Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scen...

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Main Authors: Chung, U., Gbegbelegbe, Sika, Shiferaw, Bekele, Robertson, Richard D., Yun JI, Tesfaye Fantaye, Kindie, Hoogenboom, Gerrit, Sonder, Kai
Format: Journal Article
Language:Inglés
Published: Elsevier 2014
Subjects:
Online Access:https://hdl.handle.net/10568/68175
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author Chung, U.
Gbegbelegbe, Sika
Shiferaw, Bekele
Robertson, Richard D.
Yun JI
Tesfaye Fantaye, Kindie
Hoogenboom, Gerrit
Sonder, Kai
author_browse Chung, U.
Gbegbelegbe, Sika
Hoogenboom, Gerrit
Robertson, Richard D.
Shiferaw, Bekele
Sonder, Kai
Tesfaye Fantaye, Kindie
Yun JI
author_facet Chung, U.
Gbegbelegbe, Sika
Shiferaw, Bekele
Robertson, Richard D.
Yun JI
Tesfaye Fantaye, Kindie
Hoogenboom, Gerrit
Sonder, Kai
author_sort Chung, U.
collection Repository of Agricultural Research Outputs (CGSpace)
description This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s respectively, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively.
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spelling CGSpace681752025-05-01T21:01:53Z Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world Chung, U. Gbegbelegbe, Sika Shiferaw, Bekele Robertson, Richard D. Yun JI Tesfaye Fantaye, Kindie Hoogenboom, Gerrit Sonder, Kai maize agriculture developing countries food security crop modelling climate change This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s respectively, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. 2014-10 2015-09-16T17:00:27Z 2015-09-16T17:00:27Z Journal Article https://hdl.handle.net/10568/68175 en Open Access Elsevier Chung U, Gbegbelegbe S, Shiferaw B, Robertson R, Yun JI, Tesfaye K, Hoogenboom G, Sonder K. 2014. Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world. Weather and Climate Extremes 5-6:67-77.
spellingShingle maize
agriculture
developing countries
food security
crop modelling
climate change
Chung, U.
Gbegbelegbe, Sika
Shiferaw, Bekele
Robertson, Richard D.
Yun JI
Tesfaye Fantaye, Kindie
Hoogenboom, Gerrit
Sonder, Kai
Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world
title Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world
title_full Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world
title_fullStr Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world
title_full_unstemmed Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world
title_short Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world
title_sort modeling the effect of a heat wave on maize production in the usa and its implications on food security in the developing world
topic maize
agriculture
developing countries
food security
crop modelling
climate change
url https://hdl.handle.net/10568/68175
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