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Extreme weather events and property values

A ULI Europe Policy & Practice Committee Report

Assessing new investment frameworks for the decades ahead

Author:Professor Sven Bienert

Visiting Fellow, ULI Europe

The mission of the Urban Land Institute is to provide leadership in the responsible use of land and in creating and sustaining thriving

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About the Author

SvenBienertisprofessorofsustainablerealestateatthe

UniversityofRegensburgandULIEurope’sVisitingFellow

onsustainability.Since2013,healsohasbeenmanaging

directoroftheIRE|BSInternationalRealEstateBusiness

SchoolattheUniversityofRegensburg,Europe´slargest

centre for real estate education.

Prof.Bienertgraduatedwithdegreesinrealestateeconomicsandbusiness

administrationandwrotehisPhDthesisonthe“ImpactofBaselIIonRealEstate

ProjectFinancing”.Hehasbeenconductingresearchinthefieldofsustainability

since2005,initiatingvariousprojectssuchasImmoValue,theIBI-RealEstate

BenchmarkingInstitute,andImmoRisk.

SinceApril2010Prof.BienerthasbeenheadoftheIRE|BSCompetenceCenterof

SustainableRealEstateattheUniversityofRegensburg,wherehisrecentresearch

hasfocusedon“greenpricing”andtheimpactofextremeweathereventson

propertyvalues,amongothertopics.Hisresearchhasreceivedseveralnational

andinternationalprizes,andhispapershavebeenpublishedinnumerousleading

internationalrealestatejournals.Prof.Bienertisalsotheauthorandeditorofseveral

realestatebooks.

Prof.Bienertcombinesacademicknowledgewithpracticalprivatesectorexperience,

having held management positions in a number of leading real estate consulting

companies.In2010hebecamefounderandmanagingdirectorofProbusRealEstate

GmbHinVienna,whichmanagesa€2.1billioncommercialrealestateportfolio

acrossCentralandEasternEuropeandSoutheasternEurope.

Credits

AuthorProfessor Sven Bienert

UniversityofRegensburg

VisitingFellow,ULIEurope

ProjectStaffJoe Montgomery

ChiefExecutiveOfficer

ULIEurope

Gesine Kippenberg

ProjectManager

James A. Mulligan

SeniorEditor

Andrew Lawrence

EditorialSupport

Createinn Design

Graphic Design

About ULI

2

©2014bytheUrbanLandInstitute.

PrintedintheUnitedKingdom.Allrightsreserved.Nopartofthisreportmaybereproducedinanyformorby

anymeans,electronicormechanical,includingphotocopyingandrecording,orbyanyinformationstorageand

retrievalsystem,withoutwrittenpermissionofthepublisher.

ISBN:978-0-87420-338-7

Recommendedbibliographiclisting:

Bienert,Sven.ExtremeWeatherEventsandPropertyValues:AssessingNewInvestmentFrameworksforthe

DecadesAhead.London:UrbanLandInstitute,2014.

About ULI 2

About the author 2

Credits 2

Introduction 4

Executive summary 4

Why climate matters 6

Extreme weather events and their effects on property values 8

Calculation methodology for expected losses from extreme weather events 13

Outlook on the future development of extreme weather events 18

Case study: Increased insurance premiums/annual expected loss 22

Conclusion 24

Appendix: Overview of the present state of research 25

Literature and footnotes 26

Contents

3

Extreme Weather Events and Property Values

Executive summary The escalating threat of extreme weather events• Realestatevaluesarebeingincreasinglythreatenedbyextremeweather

events,suchasstorms,hail,flooding,droughts,tropicalcyclones,

and landslides.

• Theseeventshavefargreaterrelevanceforrealestateinvestorsthanthe

morefrequentlydiscussedeffectsofcreepingclimatechange,suchas

rising mean temperatures.

• Thenumberofextremeweathereventshasdoubledgloballysincethe

1980stoanaverageofover800eventsperyearduringthepastdecade.

• Theoccurrenceofsucheventsisthereforeescalatingandislikelyto

continuetodosountiltheendofthiscentury(andbeyond),asclimate

change becomes more severe.

Their effects on real estate markets and values• Newfinancialuncertaintiescausedbyextremeweatherareaffectingthe

highestandbestuseofrealestatethroughouttheworld.Asrealestate

valuesaccountforabout3.5timestheGDPindevelopedcountries,even

relativelysmallchangesinvalueswillhaveanenormousfinancialimpact

on economies.

• Monetarylossesrelatedtorealestateandinfrastructureandresulting

fromsevereweathereventshavetripledgloballyduringthepastdecade,

withdirectlossesrecordedbyreinsurancecompaniesamountingto

US$150billion(€109.5billion)peryear.Inseverelyaffectedregions,

losseshavereachedupto8percentofGDP.

• Estimatesbasedonthelatestclimatedata,aswellaslossratios

calculatedbythenewly-developedtoolintroducedinthisreport,indicate

thatexpectedmonetarylossesforbuildingsarelikelytodoubleinsome

placesinthenearfuture,affectingbuildinginsurancepremiumsand

totaloccupancycostsasaresult.

Introduction

Today, the real estate industry is increasingly

having to address the causes of climate change, of

which it is a main contributor, through an evolving

range of requirements that include regulatory

controls on CO2 emissions, environmental and

sustainability strategies; and the ‘greening’ of

property investment portfolios and developments.

However, to a large degree, a major consequence

of climate change - extreme weather events - has

yet to be seriously addressed by the industry.

Many real estate investors and associated players

are simply not aware that these events - the

escalation in their occurrence and magnitude of

which is all too evident - pose a rising, compelling

and more immediate threat to property value, and

are therefore overlooking the related risks within

their investment decision-making.

