Climate, Pests and Pathogens Eugene S. Takle Professor of Agricultural Meteorology, Department of Agronomy Professor of Atmospheric Science, Department of Geological and Atmospheric Sciences Director, Climate Science Initiative Iowa State University Midwest Weather Working Group, Minneapolis, MN, 25 July 2008

Natural and anthropogenic contributions to global temperature change (Meehl et al., 2004). Observed values from Jones and Moberg Grey bands indicate 68% and 95% range derived from multiple simulations.

Natural cycles

Natural and anthropogenic contributions to global temperature change (Meehl et al., 2004). Observed values from Jones and Moberg Grey bands indicate 68% and 95% range derived from multiple simulations. Not Natural

Source: Jerry Meehl, National Center for Atmospheric Research

IPCC Fourth Assessment Report Summary for Policy Makers Reduced Consumption Energy intensive Energy conserving Adaptation Necessary Mitigation Possible

Suitability Index for Rainfed Agriculture IPCC 2007

Suitability Index for Rainfed Agriculture IPCC 2007

Projected changes in precipitation between and for an energy- conserving scenario of greenhouse gas emissions IPCC 2007

Projected Changes* for the Climate of the Midwest Temperature *Estimated from IPCC reports

Projected Changes* for the Climate of the Midwest Precipitation *Estimated from IPCC reports

Projected Changes* for the Climate of the Midwest Other *Estimated from IPCC and CCSP reports

D. Herzmann, Iowa Environmental Mesonet

Improving Seasonal Climate Forecasts Seasonal climate forecasts (2 week – 9 month) show little if any skill Ensembles of climate models representing a range of physical parameterizations and initializations consistently outperform single models Soil moisture (SM) is the terrestrial equivalent of sea-surface temperature in providing “memory” to the climate system Forthcoming satellite retrievals by ESA and NASA provide optimism for better characterization of SM We at Iowa State are launching a partnership with NOAA and NASA to improve seasonal forecasts by use of improved initialization and ensemble forecasts Goal of this research is to improve decision-making tools for use in agriculture, primarily in the Midwest

Multi-RCM Ensemble Downscaling of NCEP CFS Seasonal Forecasts (MRED) Multi-institutional program funded by NOAA Led by Ray Arritt of ISU Uses NOAA and NASA global forecast models for initialization of eight regional climate models Uses 15 different initialization points to produce about 120 seasonal forecasts This is a retrospective study ( ) Focus on winter period (Dec – Apr) Not much help for growing seasons

Improving Agricultural Decisions And PredicTions (ADAPT) for the US Midwest by Use of Satellite Products and Regional Climate Models Parallel project to MRED being proposed to NASA Led by Gene Takle Uses NASA global model and NASA Land Information System for initializing regional climate models Will use the latest satellite-based observations of soil moisture to initialize and validate Focus on growing season (Mar – Oct) Ensemble of two regional climate models with multiple initialization states and many parameterizations

Forthcoming Collaborations Opportunities We need examples of decision tools having strong dependence on daily weather conditions that would benefit from seasonal forecasts Contact me if you are interested in collaborating on this