The Impact of Climate Change on the Hydro-Climate of Malaysia Based on IPCC Fifth Assesment Report.

a)

b)

Figure 4.4 – 16 categories of (a) top and (b) bottom layer soil types

Table 4.1 – 16 categories of soil types

Soil Category Soil Description

1 Sand
2 Loamy Sand
3 Sandy Loam
4 Silt Loam
5 Silt
6 Loam
7 Sandy Clay Loam
8 Silty Clay Loam
9 Clay Loam
10 Sandy Clay
11 Silty Clay
12 Clay
13 Organic Material
14 Water
15 Bedrock
16 Other (land-ice)

29

a)

b)

Figure 4.5 - Sample monthly surface albedo for January (%) for (a) Peninsular Malaysia and
(b) Sabah and Sarawak

30

a)

b)

Figure 4.6 - Sample monthly green fraction for January (unitless) for (a) Peninsular
Malaysia and (b) Sabah and Sarawak

31

4.3. Initial and Boundary Conditions for WRF Model over Peninsular Malaysia and
Sabah-Sarawak

After retrieving and collecting 30 years (1970-2000) of climate data from historical control
simulations of the 5 GCMs and 94 years (2006-2100) of GCM simulations for 16 future
projections, the initial and boundary conditions have been prepared separately for each of the
5 GCMs' historical control simulations over Peninsular Malaysia and Sabah-Sarawak regions.

Sample of initial and boundary conditions for the historical control simulations over
Peninsular Malaysia for GFDL-ESM2M, CCSM4, MIROC, IPSL-CM5A-LR, and MRI-
CGCM GCMs at 1990-07-01 00:00 UTC are demonstrated from Figure 4.7 through Figure
4.41. Geopotential height in meters (Figure 4.7 for GFDL-ESM2M, Figure 4.14 for CCSM4,
Figure 4.21 for MIROC, Figure 4.28 for IPSL-CM5A-LR, and Figure 4.35 for MRI-CGCM),
temperature in K (Figure 4.8 for GFDL-ESM2M, Figure 4.15 for CCSM4, Figure 4.22 for
MIROC, Figure 4.29 for IPSL-CM5A-LR, and Figure 4.36 for MRI-CGCM), relative
humidity in % (Figure 4.9 for GFDL-ESM2M, Figure 4.16 for CCSM4, Figure 4.23 for
MIROC, Figure 4.30 for IPSL-CM5A-LR, and Figure 4.37 for MRI-CGCM), eastward
velocity in m/s (Figure 4.10 for GFDL-ESM2M, Figure 4.17 for CCSM4, Figure 4.24 for
MIROC, Figure 4.31 for IPSL-CM5A-LR, and Figure 4.38 for MRI-CGCM), and northward
velocity in m/s (Figure 4.11 for GFDL-ESM2M, Figure 4.18 for CCSM4, Figure 4.25 for
MIROC, Figure 4.32 for IPSL-CM5A-LR, and Figure 4.39 for MRI-CGCM), sea-level
pressure and surface pressure in Pa (Figure 4.12 for GFDL-ESM2M, Figure 4.19 for CCSM4,
Figure 4.26 for MIROC, Figure 4.33 for IPSL-CM5A-LR, and Figure 4.40 for MRI-CGCM),
and soil temperature in K for various ground layer (Figure 4.13 for GFDL-ESM2M, Figure
4.20 for CCSM4, Figure 4.27 for MIROC, Figure 4.34 for IPSL-CM5A-LR, and Figure 4.41
for MRI-CGCM) are demonstrated from Figure 4.7 through Figure 4.41.

Sample of initial and boundary conditions for the future simulations over Peninsular Malaysia
for MIROC GCM for RCP8.5 scenarios at 2050-07-01 00:00 UTC are demonstrated from
Figure 4.42 through Figure 4.48. The variables plotted in these figures are geopotential height
in meters, temperature in K, relative humidity in %, eastward velocity and northward velocity
in m/s, sea-level pressure and surface pressure in Pa, and soil temperature in K for various
ground layers, respectively. Sample of initial and boundary conditions for the historical and
future simulations over Sabah and Sarawak can be referred in Appendix A.

