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Using a Multi-Model Regional Simulation of
Climate Change Impacts on Agriculture in
the Southwestern United States and Its
Application to a Research Framework in
the Korean Peninsula
Project Director: Menas Kafatos, Chapman University
(NIFA Award: 2011- 67004-30224)
Agroclimatology PD
Overview
Objective
• To assess the potential impacts of climate variability and change on ecosystems and agriculture
in semi-arid regions, specifically the Southwestern US (SW US).
Approach
• Utilize accurate regional
modeling, and capture
climate impacts at
regional ecosystem
scales
• Inter-compare multi-crop
model simulations driven
by regional climate
models and create an
ensemble to reduce
uncertainties in
forecasting crop yields.
Impact
• A better understanding of the relationship between climate variability and ecosystems and
agriculture in the SW US.
• Simulate future yield projections for use by growers and decision makers
A schematic illustration of the data flow from
climate projection to crop productivity
assessment in a typical nested modeling using
a agricultural model.
Agroclimatology PD
Future Projection of Agroecosystem
Maze Yp changes between historical (1981-2000) and
future projection (2031-2050).
[Kim et al., 2016]
[Medvigy et al., 2016]
Impact of warming
Impact of Downscaling
deciduous tree leaf
emergence in California
under current and future
climate
Agroclimatology PD
Future projection based on RCP85
shows decrease of maize yields over
the warmer climate region in the SW
US. Changing sowing date in future
alleviates significant Yp decrease under
climate change.
Impacts of Climate Variability
Impact of NAO (North Atlantic Oscillation) on
the early warm season temperature in SWUS
Temperature, Sowing dates, and Yield Potential of Maize in
the Southwestern US
RED (WARM): Early planting/harvesting favors higher yields due to
the extremely hot summer.
BLUE (COOL): Early planting and late harvesting (lengthening GS)
favor higher yields.
YELLOW (INT): Late planting/harvesting favors higher yields, which
can take advantage of “mild” (25~35°C) summer climate.
[Myoung et al., 2015] [Myoung et al., 2016]
The NAO-Ts linkage in SWUS has been strengthened in the last 30-year period (1980-2009)
compared to the earlier 30-year period (1950-1979).
NAO-Ts relationships are primarily due to positioning of upper-tropospheric anticyclone in
the western US that is associated with development of positive NAO phases in the Atlantic.
Agroclimatology PD
Results: 21-year Ave. of the OPT run
WARM: Warm low-elevation regions
COOL: Cool high-elevation regions
INT: Intermediate regions
(kg/ha)(month)
(day) OPT-FIXED YLD diff (%)
COOL
INT
GS: Growing season (from SD to
HD)
Region SD
(Sowing
date)
HD
(Harvest
date)
LGS
(Lengt
h of
GS)
YLD
(Yield
Poten.
)
WARM Very early
(Mar)
Early
(Jun & Jul)
Short Low
COOL Early (Apr) Late
(Sep & Oct)
Long High
INT Late
(May &
Jun)
Late (Sep) Short High
Suitable management decisions can
substantially enhance yield potential over many
places.
Summary of the variables
Agroclimatology PD
Assessment of Future Maize Yield
Potential Changes in the Korean
Peninsula Using Multiple Crop Models
2Seung Hee Kim, 3Chul-Hee Lim, 4Jinwon Kim, 3Woo-Kyun Lee,
1Menas C. Kafatos
1Fletcher Jones Endowed Professor of Computational Physics,
Chapman University
Outstanding Visiting Professor, Korea University, Seoul, Korea
Affiliated Researcher, National Observatory of Athens, Greece
2Chapman University, 3Korea University, 4UCLA
Agroclimatology PD
The Korean Peninsula has unique agricultural environment due to the differences of political and
socio-economical system. NK has been suffering lack of food supplies caused by natural disasters,
land degradation and political failure. The neighboring developed country SK has better agricultural
system but very low food self-sufficiency rate (around 1% of maize). Maize is an important crop in
both countries since it is staple food for NK and SK is No. 2 maize importing country in the world
after Japan. Therefore evaluating maize yield potential (Yp) in the two distinct regions is essential to
assess food security under climate change and variability.
Motivation
Agroclimatology PD
Orange Boxes show improved/modified components
Map RCM data
onto geographic
areas of interests
Quality Control of
met forcing data
Evaluation/bias
correction
Bias-corrected RCM data (PR, T, etc.)
Agricultural model
(APSIM)
Crop
productivity
assessmentManagement
decisions,
Korean Policy
makers
GCMs +
emissions
scenarios
Global climate
scenarios
RCMs
over East Asia
Downscaled
climate scenarios
Obs. PR, T, etc..
