10th AIM Workshop, NIES, Japan: Mar 10-12, 2005

Approaches to Development ofHigh Resolution Climate Change Scenarios
for Integrated Impact Assessment
M. LalPacific Centre for Environment & Sustainable Development

The University of the South PacificObtaining reliable projections ofclimatic change at the regional scale isthe central issue within the globalchange debate.
In order to assess the social andenvironmental impacts of climatechange and to develop suitable policies
to respond to such impacts,
information about climate change isneeded not only at a national level, buton a regional and local scale as well.

Future Climate Change Scenarios
The estimates of human induced global
warming by the IPCC are based on the premisethat the growth rate of atmospheric greenhousegases will accelerate in the future.
According to most recent estimates by IPCC,
the average global surface temperature is
projected to increase by between 1.4° and
3°C above 1990 levels by 2100 for low
emission scenarios and between 2.5° and
5.8°C for higher emission scenarios ofgreenhouse gases in the atmosphere.

Regional Pattern of Changes in Maize Yield by 2080s

Hadley Centre, UKM P I, Germany

Yield forecasts due to inter-model variance in climate projections

ReducedNo Change
IncreasedGlobal climate modeling has undergone a
steady development during the last three tofour decades.
However, current uncertainties remain very
high in the projection of regional climatechange.
This is due to the complexity of theprocesses that determine regional climatechange, and the need for more comprehensivemodeling tools and research strategies toaddress this problem.

Both topography and the land surface conditions
strongly affect the surface climate change signal
at scales smaller than the grid interval of A-OGCMs.
This implies that the information obtained from
A-O GCMs needs to be used cautiously in studiesof the impacts of climate change, particularly inregions that are characterized by pronounced
variability in forcings on fine scales.
The potentials and limitations of different
regionalisation techniques need to be wellunderstood before they are applied to theconstruction of specific regional climate change
scenarios.

The primary tools today available to simulate
long-term climate change are known as coupled
A-O GCMs.
These are 3-D mathematical representations ofthe global atmosphere-ocean-sea ice system.
Limitations in computer power force thehorizontal grid interval of present day A-O
GCMs to be about a few hundred kilometres.
As a result, processes and atmosphericcirculations occurring at smaller scales cannot be
explicitly described.

None-the-less, current A-O GCMs haveperformed relatively well in reproducing many
basic characteristics of the general circulation,such as major belts of precipitation in thetropics or the seasonal migration of midlatitude storm tracks.
These climate models have also shown somesuccess in describing the El Niño SouthernOscillation and North Atlantic Oscillation
phenomena and related teleconnection patterns,
although significant improvements are stillneeded.

The smoke from biomassburning inhibits cloudformation in the tropics.

The recent model simulations
suggest that the aerosols madeup of black carbon lead to a
weaker hydrological cycle,
which connects directly towater availability and quality.

Climate Variability
PNA

Monsoon

PN A

NAO
APN

North AtlanticOscillation

PNA

SahelSST

SST

NordesteThe
Theinteractions
interactionsbetween
betweenatmosphere
atmosphereandandoceansoceansininthethetropics
tropicsdominate
dominatethe
thevariability
variability
atatinter-annualscales.
Themainplayeristhevariability
intheequatorial
Pacific.
inter-annual scales. The main player is the variability in the equatorial Pacific. WaveWavetrains
trainsofofanomaly
anomalystem
stemfrom
fromthetheregion
regioninto
intothethemid-latitudes,
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NorthAmerican
AmericanPattern
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(PNA).The
Thetropics
tropicsare
areconnectedconnectedthroughthroughthe
thePacificPacificSST
SSTinfluence
influenceon
ontheIndianOcean
SSTandthemonsoon,
SahelandNordeste
precipitation.
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been
the Indian Ocean SST and the monsoon, Sahel and Nordeste precipitation. It has been
proposed
proposedthat
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yearsthethecircle
circleisisclosed
closedandandandandaafull
fullchainchainofofteleconnections
teleconnections
goes
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Also
shown
istheNorth
Atlantic
Oscillationagoes all around the tropics. Also shown is the North Atlantic Oscillation amajor
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modeofofvariability
variabilityininthe
theEuro-Atlantic
Euro-Atlanticsector
sectorwhose
whosecoupledcouplednature
natureisisstill
stillunderunderinvestigation.
investigation.