32

a) b)

c) d)

Figure 4.7 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for GFDL-ESM2M GCM historical control simulation (1990-07-01 00:00 UTC):
Geopotential Height in m at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

33

a) b)

c) d)

Figure 4.8 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for GFDL-ESM2M GCM historical control simulation (1990-07-01 00:00 UTC):
Temperature in K at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

34

a) b)

c) d)

Figure 4.9 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for GFDL-ESM2M GCM historical control simulation (1990-07-01 00:00 UTC):
Relative Humidity in % at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

35

a) b)

c) d)

Figure 4.10 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for GFDL-ESM2M GCM historical control simulation (1990-07-01 00:00 UTC):
Eastward velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

36

a) b)

c) d)

Figure 4.11 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for GFDL-ESM2M GCM historical control simulation (1990-07-01 00:00 UTC):
Northward velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)
a) b)

Figure 4.12 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for GFDL-ESM2M GCM historical control simulation (1990-07-01 00:00 UTC):
Sea-level Pressure in Pa (a), Surface Pressure in Pa (b)

37

a) b)

c) d)

Figure 4.13 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for GFDL-ESM2M GCM historical control simulation (1990-07-01 00:00 UTC):
Soil Temperature in K of 0-10 cm ground layer (a), of 10-40 cm ground layer (b), of 40-100
cm ground layer (c), and of 100-200 cm ground layer (d)

38

a) b)

c) d)

Figure 4.14 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for CCSM4 GCM historical control simulation (1990-07-01 00:00 UTC):
Geopotential Height in m at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

39

a) b)

c) d)

Figure 4.15 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for CCSM4 GCM historical control simulation (1990-07-01 00:00 UTC):
Temperature in K at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

40

a) b)

c) d)

Figure 4.16 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for CCSM4 GCM historical control simulation (1990-07-01 00:00 UTC): Relative
Humidity in % at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

41

a) b)

c) d)

Figure 4.17 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for CCSM4 GCM historical control simulation (1990-07-01 00:00 UTC): Eastward
velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

42

a) b)

c) d)

Figure 4.18 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for CCSM4 GCM (1990-07-01 00:00 UTC): Northward velocity in m/s at 300 hPA
(a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)
a) b)

Figure 4.19 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for CCSM4 GCM historical control simulation (1990-07-01 00:00 UTC): Sea-level
Pressure in Pa (a), Surface Pressure in Pa (b)

43

a) b)

c) d)

Figure 4.20 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for CCSM4 GCM historical control simulation (1990-07-01 00:00 UTC): Soil
Temperature in K of 0-10 cm ground layer (a), of 10-40 cm ground layer (b), of 40-100 cm
ground layer (c), and of 100-200 cm ground layer (d)

44

a) b)

c) d)

Figure 4.21 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MIROC GCM historical control simulation (1990-07-01 00:00 UTC):
Geopotential Height in m at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

45

a) b)

c) d)

Figure 4.22 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MIROC GCM historical control simulation (1990-07-01 00:00 UTC):
Temperature in K at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

46

a) b)

c) d)

Figure 4.23 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MIROC GCM historical control simulation (1990-07-01 00:00 UTC): Relative
Humidity in % at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

47

a) b)

c) d)

Figure 4.24 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MIROC GCM historical control simulation (1990-07-01 00:00 UTC): Eastward
velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

48

a) b)

c) d)

Figure 4.25 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MIROC GCM historical control simulation (1990-07-01 00:00 UTC):
Northward velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)
a) b)

Figure 4.26 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MIROC GCM historical control simulation (1990-07-01 00:00 UTC): Sea-level
Pressure in Pa (a), Surface Pressure in Pa (b)

49

a) b)

c) d)

Figure 4.27 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MIROC GCM historical control simulation (1990-07-01 00:00 UTC): Soil
Temperature in K of 0-10 cm ground layer (a), of 10-40 cm ground layer (b), of 40-100 cm
ground layer (c), and of 100-200 cm ground layer (d)

50

a) b)

c) d)

Figure 4.28 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for IPSL-CM5A-LR GCM historical control simulation (1990-07-01 00:00 UTC):
Geopotential Height in m at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

51

a) b)

c) d)

Figure 4.29 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for IPSL-CM5A-LR GCM historical control simulation (1990-07-01 00:00 UTC):
Temperature in K at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

52

a) b)

c) d)

Figure 4.30 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for IPSL-CM5A-LR GCM historical control simulation (1990-07-01 00:00 UTC):
Relative Humidity in % at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

53

a) b)

c) d)

Figure 4.31 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for IPSL-CM5A-LR GCM historical control simulation (1990-07-01 00:00 UTC):
Eastward velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

54

a) b)

c) d)

Figure 4.32 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for IPSL-CM5A-LR GCM historical control simulation (1990-07-01 00:00 UTC):
Northward velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)
a) b)

Figure 4.33 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for IPSL-CM5A-LR GCM historical control simulation (1990-07-01 00:00 UTC):
Sea-level Pressure in Pa (a), Surface Pressure in Pa (b)

55

a) b)

c) d)