Observations
GIS information
over Korea
Agroecosystem
model
(EPIC and GEPIC)
Agricultural
water demand
assessment
Agroclimatology PD
Crop Model Validation
[Mgha-1][Mgha-1]
Blue shaded
region is simulated
Yp at each region
and black solid line
shows median of
the Yp. Box plot
shows observed
yields.
Agroclimatology PD
Time series of Maize Yp with adaptation strategies[%][%]
[%]
Fixed Planting Date Optimal Planting Date
3/21
3/31
4/10
4/20
4/30
5/10
5/20
5/30
6/9
2031 2033 2035 2037 2039 2041 2043 2045 2047 2049
Adaptation (shifting planting date)
Optimal planting date
shifted 20 days earlier
Agroclimatology PD RCP8.5 shows 10 to 20% decrease of
maize yields potential
Adaptation (shifting planting date)
3/21
3/31
4/10
4/20
4/30
5/10
5/20
5/30
6/9
2031 2033 2035 2037 2039 2041 2043 2045 2047 2049
The optimal planting date is shifted about 20 days earlierAgroclimatology PD
Summary
 The yield sensitivity varies geographically according to
regional mean climate states.
 Both crop models are reasonably well represent the actual
yield in the Korean Peninsula.
 Future projection based on RCP8.5 scenario shows
significant decrease of maize yields potential.
 However, with proper adaptation strategies, the maize
yields potential stays in similar level of historical period.
 Optimal planting date is shifted about 20 days earlier in
the mid-century because it helps to avoid damages from
frost in spring and extreme heat in summer.
Agroclimatology PD

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Using a Multi-Model Regional Simulation of Climate Change Impacts on Agriculture in the Southwestern United States and Its Application to a Research Framework in the Korean Peninsula

  • 1. Using a Multi-Model Regional Simulation of Climate Change Impacts on Agriculture in the Southwestern United States and Its Application to a Research Framework in the Korean Peninsula Project Director: Menas Kafatos, Chapman University (NIFA Award: 2011- 67004-30224) Agroclimatology PD
  • 2. Overview Objective • To assess the potential impacts of climate variability and change on ecosystems and agriculture in semi-arid regions, specifically the Southwestern US (SW US). Approach • Utilize accurate regional modeling, and capture climate impacts at regional ecosystem scales • Inter-compare multi-crop model simulations driven by regional climate models and create an ensemble to reduce uncertainties in forecasting crop yields. Impact • A better understanding of the relationship between climate variability and ecosystems and agriculture in the SW US. • Simulate future yield projections for use by growers and decision makers A schematic illustration of the data flow from climate projection to crop productivity assessment in a typical nested modeling using a agricultural model. Agroclimatology PD
  • 3. Future Projection of Agroecosystem Maze Yp changes between historical (1981-2000) and future projection (2031-2050). [Kim et al., 2016] [Medvigy et al., 2016] Impact of warming Impact of Downscaling deciduous tree leaf emergence in California under current and future climate Agroclimatology PD Future projection based on RCP85 shows decrease of maize yields over the warmer climate region in the SW US. Changing sowing date in future alleviates significant Yp decrease under climate change.
