Developing Perturbations for Climate ChangeImpact Assessments

Bruce Hewitson*

AIACC Working Paper No. 3December 2003

*Corresponding Author. Email address: hewitson@egs.uct.ac.za

An electronic publication of the AIACC project available at www.aiaccproject.org.

AIACC Working Papers, published on the web by Assessments of Impacts andAdaptations to Climate Change (AIACC), is a series of working papers produced byresearchers participating in the AIACC project. The papers published in AIACC WorkingPapers have been peer reviewed and accepted for publication as being (i) fundamentallysound in their methods and implementation, (ii) informative about the methods and/orfindings of new research, and (iii) clearly written for a broad, multi-disciplinaryaudience. The purpose of the series is to circulate results and descriptions ofmethodologies from the AIACC project and elicit feedback to the authors. Becausemany of the papers report preliminary results from ongoing research, thecorresponding author should be contacted for permission before citing or quotingpapers in this series.

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The following paper is reprinted from EOS, Vol 84, no 35, Hewitson, B., DevelopingPerturbations for Climate Change Impact Assessments, pp. 337, 341, with permission of theAmerican Geophysical Union. The paper reports on results from research supported in part bygrant number AF07 from the AIACC project.

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Following the 2001 Intergovernmental Panelon Climate Change (IPCC) Third AssessmentReport [TAR; IPCC, 2001], and the paucity ofclimate change impact assessments fromdeveloping nations,there has been a significantgrowth in activities to redress this shortcoming.However, undertaking impact assessments (inrelation to malaria, crop stress, regional watersupply,etc.) is contingent on available climate-scale scenarios at time and space scales of rele-vance to the regional issues of importance.These scales are commonly far finer thaneven the native resolution of the Global Cli-mate Models (GCMs) (the principal tools forclimate change research), let alone the skillfulresolution (scales of aggregation at which GCM-observational error is acceptable for a givenapplication) of GCMs.

Consequently, there is a growing demand forregional-scale scenarios, which in turn arereliant on techniques to downscale from GCMs,such as empirical downscaling or nestedRegional Climate Models (RCMs).These methodsrequire significant skill,experiential knowledge,and computational infrastructure in order toderive credible regional-scale scenarios. Incontrast, it is often the case that impactassessment researchers in developing nationshave inadequate resources with limitedaccess to scientists in the broader internationalscientific community who have the time andexpertise to assist. However,where developingeffective downscaled scenarios is problematic,it is possible that much useful informationcan still be obtained for impact assessmentsby examining the system sensitivity to larger-scale climate perturbations. Consequently, onemay argue that the early phase of assessing sen-sitivity and vulnerability should first be char-acterized by evaluation of the first-orderimpacts, rather than immediately addressingthe finer, secondary factors that are dependanton scenarios derived through downscaling.

The necessity for downscaling then becomesan activity justified on the basis of needs andunderstanding not addressed through initialsensitivities based on the large-scale perturba-tions.This assessment of the first-order sensi-tivity of a regional response develops theessential base understanding for furtherimpact studies,and is as important in developedas well as developing nations.

For climate change issues, there is muchuncertainty implicit in the choice of GCMand greenhouse gas forcing scenarios; anuncertainty further compounded by the additional complications introduced bydownscaling.This further supports the argu-ment that initial steps in impact studies arebetter served by regional-scale scenarios thatare plausible perturbations of the current climate, and which access the future climateenvelope, sidestepping factors such as optimaldownscaling solutions.To this end, a method-ological approach that produces climate per-turbations that relate to the skill resolution ofa GCM, and is thus guided by the large-scaleresponse simulated by the GCM, may be amore robust means to address the initial sensitivity questions in impact assessmentresearch.

A particular problem has arisen in this regardwith the advent of the ready availability ofGCM climate change products on the Internet.The provision of grid cell resolution GCM output invites the use of these at the GCMgrid scale. However, the skill resolution of theGCM is typically some spatial and temporalaggregation of the native GCM resolution.“Skill”in this context may be considered the spatialand temporal scales of aggregation where theerror between GCM output and observationaldata does not preclude its use in a given appli-cation.For example,comparison of a GCM gridcell value with point station observations isnot valid.Even after aggregating station data toestimates of area averages comparable to agrid cell average (a problematic process itself),one still finds significant errors between theGCM and the observations for parameterssuch as the number of rain days, or for deter-

mining frost occurrence, etc.As GCM gridcells are aggregated, however, one finds thatthe GCM output and the comparable observa-tional data begin to converge.At the final levelof aggregation, the global mean GCMs havebeen shown to track temperature well evenover the last century.

