Uncertainty in Climate Change Projections: Results from Different GCMs/RCMs in the Context of Nepal
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Pabitra Gurung PhD Student Natural Resources and Environmental Studies (NRES) University of Northern British Columbia
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Nepal does not have own climate projection model. Therefore, climate change studies in Nepal completely depend on the results of available model throughout the world. Many field based studies have proven that Nepal is the most vulnerable country in the context of climate change due to limited capacity to adapt to it. On the other hand, it is a big challenge to natural scientists to demonstrate climate change physically because of limited resources. Due to the complex geography of Nepal, most of the global climate projections are not able to capture the temporal and spatial climatic variability. In consideration to this problem, the Department of Hydrology and Meteorology (DHM) of Nepal has initiated a project to downscale climatic parameters regionally with technical support from the Asian Disaster Preparedness Centre (ADPC) under the financial support of Asian Development Bank (ADB). They used three different Regional Climate Models (RCM); PRECIS, RegCM4, and WRF under AR4 scenarios. However, there is still a lot of discrepancy among these projections which have created confusion among the stakeholders. Therefore, the objective of my presentation will be to focus on the discussion over these issues among the climate experts at UNBC.
Transcript of Uncertainty in Climate Change Projections: Results from Different GCMs/RCMs in the Context of Nepal
Pabitra GurungPhD Student
Natural Resources and Environmental Studies (NRES)
University of Northern British Columbia
Curious to Know?
What are the potential sources of uncertainty?
Is it due to Model resolution?
Is physics missing for such discrepancies?
Is it a problem to capture monsoon well?
Is this a common problem of the world? What is a
scenario in Canada?
What can be done to improve the climate model to fit into
the Himalayan regions?
Is there any improvement in IPCC AR5 that can address
the orographic effects of the mountain?
Hindu-Kush Himalayan Region
“Slope and Aspect”
Source: Google Earth
How can we say climate is changing in the
region?
Snow and Glacier Retreat
Shifting of Agro-ecological Zones
Drying up Spring Water Sources and Migration
Source: From my own experiences and various studies
Climate Data Portal: http://dhm.gov.np/dpc
Department of Hydrology and Meteorology (DHM)
Projected Climate Data of Nepal
RCM Climate
Variable
Data Period GCM SRES
Family
Resolution Source
PRECIS
Rainfall (mm),
Temperature (⁰C)
(Min and Max),
Relative Humidity,
Wind Speed,
Solar Radiation, &
Other
1970-2000 (Baseline),
2030-2060 (Projected)
HadCM3Q0,
ECHAM5A1B 20 km
DHM
RegCM4
1960-1990 (Baseline),
2030-2060 (Projected)
ECHAM4 A2
20 km
ECHAM5 A1B
WRF
1970-2000 (Baseline)
2030-2060 (Projected)
Era40,
CCSM3,
ECHAM5,
GFDL-V2,
HadCM3
A1B 12 km
Source: ADB/DHM/ADPC
Projected Mean Annual Climatic Variables
3 RCMs (WRF, RegCM4 and PRECIS) for all
scenarios from A1B….
grey lines: HadCM3Q0, ECHAM05, CCSM3, GFDL-V2, and HadCM3…
mean as black line representing scenario A1B … ...
red line represents scenario A2: ECHAM04…..
Precipitation Maximum Temperature
Minimum Temperature
Source: ADB/DHM/ADPC
Change of Annual Mean Precipitation
(mm)
(2030-2060)
Source: ADB/DHM/ADPC
Change of Annual Mean Maximum Daily
Temperature ( C)
(2030-2060)
Source: ADB/DHM/ADPC
Change of Annual Mean Minimum Daily
Temperature ( C)
(2030-2060)
Source: ADB/DHM/ADPC
Change in Monsoon (JJAS) Rainfall
WRF-ECHAM5 WRF-GFDL-V2 WRF-HADCM3
PRECIS-HadCM3Q0 RegCM4-ECHAM5 WRF-CCSM3
SRES Family – A1B
Source: IWMI
Change in Monsoon (JJAS) Max. Temperature
WRF-ECHAM5 WRF-GFDL-V2 WRF-HADCM3
PRECIS-HadCM3Q0 RegCM4-ECHAM5 WRF-CCSM3
SRES Family – A1B
Source: IWMI
Example of Hydrological Modeling: West Seti River Sub-basin of Nepal
- Located at Far Western Region of Nepal
- Catchment Area: 7,438 km2
- Elevation : 314 m to 7043 m (2505 m)
- Annual Rainfall: 1921 mm
- > 75 % Rainfall occurs only in monsoon Source: IWMI
Agro-Hydrological Model: Soil Water Assessment Tool
(SWAT)
Source: SWAT Document
Precipitation (2031-2060)
Percentage Change in Water Balance
(-13% to
+40%)(+6% to
+45%)
(-36% to
0%)
(-19% to
+25%)
Actual ET (2031-2060)
(-39% to
+122%)(-29% to
+108%)
(-30% to
+75%)
(-42% to
+50%)
Sou
rce:
IW
MI
Percentage Change in Water Balance
Total Flow Volume (2031-2060)
(-74% to
+736%)(-94% to
+714%)
(-96% to
+475%)(-67% to
+939%)
Net Water Yield (2031-2060)
(-68% to
+64%)(-68% to
+66%)
(-80% to
+15%)(-76% to
+22%)
Sou
rce:
IW
MI
Thank you !!!
Acknowledgement
Dr. Luna BharatiSenior Researcher
International Water Management Institute (IMWI)
Dr. Stephen DeryAssociate Professor
University of Northern British Columbia (UNBC)
Climate Science Informal Seminar (CSIS)University of Northern British Columbia (UNBC)
Potential Issues to Discuss?
What are the potential sources of uncertainty?
Is it due to Model resolution?
Is physics missing for such discrepancies?
Is it a problem to capture monsoon well?
Is this a common problem of the world? What is a
scenario in Canada?
What can be done to improve the climate model to fit into
the Himalayan regions?
Is there any improvement in IPCC AR5 that can address
the orographic effects of the mountain?
