A multivariate comparison of the BERMS flux-tower climate observations and Canadian Coupled Global Climate Model (CGCM3) outputs

•Comparisons are made between the Canadian GCM (CGCM3) outputs and flux observations.•The CGCM3 outputs and observations have different multivariate relationships.•The observations and CGCM have different relationships of humidity and radiation.•The CGCM3 relative humidity may not be suitable for hy...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of hydrology (Amsterdam) 2014-11, Vol.519, p.1537-1550
Hauptverfasser: Chun, K.P., Wheater, H.S., Barr, A.G.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1550
container_issue
container_start_page 1537
container_title Journal of hydrology (Amsterdam)
container_volume 519
creator Chun, K.P.
Wheater, H.S.
Barr, A.G.
description •Comparisons are made between the Canadian GCM (CGCM3) outputs and flux observations.•The CGCM3 outputs and observations have different multivariate relationships.•The observations and CGCM have different relationships of humidity and radiation.•The CGCM3 relative humidity may not be suitable for hydrological modelling directly.•The CGCM3 wind speed outputs can be unreliable for hydrological modelling. Multiple variables from simulated climate fields are widely used in hydrological and ecological models and climate impact assessments, yet the importance of multivariate climate relationships is not widely recognised. This study evaluates climatic outputs from the Canadian Coupled Global Climate Model (CGCM3) in the southern boreal forests of western Canada, by comparing the simulated multivariate relationships with those observed at three representative forest sites. Monthly mean data for five near-surface climate variables (net radiation RN, air temperature TA, relative humidity RH, wind speed WS and surface pressure P) are analysed and compared using visual inspection, hypothesis testing and principal component analysis. The projections of the 1st and 2nd principal components, which explain about 75% of the variation in the data, show remarkable similarities in the observations from the three forest sites (with some subtle differences between the evergreen and deciduous plant functional types), but some broad differences between the observations and model outputs. The model reproduces the observed relationships among RN, TA and P, but not between RH or WS and the other variables. In particular, RH is strongly and negatively related to TA and RN in the forest observations but independent in the model outputs; RH is negatively related to WS in the observations but positively related in the model output; and P is uncoupled from the other variables in the observations but negatively related to RH and WS in the model output. The broad scope of the differences indicates a divergence of process representation at large time and space scales. We explore possible reasons for the observed discrepancies, which indicate some limitations in using climate model outputs directly to drive hydrological models.
doi_str_mv 10.1016/j.jhydrol.2014.08.059
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1651412296</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0022169414006696</els_id><sourcerecordid>1647010724</sourcerecordid><originalsourceid>FETCH-LOGICAL-a498t-b5c78c095c6ce4c1d49b64b21d664954386d2cee98811a0afded44b246f288f73</originalsourceid><addsrcrecordid>eNqNkc-L1DAUx4soOK7-CUIuwnpoTdI0TU6ylnUUdhD8cQ5p8spmyDQ1SWfdm3-6GWbwqrkk8D7fPN77VNVrghuCCX-3b_b3jzYG31BMWINFgzv5pNoQ0cua9rh_Wm0wprQmXLLn1YuU9rictmWb6vcNOqw-u6OOTmdAJhyW8kxhRmFC-R7Qh9uvu29o8uuvOocHiMh4dzihYUwQjzq7MCekZ4sGPWvr9IyGsC4eLNr6MGqPhktgFyx4dD1sh137FoU1L2tOL6tnk_YJXl3uq-rHx9vvw6f67sv283BzV2smRa7HzvTCYNkZboAZYpkcORspsZwz2bFWcEsNgBSCEI31ZMGyUmd8okJMfXtVXZ__XWL4uULK6uCSAe_1DGFNivCOMEKp5P-Bsh4T3FNW0O6MmhhSijCpJZZh46MiWJ3kqL26yFEnOQoLVeSU3JtLC52M9lPUs3Hpb5hK3BdDonDvzxyU1RwdRJWMg9mAdRFMVja4f3T6A6ifp_o</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1647010724</pqid></control><display><type>article</type><title>A multivariate comparison of the BERMS flux-tower climate observations and Canadian Coupled Global Climate Model (CGCM3) outputs</title><source>Elsevier ScienceDirect Journals Complete</source><creator>Chun, K.P. ; Wheater, H.S. ; Barr, A.G.