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Climate, Pests and Pathogens Eugene S. Takle Professor of Agricultural Meteorology, Department of Agronomy Professor of Atmospheric Science, Department.

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Presentation on theme: "Climate, Pests and Pathogens Eugene S. Takle Professor of Agricultural Meteorology, Department of Agronomy Professor of Atmospheric Science, Department."— Presentation transcript:

1 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 gstakle@iastate.edu Midwest Weather Working Group, Minneapolis, MN, 25 July 2008

2 http://www.ncdc.noaa.gov/img/climate/research/2007/ann/glob-jan-dec-error-bar-pg.gif

3 Natural and anthropogenic contributions to global temperature change (Meehl et al., 2004). Observed values from Jones and Moberg 2001. Grey bands indicate 68% and 95% range derived from multiple simulations.

4 Natural cycles

5 Natural and anthropogenic contributions to global temperature change (Meehl et al., 2004). Observed values from Jones and Moberg 2001. Grey bands indicate 68% and 95% range derived from multiple simulations. Not Natural

6 Source: Jerry Meehl, National Center for Atmospheric Research

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

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9 Suitability Index for Rainfed Agriculture IPCC 2007

10 Suitability Index for Rainfed Agriculture IPCC 2007

11 Projected changes in precipitation between 1980-1999 and 2080- 2099 for an energy- conserving scenario of greenhouse gas emissions IPCC 2007

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

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

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

15 D. Herzmann, Iowa Environmental Mesonet

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17 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

18 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 (1982-2004) Focus on winter period (Dec – Apr) Not much help for growing seasons

19 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

20 Forthcoming Collaborations Opportunities We need examples of decision tools having strong dependence on daily weather conditions that would benefit from seasonal forecasts Contact me (gstakle@iastate.edu) if you are interested in collaborating on this projectgstakle@iastate.edu


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