Integrated Assessment of Climate Change Impacts on Corn Yield in the U.S. Using a Crop Model

2017 ◽  
Vol 60 (6) ◽  
pp. 2123-2136
Author(s):  
Kenichi Tatsumi

Abstract. A detailed analysis was conducted of the effects of climate change and increased carbon dioxide (CO2) concentrations on corn yield in the U.S. with a crop model using outputs from multiple general circulation models (multi-GCMs). Corn yield was simulated for 1999-2010, for the 2050s (average for 2041-2060), and for the 2070s (average for 2061-2080) under the representative concentration pathway 8.5 (RCP8.5) climate scenario. Results indicated a shortening of the growing period (GP), decreased water use efficiency (WUE) in almost all regions, and increased evapotranspiration (ET) during GP in almost all regions except for the southern U.S. Using multi-GCMs, the simulations under the RCP8.5 scenario resulted in negative effects of climate change on yield in almost all regions during both future periods. Especially strong negative impacts were reported south of latitude 40° N due to less optimal growing conditions. On the other hand, there were relatively smaller negative impacts in high-latitude regions (approximately north of latitude 40° N) due to more optimal growing conditions because of larger temperature changes compared to low-latitude and mid-latitude regions. Higher CO2 concentrations have the potential to increase corn yield. CO2 effects resulted in an approximately 0.04% to 0.05% increase in yield per 1 ppm increase in CO2 concentration under the RCP8.5 scenario, but the negative impacts of increased temperatures fully outweighed the CO2-fertilization effects. Keywords: Climate change impacts, CO2 effects, Corn yield, Multiple GCMs, Uncertainty.

2014 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Alireza Nikbakht Shahbazi

Drought is one of the major natural disasters in the world which has a lot of social and economic impacts. There are various factors that affect climate changes; the investigation of this incident is also sensitive. Climate scenarios of future climate change studies and investigation of efficient methods for investigating these events on drought should be assumed. This study intends to investigate climate change impacts on drought in Karoon3 watershed in the future. For this purpose, the atmospheric general circulation models (GCM) data under Intergovernmental Panel on Climate Change (IPCC) scenarios should be investigated. In this study, watershed drought under climate change impacts will be simulated in future periods (2011 to 2099). In this research standard precipitation index (SPI) was calculated using mean monthly precipitation data in Karoon3 watershed. SPI was calculated in 6, 12 and 24 months periods. Statistical analysis on daily precipitation and minimum and maximum daily temperature was performed. To determine the feasibility of future periods meteorological data production of LRAS-WG5 model, calibration and verification was performed for the base year (1980-2007). Meteorological data simulation for future periods under General Circulation Models and climate change IPCC scenarios was performed and then the drought status using SPI under climate change effects analyzed. Results showed that differences between monthly maximum and minimum temperature will decrease under climate change and spring precipitation shall increase while summer and autumn rainfall shall decrease. The most increase of precipitation will take place in winter and in December. Normal and wet SPI category is more frequent in B1 and A2 emissions scenarios than A1B. Wet years increases in the study area during 2011-2030 period and the more continuous drought years gradually increases during 2046-2065 period, the more severe and frequent drought will occur during the 2080-2099 period.


2018 ◽  
Vol 7 (7) ◽  
pp. 280 ◽  
Author(s):  
Md Alam ◽  
Mehmet Ercan ◽  
Faria Zahura ◽  
Jonathan Goodall

Many watersheds are currently experiencing streamflow and water quality related problems that are caused by excess nitrogen. Given that weather is a major driver of nitrogen transport through watersheds, the objective of this study was to predict climate change impacts on streamflow and nitrogen export. A forest and pasture dominated watershed in North Carolina Piedmont region was used as the study area. A physically-based Soil and Water Assessment Tool (SWAT) model parameterized using geospatial data layers and spatially downscaled temperature and precipitation estimates from eight different General Circulation Models (GCMs) were used for this study. While temperature change predictions are fairly consistent across the GCMs for the study watershed, there is significant variability in precipitation change predictions across the GCMs, and this leads to uncertainty in the future conditions within the watershed. However, when the downscaled GCM projections were taken as a model ensemble, the results suggest that both high and low emission scenarios would result in an average increase in streamflow of 14.1% and 12.5%, respectively, and a decrease in the inorganic nitrogen export by 12.1% and 8.5%, respectively, by the end of the century. The results also show clear seasonal patterns with streamflow and nitrogen loading both increasing in fall and winter months by 97.8% and 50.8%, respectively, and decreasing by 20.2% and 35.5%, respectively, in spring and summer months by the end of the century.


