NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model EnsemblesTo improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.
Document ID
20160011156
Document Type
Reprint (Version printed in journal)
Authors
Maiorano, Andrea (French National Institute for Agricultural Research (INRA) Paris, France)
Martre, Pierre (French National Institute for Agricultural Research (INRA) Paris, France)
Asseng, Senthold (Florida Univ. Gainesville, FL, United States)
Ewert, Frank (Bonn Univ. Germany)
Mueller, Christoph (Potsdam-Inst. fuer Klimafolgenforschung Potsdam, Germany)
Roetter, Reimund P. (Natural Resources Institute Finland Helsinki, Finland)
Ruane, Alex C. (NASA Goddard Inst. for Space Studies New York, NY, United States)
Semenov, Mikhail A. (Rothamsted Experimental Station Harpenden, United Kingdom)
Wallach, Daniel (French National Institute for Agricultural Research (INRA) Paris, France)
Wang, Enli (Commonwealth Scientific and Industrial Research Organization Canberra, Australia)
Date Acquired
September 9, 2016
Publication Date
May 24, 2016
Subject Category
Life Sciences (General)
Meteorology and Climatology
Report/Patent Number
GSFC-E-DAA-TN32839
Distribution Limits
Public
Copyright
Other
Keywords
damage assessment
wheat
simulation
climate change
impact
calibrating