In this report, the threat of extreme weather events

and their impact on real estate and property

value is analysed, and a new tool is introduced to

show how expected losses can be calculated. In

also giving an outlook on the future development

of events, this paper highlights why weather

risks should be considered as a key emerging

driver to future investment strategies. It looks to

stimulate debate by presenting new valuation-

related methodologies and by making clear

recommendations for market participants that

range from the future-proofing of portfolios to the

re-thinking of asset allocation.

Extreme weather events and their effects on property valuesAssessing new investment frameworks for the decades ahead

4

• Moresignificantly,itmightbecomeimpossibletoinsureagainstsevere

fundamentalchangesresultingfromextremeweather-andfrom

intensive events in particular.

• Totallossesfromextremeweathereventsarebeingseriously

underestimatedastrackeddataonlyaccountsfordirectlossesandnot

consequentiallosses(e.g.,areductionintourism)orindirectlosses(e.g.,

reducedturnoverandrent).Thedepreciationofnaturalcapitalisalso

being ignored.

• Agreaterfrequencyofextremeweathereventswillleadtomorepeople

leavingaffectedregions,therebyaffectingpropertyvaluesat

bothendsofthemigratorypath.

An inadequately prepared real estate market• Thefinancialuncertaintiescausedbyextremeweatherarebeing

considerablyunderestimatedbyrealestateinvestors.Untilrecently,

theirportfolioallocationshaverarelytakenintoaccountthescienceof

climate change.

• Thisisprobablyduetotheabsenceofcomprehensiveriskmodels/

tools;alackofready-to-processdatathatcanbeusedinrealestate

forecastingmodels;and,tosomeextent,continueduncertaintyonthe

forecastsforgreenhousegasemissions,andthereforeclimatechange.

• Realestatemarketparticipantsarealsotendingtounderestimaterisks

fromweathereventsthathaveaveryhighpotentialforacutemonetary

lossesbuthaveaverylowprobabilityofoccurring.

Calculating expected losses from extreme weather events • Therisksfromeventsareeithernotbeingintegratedintorealestate

investmentsorvaluations,orareonlybeingaddressedindirectlyby

adjustinginputparameterssuchasrents,yields,orcostsonamore

qualitativebasis.

• Fromarealestateindustryperspective,theriskfromnaturalhazards

shouldbeunderstoodasonlybeingone-sided:downsidewithno

potential upside.

• Thecalculationofannualexpectedlossesasameasureofriskfor

propertyvaluesisderivedfromthehazardoftherespectiveextreme

weatherevent,anempirically-validateddamagefunction(vulnerability),

and a value.

• Throughtheuseofdatafromclimatemodelsandinsurancecompanies

(concerninghistoricaldamages),aswellasfromcost-basedvaluations,

far-reachingconclusionscanbemaderegardingthefuturedevelopment

ofpropertyvaluesinaspecificsituation.

Recommendations for real estate investors• Regardsustainabilityinitiativesasmorethanjustacostdriver,andmake

more intensive efforts to ensure that assets and the respective allocation

oftheseassetsare“future-proofed”.Fulfillingtoday’sregulatory

requirementsisjustthestartingpointonamuchlongerandbroader

routetoasuccessfulsustainabilitystrategy.

• Ensureahigherawarenessofrisksrelatedtoclimatechangesothat,

corporation-wide,theyaretreatedasastrategicissue.

• Evaluatetheannualexpectedlossforpropertiesorportfolioscausedby

futureclimatechangeandextremeweatherevents.

• Bealerttothebroaderindirectandconsequentialeffectsofsevere

weather on real estate.

• Rethinkassetallocationintermsofregions,assetsubclasses,and

micro-locations.Inaddition,re-evaluatecoreandotherassetsin

locationsthatmaycurrentlybetreatedasa“safehaven”

for investments.

• Increasetheadaptationofexistingbuildingstockiftheoutcomeofan

assetanalysisis“hold”.Somepropertiescanbemademoreresilient

throughrelativelyminorretrofits(suchasimprovementstofacades,

roofs,siteinfrastructure,windowsanddoors,connectionsbetween

buildingparts,etc.).

• Developproperrisk-managementtoolsthatfocusonclimatechange,

andintegratethemintoexistingcontrollingfunctionsandprocesses.

• Improveawarenessofpotentialnewregulationofgreenhousegas

emissions as part of stricter climate policies.

• Considermitigatingpotentialsevereweatherimpactsthroughuseof

weatherderivativesorportfoliodiversification.

• Thinkonaregionalorevenproperty-specificlevelbecausenatural

disasters are best treated with regional climate data and models.

• Actnowtoreduceriskfromclimateextremeswithmeasuresthatmight

rangefromincrementalstepstotransformationalchanges.Extreme

weathereventsarealreadyimpactingfinancialreturnsintherealestate

industryandinthefuturewillcontinuetodosoonafargreaterscale.

5


Today, man-made climate change is widely

accepted to be the cause of rising global

temperatures, the melting of the Arctic ice cover,

changing weather patterns and related impacts to

the natural environment and ecosystems.

Despite global political efforts, levels of harmful

emissions are increasing without effective restraint

and, if this remains the case, the acceleration in

climate change is likely to continue unabated.

The looming economic consequences of climate

change will have a significant and growing impact

on the real estate industry, which makes it ever

more important for market participants across

most real estate disciplines to be proactive in

mitigating and adapting to its effects.

In2011and2012thehighest-everaveragetemperatureswererecordedin

Europeandtheworldfortwoconsecutiveyears.1

Proof of considerable global warming: record high temperatures are being reported.

