1. Climate Change and Agriculture
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
Agricultural Summit and Roundtable, Ames, IA 31 July 2008

2. 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

3. 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

4. Source: Jerry Meehl, National Center for Atmospheric Research
From Jerry Meehl
This slide shows the time evolution of globally averaged surface air
temperature from multiple ensemble simulations of 20th century climate
from the NCAR Parallel Climate Model (PCM) compared to observations.
The simulations start in the late 19th century, and continue to the year
The temperature scale at left is in degrees Centigrade, and
temperature anomalies are calculated relative to a reference period
averaged from 1890 to The black line shows the observed data, or
the actual, recorded
globally averaged surface air temperatures from the past century. The
blue and red lines are the average of four simulations each from the
computer model. The pink and light blue shaded areas depict the range
of the four simulations for each experiment, giving an idea of the
uncertainty of a given realization of 20th century climate from the
climate model. The blue line shows the average from the four member
ensemble of the simulated time evolution of globally average surface air
temperature when only "natural" influences (solar variability and
volcanic eruptions) are included in the model. Therefore, the blue
line represents what the model says global average temperatures would
have been if there had been no human influences. The red line shows the
average of the four member ensemble experiment when natural forcings AND
anthropogenic influences (greenhouse gases including carbon dioxide,
sulfate aerosols from air pollution, and ozone changes) are included in
the model. Note that this model can reproduce the actual, observed data
very well only if the combined effects of natural and anthropogenic
factors are included. The conclusion that can be drawn is that
naturally occuring influences on climate contributed to most of the
warming that occurred before WWII, but that the large observed
temperature increases since the 1970s can only be simulated in the model
if anthropogenic factors are included.
This confirms the conclusion of the IPCC Third Assessment Report that
most of the warming we have observed in the latter part of the 20th
century has been due to human influences.
Source: Jerry Meehl, National Center for Atmospheric Research

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

7. Suitability Index for Rainfed Agriculture
IPCC 2007

8. Suitability Index for Rainfed Agriculture
IPCC 2007

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

10. Insured Crop Loss for Corn in Iowa*
Factor Percent
Cold Winter
Decline in Price
Drought
Excess Moist/Precip/Rain
Flood
Freeze
Hail
Heat
Hot Wind
Mycotoxin (Aflatoxin)
Plant Disease
Winds/Excess Wind
Other
Total
*Milliman, Inc., based on data from the Risk Management Agency Website (

11. Insured Crop Loss for Corn in Iowa*
Factor Percent
Cold Winter
Decline in Price
Drought
Excess Moist/Precip/Rain
Flood
Freeze
Hail
Heat
Hot Wind
Mycotoxin (Aflatoxin)
Plant Disease
Winds/Excess Wind
Other
Total
*Milliman, Inc., based on data from the Risk Management Agency Website (

12. Insured Crop Loss for Soybeans in Iowa*
Factor Percent
Cold Winter
Decline in Price
Drought
Excess Moist/Precip/Rain
Flood
Freeze
Hail
Heat
Hot Wind
Mycotoxin (Aflatoxin)
Plant Disease
Winds/Excess Wind
Other
Total
*Milliman, Inc., based on data from the Risk Management Agency Website (

13. Insured Crop Loss for Soybeans in Iowa*
Factor Percent
Cold Winter
Decline in Price
Drought
Excess Moist/Precip/Rain
Flood
Freeze
Hail
Heat
Hot Wind
Mycotoxin (Aflatoxin)
Plant Disease
Winds/Excess Wind
Other
Total
*Milliman, Inc., based on data from the Risk Management Agency Website (

14. Projected Changes* for the Climate of the Midwest Temperature
Longer frost-free period (high)
Higher average winter temperatures (high)
Fewer extreme cold temperatures in winter (high)
Fewer extreme high temperatures in summer in short term but more in long term (medium)
Higher nighttime temperatures both summer and winter (high)
More freeze-thaw cycles (high)
Increased temperature variability (high)
Follows trend of last 25 years and projected by models No current trend but model suggestion or current trend but models inconclusive
*Estimated from IPCC reports

15. Projected Changes* for the Climate of the Midwest Precipitation
More (~10%) precipitation annually (medium)
Change in “seasonality”: Most of the increase will come in the first half of the year (wetter springs, drier summers) (high)
More water-logging of soils (medium)
More variability of summer precipitation (high)
More intense rain events and hence more runoff (high)
Higher episodic streamflow (medium)
Longer periods without rain (medium)
Higher absolute humidity (high)
Stronger storm systems (medium)
Snowfall increases (late winter) in short term but decreases in long run (medium)
More winter soil moisture recharge
Follows trend of last 25 years and projected by models No current trend but model suggestion or current trend but models inconclusive
*Estimated from IPCC reports

16. Projected Changes* for the Climate of the Midwest Other
Reduced wind speeds (high)
Reduced solar radiation (medium)
Increased tropospheric ozone (high)
Accelerated loss of soil carbon (high)
Phenological states are shortened (high)
Weeds grow more rapidly under elevated atmospheric CO2 (high)
Weeds migrate northward and are less sensitive to herbicides (high)
Plants have increased water used efficiency (high)
Follows trend of last 25 years and projected by models No current trend but model suggestion or current trend but models inconclusive
*Estimated from IPCC and CCSP reports