Integration of AgMIP results for the development of agricultural response functions for PNNL Models

Lead PI: Carolyn Mutter

Unit Affiliation: Center for Climate Systems Research (CCSR)

April 2016 - August 2018
Inactive
Global ; New York City, NY ; New York
Project Type: Research

DESCRIPTION: Agricultural response functions are designed to efficiently represent the complex behavior of agricultural systems undergoing changing climate conditions, most notably shifts in average temperature, precipitation, and carbon dioxide concentration. As these complex systems cannot be distilled into simple and precise functions, uncertainty across space, time, event types, management systems, models, and species will also be considered. The primary source of information used to develop agricultural response functions will be results from the Agricultural Model Intercomparison and Improvement Project (AgMIP; www.agmip.org).

OUTCOMES: The work resulted in a report summarizing AgMIP findings related to the response of agricultural systems to changes in carbon dioxide, temperature, and precipitation. This report will include suggestions as to how these may be incorporated into new agricultural response functions for GCAM, including possible drawbacks and limitations of this approach; pilot response surfaces for use in initial GCAM tests; presentations of findings and project developments at AgMIP and JGCRI events; and co-authorship of resulting peer-reviewed publications.

SPONSOR:

Pacific Northwest National Laboratory

ORIGINATING SPONSOR:

Department of Energy

FUNDED AMOUNT:

$114,220

PUBLICATIONS:

*Ruane, A.C., Rosenzweig, C., Asseng, S., Boote, K.J., Elliott, J., Ewert, F., Jones, J.W., Martre, P., McDermid, S.P., Müller, C. and Snyder, A., 2017. An AgMIP framework for improved agricultural representation in integrated assessment models. Environmental Research Letters, 12(12), p.125003.

DATASETS: Contact alexander.c.ruane@nasa.gov, 212-678-5640

KEYWORDS

global change assessment agriculture

THEMES

Modeling and Adapting to Future Climate