Theconsequencesofclimatechange,andthechangesintheglobal

averagetemperatureassociatedwithit,arefar-reaching.TheArcticice

coverhasdecreasedfromover8millionsquarekilometresin1980tounder

5millionsquarekilometresin2012–2013.2Andthewaterreleasedbythe

meltingiceisoneofthemainreasonswhysealevelshaverisenby20

centimetressince1880.3

Leadingscientistsagreethatmostclimatechangehasbeencausedby

man(anthropogenicclimatechange).4Despiteworldwideefforts,global

greenhousegasemissions(measuredincarbondioxideequivalents)

rose3percentin2012toabout32gigatonsperyear,thehighestlevel

ever measured.5

Arctic Sea Ice Minimum Comparison 1984 - 2012

Source:NASAEarthObservatory

In2013,theconcentrationofgreenhousegasesintheatmosphere

exceededwhatisconsideredthecriticallevelof400partspermillion

(ppm),comparedwith280ppmduringthepre-industrialera.6Againstthis

background,andevenwiththegreatesteffortsbeingmade,itisalmost

impossibleforcontinuingpoliticalattemptstolimitglobalwarmingto2°C

to succeed.7

Atmospheric Concentration of CO2 (EEA) 1750-2010

Source:EEAEurope

Why climate matters

1 MüRe,2013,p.40ff/IPCC,2013,p.4.2 Petersonetal.,2013,p.20/IPCC,2013,p.5.3 Rahmstorf,2007,p.1ff/IPCC,2013,p.6.4 MüRe,2008,p.6/Latif,2009,p.153/Petersonetal.,2013,p.IV/IPCC,2013,p.8f,p.12f./Bouwer,2011,p.39f.

5 MüRe,2013,p.40.6 NationalOceanicandAtmosphericAdministration(NOAA),10.Mai2013/IPCC,2013,p.7.7 Note:“DohaClimateGateway”negotiationswithmandatoryregulationsfrom2020onstillrefertothe2degreeCelsius goalattheDohaclimateconferenceinDecember2012.

6

Climatechangeisalreadycausingmassivechangesinecosystemsandwill

havefurtherseriousconsequencesasglobaltemperaturescontinuetorise.

Thiswillimpactmanyareasofsocietyandtheeconomy,includinghealth,

foodproduction,andurbandevelopment.Measuresmustthereforebe

takentosimultaneouslylimitthedriversofclimatechangewhileadapting

to its effects in all areas of life.

Thispaperconcentratesonarealestate-basedeconomicapproachto

globalwarmingandpursuesthefollowingquestions:

• Whatarethefinancialimplicationsforrealestateassetsofanincreasing

numberofextremeweatherevents?

• Howmightthefrequencyofextremeweathereventschange?

• Whyshouldtherealestateindustryintensivelyaddressclimate

changenow?

Climate change massively reduces real estate related income potential in the form of ground rent.

Realestateisboundbylocation,andrealestatevaluesarealwaysbased

on the highest and best possible use of a location. The protection of

real estate against the hazards of natural disaster and the loss of use is

thereforeclearlyvital-whetheritissafeguardingtheincome-generation

ofagriculturalandforestland(andthequalityoflife),theinvestmentand

occupancycredentialsofcommercialandresidentialbuildingsorthe

durabilityofinfrastructurefacilities.

Aninitial,purelyqualitativeanalysisthatfocusesonthevariousdrivers

forrealestatemarketvalue-assuggestedbythevaluationtechnique

“comparisonapproach”-showsthatmanyfeaturesofasiterelevantfor

valuationaredirectlylinkedtoenvironmentalconditions,andaretherefore

alsoexposedtotherisksofclimatechange.Thesefeaturesinclude:

• Macro-andmicro-locations-climaticconditions,especiallyillumination,

wind,emissions(noise,smoke,dust),andrainfall;and

• Soilconditions-surfaceformation,naturalcover,bearingcapacity,

groundwaterconditions,mudslideareas,andexposuretorisks(flooding,

avalanches,storms,hurricanes,etc.).

Andsomemorerecentimpactsofclimatechangeonenvironmental

conditionsareonlygraduallyemerging.Forexample,NorthernRussia’s

regions are seeing an increasing impact from the thawing of the

permafrost,withthecoolertemperaturespreventingtheairfromabsorbing

thewatervapourgenerated;asaresult,theamountofmoistureinthesoil

isconstantlyincreasing,formingsmalllakes.Thisishavingasubstantial

impactonregionalecosystems,aswellasbuildingsandinfrastructure,

which in some places no longer stand on solid ground.

Thelossofthepotentialuseoftherealestateautomaticallyleadstolost

value,whichhasnegativeconsequencesforaneconomyasawhole.In

developedeconomies,thevalueofpropertyamountstoanaverageof3.5

timesacountry’sGDP.8Thus,evensmallchangesinvaluecanleadtolarge

monetarydamages.Moreover,inrealestatevaluation,presentvalueis

regularlyconsideredinassessingfuturepotentialbenefits.Therefore,even

relativelymoderatereductionsinvaluecanleadtobiglossesinannual

expectedreturns.

Due to the wider economic significance of property values, even relatively small drops in value will constitute massive economic losses.

Thisandotherimpactsofclimatechangearelikelytocontinueto

predominateandresultinmassiveadjustmentsintherealestate

industryuntilanewbalanceisstruck.Ontheotherhand,afewinthe

realestateindustrycouldactuallybenefitfromclimatechange.For

instance,agriculturewillbefeasibleinregionspreviouslyconsideredtoo

cold,allowing,forexample,vineyardstomovefarthernorth;likewise,

warmertemperaturesatmorenorthernlatitudeswillraisepropertyprices

as climate refugees migrate and encourage more tourists to visit high

mountain areas.

