Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles

Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles

Various climate models have been developed to analyze and predict climate change; however, model uncertainties cannot be easily overcome. A statistical approach has been presented in this paper to calculate the distributions of future climate change based on an ensemble of the Weather Research and F...

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Bibliographic Details
Main Author: Cai, Yihua
Format: Others
Language:English
Published: 2010
Subjects:
Bayesian analysis
wavelet analysis
multimodel ensembles
Online Access:http://hdl.handle.net/2152/ETD-UT-2009-08-293
id ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2009-08-293
record_format oai_dc
spelling ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2009-08-2932015-09-20T16:53:47ZStatistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensemblesCai, YihuaBayesian analysiswavelet analysismultimodel ensemblesVarious climate models have been developed to analyze and predict climate change; however, model uncertainties cannot be easily overcome. A statistical approach has been presented in this paper to calculate the distributions of future climate change based on an ensemble of the Weather Research and Forecasting (WRF) models. Wavelet analysis has been adopted to de-noise the WRF model output. Using the de-noised model output, we carry out Bayesian analysis to decrease uncertainties in model CAM_KF, RRTM_KF and RRTM_GRELL for each downscaling region.text2010-06-04T14:43:16Z2010-06-04T14:43:16Z2009-082010-06-04T14:43:16ZAugust 2009thesisapplication/pdfhttp://hdl.handle.net/2152/ETD-UT-2009-08-293eng
collection NDLTD
language English
format Others
sources NDLTD
topic Bayesian analysis
wavelet analysis
multimodel ensembles
spellingShingle Bayesian analysis
wavelet analysis
multimodel ensembles
Cai, Yihua
Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles
description Various climate models have been developed to analyze and predict climate change; however, model uncertainties cannot be easily overcome. A statistical approach has been presented in this paper to calculate the distributions of future climate change based on an ensemble of the Weather Research and Forecasting (WRF) models. Wavelet analysis has been adopted to de-noise the WRF model output. Using the de-noised model output, we carry out Bayesian analysis to decrease uncertainties in model CAM_KF, RRTM_KF and RRTM_GRELL for each downscaling region. === text
author Cai, Yihua
author_facet Cai, Yihua
author_sort Cai, Yihua
title Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles
title_short Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles
title_full Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles
title_fullStr Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles
title_full_unstemmed Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles
title_sort statistical analysis in downscaling climate models : wavelet and bayesian methods in multimodel ensembles
publishDate 2010
url http://hdl.handle.net/2152/ETD-UT-2009-08-293
work_keys_str_mv AT caiyihua statisticalanalysisindownscalingclimatemodelswaveletandbayesianmethodsinmultimodelensembles
_version_ 1716820833525039104

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