Indian Ocean temperatures affect intensityof the Indian monsoon and rainfall• A phenomenon “the Madden Julian Oscillation(MJO)” in the atmospheric circulation explainsvariations of weather in the tropics and regulates
the intensity of rainfall and break conditions
associated with the south Asian monsoons.
• The fluctuations the MJO involve variations inwind, SST, cloudiness, and rainfall. The MJO canbe characterized by a large-scale eastward
movement of air in the upper troposphere with aperiod of about 20-70 days, over the tropicaleastern Indian and western Pacific Oceans atapproximately 200 hPa in the upper troposphere.

While drought conditions prevailed in Vidarbha(in the state of Maharashtra) during June andJuly 2002, heavy downpours in August
amounted to 80 cm of rainfall, compared to 95
cm of normal seasonal rainfall.
On 2-3 September, 25 cm of rainfall was recorded,
which lifted the water level of Sardar Sarovar
dam along the Narmada River to 12 m above its
full capacity of 95 m, inundating hundreds ofvillages in the region.
The monsoon wreaked havoc in seven districtsof Maharashtra from 1 to 3 September 2002,claiming 35 lives and causing massive damage
to crops and throwing normal life out of gear.

Different ‘regionalisation’ techniques havetherefore been developed over the last
decade or so to improve the regional
information provided by coupled A-O
GCMs, and to provide climate information
at a finer scale.
Such techniques can be classified into
three categories:
1. Statistical downscaling methods;
2. ‘Nested’ limited area (or regional)
climate models;
3. High and variable resolution ‘time-slice’
AGCM experiments.

Statistical DownscalingUnder this approach, regional or local climate
information is derived by first developing astatistical model which links large-scale climatevariables (or ‘predictors’) to regional and localvariables (or ‘predictands’).
The large-scale output of an A-O GCM simulation isthen fed into this statistical model in order toestimate the corresponding local and regional climatecharacteristics.
A range of such statistical downscaling models havebeen developed for regions where sufficiently gooddatasets are available to allow the models to beproperly calibrated. These techniques are currentlyused for a wide range of climate applications.

One of the main advantages of statistical downscaling techniques isthat they do not require large amounts of computational resources.
Another advantage is that they can be used to provide information at
specific locations.
However, statistical downscaling methods are based on empiricalmodels and not on models that explicitly describe the physicalprocesses that affect climate and this may limit their applicability.
In addition, the major theoretical weakness of statistical downscaling
methods is that the fundamental assumption on which they are based— that the statistical relationships developed for present-day climate
also hold under the different forcing conditions of possible futureclimates — is often not verifiable.

Nested Regional Climate Models
These can be visualized as providing a high-resolution
zoom in effect over a selected region.
Up to now, this technique has only been used in one
direction, that is with no feedback from the regional
climate model to the global climate model.
These have proven to be flexible tools, capable ofreaching high resolution (down to 10-20 km or less)and simulation times of several decades.
They have also been able to describe successfully
climate feedback mechanisms acting at the regionalscale.

PRECIPITATION PATTERNSJJAS from GCM and RCM control climates, and observations

Hadley Centre GCM

Hadley Centre RCM

CRU Climatologymm/day

BREAK-ACTIVE PRECIPITATIONwind vectors (m/s) are (mean active) - (mean break)

GCM

RCM%
More rainfall in Tamil Nadu during monsoon break eventCYCLONE SIMULATION
Pressure (hPa) and wind fields (m/s) every 6h from control run

COASTAL SURGES DUE TO TROPICAL STORMS
IN BAY OF BENGAL CAN BE PREDICTED

Resulting surge simulated using
a storm surge modelRAINFALL CHANGE OVER SOUTH ASIA
as simulated by Regional Climate Modelmm/day21st Century Changes in Monsoon
Rainfall under A2 and B2 Scenarios

Nested Regional Climate Modeling approach,however, has some theoretical limitations.
For example, the regional model simulations areaffected by systematic errors in the driving
meteorological fields provided by global models,
and two-way interaction between regional andglobal climate is not described.
In addition, for each application, carefulconsideration needs to be given to the ways thatthe models are configured.
From the practical viewpoint, regional model
simulations can be demanding on computational
resources, both in terms of computation powerand data storage.

