Environmental modeling climate model used in Sri Lanka

1. CLIMATE MODELLING
AS2016078

2. Contents critical review discuss
▪ Introduction
▪ GCM
▪ RCM
▪ Current Problems
▪ Main limitations and Challenges
▪ Projected changes
▪ Model usage in sri lanka
▪ Conclusion
▪ References
2

3. Introduction
▪ Model
Smaller representation of a larger object.
▪ Climate Model?
Predict How average conditions will change in a region over the
coming decades.
3

4. Basic 4 types of climate model
1. Energy balance models (EBMs) (Surface temperature)
2. One-dimensional radiative convective (RC)
models(Modelling of radiative and a ‘convective adjustment)
3. Dimensionally-constrained models (surface processes and
dynamics)
4. Global climate models (GCMs) (3-dimensional nature of the
atmosphere and ocean is incorporated)
4

5. Climate and climate modelling
(Source: IPCC, 2007 )
5

6. 5 components
1. Solar Radiation
2. Dynamics
3. Surface processes
4. Chemistry
5. Resolution in both time and space
(Source: McGuffie and Henderson-
Sellers, 2005)
6

7. Contemporary GCMs
▪ (GCMs) simulate the Earth‘s climate via
mathematical equations that describe
atmospheric, oceanic, and biotic
processes, interactions, and feedbacks.
▪ The primary tool for understanding how
the global climate may change in the
future
▪ They have between 10 and 20 layers in
the atmosphere, and as many as 30
layers in the ocean.
▪ Contemporary AOGCMs have a
horizontal resolution of between 250km
and 600km.
7

8. Contemporary GCMs
▪ Based on the Navier–Stokes
equations on a rotating sphere with
thermodynamic terms for various
energy sources (radiation, latent
heat).
𝜌 𝐷𝑣/𝐷𝑡 = 𝛻𝑝 + 𝜇𝛻2𝑣 + 𝑓
(Where, “𝜌” is a density; “𝑣” is a flow
speed; “𝑡” is a time; “𝑝” is a pressure; “𝜇”
is a dynamic viscosity; and “𝑓” is a body
forces) 8

9. Types of GCMs
1. AGCM (Atmospheric GCM)
Atmosphere & impose sea surface
temperature
2. OGCM (Ocean GCM) Global sea
patterns
3. AOGCM (Atmosphere and Ocean
GCM)
HadCM3
GFDL
CGSM 9

10. GCM process
10

11. Inputs
Past and present forcings
▪ Changes in the sun’s output,
▪ Long-lived greenhouse gases – CO2, CH4, N2O
and halocarbons and aerosols
▪ The “Representative Concentration Pathways” (RCPs)
which provide plausible descriptions of the future, based on
socio-economic scenarios of how global society grows and
develops
11

12. Outputs
Complete picture of the Earth’s climate
▪ Temperatures & humidity
▪ Salinity and acidity (pH) of the oceans
▪ Estimates of snowfall, rainfall, snow cover and the
extent of glaciers, ice sheets and sea ice.
▪ Generate wind speed, strength and direction,
▪ Jet stream and Ocean currents
12

13. Regional Climate Models (RCMS)
13

14. Regional Climate Models (RCMs)
The added value of the RCMs in
comparison with the GCMs
▪ Higher detail for mountain
ranges and coastal zones,
differing vegetation coverage
and soil characteristics
A description of smaller-scale
atmospheric processes
14

15. Model evaluation
▪ Comparison with observational data
▪ Even more data produced
▪ More data collected at selected sites
▪ Comparing against the average state of the climate
▪ Model inter-comparison projects, provide a way to look at
similarities and differences between models.
15

16. Emission Scenarios
▪ A1 rapid economic growth, a global population that peaks in
mid-century and more efficient technologies.
▪ A2 high population growth, slow economic and technological
change
▪ B1 same global population as A1,& more rapid changes in
economy
▪ B2 intermediate population and economic growth,
Climate projections for South Asia and Sri Lanka are available for
scenarios A1, A2, B1 and B2 (IPCC 2000)
16