</creator><creatorcontrib>Chun, K.P. ; Wheater, H.S. ; Barr, A.G.</creatorcontrib><description>•Comparisons are made between the Canadian GCM (CGCM3) outputs and flux observations.•The CGCM3 outputs and observations have different multivariate relationships.•The observations and CGCM have different relationships of humidity and radiation.•The CGCM3 relative humidity may not be suitable for hydrological modelling directly.•The CGCM3 wind speed outputs can be unreliable for hydrological modelling. Multiple variables from simulated climate fields are widely used in hydrological and ecological models and climate impact assessments, yet the importance of multivariate climate relationships is not widely recognised. This study evaluates climatic outputs from the Canadian Coupled Global Climate Model (CGCM3) in the southern boreal forests of western Canada, by comparing the simulated multivariate relationships with those observed at three representative forest sites. Monthly mean data for five near-surface climate variables (net radiation RN, air temperature TA, relative humidity RH, wind speed WS and surface pressure P) are analysed and compared using visual inspection, hypothesis testing and principal component analysis. The projections of the 1st and 2nd principal components, which explain about 75% of the variation in the data, show remarkable similarities in the observations from the three forest sites (with some subtle differences between the evergreen and deciduous plant functional types), but some broad differences between the observations and model outputs. The model reproduces the observed relationships among RN, TA and P, but not between RH or WS and the other variables. In particular, RH is strongly and negatively related to TA and RN in the forest observations but independent in the model outputs; RH is negatively related to WS in the observations but positively related in the model output; and P is uncoupled from the other variables in the observations but negatively related to RH and WS in the model output. The broad scope of the differences indicates a divergence of process representation at large time and space scales. We explore possible reasons for the observed discrepancies, which indicate some limitations in using climate model outputs directly to drive hydrological models.</description><identifier>ISSN: 0022-1694</identifier><identifier>EISSN: 1879-2707</identifier><identifier>DOI: 10.1016/j.jhydrol.2014.08.059</identifier><identifier>CODEN: JHYDA7</identifier><language>eng</language><publisher>Kidlington: Elsevier B.V</publisher><subject>Boreal forest ; Climate ; Climate models ; Climate variables ; Computer simulation ; Correlation structure ; Earth sciences ; Earth, ocean, space ; Exact sciences and technology ; Flux towers ; Forests ; Global climate models ; Hydrology ; Hydrology. Hydrogeology ; Joining ; Mathematical models ; Multivariate analysis</subject><ispartof>Journal of hydrology (Amsterdam), 2014-11, Vol.519, p.1537-1550</ispartof><rights>2014 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a498t-b5c78c095c6ce4c1d49b64b21d664954386d2cee98811a0afded44b246f288f73</citedby><cites>FETCH-LOGICAL-a498t-b5c78c095c6ce4c1d49b64b21d664954386d2cee98811a0afded44b246f288f73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0022169414006696$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=29070008$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Chun, K.P.</creatorcontrib><creatorcontrib>Wheater, H.S.</creatorcontrib><creatorcontrib>Barr, A.G.</creatorcontrib><title>A multivariate comparison of the BERMS flux-tower climate observations and Canadian Coupled Global Climate Model (CGCM3) outputs</title><title>Journal of hydrology (Amsterdam)</title><description>•Comparisons are made between the Canadian GCM (CGCM3) outputs and flux observations.•The CGCM3 outputs and observations have different multivariate relationships.•The observations and CGCM have different relationships of humidity and radiation.•The CGCM3 relative humidity may not be suitable for hydrological modelling directly.