Download - Kavvas Presentation
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 1/120
PROJ ECTI ON OF TH E IMPACT OFCLIM AT E CHAN GE ONLI MA TE CHA NGE ON
THE HY DROLOGIC REGIM E AND WAT ER RESOURCESOF
A GEOGRAPHI CAL REGIONGEOGRAPHICAL REGION:A DYN AM ICAL APPROACH
The views expressed in this paper/presentation are the views of the author and do not necessarily reflect the views or policies of the
M.L. K avv as , Z.Q.Chen, N.Oha r a, E.TanCal i fo r n ia Hydro log ic Researc h Labora t o r y (CHRL)
, , .accuracy of the data included in this paper and accepts no responsibility for any consequence of their use. Terminology used may notnecessarily be consistent with ADB official terms.
Cal i fo r n ia Hydro log ic Researc h Labora t o r y (CHRL)A .J a m a l l u dd i n B in Sh a ab a n, M .Z a k i M .A m i n
Na t iona l Hydrau l i c Resea rc h In s t i t u t e o f Ma lays i a (NAHRIM)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 2/120
Introduction
• Weather - day to day fluctuations in thestate of the atmos here
• Climate - atmospheric state averaged over a
• Climate Change - change in averaged
natural and anthropogenically induced)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 3/120
Modeling Climate Change
The main tools for simulating the global climate evolution in time andspace are the coupled Atmosphere-Ocean Global Circulation Models
.
Confidence in AOGCMs is due to the physical basis of these models in,skills in simulating the observed historical climate and past climatechanges.
At large spatial scales there is confidence that AOGCMs provide crediblequantitative estimates of the change in the future climate.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 4/120
nce m - s s s ar e s mu a ng
gradually changing climate conditions under variousgreen ouse em ss on scenar os.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 5/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 6/120
SRES (Special Report on Emissions Scenarios) (2001)
•Rapid economic growth.•A global population that reaches 9 billion in 2050 and then gradually declines.•The quick spread of new and efficient technologies.•A convergent world - income and way of life converge between regions. Extensive social andcultural interactions worldwide.
There are subsets to the A1 family based on their technological emphasis:•A1FI - An emphasis on fossil-fuels (fossil fuel intensive).•A1B - A balanced emphasis on all energy sources (balanced).• - mp as s on non- oss energy sources pre om nant y non oss ue .
A2•A world of independently operating, self-reliant nations.•Continuously increasing population.
.•Slower and more fragmented technological changes and improvements to per capita income.
B1•Rapid economic growth as in A1, but with rapid changes towards a service and informationeconom .•Population rising to 9 billion in 2050 and then declining as in A1.•Reductions in material intensity and the introduction of clean and resource efficient technologies.•An emphasis on global solutions to economic, social and environmental stability.
B2•Continuously increasing population, but at a slower rate than in A2.•Emphasis on local rather than global solutions to economic, social and environmental stability.
•Intermediate levels of economic development.•Less rapid and more fragmented technological change than in B1 and A1.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 7/120
SRES (Special Report on Emissions Scenarios)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 8/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 9/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 10/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 11/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 12/120
Climate Change Projection Methodology shall be
emons ra e
by a completed study on the
p e e e e es u es
Peninsular Malaysia
–at 9km spatial grid resolution and 1hr time intervals.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 13/120
In 2001 t e on y pu ic y avai a e mu ti-rea ization g o a c imatechange AOGCM simulation data (3 realizations) was from
Canadian Climate Center.
Due to its well-documented validation with the historical observations,
and
due to its use of the most realistic climate change scenario (IS92a),as o , ,
in its climate change simulation studies
CGCM1 (Canadian Global Climate Model 1) climate change simulationresults were selected
.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 14/120
CGCM1-modeled mean DJF surface air temperature. b. Difference between modeled DJF surface airtemperature and NCAR DJF climatology c. As in a but for JJA. d. as in b but for JJA. Contour interval is5 ° C. Hatching indicates positive differences greater than 5 ° C, whereas shading indicates negativedifferences less than ) 5 ° C
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 15/120
a. CGCM1 modeled mean DJF precipitation. b. Observed DJF precipitation climatology (Xieand Arkin 1996, 1997). c. As in a. but for JJA.. d. as in b but for JJA.. Contour interval is 2mm/ d (from Flato et al.2000)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 16/120
Simulations of CGCM1 during the period 1850 – 2100 thatwere used for the Peninsular Malaysia climate change study:
They consist of a control simulation (in order to compare the modelperformance against historical observations), and the ensemble averageof three independent simulations with the same greenhouse gas andaerosol changes.
These simulations spanned from the “preindustrial” 1850 conditions
to the end of twenty-first century.
A representation of the historical change in greenhouse gas (GHG) andaerosol (A) forcing from 1850 to the present (1993) was specified
in terms of equiva ent CO 2 concentration an aeroso oa ing c anges.
