Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific Seascape

Two methods for selecting a subset of simulations and/or general circulation models (GCMs) from a set of 30 available simulations are compared: 1) Selecting the models based on their performance on reproducing 20th century climate, and 2) random sampling. In the first case, it was found that the per...

Full description

Bibliographic Details
Main Authors: Hugo G. Hidalgo, Eric J. Alfaro
Format: Article
Language:English
Published: Vicerractoría Investigación 2012-11-01
Series:Revista de Biología Tropical
Subjects:
Online Access:http://www.scielo.sa.cr/scielo.php?script=sci_arttext&pid=S0034-77442012000800006&lng=en&tlng=en
_version_ 1797763652871258112
author Hugo G. Hidalgo
Eric J. Alfaro
author_facet Hugo G. Hidalgo
Eric J. Alfaro
author_sort Hugo G. Hidalgo
collection DOAJ
description Two methods for selecting a subset of simulations and/or general circulation models (GCMs) from a set of 30 available simulations are compared: 1) Selecting the models based on their performance on reproducing 20th century climate, and 2) random sampling. In the first case, it was found that the performance methodology is very sensitive to the type and number of metrics used to rank the models and therefore the results are not robust to these conditions. In general, including more models in a multi-model ensemble according to their rank (of skill in reproducing 20th century climate) results in an increase in the multi-model skill up to a certain point and then the inclusion of more models degrades the skill of the multi-model ensemble. In a similar fashion when the models are introduced in the ensemble at random, there is a point where the inclusion of more models does not change significantly the skill of the multi-model ensemble. For precipitation the subset of models that produces the maximum skill in reproducing 20th century climate also showed some skill in reproducing the climate change projections of the multi-model ensemble of all simulations. For temperature, more models/simulations are needed to be included in the ensemble (at the expense of a decrease in the skill of reproducing the climate of the 20th century for the selection based on their ranks). For precipitation and temperature the use of 7 simulations out of 30 resulted in the maximum skill for both approaches to introduce the models.
first_indexed 2024-03-12T19:44:29Z
format Article
id doaj.art-a294c6d5b37c4720917363dddfe16269
institution Directory Open Access Journal
issn 0034-7744
language English
last_indexed 2024-03-12T19:44:29Z
publishDate 2012-11-01
publisher Vicerractoría Investigación
record_format Article
series Revista de Biología Tropical
spelling doaj.art-a294c6d5b37c4720917363dddfe162692023-08-02T03:36:21ZengVicerractoría InvestigaciónRevista de Biología Tropical0034-77442012-11-0160suppl 36781S0034-77442012000800006Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific SeascapeHugo G. Hidalgo0Eric J. Alfaro1Universidad de Costa RicaUniversidad de Costa RicaTwo methods for selecting a subset of simulations and/or general circulation models (GCMs) from a set of 30 available simulations are compared: 1) Selecting the models based on their performance on reproducing 20th century climate, and 2) random sampling. In the first case, it was found that the performance methodology is very sensitive to the type and number of metrics used to rank the models and therefore the results are not robust to these conditions. In general, including more models in a multi-model ensemble according to their rank (of skill in reproducing 20th century climate) results in an increase in the multi-model skill up to a certain point and then the inclusion of more models degrades the skill of the multi-model ensemble. In a similar fashion when the models are introduced in the ensemble at random, there is a point where the inclusion of more models does not change significantly the skill of the multi-model ensemble. For precipitation the subset of models that produces the maximum skill in reproducing 20th century climate also showed some skill in reproducing the climate change projections of the multi-model ensemble of all simulations. For temperature, more models/simulations are needed to be included in the ensemble (at the expense of a decrease in the skill of reproducing the climate of the 20th century for the selection based on their ranks). For precipitation and temperature the use of 7 simulations out of 30 resulted in the maximum skill for both approaches to introduce the models.http://www.scielo.sa.cr/scielo.php?script=sci_arttext&pid=S0034-77442012000800006&lng=en&tlng=enCorredor del Pacífico Tropical del EsteModelos de Circulación GeneralCambio ClimáticoPrecipitaciónTemperatura superficial del aire
spellingShingle Hugo G. Hidalgo
Eric J. Alfaro
Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific Seascape
Revista de Biología Tropical
Corredor del Pacífico Tropical del Este
Modelos de Circulación General
Cambio Climático
Precipitación
Temperatura superficial del aire
title Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific Seascape
title_full Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific Seascape
title_fullStr Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific Seascape
title_full_unstemmed Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific Seascape
title_short Global Model selection for evaluation of Climate Change projections in the Eastern Tropical Pacific Seascape
title_sort global model selection for evaluation of climate change projections in the eastern tropical pacific seascape
topic Corredor del Pacífico Tropical del Este
Modelos de Circulación General
Cambio Climático
Precipitación
Temperatura superficial del aire
url http://www.scielo.sa.cr/scielo.php?script=sci_arttext&pid=S0034-77442012000800006&lng=en&tlng=en
work_keys_str_mv AT hugoghidalgo globalmodelselectionforevaluationofclimatechangeprojectionsintheeasterntropicalpacificseascape
AT ericjalfaro globalmodelselectionforevaluationofclimatechangeprojectionsintheeasterntropicalpacificseascape