Nonetheless, for the unaware, the simplestmeans of obtaining a regional climate changescenario is to use the values of the GCM gridcell most co-located with the region of interest,possibly interpolating this further to a pointlocation.Apart from the fact that GCM gridcells are area averages and not point values, theGCM grid cell value is typically well below theskill scale of the model,especially with regard toprecipitation—the variable most often required.This exacerbates the uncertainty associatedwith any derived regional-scale climate changescenario, and reduces the value of any impactassessment intended for developing policy andadaptation strategies.

Presented here is a simple approach forregional scenarios appropriate to the userneeds described above.Using GCM simulationoutput of future climate change, at spatial andtemporal scales more associated with theGCM skill resolution,one may develop “guidedperturbations”—perturbations to baselineobservational data that are guided by,or inaccordance with, the GCM large-scale anomalyunder future climates.This allows the impactsresearcher to investigate vulnerability andpotential consequences of climate change atthe relevant regional scales,using a perturbationof the present climate that is guided by theindicated change from the GCM. Further, thisavoids potential errors associated with usingraw GCM grid cell output, requires minimalstatistical or modeling expertise andinfrastructure, and supports the developmentof an initial understanding of regional sensi-tivity prior to drawing on more advanceddownscaling techniques.

Methods

The approach to developing GCM-guidedperturbations is conceptually simple, andreadily undertaken with basic computationalinfrastructure and skills. Primarily, one seeksto draw useful information from the GCMwhile accommodating the systematic bias ofdifferent GCMs.The “useful information”hererefers to the first-order (spatial large-scale)response of the GCM to greenhouse gas forcing.This has the immediate benefit of avoidingthe problems associated with the validity of

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Developing Perturbations forClimate Change ImpactAssessments

BY BRUCE HEWITSON

single-grid cell values.In essence,this approachesthe regional climate change question fromthe view that there is a spatial large-scale changesignal that is closer to the skill resolution of theGCM than individual grid cells, and whichprovides a first-order anomaly for an impactassessment sensitivity study. It is explicitly recognized that there will be additional local-scale variance of the climate change signal, butthis remains the subject for subsequent andmore refined impact assessment research.

Inherent in using the GCM climate changeoutput is that significant uncertainty arisesfrom differences in GCMs.This is due in partto differing model physics parameterizationof sub-grid scale processes.These differencesare reflected in various systematic biases andclimate sensitivities to greenhouse gas forcing.The inter-model differences are important,andreveal a measure of the uncertainty envelopeof projected future climate change. However,the systematic bias and spatial errors in GCMsobscure the climate change signal.The simplemethodology outlined here addresses theseissues in a manner appropriate to the objectivesoutlined earlier for early phases of impactassessments. Only a brief outline of the proce-dural steps is presented, as the method is simple.Full details are available in the supportdocumentation for the Africa guided pertur-bation products on the Internet (availablelate-2003,see http:// www.csag.uct.ac.za/AIACC).

The summary procedure,however,is as follows:1. Derive a large-scale spatial response sur-

face from the GCM using a simple spatial filter.In this example,a spatial 3 x 3 grid cell movingaverage is used on the control and future GCMsimulation output. Figure 1a shows the un-modified GCM 30-year current climate climatology (1970–1999) from the HadCM3GCM over southern Africa for the December-February (DJF) season.The same field smoothedwith a 3 x 3 spatial smoother (panel b), andthe large-scale response surface using a bi-cubic spline is applied to the data in panel (c).

2. Express the climate change anomaly as the difference between the large-scaleresponse (spline) surfaces of the present andfuture climate simulations, thereby removingsystematic bias which affects both the seasonaland spatial magnitudes of the anomaly andfacilitating comparison between models.

For precipitation this may then further be expressedas a percentage change (anomaly divided bythe GCM control climatology), which is a typical treatment of precipitation anomaliesin climate change studies (conversely, temper-ature is more typically treated in terms ofabsolute anomaly). In this discussion wefocus on precipitation,which is commonly thevariable of greatest concern. Figure 2 showsthe climate change percentage anomaly forDJF for two GCMs, the HadCM3 and theECHAM4-OPYC GCMs,using the bi-cubic,spline-fitted surface.

