{"title":"CORRIGENDUM: Radiation budget in RegCM4: simulation results from two radiative schemes over the South West Indian Ocean","authors":"P. Li, B. Morel, M. Bessafi, Q. Li, M. Chiacchio","doi":"10.3354/cr01669_c","DOIUrl":"https://doi.org/10.3354/cr01669_c","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76409926","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}
AA Adetoro, Msc Ngidi, T. Ojo, G. Danso-Abbeam, A. Ogundeji, IR Orimoloye
{"title":"Weather-index insurance as an adaptation strategy to climate change: a global insight","authors":"AA Adetoro, Msc Ngidi, T. Ojo, G. Danso-Abbeam, A. Ogundeji, IR Orimoloye","doi":"10.3354/cr01697","DOIUrl":"https://doi.org/10.3354/cr01697","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73246066","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}
Prakash K. Jha, Panos Athanasiadis, Silvio Gualdi, Antonio Trabucco, Valentina Mereu, Vakhtang Shelia, Gerrit Hoogenboom
ABSTRACT: The direct application of forecasts from seasonal prediction systems (SPSs) in agriculture is limited by their skill, and SPSs are more skilled at El Niño-Southern Oscillation (ENSO) prediction than precipitation prediction. An alternative to the direct application of forecasts from SPSs could be to link the forecast of ENSO conditions with dynamic crop models to evaluate alternate crop management options prior to the start of the actual planting. Although potential benefits of this approach have been tested in many areas of the world, so far limited evidence exists regarding its application in Nepal’s Terai region. The overall goal of this study was to determine the potential relationship between ENSO and summer monsoon precipitation over Nepal’s Terai and ascertain SPSs’ skill in predicting ENSO. This analysis included disentangling the relative contribution of precipitation to interannual variability in rice yield from other factors using a cropping system model, namely, the Crop Environment Resource Synthesis-Rice (CSM-CERES-Rice). The crop model was also employed to explore options for increasing rice yield and minimizing risk by adjusting crop management. This study found that precipitation was the main variable affecting interannual variability in rice yield, that SPSs are good at predicting ENSO, and that the ENSO signal can be used to predict seasonal precipitation anomalies in the study area in all years except ENSO neutral years. Prior knowledge of seasonal precipitation anomalies can then be used to optimize rice yield using a crop model, and ultimately to assist farmers with decision making.
{"title":"Using ENSO conditions to optimize rice yield for Nepal’s Terai","authors":"Prakash K. Jha, Panos Athanasiadis, Silvio Gualdi, Antonio Trabucco, Valentina Mereu, Vakhtang Shelia, Gerrit Hoogenboom","doi":"10.3354/cr01699","DOIUrl":"https://doi.org/10.3354/cr01699","url":null,"abstract":"ABSTRACT: The direct application of forecasts from seasonal prediction systems (SPSs) in agriculture is limited by their skill, and SPSs are more skilled at El Niño-Southern Oscillation (ENSO) prediction than precipitation prediction. An alternative to the direct application of forecasts from SPSs could be to link the forecast of ENSO conditions with dynamic crop models to evaluate alternate crop management options prior to the start of the actual planting. Although potential benefits of this approach have been tested in many areas of the world, so far limited evidence exists regarding its application in Nepal’s Terai region. The overall goal of this study was to determine the potential relationship between ENSO and summer monsoon precipitation over Nepal’s Terai and ascertain SPSs’ skill in predicting ENSO. This analysis included disentangling the relative contribution of precipitation to interannual variability in rice yield from other factors using a cropping system model, namely, the Crop Environment Resource Synthesis-Rice (CSM-CERES-Rice). The crop model was also employed to explore options for increasing rice yield and minimizing risk by adjusting crop management. This study found that precipitation was the main variable affecting interannual variability in rice yield, that SPSs are good at predicting ENSO, and that the ENSO signal can be used to predict seasonal precipitation anomalies in the study area in all years except ENSO neutral years. Prior knowledge of seasonal precipitation anomalies can then be used to optimize rice yield using a crop model, and ultimately to assist farmers with decision making.","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138530461","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}
The coronavirus disease 2019 (COVID-19) pandemic has demonstrated that with daily data informing citizens and governments of the situation, society can respond to a crisis rapidly. We suggest that the current multi-yearly assessments of the, by comparison, chronic crises of climate change and biodiversity loss are no longer fit for purpose. Instead, annual assessments (as is standard for governmental budgets, commercial and personal taxes) are now required. As with COVID-19 data, the annual progress reports proposed here must be accompanied by new biodiversity and climate data that are both timely and open access, thus supporting scientific advice. With public transparency and accessibility of facts and figures, annual reports will lead to more accountability and progress in addressing the causes of these crises.
