Published on December 22, 2016
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
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