•The CGCM3 wind speed outputs can be unreliable for hydrological modelling. Multiple variables from simulated climate fields are widely used in hydrological and ecological models and climate impact assessments, yet the importance of multivariate climate relationships is not widely recognised. This study evaluates climatic outputs from the Canadian Coupled Global Climate Model (CGCM3) in the southern boreal forests of western Canada, by comparing the simulated multivariate relationships with those observed at three representative forest sites. Monthly mean data for five near-surface climate variables (net radiation RN, air temperature TA, relative humidity RH, wind speed WS and surface pressure P) are analysed and compared using visual inspection, hypothesis testing and principal component analysis. The projections of the 1st and 2nd principal components, which explain about 75% of the variation in the data, show remarkable similarities in the observations from the three forest sites (with some subtle differences between the evergreen and deciduous plant functional types), but some broad differences between the observations and model outputs. The model reproduces the observed relationships among RN, TA and P, but not between RH or WS and the other variables. In particular, RH is strongly and negatively related to TA and RN in the forest observations but independent in the model outputs; RH is negatively related to WS in the observations but positively related in the model output; and P is uncoupled from the other variables in the observations but negatively related to RH and WS in the model output. The broad scope of the differences indicates a divergence of process representation at large time and space scales. We explore possible reasons for the observed discrepancies, which indicate some limitations in using climate model outputs directly to drive hydrological models.</description><subject>Boreal forest</subject><subject>Climate</subject><subject>Climate models</subject><subject>Climate variables</subject><subject>Computer simulation</subject><subject>Correlation structure</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>Flux towers</subject><subject>Forests</subject><subject>Global climate models</subject><subject>Hydrology</subject><subject>Hydrology. Hydrogeology</subject><subject>Joining</subject><subject>Mathematical models</subject><subject>Multivariate analysis</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqNkc-L1DAUx4soOK7-CUIuwnpoTdI0TU6ylnUUdhD8cQ5p8spmyDQ1SWfdm3-6GWbwqrkk8D7fPN77VNVrghuCCX-3b_b3jzYG31BMWINFgzv5pNoQ0cua9rh_Wm0wprQmXLLn1YuU9rictmWb6vcNOqw-u6OOTmdAJhyW8kxhRmFC-R7Qh9uvu29o8uuvOocHiMh4dzihYUwQjzq7MCekZ4sGPWvr9IyGsC4eLNr6MGqPhktgFyx4dD1sh137FoU1L2tOL6tnk_YJXl3uq-rHx9vvw6f67sv283BzV2smRa7HzvTCYNkZboAZYpkcORspsZwz2bFWcEsNgBSCEI31ZMGyUmd8okJMfXtVXZ__XWL4uULK6uCSAe_1DGFNivCOMEKp5P-Bsh4T3FNW0O6MmhhSijCpJZZh46MiWJ3kqL26yFEnOQoLVeSU3JtLC52M9lPUs3Hpb5hK3BdDonDvzxyU1RwdRJWMg9mAdRFMVja4f3T6A6ifp_o</recordid><startdate>20141127</startdate><enddate>20141127</enddate><creator>Chun, K.P.</creator><creator>Wheater, H.S.</creator><creator>Barr, A.G.</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>20141127</creationdate><title>A multivariate comparison of the BERMS flux-tower climate observations and Canadian Coupled Global Climate Model (CGCM3) outputs</title><author>Chun, K.P. ; Wheater, H.S. ; Barr, A.G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a498t-b5c78c095c6ce4c1d49b64b21d664954386d2cee98811a0afded44b246f288f73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Boreal forest</topic><topic>Climate</topic><topic>Climate models</topic><topic>Climate variables</topic><topic>Computer simulation</topic><topic>Correlation structure</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>Exact sciences and technology</topic><topic>Flux towers</topic><topic>Forests</topic><topic>Global climate models</topic><topic>Hydrology</topic><topic>Hydrology. Hydrogeology</topic><topic>Joining</topic><topic>Mathematical models</topic><topic>Multivariate analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chun, K.P.</creatorcontrib><creatorcontrib>Wheater, H.S.</creatorcontrib><creatorcontrib>Barr, A.G.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chun, K.P.