Figure 4.34 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for IPSL-CM5A-LR GCM historical control simulation (1990-07-01 00:00 UTC):
Soil Temperature in K of 0-10 cm ground layer (a), of 10-40 cm ground layer (b), of 40-100
cm ground layer (c), and of 100-200 cm ground layer (d)

56

a) b)

c) d)

Figure 4.35 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MRI-CGCM GCM historical control simulation (1990-07-01 00:00 UTC):
Geopotential Height in m at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

57

a) b)

c) d)

Figure 4.36 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MRI-CGCM GCM historical control simulation (1990-07-01 00:00 UTC):
Temperature in K at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

58

a) b)

c) d)

Figure 4.37 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MRI-CGCM GCM historical control simulation (1990-07-01 00:00 UTC):
Relative Humidity in % at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

59

a) b)

c) d)

Figure 4.38 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MRI-CGCM GCM historical control simulation (1990-07-01 00:00 UTC):
Eastward velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

60

a) b)

c) d)

Figure 4.39 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MRI-CGCM GCM historical control simulation (1990-07-01 00:00 UTC):
Northward velocity in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)
a) b)

Figure 4.40 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MRI-CGCM GCM historical control simulation (1990-07-01 00:00 UTC): Sea-
level Pressure in Pa (a), Surface Pressure in Pa (b)

61

a) b)

c) d)

Figure 4.41 - Sample initial and boundary conditions for historical simulations over Peninsular
Malaysia for MRI-CGCM GCM historical control simulation (1990-07-01 00:00 UTC): Soil
Temperature in K of 0-10 cm ground layer (a), of 10-40 cm ground layer (b), of 40-100 cm
ground layer (c), and of 100-200 cm ground layer (d)

62

a) b)

c) d)

Figure 4.42 - Sample initial and boundary conditions for future simulations over Peninsular
Malaysia for MIROC GCM RCP8.5 scenario (2050-07-01 00:00 UTC): Geopotential Height
in m at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

63

a) b)

c) d)

Figure 4.43 - Sample initial and boundary conditions for future simulations over Peninsular
Malaysia for MIROC GCM RCP8.5 scenario (2050-07-01 00:00 UTC): Temperature in K at
300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

64

a) b)

c) d)

Figure 4.44 - Sample initial and boundary conditions for future simulations over Peninsular
Malaysia for MIROC GCM RCP8.5 scenario (2050-07-01 00:00 UTC): Relative Humidity in
% at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

65

a) b)

c) d)

Figure 4.45 - Sample initial and boundary conditions for future simulations over Peninsular
Malaysia for MIROC GCM RCP8.5 scenario (2050-07-01 00:00 UTC): Eastward velocity in
m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)

66

a) b)

c) d)

Figure 4.46 - Sample initial and boundary conditions for future simulations over Peninsular
Malaysia for MIROC GCM RCP8.5 scenario (2050-07-01 00:00 UTC): Northward velocity
in m/s at 300 hPA (a), 500 hPA (b), 700 hPA (c), and 900 hPA (d)
a) b)

Figure 4.47 - Sample initial and boundary conditions for future simulations over Peninsular
Malaysia for MIROC GCM RCP8.5 scenario (2050-07-01 00:00 UTC): Sea-level Pressure
in Pa (a), Surface Pressure in Pa (b)

67

a) b)

c) d)

Figure 4.48 - Sample initial and boundary conditions for future simulations over Peninsular
Malaysia for MIROC GCM RCP8.5 scenario (2050-07-01 00:00 UTC): Soil Temperature in
K of 0-10 cm ground layer (a), of 10-40 cm ground layer (b), of 40-100 cm ground layer (c),
and of 100-200 cm ground layer (d)

68

5. HISTORICAL CONTROL SIMULATIONS: MODEL CONFIGURATION, BIAS
CORRECTION AND MODEL VALIDATION

It is important to recall the difference between weather and climate. Weather is the status of
atmosphere in a very short time span, at hourly and daily intervals. As such, a weather forecast
tries to provide the near-term atmospheric conditions, whether it will be sunny, cloudy, rainy,
or snowy at a specific location. When weather is discussed, the timing, duration, and location
of the atmospheric event are important. Meanwhile, climate is the long-term state of the
atmosphere. Climate is usually evaluated by averaging the atmospheric conditions over a
certain time period: over a month, a season, a year, or a number of years. World
Meteorological Organization (WMO) suggests the time span of climate to be about 30 years.
Therefore, when climate is discussed, the timing of each individual flood event and drought
period is of no importance. Consequently, “climate change” means the difference between the
current and the future average states of the atmospheric conditions (the "climate conditions")
at a geographical location or at a region, and a climate simulation does not intend to predict
near-term atmospheric conditions. When the climate change projections are studied, it is
important to evaluate the statistics of the projected climate data rather than every single
atmospheric event within a climatic sequence. WRF-PM and WRF-SS model options were
configured by comparing the results of WRF's downscaling of GCM control runs with the
corresponding historical climate observations of rainfall and air temperature.