The ro ected forcin chan e from the resent 1993 to 2100essentially follows IPCC IS92a scenario.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 17/120
Global-scale AOGCM Climate Change Projections areunreliable at regional (country) and watershed scales
• AOGCM spatial grid resolutions are too coarse for theescr pt on o t e ne eatures o oca c mate spat a
grid resolution is on the order of 410 km over PeninsularMala sia)
• At Regional and watershed scales– more refined topographic & land surface characteristics have
profound impact on regional climate
–
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 18/120
Malaysia during 2049. Letters indicate the locations of the CGCM1 grids.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 19/120
As such, at Regional and Watershed scalesit is necessary to refine the coarse-grid information from
by downscaling such information to a
a muc ner gr networ over t e mo e e reg on .
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 20/120
Downscaling AOGCM Climate Change Simulation Resultso eg ona ca e
• Statistical Downscaling– Statistical relations, developed among regional climate
var a es an arge sca e a mosp er c s a e var a es, are enused to downscale AOGCM results to regional scale;
• Numerical or Nested Grid Downscaling ( Dynamical approach ):– AOGCM results are used as initial and boundary conditions
which are nested into AOGCMs.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 21/120
Reliability Problems with Statistical Downscaling
• arge gr reso u on n s a s ca ownsca ng s oo coarse o accoun or eeffect of steep topography on local climate;
• Runoff estimates are fundamentally determined by precipitation projections;• Future projections of precipitation by AOGCMs, when downscaled to regional
,the neglect of the fundamental influence of topography on regional climate;
•climate are not accounted for.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 22/120
Numerical Downscalingof AOGCM Climate Change Simulation Results by
Regional Hydroclimate Models (RegHCM)(Dynamical Approach)
• AOGCM climate simulation results form initial andboundary conditions for regional hydroclimate model
• Regional model has substantially more refinedtopographic and land surface characteristics data (grid
resolution <10km)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 23/120
Consequently,
A Regional Hydroclimate Model of Peninsular Malaysia (RegHCM-PM)
was developed in order to downscale dynamically
the climate change simulations of the Canadian GCM (CGCM1)
at coarse spatial resolution (~410km)
to t e region of Peninsu ar Ma aysia at fine spatia reso ution (9 m)
the effect of the topography and land surface conditions
on its local hydroclimate .
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 24/120
=the atmos heric com onent of
MM5 (Fifth Generation Mesoscale Model)
or ofWRF (Weather Research and Forecasting Model)
+
the land surface process module of IRSHAM (Integrated.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 25/120
F θ σ 1 ( u * , θ * , θ 1 , θ 2 ) F q σ 1 ( u * , θ * , q 1 , q 2 )
θ = θ 1 q = q 1F i r s t A t m o s p h e r ic L a y e r( σ = 0 . 9 9 5 , z ≈ 5 0 m )
θ ( u * , θ * , T s u r f ; z ) q ( E ; u * ; L ( u * , θ * ( T s u r f ) ; z )
C o n s t a n t f l u x
R o u g h n e s sR N H s ( u * , θ * ) E ( w s , u * , θ * , q )
P
θ s o ( u * , θ * , T s u r f ) q s o ( w s )
S o il s u r f a c e T s u r f ( R N , E , H s , G ) w s ( E , P )
P u r e D i f f u s i o n Z o n e
z = 0
S o i l w a t e rc o n t e n t w
S o i l V a d o s e Z o n e
s u r , s o
A schematic description of regional hydroclimate model RegHCMas the model for the interactive evolution of atmospheric processes aloft,
atmospheric planetary boundary layer, and land surface processes(From Kavvas et al. (1998), Journal of Hydrological Sciences, IAHS)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 26/120
MM5 Atmos heric Model
NCAR (US National Center for AtmosphericResearch and Penn State Universit
• Nonhydrostatic 3-D dynamic simulation of
• Downscaling and upscaling capabilities;
• Many modeling options for various atmosphericprocesses .
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 27/120
MM5 has a wide ran e of h sical rocess routinessuch as those
handling advection, diffusion, radiation, the boundary layer,
surface slab model, cumulus parameterization and moisture .
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 28/120
MM5 can be downscaled even to 0.5km spatial grid resolution,
which makes it very desirable for downscaling climate study results
even to t e sca e o sma waters e s, an e a e to capturethe impact of steep topography of the modeled region
on the local climatic conditions.
In the horizontal directions MM5 has two-way nesting capability.
Each nested domain takes information from its parent domain at every time-step, and
runs three time steps for each parent step before feeding back informationto the parent domain on the coincident interior points.
e ee ac s ngu s es wo-way nes ng rom one-way nes ng,
and allows nests to affect the coarse mesh solution,
usually leading to better behavior at outflow boundaries.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 29/120
Weather Research and Forecasting Model (WRF)
• WRF is a supported community regional climate model which is a free andshared resource with distributed development and centralized support.
