Eugene S. Takle1 and Zaitao Pan2

1
Climate Change Impacts on Agriculture

• Eugene S. Takle1 and Zaitao Pan2

1Iowa State University, Ames, IA USA 2St. Louis
University, St. Louis, MO USA
Third ICTP Workshop on Theory and Use of Regional
Climate Models, Trieste, Italy, 29 May - 9 June
2006
2
Outline

• Overview of climate change impacts on agriculture
• Modeling crop yield changes with climate model
  output - an example
• Crop characteristics within land-surface models

3
Climate Change Impacts on Agriculture Crops

• Crop yields (winners and losers)

4
Climate Change Impacts on Agriculture Crops

• Crop yields (winners and losers)
• Pest changes
• Weed germination changes (soil temperature, soil
  oxygen)
• Pathogens (fungus, insects, diseases)
• Changes in migratory pest patterns

5
Climate Change Impacts on Agriculture Crops

• Crop yields (winners and losers)
• Pest changes
• Weed germination changes (soil temperature, soil
  oxygen)
• Pathogens (fungus, insects, diseases)
• Changes in migratory pest patterns
• Water issues
• Water availability for non-irrigated agriculture
• Irrigation water availability
• Water quality (nitrates, phosphates, sediment)
• Soil water management

6
Climate Change Impacts on Agriculture Crops

• Crop yields (winners and losers)
• Pest changes
• Weed germination changes (soil temperature, soil
  oxygen)
• Pathogens (fungus, insects, diseases)
• Changes in migratory pest patterns
• Water issues
• Water availability for non-irrigated agriculture
• Irrigation water availability
• Water quality (nitrates, phosphates, sediment)
• Soil water management
• Spread of pollen from genetically modified crops

7
Climate Change Impacts on Agriculture Crops

• Crop yields (winners and losers)
• Pest changes
• Weed germination changes (soil temperature, soil
  oxygen)
• Pathogens (fungus, insects, diseases)
• Changes in migratory pest patterns
• Water issues
• Water availability for non-irrigated agriculture
• Irrigation water availability
• Water quality (nitrates, phosphates, sediment)
• Soil water management
• Spread of pollen from genetically modified crops
• Food crops vs. alterantive crops
• Biofuels (ethanol, cellulosic impact on water
  demand)
• Bio-based materials
• Farm-a-ceuticals

8
Climate Change Impacts on Agriculture Soil

• Erosion changes (more extreme rainfall)
• Salinization
• Soil carbon changes
• Nutrient deposition
• Long-range transport of soil pathogens

9
Climate Change Impacts on Agriculture Animals

• Dairy production (milk)
• Beef production (metabolism)
• Breeding success
• Stresses for confinement feeding operations
• Changes in disease ranges
• Changes in insect ranges
• Fish farming (reduced dissolved oxygen)

10
Modeling Crop Yield Changes with Climate Model
Output An Example
11
Climate Models and Crop Model

• RegCM2 and HIRHAM regional climate models
• HadCM2 global model for control and future
  scenario climate
• CERES Maize (corn) crop model (DSSATv3)
• Includes crop physiology
• Daily time step
• Uses Tmax, Tmin, precipitation, solar radiation
  from the regional model

12
CERES Maize

• Phenological development sensitive to weather
• Extension growth of leaves, stems, roots
• Biomass accumulation and partitioning
• Soil water balance and water use by crop
• Soil nitrogen transformation, uptake by crop,
  partitioning

13
Simulation Domain and Period

• Domain
• Continental US
• Time Period
• 1979-88 Reanalysis driven
• Control (current) climate (HadCM2)
• Future (2040-2050) (HadCM2)

14
(No Transcript)
15
Validation RegCM2

• Less that 0.5oC bias for daily maximum
  temperatures
• Less than 0.5oC bias for daily minimum
  temperature
• Precipitation

16
(No Transcript)
17
(No Transcript)
18
Validation HIRHAM

• About 1.5oC bias for daily maximum temperatures
• About 5oC bias for daily minimum temperature
• Precipitation

19
(No Transcript)
20
Growing Season Precipitation Summary (all values
in mm)
Mean St. Dev. Diff Obs St. Dev
Observed 446 114
NCEP-Driven RegCM2 341 87
-76 122 HIRHAM 275 73
-137 151 Control-Driven RegCM2 441
102 HIRHAM 313 77 Scenario-Driven RegCM2 483
105 HIRHAM 378 80
21
Validation Yields

• Reported
• Calculated by crop model by using
• Observed weather conditions at Ames station
• RegCM2 with NCEP/NCAR reanalysis bc
• HIRHAM with NCEP/NCAR reanalysis bc

22
Simulated with Ames weather observations
23
(No Transcript)
24
Yields Calculated by CERES/RCM/HadCM2

• HadCM2 current climate -gt RegCM2 -gt CERES
• HadCM2 current climate -gt HIRHAM -gt CERES
• HadCM2 future scenario climate -gt RegCM2 -gt CERES
• HadCM2 future scenario climate -gt HIRHAM -gt CERES

