Prediction of the occurrence or non-occurrence of daily rainfall plays a significant role in agricultural planning and water resource management projects. In this study, gamma distribution function (GDF), kernel, and exponential (EXP) distributions were coupled (piecewise) with a generalized Pareto distribution. Thus, the gamma-generalized Pareto (GGP), kernel-generalized Pareto (KGP), and exponential-generalized Pareto (EGP) models were used. The aim of the present study was to introduce new methods to modify the simulated generation of extreme rainfall amounts of rainy seasons based on the preserved spatial correlation. The best approach was identified using the normalized root mean square error (NRMSE) criterion. For this purpose, the 30-yr daily rainfall datasets of 21 synoptic weather stations located in different climates of West Iran were analyzed. The first, second, and third-order Markov chain (MC) models were used to describe rainfall time series frequencies. The best MC model order was detected using the Akaike information criterion and Bayesian information criterion. Based on the best identified MC model order, the best piecewise distribution models, and the Wilks approach, rainfall events were modeled with regard to the spatial correlation among the study stations. The performance of the Wilks approach was verified using the coefficient of determination. The daily rainfall simulation resulted in a good agreement between the observed and the generated rainfall data. Hence, the proposed approach is capable of helping water resource managers in different contexts of agricultural planning.
{"title":"Improving daily rainfall extremes simulation using the generalized Pareto distribution: a case study in Western Iran","authors":"N. Shahraki, S. Marofi, S. Ghazanfari","doi":"10.3354/cr01665","DOIUrl":"https://doi.org/10.3354/cr01665","url":null,"abstract":"Prediction of the occurrence or non-occurrence of daily rainfall plays a significant role in agricultural planning and water resource management projects. In this study, gamma distribution function (GDF), kernel, and exponential (EXP) distributions were coupled (piecewise) with a generalized Pareto distribution. Thus, the gamma-generalized Pareto (GGP), kernel-generalized Pareto (KGP), and exponential-generalized Pareto (EGP) models were used. The aim of the present study was to introduce new methods to modify the simulated generation of extreme rainfall amounts of rainy seasons based on the preserved spatial correlation. The best approach was identified using the normalized root mean square error (NRMSE) criterion. For this purpose, the 30-yr daily rainfall datasets of 21 synoptic weather stations located in different climates of West Iran were analyzed. The first, second, and third-order Markov chain (MC) models were used to describe rainfall time series frequencies. The best MC model order was detected using the Akaike information criterion and Bayesian information criterion. Based on the best identified MC model order, the best piecewise distribution models, and the Wilks approach, rainfall events were modeled with regard to the spatial correlation among the study stations. The performance of the Wilks approach was verified using the coefficient of determination. The daily rainfall simulation resulted in a good agreement between the observed and the generated rainfall data. Hence, the proposed approach is capable of helping water resource managers in different contexts of agricultural planning.","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90274060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Brito, J. Veiga, F. Correia, A. Michiles, V. Capistrano, Sc Chou, AdA Lyra, G. Medeiros
{"title":"Impacts of greenhouse gases and deforestation in Amazon Basin climate extreme indices","authors":"A. Brito, J. Veiga, F. Correia, A. Michiles, V. Capistrano, Sc Chou, AdA Lyra, G. Medeiros","doi":"10.3354/cr01694","DOIUrl":"https://doi.org/10.3354/cr01694","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85838515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Role of changing land use and land cover on the 2018 megafloods over Kerala, India","authors":"A. Dixit, S. Sahany, B. Rajagopalan, S. Choubey","doi":"10.3354/cr01701","DOIUrl":"https://doi.org/10.3354/cr01701","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87764406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Masoud Yazdanpanah, T. Zobeidi, S. Sieber, K. Löhr, SB Homayoon
{"title":"Changing rice cropping patterns to crops with less water consumption","authors":"Masoud Yazdanpanah, T. Zobeidi, S. Sieber, K. Löhr, SB Homayoon","doi":"10.3354/cr01700","DOIUrl":"https://doi.org/10.3354/cr01700","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84453424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sensitivity of precipitation and atmospheric low-level circulation patterns to domain size and choice of parameterization schemes in RegCM4.4 over Central America","authors":"E. Rivera, J. Amador, F. Sáenz","doi":"10.3354/cr01707","DOIUrl":"https://doi.org/10.3354/cr01707","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84966326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Qu, Q. Wang, Z. Li, R. Zhang, J. Zeng, Y. Song, X. Yang, J. Lv
{"title":"Reconstruction of the severe drought events of 1875–1879 in Shanxi Province, China, based on rain and snow record data from the Qing Palace Archives","authors":"Y. Qu, Q. Wang, Z. Li, R. Zhang, J. Zeng, Y. Song, X. Yang, J. Lv","doi":"10.3354/cr01690","DOIUrl":"https://doi.org/10.3354/cr01690","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85215444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatio-temporal trend and frequency analysis of precipitation in South-southern Nigeria (SSN)","authors":"AT Ogunrinde, Y. Olotu, O. Ilesanmi","doi":"10.3354/cr01698","DOIUrl":"https://doi.org/10.3354/cr01698","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88400788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of rainfall and temperature trends and variability in semi-arid Tharaka South Subcounty, Kenya","authors":"CG Kaua, T. Thenya, J. Mutune","doi":"10.3354/cr01696","DOIUrl":"https://doi.org/10.3354/cr01696","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85079057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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