• Its development is led by US NCAR, NOAA/GSD and NOAA/NCEP/EMCwith partnerships at AFWA, FAA, NRL, and collaborations with universitiesand other government agencies in the US and overseas.
• WRF has two different dynamical cores: The Advanced Research WRF(ARW) and Nonhydrostatic Mesoscale Model (NMM).
• Dynamical cores include mostly advection, pressure-gradients, Coriolis,buoyancy, filters, diffusion, and time stepping..
• ARW is supported by NCAR/MMM whereas NMM development is centeredat NCEP/EMC with the support of NCAR/DTC
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 30/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 31/120
The hydrologic and atmospheric processes that take place at the interfacebetween the earth surface and atmosphere, such as infiltration and
,“land surface processes”.
These land surface processes have scales much smaller than thehorizontal resolution of mesoscale atmospheric models.
For exam le, the rid size of the Re HCM for Peninsular Mala sia is9 km for the inner domain, while the actual hydrologic processes take
place at a scale of much less than 1 km (~10s of meters).
It is impossible to resolve the land surface processesat their actual spatial resolution
over t e computationa gri s of a regiona y roc imate mo e .Numerical schemes that model the areal-average behavior of
mesoscale atmospheric model are called“land surface parameterization”.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 32/120
MM5/WRF only have one-way interaction in the vertical direction.Their land surface model component options are all based on
- -fundamental role land heterogeneity plays in the modeled land surfaceprocesses as they vary with the scale of the model horizontal gridresolution.
What is necessary is a model of land surface fluxes and landhydrologic processes that will scale with the horizontal grid
.
Our Regiona Hy roc imate Mo e (RegHCM) is ase upon sucscalable land surface hydrologic conservation equations (Kavvas etal. 1998, Journal of H drolo ical Sciences
and is fully coupled to MM5 in a two-way interaction in the verticaldirection .
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 33/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 34/120
Regional Land Surface Module of RegHCMfrom land surface com onent of IRSHAM Kavvas et al. 1998
Areally averagedsoil water flow and
Rain Sun Rain Rain SunSun
so eat ow
equationsComputes
Interceptionby vegetation
Direct Evaporationof Intercepted Water Transpiration of
Root Zone Water Interceptionby vegetation
Direct Evaporationof Intercepted Water
Direct Evaporationof Intercepted Water Transpiration of
Root Zone Water Transpiration of
Root Zone Water Transpiration of
Root Zone Water
interception,evapotranspiration,
infiltration, exfiltration,
Through Fall
Rainfall excess
Bare Soil Evaporation
Through Fall
Rainfall excess
Bare Soil Evaporation
soil water contentprofile, soil waterstorage, direct runoff
Infiltration Root Zone
Unsaturated Zone
Groundwater Rechar e
Infiltration
Infiltration Root Zone Root Zone
Unsaturated Zone
Groundwater Rechar e
Infiltration,temperature asareally-averaged
Groundwater TableGroundwater Table model grid area
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 35/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 36/120
Necessary data for RegHCM
Land Use/Land Cover: Global Land CoverCharacterization (GLCC) by USGS
: ata
Aerodynamic Roughness Length and Surface Albedo:oo up a e w c re a es e aero ynam c roug ness
length and albedo with GLCC for winter and summer
respectively. (developed by NCAR)Soil Data: Digital Soil Map of the World (DSMW) byFAO
Sea Surface Temperature: ICOADS or AOGCM
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 37/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 38/120
Peninsular Malaysia and FAO soil survey dataset separately.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 39/120
Saturated hydraulic conductivity estimated using both the soilsurvey dataset of Peninsular Malaysia and FAO soil survey dataset together.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 40/120
Mean saturated hydraulic conductivity [unit: cm/hr] overRegHCM-PM’s inner domain grids.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 41/120
Standard deviation of saturated hydraulic conductivity [unit: cm/hr] over
RegHCM-PM’s inner domain grids.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 42/120
Aerodynamic roughness in winter over Peninsular Malaysia
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 43/120
Albedo in winter over Peninsular Malaysia
Stream channel routing model
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 44/120
Stream channel routing model
The land hydrology component of RegHCM-PM, described above,
computes
the flow from neighboring lands
to the stream network of a watershed.
In order to compute the flow at the outlet of a watershed,
s necessary o accoun or e s orage an rans a on processes w n
the stream network of a watershed.
For this purpose Muskingum Flow Routing algorithm
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 45/120
P ET P ET
OO
I is river inflow, O is outflow from the watershed, ET is evapotranspiration,s prec p a on, an s e c anne s orage w n e wa ers e .
The river inflow I , evapotranspiration ET , and precipitation P are computed bythe land hydrology and atmospheric components of RegHCM-PM.