25
Yield Summary (all in kg/ha)
Mean St. Dev. Observed Yields 8381
1214 Simulated by CERES with Observed weather
8259 4494 RegCM2/NCEP 5487
3796 HIRHAM/NCEP 3446 2716 RegCM2/HadCM2
current 5002 1777 HIRHAM/HadCM2 current
6264 3110 RegCM2/HadCM2 future 10,610
2721 HIRHAM/HadCM2 future 6348 1640
26
Summary

• Crop model offers more detailed plant physiology
  and dynamic vegetation for regional models
• Current versions of crop models show skill with
  mean yield but variability is a challenge
• Crop model exposes and amplifies
  vegetation-sensitive features of regional climate
  model

27
Need Ensembles

• Ensembles of global models

28
Need Ensembles

• Ensembles of global models
• Ensembles of regional models

29
Need Ensembles

• Ensembles of global models
• Ensembles of regional models
• Ensembles of crops

30
Need Ensembles

• Ensembles of global models
• Ensembles of regional models
• Ensembles of crops
• Ensembles of regions

31
Need Ensembles

• Ensembles of global models
• Ensembles of regional models
• Ensembles of crops
• Ensembles of regions
• Ensembles of minds!!

32
Crop Characteristics within Land-Surface Models
Work in Progress
33
0 1 2 3 4 5 6 7 8 9 10
11 12 13 14 15 16 17 18 19 20 21 22 23 24
2 Dry-land crop
34
Gross Ecosystem Production is Related to
Evapotranspiration
GEP AET B
Plant class A (gCO2/kg H2O) B (gCO2)
r2 Evergreen conifers 3.43 2.43 0.58 Deciduous
broadleaf 3.42 -0.35 0.78 Grasslands 3.39 -6
7.9 0.72 Crop (wheat,corn, soyb) 3.06 -31.6 0.5
0 Corn/soybean 5.40 -120 (est) 0.89 Tundra 1.4
6 -0.57 0.44
Law et al., 2002 Agric. For. Meteorol. 113,
97-120
35
Gross Ecosystem Production is Related to
Evapotranspiration
GEP AET B
Plant class A (gCO2/kg H2O) B (gCO2)
r2 Evergreen conifers 3.43 2.43 0.58 Deciduous
broadleaf 3.42 -0.35 0.78 Grasslands 3.39 -6
7.9 0.72 Crop (wheat,corn, soyb) 3.06 -31.6 0.5
0 Corn/soybean 5.40 -120 (est) 0.89 Tundra 1.4
6 -0.57 0.44
Law et al., Agric. For. Meteorol. 113, 97-120
36
Evergreen Conifer
Broadleaf Deciduous
Corn/Soybean
37
Evergreen Conifer
Broadleaf Deciduous
Need to fix this
Corn/Soybean
38
Photosynthesis in LSM, CLM, NOAH
Leaf photosynthesis (A) is computed as minimum of
three independent limiting carbon flux rates in
the plants Amin(wc, wj, we) wc -
carboxylation/oxygenation (Rubisco) limiting
rate wj - PAR (light) limiting rate we -
export limiting rate
39
PAR
Export
Rubisco
PAR
Export
Rubisco
40
wc is proportional to maximum carboxylation
capacity (Vmax), where
Vmax25 is Vmax at 25C f(N) - sensitivity
parameter to vegetation nitrogen content, N, is
assumed to be 1 f(Tv) - sensitivity to leaf
temperature Tv - vegetation temperature
(C) f(?) - sensitivity to soil water content
- is soil volumetric water content

- quantum efficiency
41
Calibration of Carbon Uptake Model (Meteorological
conditions supplied by observations)
Bondville, IL
Observed Flux
Modeled Flux
Modeled Flux

• More representative root distribution

• CERES seasonal LAI
• 50 plants C4

42
Calibration of Carbon Uptake Model (Meteorological
conditions supplied by MM5)
Bondville, IL
Observed Flux
Modeled Flux
Modeled Flux
43
Average Simulated CO2 Flux 1 May 31 August
1999 Default vegetation
µmol CO2/s/m2
44
Average Simulated CO2 Flux 1 May 31 August
1999 Full accounting for C4 plants (Maize)
µmol CO2/s/m2
45
Average Simulated CO2 Flux 1 May 31 August
2001 Full accounting for C4 plants (Maize)
µmol CO2/s/m2
Fan et al., 1998 A large terrestrial carbon sink
in North America...  Science 282 442-446.
46
Future Work

• Evaluate role of specialized crops in moisture
  recycling (fivefold increase in GEP requires
  doubling of ET).
• Use MM5 with modified crop characteristics to
  investigate interactive climate sensitivity to
  crop development