3. Perturb the observational climatology bythe fractional change indicated by the GCMspline-fitted surface of the large-scale percentage

anomaly.This may be applied to observationaldata at any spatial scale—from station obser-vations to gridded products.Temporal scalesshould be limited to some time average greaterthan daily (where GCMs have low skill inreflecting observed climate variability).

In this example, the focus is on the DJF seasonal mean; and subjectively, it is suggestedthat monthly means are likely to be close tothe finest temporal resolution one should use.In the example here, the GCM percentageanomalies are applied to an experimental,high-resolution, 10-km gridded precipitationclimatology for South Africa, demonstratingthe application of the perturbation on a finespatial resolution for a developing nation.

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Fig.1.HadCM3 30-year precipitation climatology (mm/day) for the control climate (a),and smoothed with a spatial moving average (b).Panel (c)shows the bi-cubic spline surface fitted to the smoothed data of panel (b).

Fig.2.Precipitation percentage change for DJF from the spline surface fitted to the current andfuture climate means for (a) HadCM3 and (b) ECHAM4.Dashed lines are negative.

Fig.3.Precipitation anomaly (mm/day) of the DJF baseline climatology using the GCM percentagechange.This represents a guided perturbation of the current observed climate,guided spatiallarge-scale anomaly from (a) the HadCM3 and (b) the ECHAM4 models.

As continental rift zones evolve to sea floorspreading, they do so through progressiveepisodes of lithospheric stretching, heating,and magmatism, yet the actual process ofcontinental breakup is poorly understood.The East African Rift system in northeasternEthiopia is central to our understanding ofthis process, as it lies at the transition betweencontinental and oceanic rifting [Ebinger andCasey, 2001].

We are exploring the kinematics anddynamics of continental breakup through theEthiopia Afar Geoscientific LithosphericExperiment (EAGLE), which aims to probethe crust and upper mantle structure betweenthe Main Ethiopian (continental) and Afar(ocean spreading) rifts, a region providing anideal laboratory to examine the process ofbreakup as it is occurring.EAGLE is a multidis-ciplinary study centered around the mostadvanced seismic project yet undertaken inAfrica (Figure 1). Our study follows the KenyaRift International Seismic Project [e.g., KRISPWorking Group, 1995], and capitalizes on theIRIS/ PASSCAL broadband seismic array[Nyblade and Langston, 2002], providing atelescoping view of the East African Rift withinthis suspected plume province.

EAGLE fieldwork was undertaken betweenOctober 2001 and March 2003. Many results

will be presented in a session at the “The EastAfrican Rift System: Development, Evolutionand Resources”Meeting to be held in AddisAbaba in June 2004.The lead Ethiopian insti-tutions were the Geophysical Observatory, theDepartment of Geology and Geophysics ofAddis Ababa University,the Ethiopian GeologicalSurvey, and the Petroleum Operations Depart-ment of the Ethiopian Ministry of Mines.Thelead European and U.S. institutions were theuniversities of Leicester, Royal Holloway Lon-don, Leeds, and Edinburgh, together withStanford, the University of Texas, El Paso,Southwest Missouri State, and Penn State uni-versities.The entire project was coordinatedin Ethiopia by the Commission of Scienceand Technology of the Democratic Republicof Ethiopia.

Models for Continental Breakup

The three-dimensional structure of oceanicrifts is primarily controlled by the supply ofmagma [e.g., Phipps-Morgan and Chen, 1993],whereas that of youthful continental rifts iscontrolled by the spatial arrangement of largedisplacement border faults [e.g.,Hayward andEbinger, 1996].Thus, magmatic processesincrease in importance as rifting proceeds tosea floor spreading, but there is no consensusas to when or how this transition occurs.Thevolume of melt produced and its seismicvelocity structure provide critical constraints

on mantle dynamics as continental breakupproceeds to sea floor spreading, but thereremain fundamental questions regarding thethree-dimensional distribution of strain andmelt as continents rift apart.

