A multi-model analysis of teleconnected crop yield variability in a range of cropping systems
Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño-Southern Oscillation (ENSO), which has been...
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2020
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ftdatacite:10.34657/5978 2023-05-15T17:30:09+02:00 A multi-model analysis of teleconnected crop yield variability in a range of cropping systems Heino, Matias Guillaume, Joseph H.A. Müller, Christoph Iizumi, Toshichika Kummu, Matti 2020 https://dx.doi.org/10.34657/5978 https://oa.tib.eu/renate/handle/123456789/6931 unknown Göttingen : Copernicus Publ. Creative Commons Attribution 4.0 International CC BY 4.0 Unported https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Atmospheric pressure Crops Cultivation Atmospheric phenomena Climate oscillation Crop managements Growing conditions Indian ocean dipoles North Atlantic oscillations Southern oscillation Weather patterns Climatology air-sea interaction climate effect crop yield cropping practice El Nino-Southern Oscillation ensemble forecasting Indian Ocean Dipole North Atlantic Oscillation teleconnection Australia Europe Glycine max Triticum aestivum Zea mays 550 CreativeWork article 2020 ftdatacite https://doi.org/10.34657/5978 2022-03-10T12:44:35Z Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño-Southern Oscillation (ENSO), which has been found to impact crop yields on all continents that produce crops, while two other climate oscillations - the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) - have been shown to especially impact crop production in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD, and NAO on the growing conditions of maize, rice, soybean, and wheat at the global scale by utilising crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that, while accounting for their potential co-variation, climate oscillations are correlated with simulated crop yield variability to a wide extent (half of all maize and wheat harvested areas for ENSO) and in several important crop-producing areas, e.g. in North America (ENSO, wheat), Australia (IOD and ENSO, wheat), and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed and fully fertilised scenarios, while the sensitivity tends to be lower if crops were to be fully irrigated. Since the development of ENSO, IOD, and NAO can potentially be forecasted well in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate-related shocks. © 2020 American Institute of Physics Inc.. All rights reserved. Article in Journal/Newspaper North Atlantic North Atlantic oscillation DataCite Metadata Store (German National Library of Science and Technology) Indian |
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Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
Atmospheric pressure Crops Cultivation Atmospheric phenomena Climate oscillation Crop managements Growing conditions Indian ocean dipoles North Atlantic oscillations Southern oscillation Weather patterns Climatology air-sea interaction climate effect crop yield cropping practice El Nino-Southern Oscillation ensemble forecasting Indian Ocean Dipole North Atlantic Oscillation teleconnection Australia Europe Glycine max Triticum aestivum Zea mays 550 |
spellingShingle |
Atmospheric pressure Crops Cultivation Atmospheric phenomena Climate oscillation Crop managements Growing conditions Indian ocean dipoles North Atlantic oscillations Southern oscillation Weather patterns Climatology air-sea interaction climate effect crop yield cropping practice El Nino-Southern Oscillation ensemble forecasting Indian Ocean Dipole North Atlantic Oscillation teleconnection Australia Europe Glycine max Triticum aestivum Zea mays 550 Heino, Matias Guillaume, Joseph H.A. Müller, Christoph Iizumi, Toshichika Kummu, Matti A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
topic_facet |
Atmospheric pressure Crops Cultivation Atmospheric phenomena Climate oscillation Crop managements Growing conditions Indian ocean dipoles North Atlantic oscillations Southern oscillation Weather patterns Climatology air-sea interaction climate effect crop yield cropping practice El Nino-Southern Oscillation ensemble forecasting Indian Ocean Dipole North Atlantic Oscillation teleconnection Australia Europe Glycine max Triticum aestivum Zea mays 550 |
description |
Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño-Southern Oscillation (ENSO), which has been found to impact crop yields on all continents that produce crops, while two other climate oscillations - the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) - have been shown to especially impact crop production in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD, and NAO on the growing conditions of maize, rice, soybean, and wheat at the global scale by utilising crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that, while accounting for their potential co-variation, climate oscillations are correlated with simulated crop yield variability to a wide extent (half of all maize and wheat harvested areas for ENSO) and in several important crop-producing areas, e.g. in North America (ENSO, wheat), Australia (IOD and ENSO, wheat), and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed and fully fertilised scenarios, while the sensitivity tends to be lower if crops were to be fully irrigated. Since the development of ENSO, IOD, and NAO can potentially be forecasted well in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate-related shocks. © 2020 American Institute of Physics Inc.. All rights reserved. |
format |
Article in Journal/Newspaper |
author |
Heino, Matias Guillaume, Joseph H.A. Müller, Christoph Iizumi, Toshichika Kummu, Matti |
author_facet |
Heino, Matias Guillaume, Joseph H.A. Müller, Christoph Iizumi, Toshichika Kummu, Matti |
author_sort |
Heino, Matias |
title |
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
title_short |
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
title_full |
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
title_fullStr |
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
title_full_unstemmed |
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
title_sort |
multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
publisher |
Göttingen : Copernicus Publ. |
publishDate |
2020 |
url |
https://dx.doi.org/10.34657/5978 https://oa.tib.eu/renate/handle/123456789/6931 |
geographic |
Indian |
geographic_facet |
Indian |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_rights |
Creative Commons Attribution 4.0 International CC BY 4.0 Unported https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.34657/5978 |
_version_ |
1766125965283426304 |