The Muskingum flow routing model routes the streamflows within the stream
channel network toward watershed outlet.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 46/120
InflowInflow
Spill
Release
Spill
Release
Outflow
Generator
Irrigation
AdditionalIrrigation
water Outflow
Generato r
Irrigation
AdditionalIrrigation
water wa er
Irrigated land
wa er
Irrigated land
Schematic description of the operation of a reservoir
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 47/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 48/120
involves computation of crop potential evapotranspiration (PET), andthen balancing this PET by rain that falls over the region and
y so wa er s orage.
But the standard method for computing soil water storage is by theThornthwaite-Mather water balance method of 1950s which does not
accoun or e curren y roc ma e mo e ng ec no ogy a prov esmuch more reliable soil water balances and estimates.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 49/120
Estimation of Crop Irrigation demand :
After the actual evapotranspiration rate is calculated byRegional Hydroclimate Model RegHCM
Accounting forCro t e cro season state of soil water stora e and state of
atmospheric boundary layer
Crop Irrigation Demand = PET – Actual ET
Global ScaleAtmospheric TopographyBoundary
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 50/120
Atmospheric&
OceanData
Topography&
LandcoverUSGS
BoundaryConditions
Initial
MM5ModelOuter
CGCM, NCEP Soil (FAO)Fieldsoma n
BoundaryConditions
InitialFields
MM5
Model2ndDomain Model
BoundaryConditions
MM5
Fields InnerDomain
Watershed ScaleHydro-climate
Out ut
IRSHAMModel
Domain
,Landcover
&Soil
(NAHRIM)
NCEP: stands for United States National Center for Environmental Prediction;USGS: United States Geological Survey;
FAO: Food and Agriculture Organization of the United Nations;
Nested Domains and Configuration of RegHCM-PM
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 51/120
g gThe RegHCM-PM was nested into the First Generation Coupled General Circulation
figure. The CGCM1 provides the initial fields and boundary conditions to theRegHCM-PM, and then the CGCM1 simulation results are downscaled to the regionof Peninsular Malaysia through several nesting procedures.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 52/120
The grid layout for the 1st domain of the RegHCM-PM under Mercatorprojection. GTOPO30 DEM of the region is overlaid on the outer domain grids.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 53/120
este gr s o t e nner 3 r an t e outer 1 s oma ns o eg - un erMercator projection. The boundaries of the Peninsular Malaysia and nearby islands
are overlaid on the grids.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 54/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 55/120
VALIDATION OF REGHCM-PM OVER SUBREGIONS OF PENINSULAR MALAYSIA
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 56/120
Selected subregions in Peninsular Malaysia for hydroclimate comparisons
between the RegHCM-PM modeled values and observations
600
800
1000
n ( m m
)Obs Sim
5. Kelantan
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 57/120
400
600
c i p i t a t i o
0Jan-83 Jan-84 Jan-85 Jan-86 Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92
Month-Year
P r
800
1000 m
)Obs Sim
6. Pahang
0
200
400
600
Jan-83 Jan-84 Jan-85 Jan-86 Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92
P r e c i p i t a t i o n
(
ont - ear
400
600
800
1000
c i p i t a t i o n ( m m
)Obs Sim
7. Perak
0
200
Jan-83 Jan-84 Jan-85 Jan-86 Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92
Month-Year
P r
1000 )
Obs Sim8. Kedah
0
200
400600
800
- - - - - - - - - -
P r e c i p i t a t i o n
( m
Month-Year
Observed and simulated monthly precipitation over the subregions in Malaysian Peninsuladuring the validation period
202530
a t u r e
( o C )
Obs Sim2. Klang
20
2530
a t u r e
( o C )
O bs S im1. West Coast
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 58/120
10
15
t e m p e r a
1015
t e m p e r a
0Jan-91 Jan- 92 Jan-93
Month-Year
A i r
25
30 o C
)
Obs S im3. Selangor
25
30 o
C )
O bs S im4. Terengganu
0Jan-91 Jan-92 Jan-93
M onth-Year
A i r
0
51015
20
Jan-91 Jan-92 Jan-93
A i r t e
m p e r a
t u r e (
0
5
1015
20
Jan-91 Jan-92 Jan-93
A i r t e m p e r a
t u r e
(
o n - e ar ont - ear
15
20
25
30
p e r a
t u r e
( o C )
Obs S im5. Kelantan
15202530
p e r a
t u r e
( o C )
Obs Sim6. Pahang
0
5
Jan-91 Jan-92 Jan-93
Month-Year
A i r t e
05
Ja n-9 1 Ja n-9 2 Ja n-9 3
Month-Year
A i r t e
30 )Obs Sim. Perak
35 )
Obs S im8. Kedah
05
101520
25
A i r t e m p e r a t u
r e ( o
05