Our approach in EAGLE is to examine thenature of crust and upper mantle along ahighly extended,magmatically active continentalrift prior to the modifying effects of post-riftsedimentation, erosion of the uplifted riftflanks, and thermal decay. In the EthiopianRift we can (1) trace the evolution from broadlydistributed to focused strain during rift devel-opment; and (2) study the active processes ofcontinental breakup associated with a mantleplume (or other upper mantle convectiveupwelling),while avoiding interactions betweensubducted slabs and asthenospheric flow; theregion has been tectonically stable since 600 Ma.

Ethiopia-Afar Rift Zone

There is general agreement that the broaduplifted Ethiopia-Yemen plateau and Oligoceneflood basalt province have been affected byone or more Cenozoic plumes [e.g., Nybladeand Langston, 2002].A synthesis of 40Ar/39Ardata shows that flood basalts were eruptedacross an ~1000-km diameter region at ~31Ma, presumably coincident with plume headcontact with Afro-Arabian lithosphere [e.g.,Hofmann et al., 1997]. Previous geophysicalstudies show crustal thinning northward intothe Afar depression. Refraction profiles inAfar, interpreted as near-one-dimensionalstructures due to the very small number ofshots and receivers, suggest thinned 25-km-thick crust underlain by a 10-km-thick layerwith anomalously low upper mantle P-wavevelocities above apparently normal mantle[Berkhemer et al., 1975].

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The final GCM-derived perturbation of thebaseline climate (GCM percentage anomaly x baseline observed climate) is shown in thepanels in Figure 3.

Assessment and Caveats

By using the GCM percentage change, thederived absolute magnitude of the perturbationis naturally a function of the magnitude of thebaseline climatology. Consequently, whencomparing Figures 2 and 3, it is apparent thatthe spatial expression of the derived anomalyhas differences even where the spatial com-ponent of GCM large-scale anomaly field isthe same for different locations.The perturba-tion thus captures the spatial differences ofthe existing climate,while maintaining agreementwith the large-scale response of the GCM, thescale better associated with the model skill, asopposed to the single-grid cell values. Of notehere is that the two models in Figure 3, whichhave notable differences in their control cli-matologies (not shown), indicate a degree ofconvergence in the regional anomaly patternas derived here.Both models clearly indicatesimilar west-east patterns of wet-dryanomalies, and the HadCM3-derived anomalyis, to a large extent,very similar to a “dry-shifted”ECHAM4-derived anomaly.

Such agreement does not necessarily indi-cate that the models are right in their futureprojection of climate, but does suggest thatthere is some common response, giving credi-bility to the plausibility of the anomaly. Forimpact assessment research, this is exactlywhat is needed in initial studies; namely, thatone has a plausible, credible perturbation onwhich to develop initial understanding of theregional sensitivities to climate change forcing.

Thus, assuming that regional climate bound-aries do not undergo dramatic lateral shifts,the results suggest that this approach providesa future climate perturbation at spatial scalesappropriate for initial sensitivity studies in arange of impact assessment activities. Relatedto this is the important requirement that theGCM does not misplace, or fail to resolve, fun-damental physical climate boundaries. Forexample,if the GCM allows one climate domain(say, maritime) to extend into the adjacentbut different climate region (say, continentalarid zones), this will result in inappropriateapplication of the GCM anomaly in that region.This serves to highlight the need to carefullyevaluate the GCM fields prior to application.

Finally, although this is not a downscaledproduct,and does not include local feedbacksand other forcings under future climates, itdoes represent a regional-scale perturbation

in accord with the GCM first-order responseto greenhouse gas forcing.Using this approachwith a range of GCMs allows one to undertakean assessment of fundamental regional sensi-tivities to climate change that are not arbitrary,but guided by the envelope of future climate,as characterized by GCMs.The approach iscomputationally simple and appropriate for abroad range of researcher sectors.The procedureis equally applicable to large areas and forsingle station time series, and lends itself todata-sparse regions, as commonly found indeveloping nations.Hence,especially for manydeveloping regions (although not excludingimpact assessment work in developed nations),this approach serves to provide a first look atthe regional climate change envelope.

Reference

IPCC,Climate Change 2001: the Scientific Basis, J.T.Houghton, Y.Ding,and M.Nogouer (eds.),pp.881,Cambridge University Press,2001.

Author Information

Bruce Hewitson, ENGEO Department,University ofCape Town, South Africa;E-mail:hewitson@egs.uct.ac.za

Geophysical Project in EthiopiaStudies Continental Breakup PAGES 337, 342–343