The profitability of real estate will be increasingly influenced by climate protection regulations.

However,itwouldbemisleadingtoportraytherealestateindustryonlyin

termsofitsvulnerabilitytoclimatechangebecause,throughdevelopment,

itisoneoftheprimarycontributorstotheproblem;withbuildings

accountingfor30to40percentofallenergyuse,theindustryisoneof

themainsourcesofCO2 emissions.9Asaresult,amultitudeofpolitical

initiativestoreduceemissionsarecurrentlyaimedattheconstructionand

realestatesectors-andtheintroductionofinitiativeswillcontinue.10 The

industrywillalsobeaffectedbymeasuresrequiredtoadapttoclimate

changeandrelatedlegalframeworks.Thoseimpactsarenotaddressedin

this report.

Critically,duetoitsvulnerability,11therealestateindustrymusturgently

studythedriversanddynamicsofclimatechangesoitcanadapt

proactivelytothechangesorcontributetotheirmitigation.Itisachallenge

thataffectsandmustbeaddressedbyanumberofsubdisciplineswithin

theindustry,includingrealestatevaluation,riskmanagement,investment,

andprojectdevelopment/construction.

8 Brandes,2013,p.9:EstimatedValueofInsuredCoastalPropertiesamountintheUnitedStatestoUS$27.000billionin2012.9 WBCSD,2009,p.6.10 Bosteelsetal.,2013,p.6.11 Guyattetal.,2011,p.15:Realestateisverysensitivetoclimateimpacts./Leurigetal.,2013,pp.5,7

7


Extreme weather events caused by climate change

- including storms, hail, flooding, heatwaves, and

forest fires - often lead to severe damage and must

be differentiated from long-term change, such as

rising mean temperatures.

The annual average number of extreme weather

events has more than doubled globally since 1980.

The total global damage caused by extreme

weather - mainly to property and infrastructure -

is rising dramatically and now exceeds US$150

billion (€109.5 billion) per year. Furthermore, these

losses, which are those registered by reinsurance

companies, by no means constitute all losses

related to real estate.

For example: first estimates of forests lost to more

frequent fires in Russia and the United States

top €600 billion in present values; and there is a

corresponding impact on the income-generating

potential of relevant property. Similar calculations

could be made for other extreme weather events,

regions, and property types.

The real estate industry has tended to be reactive

and is only now taking its first steps towards

preparing for foreseeable climate changes. To date,

awareness has not been strong, partly because few

quantitative studies on real estate in the context of

extreme weather events have been undertaken.

Theimpactofclimatechangeonpropertyanditsvalueiscomplex.In

thispaper’sintroductionweaddressedtheimpactsoflong-termclimate

change,suchasrisingmeantemperatures,howeverthisdoesnotinclude

themoreimmediateeffectsofextremeweatherevents,whichcanleadto

significantlossesinaveryshortperiod.12Climatechangeisalsoaltering

thefrequency,intensity,spatialimpact,duration,andtimingofevents;

andinsomeinstancestheshiftsareunprecedented.Inparticular,extreme

weatherevents-naturaldisastersthatincludestorms,hail,flooding,

heatwaves,droughtsandforestfires–arehavingasignificanteffecton

thosesectorsthatarecloselylinkedtoclimate,suchasinfrastructure,

water,agriculture,forestry,andtourism,aswellasrealestateingeneral

(seefigure1).13

Thisstudytakesanin-depthlookatextremeweathereventsandtheir

impactonpropertyvalues.Forthemarkettheseevents–whichonly

representadownsiderisk-canresultinrealestateinvestments14:

• Beingsubjecttopricerisesduetoincreasedinsurancepremiums

oralteredconstructionmethods-knownasadaptationcosts-or

deterioratingreturnsoncapital;or

• Losingvalueduetolimitedusability(wherethehighestandbestuse

maynolongerbefeasible);or

• Beingsubjecttoexpensivedamagesduetouninsuredrisks,andhence

deteriorating returns.

Therefore,therealestateindustryisinevitablyexposedtothepotentialloss

ofpropertyreturnsinlocationsthatarevulnerabletoextremeweather.15

Hurricane Katrina property damage

Source:FreeImages,PalmerCook

Extreme weather events and their effects on property values

12 WorldBank,2013,p.94:Reducedpropertyvalues.13 Guyattetal.,2011,p.61/Cruzetal.,2007,p.492:Effectsontourismmightbemassive./Lamond,2009.14 ULI,2013,p.14ff:Recommendation16:Accuratelypriceclimateriskintopropertyvalueandinsurance.15 Guyattetal.,2011,p.58.

8

Figure 1. Effects of climate change on property values

Source:IREBSUniversityofRegensburg

According to reinsurance statistics, total losses from extreme weather events already exceed €109.5 billion per year.

Theeconomicimplicationsofextremeweatherbecomeevidentifone

considersthatgloballossescausedbyweather-relatednaturaldisasters

in2011and2012exceededUS$150billion(€109.5billion)inbothyears,

rankingthemamongthefivemostcostlyyearssince1980.16However,

fromabroaderperspective,thesetotallosses(whicharefrequentlycited

inreinsurancestatistics)are,infact,farbelowtheactualfinancial

losses suffered.

Toelaborate,financiallossescanbebrokendownintofourcategories:

• Directlossesinclude17alltypesoftangibleassets(privatedwellings,and

agricultural,commercialandindustrialbuildingsandfacilities);

infrastructure(e.g.,transportfacilitiessuchasroads,bridges,andports;

energyandwatersupplylines;andtelecommunicationsequipment);and

publicfacilities(e.g.,hospitalsandschools).

• Indirectlossesmayincludehighertransportcosts,lossofjobs,and

lossofincome(bothrentandrevenuelostduetobusiness

interruption).