2021 ◽  
Author(s):  
Mohammad Reza Khazaei ◽  
Mehraveh Hasirchian ◽  
Bagher Zahabiyoun

Abstract Weather Generators (WGs) are one of the major downscaling tools for assessing regional climate change impacts. However, some deficiencies in the performance of WGs have limited their usage. This paper presents a method for correcting the low-frequency variability (LFV) of precipitation in the Improved Weather Generator (IWG) model. The method is based on bias correction in the monthly precipitation distribution of the generated daily series. The performance of the modified model was tested directly by comparing the statistics of generated and observed weather data for 14 stations, and also indirectly by comparing the characteristics of simulated stream-flows of a basin from the simulations run based on generated and observed weather data. The results showed that the method not only corrected the LFV of precipitation but also improved the reproduction of many other statistics. The provided IWG2 model can serve as a useful tool for the downscaling of General Circulation Models (GCMs) scenarios to assess regional climate change impacts, especially hydrological effects.


2016 ◽  
Vol 47 (5) ◽  
pp. 951-963 ◽  
Author(s):  
L. P. Koedyk ◽  
D. G. Kingston

Projected changes in 21st century climate are likely to impact water resources substantially, although much uncertainty remains as to the nature of such impacts. A relatively under-explored source of uncertainty is the method by which current and scenario evapotranspiration (ET) are estimated. Using the Waikaia River (New Zealand) as a case study, the influence of a potential ET (PET) method is investigated for a scenario of a 2°C increase in global mean temperature (the presumed threshold of ‘dangerous’ climate change). Six PET methods are investigated, with five general circulation models (GCMs) used to provide an indication of GCM uncertainty. The HBV-Light hydrological model is used to simulate river runoff. Uncertainty in scenario PET between methods is generally greater than between GCMs, but the reverse is found for runoff. The cause of the reduction in uncertainty from PET to runoff is unclear: the catchment is not water-limited during the summer half-year, indicating that it is not because of actual ET failing to reach the potential rate. Irrespective of the cause, these results stand in contrast to previous estimations of relatively high sensitivity of runoff projections to PET methods, indicating that further work is required to understand the controls on this source of uncertainty.


2014 ◽  
Vol 15 (5) ◽  
pp. 2085-2103 ◽  
Author(s):  
Guoyong Leng ◽  
Qiuhong Tang

Abstract Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China.


2013 ◽  
Vol 6 (5) ◽  
pp. 1689-1703 ◽  
Author(s):  
J. Heinke ◽  
S. Ostberg ◽  
S. Schaphoff ◽  
K. Frieler ◽  
C. Müller ◽  
...  

Abstract. In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere–Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilise a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.


2021 ◽  
Author(s):  
Onil Banerjee ◽  
Martin Cicowiez ◽  
Ana Rios ◽  
Cicero De Lima

In this paper, we assess the economy-wide impact of Climate Change (CC) on agriculture and food security in 20 Latin American and the Caribbean (LAC) countries. Specifically, we focus on the following three channels through which CC may affect agricultural and non-agricultural production: (i) agricultural yields; (ii) labor productivity in agriculture, and; (iii) economy-wide labor productivity. We implement the analysis using the Integrated Economic-Environmental Model (IEEM) and databases for 20 LAC available through the OPEN IEEM Platform. Our analysis identifies those countries most affected according to key indicators including Gross Domestic Product (GDP), international commerce, sectoral output, poverty, and emissions. Most countries experience negative impacts on GDP, with the exception of the major soybean producing countries, namely, Brazil, Argentina and Uruguay. We find that CC-induced crop productivity and labor productivity changes affect countries differently. The combined impact, however, indicates that Belize, Nicaragua, Guatemala and Paraguay would fare the worst. Early identification of these hardest hit countries can enable policy makers pre-empting these effects and beginning the design of adaptation strategies early on. In terms of greenhouse gas emissions, only Argentina, Chile and Uruguay would experience small increases in emissions.


2007 ◽  
Vol 3 (3) ◽  
pp. 499-512 ◽  
Author(s):  
S. Brewer ◽  
J. Guiot ◽  
F. Torre

Abstract. We present here a comparison between the outputs of 25 General Circulation Models run for the mid-Holocene period (6 ka BP) with a set of palaeoclimate reconstructions based on over 400 fossil pollen sequences distributed across the European continent. Three climate parameters were available (moisture availability, temperature of the coldest month and growing degree days), which were grouped together using cluster analysis to provide regions of homogenous climate change. Each model was then investigated to see if it reproduced 1) similar patterns of change and 2) the correct location of these regions. A fuzzy logic distance was used to compare the output of the model with the data, which allowed uncertainties from both the model and data to be taken into account. The models were compared by the magnitude and direction of climate change within the region as well as the spatial pattern of these changes. The majority of the models are grouped together, suggesting that they are becoming more consistent. A test against a set of zero anomalies (no climate change) shows that, although the models are unable to reproduce the exact patterns of change, they all produce the correct signs of change observed for the mid-Holocene.


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