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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 3 rd Annual Meeting Charlotte, NC August 6, 2010
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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)
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Iowa State-Wide Average Data
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D. Herzmann, Iowa Environmental Mesonet
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31.5” 34.0” 8% increase Iowa State-Wide Average Data
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Totals above 40” 2 years Iowa State-Wide Average Data
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Totals above 40”8 years 2 years Iowa State-Wide Average Data
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Cedar Rapids Data
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“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.
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4.2 days57% increase 6.6 days Cedar Rapids Data
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4.2 days57% increase 6.6 days 2 11Years having more than 8 days Cedar Rapids Data
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IPCC 2007
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December-January- February Temperature Change A1B Emission Scenario 2080-2099 minus1980- 1999 7.2 o F 6.3 o F
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IPCC 2007
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June-July-August Temperature Change A1B Emission Scenario 2080-2099 minus1980- 1999 4.5 o F 5.4 o F
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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.
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Low confidence
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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
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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.
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Climate Change Data 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
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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
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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
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Climate Model Resolution global regional (land) regional (water) Only every second RCM grid point is shown in each direction
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NARCCAP Plan A2 Emissions Scenario GFDLCCSM HADAM3 link to EU programs CGCM3 1960-1990 current 2040-2070 future Provide boundary conditions MM5 Iowa State/ PNNL RegCM3 UC Santa Cruz ICTP CRCM Quebec, Ouranos HADRM3 Hadley Centre RSM Scripps WRF NCAR/ PNNL Reanalyzed climate, 1979-2000
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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 Impact of Climate Change on UMRB Streamflow
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SWAT Output with Various Sources of Climate Input
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