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Strategies for Evaluating the Impact of Climate Change on Your Favorite Plant Disease. Eugene S. Takle Professor of Atmospheric Science Professor of Agricultural Meteorology Director, Climate Science Program Iowa State University Ames, IA 50011 gstakle@iastate.edu.
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Strategies for Evaluating the Impact of Climate Change on Your Favorite Plant Disease Eugene S. Takle Professor of Atmospheric Science Professor of Agricultural Meteorology Director, Climate Science Program Iowa State University Ames, IA 50011 gstakle@iastate.edu Midwest Weather Working Group 3rd Annual Meeting Charlotte, NC August 6, 2010
Strategy being proposed herein is built on our experience with assessing impact of climate change on: Streamflow in the Upper Mississippi River Basin Water quality (nitrates, sediment) in the Upper Mississippi River Basin Cracking and rutting potential of roadways Soil carbon Strategy for binary occurrence model development (Hit, Miss, False Alarm, Correct non-occurrence) is built on our experience with forecasting occurrence of frost on roadways (also analogous to forecasting occurrence of severe weather)
Iowa State-Wide Average Data 34.0” 8% increase 31.5”
Iowa State-Wide Average Data Totals above 40” 2 years
Iowa State-Wide Average Data Totals above 40” 8 years 2 years
“One of the clearest trends in the United States observational record is an increasing frequency and intensity of heavy precipitation events… Over the last century there was a 50% increase in the frequency of days with precipitation over 101.6 mm (four inches) in the upper midwestern U.S.; this trend is statistically significant “ Karl, T. R., J. M. Melillo, and T. C. Peterson, (eds.), 2009: Global Climate Change Impacts in the United States. Cambridge University Press, 2009, 196pp.
Cedar Rapids Data 6.6 days 4.2 days 57% increase
Cedar Rapids Data Years having more than 8 days 11 2 6.6 days 4.2 days 57% increase
December-January-February Temperature Change 7.2oF 6.3oF A1B Emission Scenario 2080-2099 minus1980-1999
June-July-August Temperature Change 4.5oF A1B Emission Scenario 2080-2099 minus1980-1999 5.4oF
Karl, T. R., J. M. Melillo, and T. C. Peterson, (eds.), 2009: Global Climate Change Impacts in the United States. Cambridge University Press, 2009, 196pp.
Low confidence Karl, T. R., J. M. Melillo, and T. C. Peterson, (eds.), 2009: Global Climate Change Impacts in the United States. Cambridge University Press, 2009, 196pp.
What environmental conditions promote your favorite plant disease? • + High humidity? Extended periods of high humidity? • + High temperature? Daytime? Nighttime? Both? Extended periods? • + Water-logged soils? Duration? Re-occurrence? • + Dew? Duration? Re-occurrence? • + Excessive cloudiness? • + Some combination of the above? Something else? • Are there conditions antecedent to these that allow or accelerate disease development? • + Insect damage? • + Drought? • + Wind damage
Catalog all known outbreaks of this particular disease anywhere in the world Date of onset Areal distribution of outbreak Speed of development, level of impact Existence of antecedent conditions impacting outbreak Climate conditions accompanying localized outbreaks Are there laboratory or greenhouse studies that have been or could be done to refine the conditions favoring (and suppressing) disease development? Use all available data on outbreaks and concurrent environmental conditions to develop a disease outbreak probability model (DM) . Use professional judgment to develop hypotheses.
Producing Climate Scenario Databases for Studying Impacts of Climate Change Use climate models based on fundamental physical science principles: Conservation of momentum (Newton’s laws of motion) Conservation of energy (First law of thermodynamics) Conservation of mass Equation of state (Ideal gas law: pV = nRT) Select a scenario of future trends of emissions of greenhouse gases Widespread adoption of energy conservation and renewable energy Continued upward trend of dependence on fossil fuels Use model to create a “virtual contemporary” (1980-2004) and a “virtual future” (2040-2070) climate at county level for US Create values of all measured meteorological variables and many others not measured (evapo-transpiration, long-wave upward radiation, etc.) Archive values every 3 hours for 30 years Climate Change Data
Search records of observed climate data (1980-2004) for the US using the DM to hindcast location and time of disease outbreaks + Compare with observed outbreaks; evaluate “false alarms”, etc. + This provides a model validation for the DM Search records of virtual contemporary modeled data (1980-2004) for the US using the DM to hindcast location and time of disease outbreaks + This validates the climate-model/DM combination (quantifies uncertainty) Search records of future scenario modeled data (2040-2070) for the US using the DM to predict the location and frequency of disease outbreaks in the future climate + This predicts the change in disease outbreak with climate change
For More Information • Contact me directly: gstakle@iastate.edu • Current research on regional climate and climate change is being conducted at Iowa State University under the Regional Climate Modeling Laboratory http://rcmlab.agron.iastate.edu/ • North American Regional Climate Change Assessment Program http://www.narccap.ucar.edu/ • For current activities on the ISU campus, regionally and nationally relating to climate change see the Climate Science Program website: http://climate.engineering.iastate.edu/ Or just Google Eugene Takle
Climate Model Resolution global regional (land) regional (water) Only every second RCM grid point is shown in each direction
NARCCAP Plan A2 Emissions Scenario HADAM3 link to EU programs GFDL CCSM CGCM3 Provide boundary conditions 2040-2070 future 1960-1990 current RegCM3 UC Santa Cruz ICTP CRCM Quebec, Ouranos HADRM3 Hadley Centre WRF NCAR/ PNNL MM5 Iowa State/ PNNL RSM Scripps Reanalyzed climate , 1979-2000
Impact of Climate Change on UMRB Streamflow Sub-Basins of the Upper Mississippi River Basin 119 sub-basins Outflow measured at Grafton, IL Approximately one observing station per sub-basin Approximately one model grid point per sub-basin