1015202530
Jan-91 Jan-92 Jan-93
A i r t e m p e r a t u
r e ( o C
- - -
Month-Year Month-Year
Observed and simulated monthly mean air temperature over the subregions in Malaysian Peninsuladuring the validation period.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 59/120
Locations of the selected stream gauging stations and watersheds.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 60/120
6000
7000
8000
)
Sim Obs
1000
2000
3000
4000
F l o w ( M
0
J a n -
8 J a
n - 8
J a n -
8 J a
n - 8
J a n -
8 J a
n - 8
J a n -
9 J a
n - 9 1
J a n -
9 J a
n - 9
Date
Observed monthly mean flow and simulated monthly mean flowat Jam. Guillemard, Kelantan (region no. 5)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 61/120
1000
1200
1400
1600
M C
Sim ObsMissing data
0
200
400
600
- 8 - 8 - 8 - 8 - 8 - 8 - 9 - 9 - 9 - 9
F l o w
J a J a J a J a J a J a J a J a J a J a
Date
Observed monthly mean flow and simulated monthly mean flowat Jam. Iskandar, Perak
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 62/120
OVER PENINSULAR MALAYSIA
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 63/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 64/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 65/120
West Coast Klang Selangor Terengganu
33
Kelantan Pahang Perak KedahJohor Southern Peninsula N.East Coast
27
29
r e ( o C )
21
23
i r
t e m p e r a
t
15
17
19
4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 1 2 2 4 5 6 7 8 9 0
Historical Period Simulated Future Period
1 9 8
1 9 8
1 9 8
1 9 8
1 9 8
1 9 8
1 9
1 9
1 9
1 9
1 9
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
2 0
Year
West Coarst Klang Selangor TerengganuKelantan Pahang Perack Kedah
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 66/120
Kelantan Pahang Perack Kedah
45005000
)
o or out ern en nsu a . ast oast
30003500
i p i t a t i o
n ( m
1000
15002000
n n u a
l P r e c
SimulatedSimulated Future Period
0500
9 8 4
9 8 5
9 8 6
9 8 7
9 8 8
9 8 9
9 9 0
9 9 1
9 9 2
9 9 3
0 2 5
0 2 6
0 2 7
0 2 8
0 2 9
0 3 0
0 3 1
0 3 2
0 3 3
0 3 4
0 4 1
0 4 2
0 4 3
0 4 4
0 4 5
0 4 6
0 4 7
0 4 8
0 4 9
0 5 0
stor ca er o
1 1 1 1 1 1 1 1 1 1
Year
West Coast Klang Selangor TerengganuKelantan Pahang Perak KedahJohor Southern Peninsula N East Coast
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 67/120
Johor Southern Peninsula N.East Coast
1600
18002000
t i o n
( m m )
8001000
1200
p o
t r a n s p
i r
0
200400
600
A n n u a
l e v Simulated
Historical Period Simulated Future Period
1 9 8 4
1 9 8 5
1 9 8 6
1 9 8 7
1 9 8 8
1 9 8 9
1 9 9 0
1 9 9 1
1 9 9 2
1 9 9 3
2 0 4 1
2 0 4 2
2 0 4 3
2 0 4 4
2 0 4 5
2 0 4 6
2 0 4 7
2 0 4 8
2 0 4 9
2 0 5 0
Year
West Coast Klang Selangor Terengganu
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 68/120
Kelantan Pahan Perak Kedah
160
180Johor Southern Peninsula N.East Coast
SimulatedHistorical Period
Simulated Future Period
100120
140
o r a g e
( m m
40
60
80
o i l w a
t e r s
t
0
20
8 4
8 5
8 6
8 7
8 8
8 9
9 0
9 1
9 2
9 3
2 5
2 6
2 7
2 8
2 9
3 0
3 1
3 2
3 3
3 4
4 1
4 2
4 3
4 4
4 5
4 6
4 7
4 8
4 9
5 0
1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
Year
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 69/120
Locations of the selected stream gauging stations and watersheds.
2500
SimulatedHi i l P i d
Simulated Future Period
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 70/120
Historical Period
1500
2000
f l o w
( c m s
)
1000
o n
t h l y m e a
0
500
4 5 6 7 8 9 0 1 2 3 5 6 7 8 9 0 1 2 3 4 5 1 2 2 4 5 6 7 8 9 0 1 9 8
1 9 8
1 9 8
1 9 8
1 9 8
1 9 8
1 9 9
1 9 9
1 9 9
1 9 9
2 0 2
2 0 2
2 0 2
2 0 2
2 0 2
2 0 3
2 0 3
2 0 3
2 0 3
2 0 3
2 0 3
2 0 4
2 0 4
2 0 4
2 0 4
2 0 4
2 0 4
2 0 4
2 0 4
2 0 4
2 0 5
Year
Simulated monthly river flows during the historical (1984-1993) and future (2025-2034 and 2041-2050) periods at Jambatan. Guillemard, Kelantan (region no. 5)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 71/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 72/120
ummary o s mu a e ows ur ng e s or ca an u ure per o s a eselected watersheds of Peninsular Malaysia
Maximum monthlyflow cms
Mean monthly flowcms
Minimum monthlyflow cms
Historical Future Historical Future Historical FutureKlang 31.2 45.8 14.4 13.3 2.6 3.5
Selangor 107.9 108.5 40.7 37.5 7.1 0.5
Teren anu 398.4 569.5 93.4 98.3 13.1 10.8
re ion name
Kelantan 1535.1 1950.7 535.9 601.7 158.4 125.8Pahang 1697.4 2176.6 669.6 718.1 156.3 122.7Perak 523.7 578.2 286.4 299.7 183.6 139.2
. . . . . .Johor 82.7 94.0 32.7 31.8 9.8 6.8
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 73/120
,
now available, clearly show strong trendsin climate variablesin the future.
