Assessing Three Perfect Prognosis Methods for Statistical Downscaling of Climate Change Precipitation Scenarios

Autor: M. N. Legasa, S. Thao, M. Vrac, R. Manzanas

Publikováno v: Geophysical Research Letters, Vol 50, Iss 9, Pp n/a-n/a (2023)

Abstract Under the perfect prognosis approach, statistical downscaling methods learn the relationships between large‐scale variables from reanalysis and local observational records. These relationships are subsequently applied to downscale future g

Externí odkaz: https://doaj.org/article/06067106231849979b5890c4de6e239e

Assessing Multidomain Overlaps and Grand Ensemble Generation in CORDEX Regional Projections

Autor: M. N. Legasa, R. Manzanas, J. Fernández, S. Herrera, M. Iturbide, W. Moufouma‐Okia, P. Zhai, F. Driouech, J. M. Gutiérrez

Publikováno v: Geophysical Research Letters, Vol 47, Iss 4, Pp n/a-n/a (2020)

Abstract The Coordinated Regional Climate Downscaling Experiment (CORDEX) initiative has made available an enormous amount of regional climate projections in different domains worldwide. This information is crucial for the development of adaptation s

Externí odkaz: https://doaj.org/article/c3be790066bb4320a826a5672d9fd902

Assessing multidomain overlaps and grand nnsemble generation in CORDEX regional projections

Autor: Sixto Herrera, José M. Gutiérrez, Panmao Zhai, Rodrigo Manzanas, F. Driouech, Jesús Fernández, Wilfran Moufouma-Okia, Maialen Iturbide, M. N. Legasa

Publikováno v: Geophysical Research Letters, 2020, 47(4), e2019GL086799
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)
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The Coordinated Regional Climate Downscaling Experiment (CORDEX) initiative has made available an enormous amount of regional climate projections in different domains worldwide. This information is crucial for the development of adaptation strategies

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4131f7eacd0539ec2056039411d05a6
http://hdl.handle.net/10902/19909

Near-Term Forecasting of Terrestrial Mobile Species Distributions for Adaptive Management Under Extreme Weather Events.

Autor: Dobson R; Sustainability Research Institute, School of Earth and Environment, University of Leeds, Leeds, UK.; Conservation Ecology Group, Department of Biosciences, Durham University, Durham, UK., Willis SG; Conservation Ecology Group, Department of Biosciences, Durham University, Durham, UK., Jennings S; Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK., Cheke RA; Natural Resources Institute, University of Greenwich, Chatham, Kent, UK., Challinor AJ; Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK., Dallimer M; Centre for Environmental Policy, Imperial College London, London, UK.

Publikováno v: Global change biology [Glob Chang Biol] 2024 Nov; Vol. 30 (11), pp. e17579.

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

Autor: Legasa, M. N., Manzanas, R., Calviño, A., Gutiérrez, J. M.

Publikováno v: Water Resources Research; Apr2022, Vol. 58 Issue 4, p1-17, 17p