Projecting Future Change in Growing Degree Days for Winter Wheat

被引:9
作者
Castillo, Natalie Ruiz [1 ]
Ospina, Carlos F. Gaitan [2 ,3 ,4 ]
机构
[1] Natl Weather Ctr Res Experiences Undergrad Progra, Norman, OK 73072 USA
[2] Univ Oklahoma, Coll Atmospher & Geog Sci, 120 David L Boren Blvd,Suite 3630, Norman, OK 73072 USA
[3] Univ Oklahoma, South Cent Climate Sci Ctr, 201 Stephenson Pkwy,Suite 2100, Norman, OK 73019 USA
[4] Arable Labs Inc, 252 Nassau St, Princeton, NJ 08542 USA
来源
AGRICULTURE-BASEL | 2016年 / 6卷 / 03期
基金
美国国家科学基金会;
关键词
winter wheat; Southwest Oklahoma; statistical post-processing; growing degree days; Red River Basin; climate projections;
D O I
10.3390/agriculture6030047
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Southwest Oklahoma is one of the most productive regions in the Great Plains (USA) where winter wheat is produced. To assess the effect of climate change on the growing degree days (GDD) available for winter wheat production, we selected from the CMIP5 archive, two of the best performing Global Climate Models (GCMs) for the region (MIROC5 and CCSM4) to project the future change in GDD under the Representative Concentration Pathways (RCP) 8.5 and 4.5 future trajectories for greenhouse gas concentrations. Two quantile mapping methods were applied to both GCMs to obtain local scale projections. The local scale outputs were applied to a GDD formula to show the GDD changes between the historical period (1961-2004) and the future period (2006-2098) in terms of mean differences. The results show that at the end of the 2098 growing season, the increase in GDD is expected to be between 440 degrees C and 1300 degrees C, for RCP 4.5, and between 700 degrees C and 1350 degrees C for RCP 8.5. This increase in GDD might cause a decrease in the number of days required to reach crop maturity, as all the GCM/statistical post-processing combinations showed a decreasing trend of those timings during the 21st century. Furthermore, we conclude, that when looking at the influence of the selected GCMs and the quantile mapping methods on the GDD calculation, the GCMs differences originated from the significant spatial and temporal variations of GDD over the region and not the statistical methods tested.
引用
收藏
页数:16
相关论文
共 39 条
[11]  
Gaitan C. F., 2016, STAT DOWNSCALED TIME
[12]  
Gaitan C. F., 2016, DOWNSCALED CLIMATE V
[13]  
Gaitan C. F., 2016, 1 10 DEGREE OBSERVAT
[14]   Effects of variance adjustment techniques and time-invariant transfer functions on heat wave duration indices and other metrics derived from downscaled time-series. Study case: Montreal, Canada [J].
Gaitan, Carlos F. .
NATURAL HAZARDS, 2016, 83 (03) :1661-1681
[15]   Comparison of statistically downscaled precipitation in terms of future climate indices and daily variability for southern Ontario and Quebec, Canada [J].
Gaitan, Carlos F. ;
Hsieh, William W. ;
Cannon, Alex J. .
CLIMATE DYNAMICS, 2014, 43 (12) :3201-3217
[16]   Validation of historical and future statistically downscaled pseudo-observed surface wind speeds in terms of annual climate indices and daily variability [J].
Gaitan, Carlos F. ;
Cannon, Alex J. .
RENEWABLE ENERGY, 2013, 51 :489-496
[17]   The Community Climate System Model Version 4 [J].
Gent, Peter R. ;
Danabasoglu, Gokhan ;
Donner, Leo J. ;
Holland, Marika M. ;
Hunke, Elizabeth C. ;
Jayne, Steve R. ;
Lawrence, David M. ;
Neale, Richard B. ;
Rasch, Philip J. ;
Vertenstein, Mariana ;
Worley, Patrick H. ;
Yang, Zong-Liang ;
Zhang, Minghua .
JOURNAL OF CLIMATE, 2011, 24 (19) :4973-4991
[18]   Adapting agriculture to climate change [J].
Howden, S. Mark ;
Soussana, Jean-Francois ;
Tubiello, Francesco N. ;
Chhetri, Netra ;
Dunlop, Michael ;
Meinke, Holger .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2007, 104 (50) :19691-19696
[19]  
Jeyakumar, 2013, RES REV J CROP SCI T, V2
[20]   Global Agriculture and Climate Change [J].
Kang, Manjit S. ;
Banga, Surinder S. .
JOURNAL OF CROP IMPROVEMENT, 2013, 27 (06) :667-692