Variable Resolution Models
The main advantage of this tool is that theresulting simulations are globally consistentand capture the feedback from the regional
high resolution atmospheric circulations on
the global climate.
The use of this technique is based on theassumption that the large-scale circulation
patterns in both the coarse and highresolution GCMs are not very different fromeach other.

Conformal-cubic model features· 2-time-level semi-implicit hydrostatic (recently, has non-hydrostatic option)· semi-Lagrangian horizontal advection with bi-cubic spatial interpolation· total variation diminishing (TVD) or semi-Lagrangian vertical advection· unstaggered grid, with winds transformed to/from·C-staggered positions before/after gravity wave calculations using
reversible interpolation· minimal horizontal diffusion needed:·Smagorinsky style; zero is fine
· weak off-centering (in time) used to avoid semi-Lagrangian "mountainresonances"· careful treatment of surface pressure and pressure-gradient terms nearterrain· a posteriori conservation of mass and moisture· grid is isotropicPhysical Parameterizations· cumulus convection:-new CSIRO mass-flux scheme, including downdrafts· includes advection of liquid and ice cloud-water· interactive cloud distributions· derived prognostically from liquid water· GFDL parameterization for long and short wave radiation· gravity-wave drag scheme· stability-dependent boundary layer and vertical mixing with nonlocal option· vegetation/canopy scheme· 6 layers for soil temperatures· 6 layers for soil moisture (Richard's equation)· option for cumulus mixing of trace gases· diurnally varying skin temperatures for SSTs

8 km trial simulation over Fiji
Model uses NCEP fields at all grid points.

C48 grid

Model orography

For these fine-resolution simulations, “global nudging” from the broad-scale
fields is the preferred strategy. All the Fiji land points have soil type 3 (fineclay) and vegetation type 32 - broadleaf evergreen trees (tropical forest).

Monthly Simulated Maximum Surface Air Temperature Climatology – Fiji(The observed temperature gradients between western and central divisions during the year and low
temperatures at high altitude are realistically simulated by the model)Monthly Simulated Minimum Surface Air Temperature Climatology – Fiji(The observed temperature gradients between western and central divisions during the year andlow temperatures at high altitude are realistically simulated by the model)

Comparison of observed and simulated
average monthly surface air temperatures

Comparison of intraseasonal and interannual
variability in monthly mean simulation of surface
air temperatures at Nadi and Nausori

In Fiji, Nadi (westerndivision) has a marked
seasonality in rainfall ascompared to Suva
(central division) which
has year round rainfall
under the influence oftrade winds (resulting in
more number of wetdays). The marked
differences in rainfall
seasonality at these two
locations in Fiji has been
reproduced in the model
simulations.

Monthly Simulated Rainfall Climatology – Fiji(The observed rainfall gradients between western and central divisions during the year, marked seasonality in rainfall in the westerndivision and less rainfall at the leeward side of mountains are realistically simulated by the model)

Observed and Simulated interannual
variability of monthly total Rainfall at
selected locations in Fiji

¾ Variable-resolution global models are well-suited toperform the simulations “traditionally” performed bylimited-area RCMs, whilst avoiding the usual lateralboundary problems.
¾ The variable-resolution global model C-CAM has
demonstrated substantial skill in reproducing manyobserved features of the Fiji’s climatology (precise
reasons for biases in temperature/rainfall are being
investigated).
¾ Recent modelling advances and greater computing
power can now allow regional climate simulations
down to around 8 km resolution (very relevant for
Pacific Island Countries).

To Conclude:
A coherent picture of regional climatechange for its application to impact
assessments, achieved through available
regionalisation techniques, will require morecoordinated efforts to evaluate thedifferent methodologies, compare methods
and models to each other and apply thesemethods to climate change research in acomprehensive strategy that involves arange of A-O GCM and regionalisation
experiments.

Thanks