• Consequentiallosses-or“secondarycosts”-arisethrough

repercussions such as declining tourist numbers or lower direct

investments,whichreduceeconomicactivity,andthuslowerGDP.

• Lossesrelatedtonaturalcapitalincludedamagetoecosystemsand

thedepreciationofnaturalresources(adverseecologicalimpacts).

Climate AspectCommercial and

Residential Real EstateForestry Agriculture Infrastructure

Rise in temperature

Reduced ground rent (lower potential revenue, in the case of regional population changes; also, increased need for cooling, and thus higher operating costs)

Reduced ground rent (in the case of increase in forest fires, pest infestation, extinction of species)

Reduced ground rent (in the case of increasing drought, pest infestation)

Increased wear on installations; unstable ground

Water scarcity Decline in attractiveness of a region/decline in ground rent; higher costs for water supply and treatment

Reduced revenues from forestry/increased danger of forest fires

Reduced harvests; increased costs for irrigation

Decline in bearing capacity of soil

Rising sea level Reduced settlement area in coastal regions

Reduced agricultural land area/loss of potential revenues

Danger to port facilities

Increase in extreme weather events

1. Direct loss (e.g., hail damage to buildings)

2. Indirect loss (e.g., through gaps in production or rent after hurricanes)

3. Consequential loss (e.g., declining number of tourists in flood areas, rising insurance premiums)

1. Direct loss

2. Consequential loss

3. Depreciation of natural capital (permanent damage to ecosystems, extinction of species)

1. Direct loss

2. Consequential loss

3. Depreciation of natural capital

1. Direct loss

2. Indirect loss (infrastructure damages due to extremes in temperature, precipitation/ flooding/overload of urban drainage systems/storm surges, which can lead to damage to roads, rail, airports, and ports; electricity transmission infrastructure is also vulnerable)

Increased regulation

Higher construction costs and running costs; higher costs, particularly in the case of carbon taxation

Higher construction costs and running costs

Increased adaptation costs due to climate change

Higher adaptation costs to protect properties and to make buildings energy - and resource efficient

Higher adaptation costs Higher adaptation costs Higher adaptation costs

16 MüRe,2013,p.53.17 Kronetal.,2012,p.542:Directlossesareimmediatelyvisibleandcountable(lossofhomes,householdproperty,schools, vehicles,machinery,livestock,etc.).

9


However,itisonlydirectlossesthatareeffectivelytrackedinloss

estimates–alltheothercategories,whichalsoincludeadaptationcosts

incurredforprotectingbuildingsfromextremeweatherevents,andthe

monetisationofpersonalinjuryandthedamagetohistoricstructures

and cultural heritage18,arenotincludedoradequatelyincorporatedinto

estimates.19Yetalltheseaspectsareofmajorimportanceforrealestate

marketsastheycanbedirectlylinkedtoincomeandvalues.

Truedamagecostsarethereforemuchhigherthanestimates,which

highlightstheneedfortherealestateindustrytowidenitsperspective

beyondjustdirectlosses.

Official statistics dramatically underestimate real estate-related damage.

InthecaseofforestfiresintheUnitedStates,forexample,thedamage

tothenaturalcapital-i.e.,treesandotherplants-isnotincorporatedin

damagedatacollectedbyreinsurancecompanies.However,intermsofthe

long-termincome-generatingpotentialfromforestryandtheattractiveness

oftheaffectedarea,thisdamageisfarmorerelevantthanthelossofany

buildingstofire.

Examiningthisparticularexampleinmoredetail,rainfallintheUnited

Statesin2012wasmuchlowerthantheannualaveragesfor1961to1990,

andtheyearwasalsomarkedbyalarge-scaleheatwaveandaperiod

ofseveredrought.Thisresultedinasmuchasa40percentreductionin

average agricultural production20andaconsequentdeclineinthegross

incomegeneratedbytheaffectedplotsthroughthereductionofground

rent.Inwoodedareas,thedroughtwasaccompaniedbyforestfiresthat

destroyed3.7millionhectares,thethirdhighestfiguresincerecordsbegan.

Heat wave map via NASA June 17/24, 2012

Source:NASA

Ananalysisoflong-termU.S.averagesinthepre-andpost-climatechange

situationrevealsinterestingdetails.Acomparisonof1970-1986and1987-

2003showsthatduringthelatterperiod,whichwasseverelyaffectedby

climatechange,fourtimesasmanyforestfiresoccurredandsixtimes

asmuchforestlandfellvictimtoflames,andtheforestfireseasonlasted

onaverage50percentlonger.Itcanbeestimatedthatover330million

cubicmetresofwoodwasdestroyedin2012,intheprocesslowering

bothresourceproductivityandlandvalues.Thisisirrespectiveofdamage

toforestecosystems,thedestructionofbuildingsandinfrastructure,

agriculturallosses,orthelong-termdeclineintheattractivenessofthe

affected regions.

Forest fires near Chalkidiki, Greece 2006

Source:Shutterstock/VerveridisVasilis

Atanaveragepriceof€85percubicmetre,thiscorrespondstomorethan

€28billionburnedandthereforewastedresources,andthisisdataforjust

oneyear,onecountry,andthetreeinventoryofforests.

Comparedwiththehistoricalaverageforthepre-climatechangeperiod,

this represents an increased loss of about €23billionperannumdueto

thesharpriseinforestlandlosttofire.Translatedintermsofanincome

stream,anddiscountedataninterestrateof5.0percent,thiswould

represent a loss of forestland of over €460billioninpresentvalues21 due

toforestfiresintheUnitedStates.

