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dc.contributor.authorMendez, M
dc.contributor.authorMaathuis, B
dc.contributor.authorHein-Griggs, D
dc.contributor.authorAlvarado-Gamboa, LF
dc.date.accessioned2020-08-17T13:01:09Z
dc.date.issued2020-02-11
dc.description.abstractSix bias correction (BC) methods; delta-method (DT), linear scaling (LS), power transformation of precipitation (PTR), empirical quantile mapping (EQM), gamma quantile mapping (GQM) and gamma-pareto quantile mapping (GPQM) were applied to adjust the biases of historical monthly precipitation outputs from five General Circulation Models (GCMs) dynamically downscaled by two Regional Climate Models (RCMs) for a total of seven different GCM-RCM pairs over Costa Rica. High-resolution gridded precipitation observations were used for the control period 1951-1980 and validated over the period 1981-1995. Results show that considerable biases exist between uncorrected GCM-RCM outputs and observations, which largely depend on GCM-RCM pair, seasonality, climatic region and spatial resolution. After the application of bias correction, substantial biases reductions and comparable performances among most BC methods were observed for most GCM-RCM pairs; withEQMand DT marginally outperforming the remaining methods. Consequently, EQM and DT were selectively applied to correct the biases of precipitation projections from each individual GCM-RCM pair for a near-future (2011-2040), mid-future (2041-2070) and far-future (2071-2100) period under Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 using the control period 1961-1990. Results from the bias-corrected future ensemble-mean anticipate a marked decreasing trend in precipitation from near to far-future periods during the dry season (December, January, February (DJF) and March, April, May (MAM) for RCP4.5 and 8.5; with pronounced drier conditions for those climatic regions draining towards the Pacific Ocean. In contrast, mostly wetter conditions are expected during the dry season under RCP2.6, particularly for the Caribbean region. In most of the country, the greatest decrease in precipitation is projected at the beginning of the rainy season (June, July, August (JJA) for the far-future period under RCP8.5, except for the Caribbean region where mostly wetter conditions are anticipated. Regardless of future period, slight increases in precipitation with higher radiative forcing are expected for SON excluding the Caribbean region, where precipitation is likely to increase with increasing radiative forcing and future period. This study demonstrates that bias correction should be considered before direct application of GCM-RCM precipitation projections over complex territories such as Costa Rica.en_GB
dc.description.sponsorshipVicerrectoría de Investigación & Extensión, Instituto Tecnológico de Costa Rica (TEC)en_GB
dc.identifier.citationVol. 12 (2), 482en_GB
dc.identifier.doi10.3390/w12020482
dc.identifier.urihttp://hdl.handle.net/10871/122498
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectbias-correctionen_GB
dc.subjectclimate-changeen_GB
dc.subjectGCMen_GB
dc.subjectRCMen_GB
dc.subjectRCPen_GB
dc.subjectprecipitationen_GB
dc.titlePerformance evaluation of bias correction methods for climate change monthly precipitation projections over Costa Ricaen_GB
dc.typeArticleen_GB
dc.date.available2020-08-17T13:01:09Z
dc.descriptionThis is the final version. Available from MDPI via the DOI in this record. en_GB
dc.descriptionThe following are available online at http://www.mdpi.com/2073-4441/12/2/482/s1, uncorrected GCM-RCM, observed precipitation and GPCC data for the period 1951–1995, the complete R computational code, the ggplot2-graphical code and all GeoTIFF generated maps can be access at the following Github repository: https://github.com/maikelonu/Research_Future_Precipitation_Ensemble_GCM_RCM_RCP. All R scripts have been clearly commented so any one can reproduce the Results presented in this manuscript.en_GB
dc.identifier.eissn2073-4441
dc.identifier.journalWateren_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-02-07
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-02-07
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-08-17T12:57:13Z
refterms.versionFCDVoR
refterms.dateFOA2020-08-17T13:01:17Z
refterms.panelCen_GB


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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).