How to make inferences on the future water balancetrends over a selected eo ra hical re ion?
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 74/120
With this ensemble averaging approach, one can then filter out
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 75/120
the natural variability of the hydrologic variablein order to discern the real signal that should describe
the impact of the climate change on the hydrologic variable.
Wit in t e framewor of t is ensem e of rea izations
one can also compute the strength of the real signal
at two time points to the estimated ensemble standard deviation of
.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 76/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 77/120
o a str ut on o t e s mu ate sur ace temperature yGCM control run at 0:00 January 1, 1997
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 78/120
o a str ut on o t e s mu ate sur ace temperature yGCM (SRES A1B) run 1 at 0:00 January 1, 2050
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 79/120
o a str ut on o t e s mu ate sur ace temperature y
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 80/120
o a str ut on o t e s mu ate sur ace temperature yGCM (SRES A1B) run 3 at 0:00 January 1, 2050
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 81/120
An ensemble of 14 90-year realizations from these GCMs’ global climate
simulations for the 2010-2100 future eriod ma be downscaled to a
region of interest by means of RegHCM at 9km grid resolution and
hourly intervals.
The control climate runs of these three GCMs were also obtained, and
can e ownsca e o e reg on o n eres y means o eg or a
historical period for comparison with the future climate projections in
on the future water resources of the region
In this manner it is possible to construct an ensemble of 14
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 82/120
climatic variable over the region of interest at 9km grid resolution
un e year .
Based upon this ensemble it is then possible to construct
behavior of the specified hydrologic (eg. watershed runoff
.
throughout their transient, trending evolution during
the future period until the year 2100.
The simulated ensemble of future climatic and hydrologic conditions
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 83/120
can then be compared against the counterpart historical simulationsof RegHCM over the specified region, based upon its downscalingof 3 control simulations over the re ion from ECHAM5 MRI- CGCM2.3.2, and GFDL-CM2.1 GCMs during a 30-yearcalibration/validation period.
These comparisons can be performed by graphs, by statistics(monthly means and standard deviations of streamflows, maximuman m n mum stream ows ur ng t e stor ca an uture t meperiods), and by statistical tests (tests for the equality of the meansand standard deviations of historical and future streamflows,confidences bands for ensemble averages).
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 84/120
:With the available ensemble of climate simulations from
various AOGCMs,
and
With today’s regional hydroclimate modeling technology,
t s poss e to ma e sc ent ca y soun n erences
on the impact of future climate change
on the state of the water resources
o a es gna e geograp ca reg on.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 85/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 86/120
Com arisons of the monthl reci itation that were downscaled b
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 87/120
RegHCM-SS from the coarse-resolution ECHAM5 historical control rundata, against the Willmott data at 12 selected locations
200300400500600700800900
r e c
i p i t a t i o n
( m m
)Obs MM5Willmott(65)
200300400500600700800
r e c
i p i t a t i o n
( m m
) Obs MM5Willmott(110)
0100
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
P
600700
( m m
)Obs MM5Willmott(84)
0
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
700800900
m m
) Obs MM5Willmott(136)
0100200300400
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
P r e c
i p i t a t i o n
0100200300400500600
a n - 9
3
J u
l - 9 3
a n - 9
4
J u
l - 9 4
a n - 9
5
J u
l - 9 5
a n - 9
6
J u
l - 9 6
a n - 9
7
J u
l - 9 7
a n - 9
8
J u
l - 9 8
a n - 9
9
J u
l - 9 9
P r e c
i p i t a t i o n (
400600800
10001200
1400
r e c
i p i t a t i o n
( m m
)Obs MM5Willmott(107)
J J J J J J J
200300400500600700800900
e c
i p i t a t i o n
( m m
) Obs MM5Willmott(144)
0200
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
P
0100
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
P r
Com arisons of the monthl reci itation that were downscaled b
f
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 88/120
RegHCM-SS from the coarse-resolution NCAR reanalysis data, againstthe Willmott data at 12 selected locations
500
1000
1500
2000
P r e c
i p i t a t i o n
( m m
) Obs MM5Willmott(6)
100200300400500600700
P r e c
i p i t a t i o n
( m m
) Obs MM5Willmott(40)
0
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
800
1000
n ( m m
) Obs MM5Willmott(10)
0
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
600700800900
( m m
) Obs MM5Willmott(42)
0
200
400
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
P r e c
i p i t a t i o
0100200300400500
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
P r e c
i p i t a t i o
200
400
600
800
1000
1200
P r e c
i p i t a t i o n ( m
m ) Obs MM5Willmott(23)
200300400500600700800900
1000
P r e c
i p i t a t i o n
( m
m ) Obs MM5Willmott(59)
0
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
0
J a n - 9
3
J u
l - 9 3
J a n - 9
4
J u
l - 9 4
J a n - 9
5
J u
l - 9 5
J a n - 9
6
J u
l - 9 6
J a n - 9
7
J u
l - 9 7
J a n - 9
8
J u
l - 9 8
J a n - 9
9
J u
l - 9 9
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 89/120
Climate is an evolving, transient process.