Locations of the 688 ground observation of rainfall (334 stations in Peninsular Malaysia and
354 stations in Sabah-Sarawak) and 33 meteorological (air temperature) stations (23 stations
in Peninsular Malaysia and 10 stations in Sabah-Sarawak) are depicted in Figure 5.1 and
Figure 5.2, respectively. Information for the rainfall stations are summarized in Table 8.1-8.2
and information for the meteorological (air temperature) stations are listed in Table 8.3-4.4 in
Appendix B.

69

a)

b)
DEM (m)

Figure 5.1 - Locations of the (a) 334 rainfall stations in Peninsular Malaysia and (b) 354
rainfall stations in Sabah and Sarawak

70

a)

b)
DEM (m)

Figure 5.2 - Locations of the (a) 23 meteorological stations for temperature in Peninsular
Malaysia and (b) 10 meteorological stations for temperature in Sabah and Sarawak

71

The OS ratio (bias correction ratio) of a month at a gauge station for a climate model is defined
as the ratio of the averaged gauge observation rainfall amount of that month divided by the
averaged model-simulated rainfall value of that month at the same gauge location in 30 years
from 1970 to 2000, downscaled by WRF using the boundary conditions from the climate
model’s control run.

An OS ratio of a month at a gauge was obtained by the following steps:

1) Add all monthly rainfall records excluding negative values in that month from 1970 to
2000 as ROBS(m);

2) Let NMONS(m) = 30, where m = 1 represents January, m=2 represents February, m=12
represents December. NMONS is the number of good monthly values during 1970- 2000
if there is no missing month;

3) Count the number of months with positive values during 1970 - 2000 for m=1 to 12 as
NOBMS(m);

4) Adjust ROBS using the NOBMS values to obtain averaged monthly gauge rainfall as
ROBSAVG(m),

ROBSAVG(m) = ROBS(m) * NMONS(m) / NOBMS(m)

5) Estimate the monthly model rainfall value at the gauge location using 30 year-averaged
monthly model rainfalls at 4 nearest model grids with inverse distance weights as
RSIMAVG(m);

6) Compute the OSratio (OS ratio) at the gauge location

OSratio(m) = ROBSAVG(m) / RSIMAVG(m), where m = 1, 2,…, and 12.

Monthly OSratio (bias correction ratio) values at the 6-km WRF model grids were obtained
by interpolation of the gauge OSratios of these gauges with more than two years of record

72

Number of Gaugesover the thirty years during 1970 - 2000. However, the Sabah and Sarawak region has only 40
gauges where there were more than 20 years of rainfall records in February in the 30 years
from 1970 to 2000. It has 295 gauges with more than 2 years of rainfall records in February
(more than 56 days), as shown in Figure 5.3.

350

300

250

200

150

100

50

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
20Yrs 42 40 41 42 41 42 43 46 44 41 42 43
15Yrs 94 103 105 103 103 106 106 108 107 108 108 108
10Yrs 157 153 153 157 162 162 161 159 156 157 159 161
5Yrs 185 185 184 186 186 187 188 190 188 188 188 189
2Yrs 294 295 294 294 292 292 297 299 299 298 298 297

Figure 5.3 - Number of gauges in Sabah and Sarawak with good rainfall observation records
for various durations

Weighted average of the nearest four gauges are used to a model grid to determine the model
grid OSratio. The inverse distances between gauges and the model grid were used to compute
the weights.

The simulated results of WRF-PM and WRF-SS during a historical period over the regions
are evaluated by comparing them against the observations in terms of rainfall and air
temperature. First, the annual mean values are averaged over 10-year periods (1970-1980,
1980-1990, 1990-2000) for air temperature, and the annual cumulative values are averaged
over 10-year periods for precipitation.