</au><au>Wheater, H.S.</au><au>Barr, A.G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A multivariate comparison of the BERMS flux-tower climate observations and Canadian Coupled Global Climate Model (CGCM3) outputs</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2014-11-27</date><risdate>2014</risdate><volume>519</volume><spage>1537</spage><epage>1550</epage><pages>1537-1550</pages><issn>0022-1694</issn><eissn>1879-2707</eissn><coden>JHYDA7</coden><abstract>•Comparisons are made between the Canadian GCM (CGCM3) outputs and flux observations.•The CGCM3 outputs and observations have different multivariate relationships.•The observations and CGCM have different relationships of humidity and radiation.•The CGCM3 relative humidity may not be suitable for hydrological modelling directly.•The CGCM3 wind speed outputs can be unreliable for hydrological modelling. Multiple variables from simulated climate fields are widely used in hydrological and ecological models and climate impact assessments, yet the importance of multivariate climate relationships is not widely recognised. This study evaluates climatic outputs from the Canadian Coupled Global Climate Model (CGCM3) in the southern boreal forests of western Canada, by comparing the simulated multivariate relationships with those observed at three representative forest sites. Monthly mean data for five near-surface climate variables (net radiation RN, air temperature TA, relative humidity RH, wind speed WS and surface pressure P) are analysed and compared using visual inspection, hypothesis testing and principal component analysis. The projections of the 1st and 2nd principal components, which explain about 75% of the variation in the data, show remarkable similarities in the observations from the three forest sites (with some subtle differences between the evergreen and deciduous plant functional types), but some broad differences between the observations and model outputs. The model reproduces the observed relationships among RN, TA and P, but not between RH or WS and the other variables. In particular, RH is strongly and negatively related to TA and RN in the forest observations but independent in the model outputs; RH is negatively related to WS in the observations but positively related in the model output; and P is uncoupled from the other variables in the observations but negatively related to RH and WS in the model output. The broad scope of the differences indicates a divergence of process representation at large time and space scales. We explore possible reasons for the observed discrepancies, which indicate some limitations in using climate model outputs directly to drive hydrological models.</abstract><cop>Kidlington</cop><pub>Elsevier B.V</pub><doi>10.1016/j.jhydrol.2014.08.059</doi><tpages>14</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0022-1694
ispartof Journal of hydrology (Amsterdam), 2014-11, Vol.519, p.1537-1550
issn 0022-1694
1879-2707
language eng
recordid cdi_proquest_miscellaneous_1651412296
source Elsevier ScienceDirect Journals Complete
subjects Boreal forest
Climate
Climate models
Climate variables
Computer simulation
Correlation structure
Earth sciences
Earth, ocean, space
Exact sciences and technology
Flux towers
Forests
Global climate models
Hydrology
Hydrology. Hydrogeology
Joining
Mathematical models
Multivariate analysis
title A multivariate comparison of the BERMS flux-tower climate observations and Canadian Coupled Global Climate Model (CGCM3) outputs
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-20T21%3A09%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20multivariate%20comparison%20of%20the%20BERMS%20flux-tower%20climate%20observations%20and%20Canadian%20Coupled%20Global%20Climate%20Model%20(CGCM3)%20outputs&rft.jtitle=Journal%20of%20hydrology%20(Amsterdam)&rft.au=Chun,%20K.P.&rft.date=2014-11-27&rft.volume=519&rft.spage=1537&rft.epage=1550&rft.pages=1537-1550&rft.issn=0022-1694&rft.eissn=1879-2707&rft.coden=JHYDA7&rft_id=info:doi/10.1016/j.jhydrol.2014.08.059&rft_dat=%3Cproquest_cross%3E1647010724%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1647010724&rft_id=info:pmid/&rft_els_id=S0022169414006696&rfr_iscdi=true