As such, the best way to make inferences on
h f i i i
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 90/120
the future extreme precipitation eventsunder future changed climate conditions is
to dow nscale many sim ulated climate realizations
from different GCMsfor a specified
atmospheric greenhouse gases and sulfate aerosol emissions scenario
Regional Hydroclimate Model (RegHCM )
over the specified watershedfrom which one can then select future extreme reci itation events.
One can then compare the historical MP estimate
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 91/120
aga nsthe future precipitation events
a are ownsca e rom e en e arge sca e ex reme
atmospheric conditionso e sca e o e spec e wa ers e or
by means of the RegHCM over the specified watershed
in order to verify that the
stor ca est mate
is indeed the maximum precipitation event
t at can occur over t e spec e waters e .
EH5-A1B Surface Air
Y 2016 R li i
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 92/120
Year 2016 Realizations
_ _
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 93/120
3 Realizations of Surface air tem erature simulations retrieved from
an EH5 GCM Grid (1.85x1.85degree) over California
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 94/120
3 Realizations of 6 hourly precipitation simulation data retrieved from
an EH5 GCM Grid (1.85x1.85 degree) over California
Precipitation during a potential flooding event
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 95/120
3 Realizations of 6 hourly precipitation simulation data obtained from
an EH5 GCM Grid (1.85x1.85degree) over California
Based upon this ensemble it will then be possible
to construct
an upper limit realization for the future precipitation series
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 96/120
an upper limit realization for the future precipitation series
.
There are also a limited number of GCM simulations
extending to the year 2300
that can be used to examine further the future extreme
precipitation/flood eventsb downscalin the GCM simulations to the s ecified watershed
by means of the combined RegHCM-WEHY atmospheric-hydrologic model
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 97/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 98/120
DEM of Peninsular Malaysia at a grid resolution of 3 arc-second based onthe Shuttle Radar Topography Mission. (SRTM-3 DEM, approximate horizontal grid
resolution of 90 meters)
Regional Hydroclimate Model (RegHCM) of PeninsularMalaysia
was run rst w t ts n t a an oun ary con t ons prov e rom
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 99/120
CGCM1 global historical atmospheric simulation data
at 1st domain at 81km grid resolution with 23 x 24 grids ,
cover ng e w o e en nsu ar a ays a reg on
and the surrounding areas,
and to be called “1 st domain”,
.
The longitudes of the outer domain span from 91 o E to 114 o E
and its latitudes span from 5 o S to 15 o N.
The 2 nd domain with 34 x 37 grids and a grid resolution of 27 km,
which covers a region of 918 km x 999 km,
is nested within the center of the 1st
domain.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 100/120
The 3rd domain is the inner domain of the updated RegHCM-PM , which
encompasses the entire Peninsular Malaysiaan covers a par o a an n e nor , ngapore n e sou , an a
part of Indonesia in the southeast.The inner domain is nested within the center of the 2 nd domain.
Below figure shows the whole inner domain grid layout relative to thePeninsular Malaysia under Mercator projection.
,
a region of 576 km x 684 km. In the figure, the boundary of PeninsularMalaysia is shown with black lines, the grids of the inner domain are shownas small blue squares, and the grids of the outer domains are indicated by
the large blue squares.
Twice-daily atmosphere-ocean data from the CGCM1 climate change
simulations for the desired 1984-1993, 2025-2034 and 2041-2050
study periods are available from the Canadian Center for Climate
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 101/120
y p
Anal sis and Modelin CCCma onl for the avera e of the
ensemble of three realizations.
The atmospheric data are provided at the 10 vertical levels with a 12
hour time interval, and the surface data are given with a daily time
interval. Three time periods of the GHG+A1 IPCC IS92a Scenario
Run, 1984-1993 for historical conditions, and 2025-2034, 2041-2050
for future global climate change conditions, were used in this study.