{"title":"Pandemic shows that global climate and biodiversity science assessments need to be annual","authors":"M. Costello, KS Kelly","doi":"10.3354/cr01695","DOIUrl":"https://doi.org/10.3354/cr01695","url":null,"abstract":"The coronavirus disease 2019 (COVID-19) pandemic has demonstrated that with daily data informing citizens and governments of the situation, society can respond to a crisis rapidly. We suggest that the current multi-yearly assessments of the, by comparison, chronic crises of climate change and biodiversity loss are no longer fit for purpose. Instead, annual assessments (as is standard for governmental budgets, commercial and personal taxes) are now required. As with COVID-19 data, the annual progress reports proposed here must be accompanied by new biodiversity and climate data that are both timely and open access, thus supporting scientific advice. With public transparency and accessibility of facts and figures, annual reports will lead to more accountability and progress in addressing the causes of these crises.","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88243039","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}
N. Stenseth, R. Ims, B. Sæther, L. Cadahía, I. Herfindal, A. Lee, JD Whittington, N. Yoccoz
The sustainable use of natural resources is critical for addressing the global challenges of today. Strategies for sustainable harvesting need to consider not only harvested species, but also other non-harvested species interacting with them in the same ecosystem. In addition, environmental variation needs to be considered, with climate change currently being one of the main sources of this variation. Understanding the consequences of complex interactions between different drivers and processes affecting dynamics of species and ecosystems across spatial scales requires large-scale integrative research projects. The Norwegian research initiative “Sustainable management of renewable resources in a changing environment: an integrated approach across ecosystems” (SUSTAIN) was launched to fill knowledge gaps related to the sustainable management of populations and ecosystems experiencing climate change. SUSTAIN investigated terrestrial, marine and freshwater ecosystems in boreal and Arctic regions, using both theoretical developments and empirical analyses of long-term data. This Climate Research Special contains both synthesis articles and original research exemplifying some of the approaches used in SUSTAIN. In this introduction we highlight 4 key topics addressed by SUSTAIN: (i) population structure, (ii) interactions between species, (iii) spatial processes, and (iv) adaptive management. These topics are fundamental to the understanding of harvested species from an ecosystem perspective, and to ecosystem-based management approaches, which we are striving to work towards.
{"title":"Sustainable management of populations impacted by harvesting and climate change","authors":"N. Stenseth, R. Ims, B. Sæther, L. Cadahía, I. Herfindal, A. Lee, JD Whittington, N. Yoccoz","doi":"10.3354/cr01688","DOIUrl":"https://doi.org/10.3354/cr01688","url":null,"abstract":"The sustainable use of natural resources is critical for addressing the global challenges of today. Strategies for sustainable harvesting need to consider not only harvested species, but also other non-harvested species interacting with them in the same ecosystem. In addition, environmental variation needs to be considered, with climate change currently being one of the main sources of this variation. Understanding the consequences of complex interactions between different drivers and processes affecting dynamics of species and ecosystems across spatial scales requires large-scale integrative research projects. The Norwegian research initiative “Sustainable management of renewable resources in a changing environment: an integrated approach across ecosystems” (SUSTAIN) was launched to fill knowledge gaps related to the sustainable management of populations and ecosystems experiencing climate change. SUSTAIN investigated terrestrial, marine and freshwater ecosystems in boreal and Arctic regions, using both theoretical developments and empirical analyses of long-term data. This Climate Research Special contains both synthesis articles and original research exemplifying some of the approaches used in SUSTAIN. In this introduction we highlight 4 key topics addressed by SUSTAIN: (i) population structure, (ii) interactions between species, (iii) spatial processes, and (iv) adaptive management. These topics are fundamental to the understanding of harvested species from an ecosystem perspective, and to ecosystem-based management approaches, which we are striving to work towards.","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":"72387558","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}
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}
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