Linking weather generators and crop models for assessment of climate forecast outcomes
Agricultural production responses to climate variability require salient information to support decisions. We coupled a new hybrid stochastic weather generator [combining parametric and nonparametric components] with a crop simulation model to assess yields and economic returns relevant to maize production in two contrasting regions [Pergamino and Pilar] of the Pampas of Argentina. The linked models were used to assess likely outcomes and production risks for seasonal forecasts of dry and wet climate. Forecasts involving even relatively small deviations from climatological probabilities of precipitation may have large impacts on agricultural outcomes. Furthermore, yield changes under alternative scenarios have a disproportionate effect on economic risks. Additionally, we show that regions receiving the same seasonal forecast may experience fairly different outcomes: a forecast of dry conditions did not change appreciably the expected distribution of economic margins in Pergamino [a climatically optimal location] but modified considerably economic expectations [and thus production risk] in Pilar [a more marginal location].
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| Format: | Texto biblioteca |
| Language: | eng |
| Subjects: | ARGENTINA, CLIMATE IMPACTS, MAIZE, RISK ASSESSMENT, SEASONAL FORECASTING, STATISTICAL DOWNSCALING, AGRICULTURAL PRODUCTION, CLIMATE EFFECT, CROP YIELD, DOWNSCALING, REGIONAL CLIMATE, SIMULATION, WEATHER FORECASTING, BUENOS AIRES [ARGENTINA], CORDOBA [ARGENTINA], PERGAMINO, PILAR, ZEA MAYS, |
| Online Access: | http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=46669 |
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KOHA-OAI-AGRO:466692022-02-18T13:55:05Zhttp://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=46669AAGLinking weather generators and crop models for assessment of climate forecast outcomesApipattanavis, SomkiatBert, Federico E.Podestá, Guillermo P.Rajagopalan, Balajitextengapplication/pdfAgricultural production responses to climate variability require salient information to support decisions. We coupled a new hybrid stochastic weather generator [combining parametric and nonparametric components] with a crop simulation model to assess yields and economic returns relevant to maize production in two contrasting regions [Pergamino and Pilar] of the Pampas of Argentina. The linked models were used to assess likely outcomes and production risks for seasonal forecasts of dry and wet climate. Forecasts involving even relatively small deviations from climatological probabilities of precipitation may have large impacts on agricultural outcomes. Furthermore, yield changes under alternative scenarios have a disproportionate effect on economic risks. Additionally, we show that regions receiving the same seasonal forecast may experience fairly different outcomes: a forecast of dry conditions did not change appreciably the expected distribution of economic margins in Pergamino [a climatically optimal location] but modified considerably economic expectations [and thus production risk] in Pilar [a more marginal location].Agricultural production responses to climate variability require salient information to support decisions. We coupled a new hybrid stochastic weather generator [combining parametric and nonparametric components] with a crop simulation model to assess yields and economic returns relevant to maize production in two contrasting regions [Pergamino and Pilar] of the Pampas of Argentina. The linked models were used to assess likely outcomes and production risks for seasonal forecasts of dry and wet climate. Forecasts involving even relatively small deviations from climatological probabilities of precipitation may have large impacts on agricultural outcomes. Furthermore, yield changes under alternative scenarios have a disproportionate effect on economic risks. Additionally, we show that regions receiving the same seasonal forecast may experience fairly different outcomes: a forecast of dry conditions did not change appreciably the expected distribution of economic margins in Pergamino [a climatically optimal location] but modified considerably economic expectations [and thus production risk] in Pilar [a more marginal location].ARGENTINACLIMATE IMPACTSMAIZERISK ASSESSMENTSEASONAL FORECASTINGSTATISTICAL DOWNSCALINGAGRICULTURAL PRODUCTIONCLIMATE EFFECTCROP YIELDDOWNSCALINGREGIONAL CLIMATERISK ASSESSMENTSIMULATIONWEATHER FORECASTINGBUENOS AIRES [ARGENTINA]CORDOBA [ARGENTINA]PERGAMINOPILARZEA MAYSAgricultural and Forest Meteorology |