These data were used as initial and boundary conditions for MM5
(the atmospheric component of RegHCM-PM) simulations of the
regional climate conditions over Peninsular Malaysia.
30( c m
s )
Kl
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 102/120
25 f l o w
( Klang
10
15
i c m o n
t h l y
0Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
P e r i o
d
Periodic means of simulated monthly flows during the historical (1984-1993) and future
(2025-2034 and 2041-2050) periods, and the 95% confidence band aroundthe future flows at Jam. Sulaiman, Klang
s )
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 103/120
80 ( c m s
405060
n t h l y f l o w
01020
e r i o
d i c m
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMonth
Periodic means of simulated monthly flows during the historical (1984-1993) and future(2025-2034 and 2041-2050) periods and the 95% confidence band aroundthe future flows at Rantau Panjang, Selangor
300c
m s
)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 104/120
250 w ( c
Terengganu
100
150
200
m o n
t h l y f l
0
50
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec P e r i o
d i c
Month
Periodic means of simulated monthly flows during the historical (1984-1993) and future(2025-2034 and 2041-2050) periods and the 95% confidence band around
. , ,
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 105/120
1400
1600
s )
800
1000
1200
o n
t h l y
f l o w
( c m
0
200
400
P e r i o
d i c m
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMonth
Periodic means of simulated monthly flows during the historical (1984-1993) and future(2025-2034 and 2041-2050) periods and the 95% confidence band aroundthe future flows at Temerloh Pahan
)
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 106/120
500 m s
)
300
400
t h l y f l o w
( cPerak
100
200
r i o d i c m o n
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMonth
P
Periodic means of simulated monthly flows during the historical (1984-1993) andfuture (2025-2034 and 2041-2050) periods and the 95% confidence band around thefuture flows at Jambatan. Iskandar Perak
s )
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 107/120
250 c m s
150
200
n t h l y f l o w
0
50
e r i o
d i c m
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMonth
Periodic means of simulated monthly flows during the historical (1984-1993) and future(2025-2034 and 2041-2050) periods and the 95% confidence band around
the future flows at Jambatan. Syed Omar, Muda, Kedah
70 m s )
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 108/120
60 ( cJohor
304050
o n t h l y f l o
010
P e r i o
d i c
Month
Periodic means of simulated monthly flows during the historical (1984-1993) and future
(2025-2034 and 2041-2050) periods and the 95% confidence band aroundthe future flows at Rantau Panjang, Johor
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 109/120
Land cover classification of Peninsular Malaysia. Nested grids of theinner and the outer domains of RegHCM-PM are shown in the background.
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 110/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 111/120
o a str ut on o t e s mu ate sur ace temperature yGCM (SRES A1B) run 2 at 0:00 January 1, 2050
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 112/120
o a str ut on o t e s mu ate sur ace temperature yGCM (SRES A1B) run 3 at 0:00 January 1, 2050
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 113/120
o a str ut on o t e s mu ate sur ace temperature y -CGCM2.3.2 GCM (SRES A1B) at 0:00 January 1, 2050
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 114/120
0 60.8
1
io
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 115/120
0.6 t i o
-0.20
0.20.4
l t o n o
i s e r
-1-0.8-0.6-0.4
S i g n
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Signal to noise ratio based on simulated flow data in1984-1993, 2025-2034, and 2041-2050 in Kelantan
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 116/120
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 117/120
Monthly Leaf Area Index [x10] for RegHCM-PM’s inner domain grid areas
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 118/120
Monthly green fraction [%] for RegHCM-PM’s inner domain grid areas
As such, it is necessary to developa regional hydrologic-atmospheric model of
the studied region (eg. Peninsular Malaysia)to be called as “ Regional Hydroclimate Model of (modeled region)”
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 119/120
eg -
atmospheric dynamics and hydrologic dynamics)
the coarse- rid-resolution lobal climate chan e simulation datafrom the specified AOGCM (eg. ~ 410km grid-resolution
Canadian CGCM1 current and future climate simulation data forPM Climate Change Study)
tothe studied region (eg. Peninsular Malaysia)
at fine spatial grid resolution (<10km grid resolution).
As such, the best way to make statistical inferences about climate changeis to obtain several simulated climatic realizations from different
aerosol emissions scenarioso that one can form an ensemble of several members at any given
8/6/2019 Kavvas Presentation
http://slidepdf.com/reader/full/kavvas-presentation 120/120
y gspecified time for a specified hydrologic (eg. watershed runoff) or
climatic (eg. rainfall) variable.
en a a ns an o me, one can ma e n erences ase upon eensemble average value of the variable of interest, with the ensemblestandard deviation providing a measure of the uncertainty. Ensemble
averages of the same variable, estimated at different time points wouldthen provide a measure of the change in the variable of interest.
It is also possible to develop a confidence band around the ensembleaverage n or er o ma e n erences concern ng e s gn cance o
deficits or of the severity of hydrologic extremes, as function of evolving
time toward the future.