérrez J. M.³^ORCID

Affiliation:

1. Meteorology Group Departamento de Matemática Aplicada y Ciencias de la Computación Universidad de Cantabria Santander Spain

2. Department of Statistics and Data Science Complutense University of Madrid Madrid Spain

3. Meteorology Group Instituto de Física de Cantabria (IFCA) Universidad de Cantabria‐CSIC Santander Spain

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021WR030272

Reference64 articles.

1. Forecasting local daily precipitation patterns in a climate change scenario

2. Evaluating Stochastic Precipitation Generators for Climate Change Impact Studies of New York City’s Primary Water Supply

3. Stochastic weather generators: An overview of weather type models;Ailliot P.;Journal de la Société Française de Statistique,2015

4. Configuration and intercomparison of deep learning neural models for statistical downscaling

5. Statistical downscaling with the downscaleR package (v3.1.0): contribution to the VALUE intercomparison experiment

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