  • 4. Impacts of Climate Variability Impact of NAO (North Atlantic Oscillation) on the early warm season temperature in SWUS Temperature, Sowing dates, and Yield Potential of Maize in the Southwestern US RED (WARM): Early planting/harvesting favors higher yields due to the extremely hot summer. BLUE (COOL): Early planting and late harvesting (lengthening GS) favor higher yields. YELLOW (INT): Late planting/harvesting favors higher yields, which can take advantage of “mild” (25~35°C) summer climate. [Myoung et al., 2015] [Myoung et al., 2016] The NAO-Ts linkage in SWUS has been strengthened in the last 30-year period (1980-2009) compared to the earlier 30-year period (1950-1979). NAO-Ts relationships are primarily due to positioning of upper-tropospheric anticyclone in the western US that is associated with development of positive NAO phases in the Atlantic. Agroclimatology PD
  • 5. Results: 21-year Ave. of the OPT run WARM: Warm low-elevation regions COOL: Cool high-elevation regions INT: Intermediate regions (kg/ha)(month) (day) OPT-FIXED YLD diff (%) COOL INT GS: Growing season (from SD to HD) Region SD (Sowing date) HD (Harvest date) LGS (Lengt h of GS) YLD (Yield Poten. ) WARM Very early (Mar) Early (Jun & Jul) Short Low COOL Early (Apr) Late (Sep & Oct) Long High INT Late (May & Jun) Late (Sep) Short High Suitable management decisions can substantially enhance yield potential over many places. Summary of the variables Agroclimatology PD
  • 6. Assessment of Future Maize Yield Potential Changes in the Korean Peninsula Using Multiple Crop Models 2Seung Hee Kim, 3Chul-Hee Lim, 4Jinwon Kim, 3Woo-Kyun Lee, 1Menas C. Kafatos 1Fletcher Jones Endowed Professor of Computational Physics, Chapman University Outstanding Visiting Professor, Korea University, Seoul, Korea Affiliated Researcher, National Observatory of Athens, Greece 2Chapman University, 3Korea University, 4UCLA Agroclimatology PD
  • 7. The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system. NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate (around 1% of maize). Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. Motivation Agroclimatology PD
  • 8. Orange Boxes show improved/modified components Map RCM data onto geographic areas of interests Quality Control of met forcing data Evaluation/bias correction Bias-corrected RCM data (PR, T, etc.) Agricultural model (APSIM) Crop productivity assessmentManagement decisions, Korean Policy makers GCMs + emissions scenarios Global climate scenarios RCMs over East Asia Downscaled climate scenarios Obs. PR, T, etc.. Observations GIS information over Korea Agroecosystem model (EPIC and GEPIC) Agricultural water demand assessment Agroclimatology PD
  • 9. Crop Model Validation [Mgha-1][Mgha-1] Blue shaded region is simulated Yp at each region and black solid line shows median of the Yp. Box plot shows observed yields. Agroclimatology PD
  • 10. Time series of Maize Yp with adaptation strategies[%][%] [%] Fixed Planting Date Optimal Planting Date 3/21 3/31 4/10 4/20 4/30 5/10 5/20 5/30 6/9 2031 2033 2035 2037 2039 2041 2043 2045 2047 2049 Adaptation (shifting planting date) Optimal planting date shifted 20 days earlier Agroclimatology PD RCP8.5 shows 10 to 20% decrease of maize yields potential
  • 11. Adaptation (shifting planting date) 3/21 3/31 4/10 4/20 4/30 5/10 5/20 5/30 6/9 2031 2033 2035 2037 2039 2041 2043 2045 2047 2049 The optimal planting date is shifted about 20 days earlierAgroclimatology PD
  • 12. Summary  The yield sensitivity varies geographically according to regional mean climate states.  Both crop models are reasonably well represent the actual yield in the Korean Peninsula.  Future projection based on RCP8.5 scenario shows significant decrease of maize yields potential.  However, with proper adaptation strategies, the maize yields potential stays in similar level of historical period.  Optimal planting date is shifted about 20 days earlier in the mid-century because it helps to avoid damages from frost in spring and extreme heat in summer. Agroclimatology PD

Editor's Notes

  1. Left The average advancement in leaf emergence was 5.4 days, although the impact varies considerably across the state. Dynamical downscaling greatly affects by average and the spatial variability of predicted leaf emergence in California. Right Future projection based on RCP85 scenario shows decrease of maize yields especially over the warmer climate region in the SW US. Changing sowing date in future alleviates significant Yp decrease under climate change.
  2. Left The NAO-Ts linkage in SWUS has been strengthened in the last 30-year period (1980-2009) compared to the earlier 30-year period (1950-1979). NAO-Ts relationships are primarily due to positioning of upper-tropospheric anticyclone in the western US that is associated with development of positive NAO phases in the Atlantic. Right Sowing date plays an important role in determining crop yields. Optimal sowing dates are varying depending on local climates in SWUS.
  3. Harvest dates were not shown here. INT region is idea for maize because of high yield efficiency and less sensitivity to planting date.
  4. landscape was lifeless and barren. The reddish hue of exposed soil in North Korea indicates a lack of organic matter, which is vital for farming. Due to limited access on local data, international collaboration is required for this study.
  5. Orange Boxes shows the improved or modified components from the previous research framework.
  6. Blue shaded region is simulated Yp at each region and black solid line shows median of the Yp. Box plot shows observed yields. Note that there are no North Korea’s regional yields reports for 2014 thus marked averaged value of entire country
  7. Left and Right top : Future projection based on RCP8.5 scenario shows 10 to 20% decrease of maize yields potential. However, with proper adaptation strategies (e.g. changing planting date), the maize yields potential stays in similar level of historical period except high-elevation region in the North Korea. Right bottom: The optimal planting date is shifted about 20 days earlier