1. Overview of climate variability and likely
climate change impacts on agriculture
across the Greater Mekong Sub-region
(GMS)
Eitzinger Anton, Giang Linh, Lefroy Rod, Carmona Stephania, Laderach Peter

2. Project milestones
• Assemble database and quantify impact on crop
suitability December 2013
• Engage with partners and share methods and
first results March 2014
• Incorporate feedback, rerun analysis and finalize
results May 2014

3. Data collection

4. Climate grids are constructed for nine climate variables for the period 1901-2009
- Temperature,
- Diurnal temperature range,
- Daily minimum temperature,
- Maximum temperatures,
- Precipitation,
- Wet-day frequency,
- Frost-day frequency,
- Vapor pressure, and
- Cloud cover.
CRU TS climate database 3.10.01

5. CRU TS climate database 3.10.01
Tmean + 1.8 ˚C to 2 ˚C
Tmax +1.7˚C to 2.2˚C
Tmin + 1.6˚C to 2.2˚C
No clear rainfall change pattern …Temperature increased between 1901 to 2009
?

6. http://www.worldclim.org
Worldclim stations worldwide
47,554 precipitation
24,542 tmean
14,835 tmax y tmin
Sources:
•GHCN
•FAOCLIM
•WMO
•CIAT
•R-Hydronet
•Redes nacionales
Sources:
•GHCN
•FAOCLIM
•WMO
•CIAT
•R-Hydronet
•Redes nacionales
Climate baseline

7. Temperature
Annual mean temperature, Mean diurnal range,
seasonality, Max of warmest month, Min of coldest
month, Annual Range, Mean of Wettest/Driest
Quarter, Mean of Warmest/Coldest Quarter
Rainfall
Annual, Rainfall of Wettest/Driest Month, Seasonality,
Rainfall of Wettest/Driest/Warmest/Coldest Quarter
* current annual mean temperature, current annual rainfall

8. Not available = natural (forest, wetland, …), protected, water, bare, urban areas
LU Change risk = land mixed with pastoralism (forest, herbaceous, wetlands, …)
Available = Agriculture (commercial, subsidized, irrigated, …)
Land use change at risk
for agriculture

9. Land use change
• Vegetation Index (MOD13Q1 MODIS Product , 16 days, 250m)
Normalized difference vegetation index (NDVI) … the values are closely related to​​
vegetation type and climatic conditions as well as the predominant land use pattern.
Data noise filtering

10. Crop-Climate-Suitability modeling using Ecocrop

11. Crop climate- suitability change by 2050
s of D:_modeling_OUTPUTsearun-1.gdbbanana2chg in zones of D:Anton_DAPA_Projects_ongoingSEA-CCAFSgeodatagms_mask.shp
KHM
2,000
1,800
1,600
1,400
1,200
1,000
800
600
400
200
0
LAO MMR THA VNM CHN
Histograms of D:_modeling_OUTPUTsearun-1.gdbpotato2chg in zones of D:Anton_DAPA_Projects_ongoingSEA-CCA
KHM
1,000
900
800
700
600
500
400
300
200
100
0
LAO MMR THA VNM CHN
Histogram: Banana Potato
Cambodia Laos Myanmar Thailand Vietnam China Cambodia Laos Myanmar Thailand Vietnam China

12. 2 step analysis
Compare predicted future suitability change
from climate models and Ecocrop maps and
existing land use data
A time-series analysis of Land Use change
using satellite images to identify change
patterns in land use
1
2

13. 1

14. 1 risk for land use change

15. 2006 20122000
2

16. Expansion of of Maize, Sayabouri
What can be detected?
2

17. Engage with partners and share
methods and first results

18. Validation of Ecocrop results
• Groupwork and Discussion on suitability maps
Actual production area
This area is not suitable
Temperature suit. Rainfall suit.Climate-suitability
Crop x

19. • Share & discuss methods of climate change impact assessment
with partners
• Training on EcoCrop modeling using DIVA-GIS

20. Presentations & Discussion
1. What is the evidence and observed changes in the
climate system and how reliable are climate models and
scenarios?
2. How to use climate models & future predictions for
Agriculture and modeling?
3. How can we adapt agriculture systems to unknown
future conditions?

21. Overview of climate variability and likely
climate change impacts on agriculture across
the Greater Mekong Sub-region (GMS)
Project team:
Peter Laderach, Rod Lefroy, Aparna Mani, Linh Giang, Stephania Carmona, Anton Eitzinger
Thank you
A.Eitzinger@cgiar.org