Heatcombinedwitharidityisalsoanincreasingprobleminotherpartsof

theworld.Russia’ssouthernandwesternregionslikewiseexperienced

extremeforestfiresin2012,toppingrecordhighsthathadbeensetas

recentlyas2010,atrendwhichoverthepast10yearshasseentheareain

Russiaaffectedbyforestfiresgrowfrom750,000tomorethan1.75million

hectares per annum.22 If the same valuation method is applied as for the

UnitedStates,Russianforestfireshaveincurredalossinpresentvalueof

more than €150billion.

21 Note:Theassumptionofaperpetuityservesonlytoillustratetheextentofthesituationanddoesnotclaimtobe scientificallyconclusiveastothefacts.22 MüRe,2010,p.33,p.37.

18 IPCC,2013,p.270.19 Kronetal.,2012,p.535f,p.542f.20 MüRe,2013,p.42

10

More frequent fires have destroyed over €600 billion in present values from forests in the United States and Russia alone - and have reduced land values accordingly.

Inadifferent“extreme”,Thailandexperienceditsworstfloodingin50

yearsin2011,causingestimatedeconomiclossesof€40billion.Most

ofthelossescamefrompropertydamageandthelossofgroundrent,

withcommercialandindustrialareas,roads,otherinfrastructureand

agriculturebeingparticularlyhardhit.Twomillionpeoplewereforcedfrom

theirhomes,1millionhousesweredestroyedorseverelydamaged,10

millionfarmanimalswereevacuatedorkilled,and1.6millionhectaresof

agriculturalland-10percentofthecountry’stotal-waslargelydestroyed.

About25percentofthetotalharvestfortheyear-inparticularrice-waslost.

Thailand floods 2011

Source:WikimediaCommons

Theseexamplesindicatethehugevolumesoflong-termincome-generating

realestatepotentialbeingdestroyedbyextremeweatherevents.Yetno

structuredrecordofthisdamageexists,norisitincorporatedininsurance

statistics.Whatismore,theaffectedregionswillbehitbyhumanmigration

flows23 which will further reduce residential and commercial real estate values.

The number of extreme weather events is increasing considerably. A total of over 800 events occur on a 10-year average, compared with only 400 in the 1980s.

Countlessotherexamplesexistoftheincreasingfrequencyofextreme

weatherevents-floodsaftertorrentialrainsinChina,thehighest

floodwatersinNewYorkCityin100years,cyclonesanddroughtin

Australia,andfloodinginlargeareasofGermany,Austria,andtheir

neighbours-allevidenceofongoingclimatechangeleadingtoaverifiably

significantincreaseinextremeweather.24Globally,840weather-related

naturaldisastersoccurredin201225,andstudiesbyMunichREhaveshown

thatthenumberofdisastershasmorethandoubledgloballybetween1980

and2012(seefigure2).26

23 Cruzetal.,2007,p.488.24 IPCC,2012,p.7:Inregardtothechangeswhichhaveoccurredsofar,theIPCChasdeterminedthat“atleastmedium confidencehasbeenstatedforanoveralldecreaseinthenumberofcolddaysandnightsandanoverallincreaseinthe numberofwarmdaysandnightsattheglobalscale,lengthornumberofwarmspellsorheatwaveshasincreased, PolewardshiftinthemainNorthernandSouthernHemisphereextratropicalstormtracks,therehasbeenanincreasein extremecoastalhighwaterrelatedtoincreasesinmeansealevel.”25 GDV,2011,p.1/MüRe,2013,p.52/Mechleretal.,2010,p.611ff.26 MüRe,2013,p.3ff.

Geophysical events

(Earthquake,tsunami,volcaniceruption)

Meterological events

(Storm)

Hydrological events

(Flood,massmovement)

Climatological events

(Extremetemperature,drought,forestfire)

Figure 2 : Development of the number of natural disasters throughout the world from 1980 to 2012

Source:MünchenerRückversicherungs-Gesellschaft,GeoRisksResearch,NatCatSERVICE-AsatJanuary2013

11


Flooding in Greater Bangkok 2011

Source:WikimediaCommons

Asimilartrendisevidentinrespecttothetotaldamagesresultingfrom

theseevents,whichhasmorethantripledfrom1980to2012,from

US$50billiontooverUS$150billionperyear(€36.5billionto€109.5

billion).27Furthermore,a2012reportbytheIntergovernmentalPanelon

ClimateChange(IPCC)concludedthatinareasmostaffectedbyextreme

weather,averagecostsamountedtoupto8percentofGDP.28From

amacroeconomicviewpointregardingrealestate,thequestionofthe

proportion of losses insured29islargelysecondarybecausepropertyprices

will increase regardless of rising premiums or even as a result of the claim

itself.Whatdoesrequireexplanation,however,iswhylossesinproperty

value are higher in percentage than the increase in severe weather events.

Increased settlement of high-risk areas, combined with socio-economic growth, partly accounts for the higher real estate losses.

Therearetwomainreasons.Firstly,thelossescausedbyclimatechange

arebeingexacerbatedbyman-madechangesintheaffectedareas,with

increasedlossesarisingfromdensersettlement,increasedurbanisation

ofhigh-riskareas30(e.g.,theFloridacoast),higherconstructioncostsand

quality,and,insomecases,theincreaseduseofmaterialssusceptible

todamage,suchasfacadesusingthermalprotectionmaterialsinareas

prevalent to hailstorms.31Secondly,thelossesarenotadjustedinrelation

toglobalsocio-economicgrowth;initialstudiesadjustingforthisshow

“only”alinearincreaseintotallossesof€1.7billionperyearoverthepast

30years.32

Flood damage

Source:FreeImages,NurettinKaya

There is a lack of quantitative research regarding extreme weather events and the real estate industry.