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Argentina |
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AR |
| component |
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cat-ceiba |
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biblioteca |
| region |
America del Sur |
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Biblioteca Central FAUBA |
| language |
eng |
| topic |
ARGENTINA CLIMATE IMPACTS MAIZE RISK ASSESSMENT SEASONAL FORECASTING STATISTICAL DOWNSCALING AGRICULTURAL PRODUCTION CLIMATE EFFECT CROP YIELD DOWNSCALING REGIONAL CLIMATE RISK ASSESSMENT SIMULATION WEATHER FORECASTING BUENOS AIRES [ARGENTINA] CORDOBA [ARGENTINA] PERGAMINO PILAR ZEA MAYS ARGENTINA CLIMATE IMPACTS MAIZE RISK ASSESSMENT SEASONAL FORECASTING STATISTICAL DOWNSCALING AGRICULTURAL PRODUCTION CLIMATE EFFECT CROP YIELD DOWNSCALING REGIONAL CLIMATE RISK ASSESSMENT SIMULATION WEATHER FORECASTING BUENOS AIRES [ARGENTINA] CORDOBA [ARGENTINA] PERGAMINO PILAR ZEA MAYS |
| spellingShingle |
ARGENTINA CLIMATE IMPACTS MAIZE RISK ASSESSMENT SEASONAL FORECASTING STATISTICAL DOWNSCALING AGRICULTURAL PRODUCTION CLIMATE EFFECT CROP YIELD DOWNSCALING REGIONAL CLIMATE RISK ASSESSMENT SIMULATION WEATHER FORECASTING BUENOS AIRES [ARGENTINA] CORDOBA [ARGENTINA] PERGAMINO PILAR ZEA MAYS ARGENTINA CLIMATE IMPACTS MAIZE RISK ASSESSMENT SEASONAL FORECASTING STATISTICAL DOWNSCALING AGRICULTURAL PRODUCTION CLIMATE EFFECT CROP YIELD DOWNSCALING REGIONAL CLIMATE RISK ASSESSMENT SIMULATION WEATHER FORECASTING BUENOS AIRES [ARGENTINA] CORDOBA [ARGENTINA] PERGAMINO PILAR ZEA MAYS Apipattanavis, Somkiat Bert, Federico E. Podestá, Guillermo P. Rajagopalan, Balaji Linking weather generators and crop models for assessment of climate forecast outcomes |
| description |
Agricultural production responses to climate variability require salient information to support decisions. We coupled a new hybrid stochastic weather generator [combining parametric and nonparametric components] with a crop simulation model to assess yields and economic returns relevant to maize production in two contrasting regions [Pergamino and Pilar] of the Pampas of Argentina. The linked models were used to assess likely outcomes and production risks for seasonal forecasts of dry and wet climate. Forecasts involving even relatively small deviations from climatological probabilities of precipitation may have large impacts on agricultural outcomes. Furthermore, yield changes under alternative scenarios have a disproportionate effect on economic risks. Additionally, we show that regions receiving the same seasonal forecast may experience fairly different outcomes: a forecast of dry conditions did not change appreciably the expected distribution of economic margins in Pergamino [a climatically optimal location] but modified considerably economic expectations [and thus production risk] in Pilar [a more marginal location]. |
| format |
Texto |
| topic_facet |
ARGENTINA CLIMATE IMPACTS MAIZE RISK ASSESSMENT SEASONAL FORECASTING STATISTICAL DOWNSCALING AGRICULTURAL PRODUCTION CLIMATE EFFECT CROP YIELD DOWNSCALING REGIONAL CLIMATE RISK ASSESSMENT SIMULATION WEATHER FORECASTING BUENOS AIRES [ARGENTINA] CORDOBA [ARGENTINA] PERGAMINO PILAR ZEA MAYS |
| author |
Apipattanavis, Somkiat Bert, Federico E. Podestá, Guillermo P. Rajagopalan, Balaji |
| author_facet |
Apipattanavis, Somkiat Bert, Federico E. Podestá, Guillermo P. Rajagopalan, Balaji |
| author_sort |
Apipattanavis, Somkiat |
| title |
Linking weather generators and crop models for assessment of climate forecast outcomes |
| title_short |
Linking weather generators and crop models for assessment of climate forecast outcomes |
| title_full |
Linking weather generators and crop models for assessment of climate forecast outcomes |
| title_fullStr |
Linking weather generators and crop models for assessment of climate forecast outcomes |
| title_full_unstemmed |
Linking weather generators and crop models for assessment of climate forecast outcomes |
| title_sort |
linking weather generators and crop models for assessment of climate forecast outcomes |
| url |
http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=46669 |
| work_keys_str_mv |
AT apipattanavissomkiat linkingweathergeneratorsandcropmodelsforassessmentofclimateforecastoutcomes AT bertfedericoe linkingweathergeneratorsandcropmodelsforassessmentofclimateforecastoutcomes AT podestaguillermop linkingweathergeneratorsandcropmodelsforassessmentofclimateforecastoutcomes AT rajagopalanbalaji linkingweathergeneratorsandcropmodelsforassessmentofclimateforecastoutcomes |
| _version_ |
1756046674753486848 |