The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0)

被引:113
作者
Elliott, J. [1 ,2 ]
Mueller, C. [3 ]
Deryng, D. [4 ]
Chryssanthacopoulos, J. [5 ]
Boote, K. J. [6 ]
Buechner, M. [3 ]
Foster, I. [1 ,2 ]
Glotter, M. [7 ]
Heinke, J. [3 ,8 ,15 ]
Iizumi, T. [9 ]
Izaurralde, R. C. [10 ]
Mueller, N. D. [11 ]
Ray, D. K. [12 ]
Rosenzweig, C. [13 ]
Ruane, A. C. [13 ]
Sheffield, J. [14 ]
机构
[1] Univ Chicago, Chicago, IL 60637 USA
[2] Argonne Natl Lab, Computat Inst, Chicago, IL USA
[3] Potsdam Inst Climate Impact Res, Potsdam, Germany
[4] Univ E Anglia, Tyndall Ctr, Norwich NR4 7TJ, Norfolk, England
[5] Columbia Univ, Ctr Climate Syst Res, New York, NY USA
[6] Univ Florida, Dept Agron, Gainesville, FL 32611 USA
[7] Univ Chicago, Dept Geophys Sci, Chicago, IL 60637 USA
[8] Int Livestock Res Inst, Nairobi, Kenya
[9] Natl Inst Agroenvironm Sci, Tsukuba, Ibaraki 305, Japan
[10] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[11] Harvard Univ, Ctr Environm, Cambridge, MA 02138 USA
[12] Univ Minnesota, Inst Environm, St Paul, MN 55108 USA
[13] NASA, Goddard Inst Space Studies, New York, NY 10025 USA
[14] Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA
[15] CSIRO, St Lucia, Qld 4067, Australia
基金
美国国家科学基金会;
关键词
LAND-SURFACE MODEL; CLIMATE-CHANGE; HIGH-RESOLUTION; CARBON; YIELD; WATER; AGRICULTURE; SIMULATION; GROWTH; IMPLEMENTATION;
D O I
10.5194/gmd-8-261-2015
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project includes global simulations of yields, phenologies, and many land-surface fluxes using 12-15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification of key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record.
引用
收藏
页码:261 / 277
页数:17
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