Theamountofliteratureonsocio-economicdevelopmentinconnection

withextremeweathereventsisgrowingrapidly.33However,relatively

fewquantitativeresearchresultsexist34 that cover the interface between

naturalhazardsandrealestate,duemainlytothefactthatonlyinthepast

fewyearshavethenumberofeventsandvolumeofdamageincreased

significantly.TheIPCCfindsthat“[o]nlyafewmodelshaveaimedat

representingextremesinarisk-basedframeworkinordertoassess

the potential impacts of events and their probabilities using a stochastic

approach,whichisdesirablegiventhefactthatextremeeventsarenon-

normallydistributedandthetailsofthedistributionmatter.”35Otherauthors

have also stressed the challenges related to this factor.36

Thefollowingsectiongoesintogreaterdetailinthiscontextbydescribing

aninnovativecontributiontoresearchimplementedaspartoftheImmoRisk

project.37Specifically,itpresentsanapproachtocalculateannual

expectedlosses(AELs)duetoextremeweatherevents.Thisapproach,

basedonfuture-orientedclimatemodels,canbeusedtodeterminean

approximateincreaseinexpectedlosses.Thisallowsconclusionstobe

derivedregardingthefutureperformanceofaproperty(orportfolio)and,

ifnecessary,adjustmentoftheallocationofassetsintermsofselectionof

regions,propertyuses,etc.

27 MüRe,2013,p.52.28 IPCC,2012,p.270/Guyattetal.,2011,p.14:CostofphysicalclimatechangeimpactcouldreachUS$180billionperyear by2030(€131.4billionpa)29 Mills,2005,p.1040f/Mills,2012,p.1424f/Mechleretal.,2010,p.611ff.30 Howelletal.,2013,p.46:Greaterconcentrationofpropertiesinriskzones.31 Naumannetal.,2009,p.228/MüRe,2008,p.4.32 MüRe,2013,p.58.

33 IPCC,2012,p.265.34 Note:SeetheAppendixforanextendedoverviewofthecurrentstateofresearch.35 IPCC,2012,p.266.36 Wilby,2007,p.42/Guyattetal.,2011,p.1ff:Traditionalassetallocationdoesnotaccountforclimatechange.Thereisa smallamountofresearchwhichfocusesontheinvestmentimplicationsofclimatechange./Brandes,2013,p.12ff:The riseofmodelingandfutureriskscenarios.37 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.

12

Calculation methodology for expected losses from extreme weather events

Fortherealestateindustry,questionshavearisenbasedontherisksof

climatechangeingeneralandextremeweathereventsspecifically.These

include:

• Dynamicsregardingpropertyvalues:Whatimpactsonthevaluesof

existinginvestmentscanbeexpectedinthefuture?

• Investmentanddivestmentdecisions:Whichregionswillbepositivelyor

negativelyaffectedbycontinuingclimatechange?Whatconclusionscan

bedrawnforfutureinvestmentdecisions?

• Propertytypes/sectors:Arecertaintypesofpropertyusemoreaffected

byextremeweatherthanothers?

• Portfoliomanagement:Howcaninvestmentsbeallocatedtoachieve

adiversifiedpropertyportfolio,therebyprotectingagainstpossible

increasedclimate-relatedrisks?Whatisthebestallocationof

investmenttorealestatewithinabroadermulti-assetportfoliowhen

climaterisksaretakenintoaccount?

• Externalities:Whatcantherealestateindustrycontributetowards

internalisingnegativeexternalities,38andtowhatextentcanirreversible

damagesbeavoided?

Fromaninvestor’sviewpoint,thepotentialimpactofextremeweatheron

propertyvaluesisprobablythemostfundamentalconcern,soitwillbe

addressedherefirst.(Thefuturedevelopmentofextremeweatherevents

willbediscussedinthefollowingchapter,whichwillhelptobuildagreater

understandingoflikelychanges.39)

Toassessthepossibleimpactonpropertyvalues,thisstudyintroduces

arisk-basedresearchapproach,usingabottom-upmethodologythat

quantifiestheriskintheformofexpectedlossesthroughobservationofa

singleproperty.

The risks from extreme weather events are either

not being integrated into real estate investments or

valuations, or are only being addressed indirectly by

adjusting input parameters such as rents, yields, or

costs on a more qualitative basis. Likewise, despite

its relevance, climate data is also being excluded.

From a real estate industry perspective, the risk

from natural hazards should be understood as being

only one-sided: downside with no potential upside.

In general, the risk is measured by the likelihood of

the occurrence of a specific monetary loss within a

certain time frame.

The calculation of annual expected losses (AELs)

through extreme weather events as a measure

of risk for property values is derived from (1) the

hazard of the respective extreme weather event,

(2) an empirically validated damage function

(vulnerability), and (3) a value. The modeling

is extremely complex, and the requirements

concerning the quality and quantity of data are very

high.

Through the use of data from climate models

and insurance companies (concerning historical

damages), as well as from cost-based valuations,

far-reaching conclusions can be made regarding the

future development of property values in a specific

situation.

The core task in the risk analysis of climate

impacts is to derive probability distributions for the

occurrence of specific extreme weather events, and

to determine the damage functions concerning the

extent to which the respective property is affected.

38 Note:Anexternaleffectis,forexample,airpollutioncausedbyenergyconsumptionthataffectsathirdparty(e.g.,the societyingeneral)thatwasnotresponsibleforthatemission.Theexternalityis“uncompensated”forthepolluterbecause thecostwillbebornebyothersunlesstheexternalityis“internalised”throughregulation(e.g.,taxes).

39 ULI,2013,p.17:Marketvaluedriveslanduse.

13


Performance with regard to potential capital losses is only the first issue when natural hazards are considered in real estate decision making.