17. Projected Changes (IPCC, AR5)
• Global Average Surface Temperature change
17

18. Projected Changes (IPCC, AR5)
• CMIP5 multi-model mean spatial distribution
18

19. Projected Changes (IPCC, AR5)..
(Source: IPCC,
Figure 3
19

20. Projected Changes (IPCC, AR5)..
• Global ocean surface pH
20

21. Projected Changes (IPCC, AR5)..
• Global mean sea level rise
21

22. Projected Changes (IPCC, AR5)..
• Figure: Temperature increase vs cumulative carbon emissions
22

23. RF & T Scenarios for Sri Lanka
▪ High diversity of altitude from sea level within short distance
▪ Resolution power of the grid points of the GCMs (300 km X 300
km) are not sufficient enough
▪ GCM Based Statistical Downscaling is used
o Sim CLIM Software
o ANUSPLIN Software
23

24. Baseline (1961-1990) average Rainfall in
Northeast Monsoon (NEM)
Baseline (1961-1990) average Rainfall in
Southwest Monsoon (SWM)
24

25. 1961-1990 Baseline average Tmean in
Northeast Monsoon
1961-1990 Baseline average Tmean in
Second Inter Monsoon
25

26. Annual rainfall variability in Nuwara-Eliya
-1000
-500
0
500
1000
1500
2000
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
yearRFanomalyinmm
(from1961-1990)
Annual rainfall variability in Colombo
-2000
-1500
-1000
-500
0
500
1000
1500
2000
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
year
RFanomalyinmm
(from1961-1990)
26

27. Annual minimum air Temperature anomaly trend in Colombo
y = 0.005x - 0.3796
R2
= 0.1976
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1900 1908 1916 1924 1932 1940 1948 1956 1964 1972 1980 1988 1996
yearTminAnomalyinC(from
1961-1990)
Annual minimum air Temperature anomaly trend in Nuwara-
Eliya
y = 0.02x - 1.6757
R2
= 0.6888
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
1901 1909 1917 1925 1933 1941 1949 1957 1965 1973 1981 1989 1997
year
TminAnomalyinC
(from1961-1990)
27

28. Mean Temperature and rainfall Change
Scenarios in 2100
Mean Temperature in June 2100 under the A1
CGCM
Rainfall in June 2100
Under A2
HadCM3 28

29. Range of Mean Temperature
Increment over the baseline in
June 2100
HadCM3 CSIRO CGCM
A1 2.5 – 3.0 2.2 – 2.4 2.0 – 2.2
A2 2.1 – 2.5 1.9 – 2.0 1.7 – 1.8
B1 1.1 – 1.4 1.0 – 1.1 0.9 – 1.0
29

30. Current Problems
▪ The methodologies have been only based on downscaling
the results from global scale models,
▪ The various projections have been inconsistent without
further investigation
▪ Projections have not been borne out in the last 15 years
30

31. Main limitations and Challenges
▪ Impossible to simulate with 100% accuracy
▪ Uncertainty to climate projections cope with greenhouse gas
emissions
▪ How well they represent clouds
▪ GCMs do not simulate individual storms and local high
rainfall events
31

32. Conclusion
▪ GCM are the best tool we have for determining the range
and extent of climate change, as well as for working out what
is likely to happen in the future.
▪ All current models agree that current climatic change is a
result of anthropogenic influences.
▪ Future climate change will depend on the current human
response to that knowledge.
▪ Although GCM outputs are very large scale, they can be
refined and downscaled to assist in prediction for smaller
areas.
▪ Thus, the outputs from GCMs can be exceedingly useful in
terms of for responses to climate change. 32

33. Outputs as Inputs..
Output is then used as input to assess
▪ Water availability in future.
▪ Food safety
▪ Biodiversity trends
▪ Conservation planning
33

34. References..
• 2020. http://www.meteo.gov.lk/images/sljom.pdf.
• Carbon Brief. 2020. Q&A: How Do Climate Models Work? | Carbon
Brief. [online] Available at: <https://www.carbonbrief.org/qa-how-
do-climate-models-work> [Accessed 1 August 2020].
• Globalsupportprogramme.org. 2020. [online] Available at:
<https://www.globalsupportprogramme.org/sites/default/files/resour
ces/ecca-country-report-sri-lanka.pdf> [Accessed 1 August 2020].
• User, S., 2020. Home. [online] Meteo.gov.lk. Available at:
<http://www.meteo.gov.lk/index.php?lang=en> [Accessed 2 August
2020].
34