73

Figures 5.4, 5.5, and 5.6 show the observed and simulated 10-year average annual rainfall
during 1970 - 1980, 1980 – 1990, 1990 – 2000, respectively, by 5 GCMs. The maximum and
the minimum values in the colour scale for each of the plots are fixed at 0 mm and 8,000 mm
for comparison purposes. The elevation map of Malaysia is also added to each figure to show
the effect of elevation on precipitation. High precipitation areas are consistent with the high
elevation areas. The quality of the spatial distribution maps of rainfall during 1970-1980, as
shown in Figure 5.4a and Figure 5.4b, are worse than the quality of those during 1980 – 1990,
and 1990 – 2000 periods due to limited number of available rainfall gauges during 1970-1980
period in Peninsular Malaysia and Sabah-Sarawak. In order to obtain comparable maps
between simulations and observations, the spatial distributions of rainfall by simulations are
obtained using simulation values at the available gauges during a specific period. The
differences in rainfall values for the 5 GCMs are due to model uncertainty. However, the
spatial distributions of simulated precipitation values for different GCMs are comparable to
the corresponding observed values.

Figures 5.7, 5.8, and 5.9 show the simulated 10-year average annual mean air temperature
during 1970 - 1980, 1980 – 1990, 1990 – 2000, respectively, by 5 GCMs. The maximum and
the minimum values in the colour scale for each of the plots are fixed at 10oC and 30oC for
comparison purposes. In this way, the temporal variation of the distribution of temperature
can be seen easily in one figure for the simulated five GCMs. The elevation map of Malaysia
is also added to each figure to show the effect of elevation on temperature. From the spatial
and temporal distributions of 10-year average air temperature, shown in Figure 5.7 through
Figure 5.9, it can also be seen that elevation is directly correlated with surface air temperature.
Higher elevation areas have relatively lower air temperatures. In general, the 10-year average
air temperature values for different GCMs are quite similar. The differences in air temperature
values for the five GCMs are due to model uncertainty. The upward trend in temperature may
be seen in these figures in all GCMs.

Model rainfall simulation comparisons were also performed against the corresponding ground
observation data at the selected stations. Comparisons of simulations of monthly precipitation
against observations at selected locations are shown in Figure 5.10. Model simulation results
of rainfall show fairly similar patterns to the ground observations.

74

Figure 5.11 shows the comparisons of WRF-PM and WRF-SS simulated grid area average
monthly mean air temperature against corresponding observations at selected locations, as
shown in Figure 5.2. Since the distribution of air temperature is more homogeneous than that
of the precipitation, the WRF-PM simulation results show better fit to the observed air
temperature values than those of the precipitation. Therefore, bias correction is not required
for the surface air temperature.

The comparisons between the observations of rainfall and air temperature at point-location
gauging stations over Peninsular Malaysia, Sabah and Sarawak against WRF-PM and WRF-
SS simulated grid area-average rainfall and temperature at 6km X 6km computational grids
that contain those stations show biases for rainfall only. It is concluded that the no bias
correction is needed for the average temperature simulations. Possible reasons for biases in
rainfall may be stated as follows:

i) The WRF-PM and WRF-SS simulated rainfalls are from the downscaling of the GCM
coarse-grid control run simulations of historical global climate to the Peninsular
Malaysia and Sabah-Sarawak regions at 6km X 6km grid resolution, and not from the
historical very coarse resolution global reanalysis observations of NCEP/NCAR. This
is because the simulated future climate conditions, to be downscaled by WRF-PM and
WRF-SS, are to be compared against the corresponding simulated historical climate
control conditions, downscaled by WRF-PM and WRF-SS, for an honest assessment
of the impact of global climate change on the local hydro-climatic conditions over
Malaysia.

ii) Although the GCM outputs of the historical control run were downscaled by WRF-PM
and WRF-SS to 6 km grid resolution over Peninsular Malaysia, Sabah and Sarawak,
the simulated rainfalls are still an average over a 6km X 6km grid area (36 sqkm) which
is much larger in scale than the point scale of the corresponding ground station
observations.

The main idea of the bias correction is to quantify the biases between the WRF-PM and WRF-
SS simulated historical climate conditions and the corresponding observations in order to
account for these biases in the WRF-PM and WRF-SS simulations of the future climate

75

conditions by factoring these biases into the future climate simulations. Accordingly, the
biases between the WRF-PM and WRF-SS simulated historical climate conditions and the
corresponding observations were quantified and these biases were accounted for in the WRF-
PM and WRF-SS simulations of the future climate conditions over Peninsular Malaysia and
Sabah-Sarawak by factoring these biases into the future climate simulations. This is necessary
in order to obtain realistic comparisons between the historical and the future climatic
conditions over both Peninsular Malaysia as well as Sabah and Sarawak.

76

a) CCSM4 MIROC5

MRICGCM3 GFDLESM2M

IPSLCM5ALR Observed

77

b)

DEM (m)

Figure 5.4 - Simulated 10-year average annual rainfall (mm) over (a) Peninsular Malaysia and
(b) Sabah-Sarawak during 1970 – 1980, by downscaling the control run data from five global
climate models, against observations.

78