Todetermineadeclineinvaluethatmayonlyoccurinthefuture,it

isessentialtoexploretheinteractionamongparameters,structural

characteristics,andotherfactorsthataffectthepropertyinquestionin

the form of causal chains.40Riskswithalowprobabilityofoccurrenceand

highlosspotentialtendtobeunderestimatedinmostanalyses41and,in

practice,investmentdecisionsareusuallymadeonthebasisofhistorical

dataandcorrespondingtimeseries(e.g.,rents,vacancies,etc.).42 This

observationhasgreatrelevanceforassessingextremeweatherevents

expectedinthefuture,andfortheimplicationsofthoseevents,because

thereisstrongevidencethattherelevanceoflow-probabilityrisksisstill

underestimated-notleastbyprofessionalmarketparticipants,suchas

propertyinsurersandinvestors(Lansch,2006).

Investment decisions today are often made solely on the basis of historical data series.

Naturalhazardsarepartoftheperformanceriskwhichtakeseffectonthe

supplyside43,andinmostmarketstheseriskscanbecoveredbynatural

hazard insurance. The resulting annual insurance premiums are included

intheoperatingcostsoftheproperty,andcangenerallybechargedtothe

tenantasnon-allocableoperatingcosts.Despitethefactthattheycanbe

apportioned,thesecostsneverthelessdohaveanimpactonvalueinthe

mediumtolongtermfromtheowner’sperspective,becauserisingutilitybills,

asawiderexample,mayincreasethetotaloccupancycostsintheviewofthe

tenantandultimatelylimitaproperty’spotentialtogenerateahighernetrent.

Againstthisbackdrop,fromtheperspectiveoftherealestateindustry,

extremeweathereventsconstitutethedownsideriskofamonetary

loss occurring in the future.44ThisExpectedLoss(EL)isderivedfroma

combinationoftheprobabilityofacertainextremeweathereventoccurring

(tobeunderstoodinthesenseofenvironmentalscienceasthereciprocal

ofacertainreturnperiod),andtheamountofdamageitwouldcauseifit

didoccur.Thisfundamentalrelationshipisillustratedinfigure3.

Thus,thecoretasksinvolvedintheriskassessment 45 of climate change

impactsintherealestateindustryare(1)derivingprobabilitydistributions

fortheoccurrenceofcertainextremeweatherevents(hazard),and,

similarly,(2)determiningreliabledamagefunctions(vulnerability 46)

regardingtheimpactonaspecificproperty.Thesetwoareasrepresent

thekeyelementsoftheriskmodel.47Inregardtotheimpact,themodel

generallyworkswithrelativeshares,inpercentage(2a,relativelosses)ofa

totalvalue(2b,absolutelosses).Therefore,(3)itisalsoimportanttoderive

cost-basedpropertyvalues(exposure).Thesearedeterminedaccording

totheinsurablevalue,48 in compliance with the procedures in regard to

insuranceofproperty,usingthereplacement-costapproach.49

The hazard, vulnerability, and cost-based value elements determine the expected loss.

Hence,forapropertyg,atalocationr,atapointintimet,theriskcan

bedescribedbythefollowingfunctionalrelationshipamonghazard,

vulnerability,and(cost-based)value:

Risk (r,g,t) = Hazard (r,t) * Vulnerability (g,t) * Cost Value (g)

40 IPCC,2013,p.10:climatefeedbacks.41 Osbaldistonetal.,2002,p.46/Ozdemir,2012,p.1ff.42 Wilby,2007,p.42:“Aboveall,thereisanurgentneedtotranslateawarenessofclimatechangeimpactsintotangible adaptationmeasuresatalllevelsofgovernance.”/Guyattetal.,2011,p.1:Standardapproachesrelyheavilyonhistorical dataanddonottacklefundamentalshifts.43 Lechelt,2001,p.28.44 Büchele,2006,p.485/Kaplan,Garrick,1997,p.93.

45 UNDHA,1992,p.64:“Riskareexpectedlosses(of...propertydamaged...)duetoaparticularhazardforagivenarea andreferenceperiod.Basedonmathematicalcalculations,riskistheproductofhazardandvulnerability.”45 ULI,2013,p.17:Marketvaluedriveslanduse.46 Thywissen,2006,p.36/UNDHA,1992,p.84:“Degreeofloss(from0%to100%)resultingfromapotentiallydamaging phenomenon.”47 Heneka,2006,p.722/Büchele,2006,p.493.48 InsurablevalueaccordingtoInternationalValuationStandards(IVS):Thevalueofapropertyprovidedbydefinitions containedinaninsurancecontractorpolicy.49 EuropeanValuationStandards(EVS),2012..

ClimateChange

+--

Risk Assessmentfor the exposure

Annual expected loss

Location Specific

Hazard - function

Property Specific

Vulnerability

Cost value

Extreme WeatherEvents

• Climatology• Meteorology• Hydrology• Insurance Data• Real Estate Data

Figure 3: Real estate risk assessment approach for extreme weather events

Source:IRE|BS,UniversityofRegensburgwithreferencetoBienert/Hirsch/Braun,2013,p.1ff:ImmoRiskToolforBMVBS.

14

HazardfunctionsoriginatefromtheresultsofGlobalClimateModels

(GCMs),whichgenerallyhavenodirectrelationtotherealestateindustry.

Climatemodelsareabletoforecastfuturechangesintheprobabilityof

occurrence,theintensity,andthetypicaldurationofextremeweather

events-forexample,ofaparticularwindspeedbeingreachedorvolume

of hail falling.50Inordertogetalocation-specifichazardfunction,GCMs

mustbedownscaledtoaregionallevel(aRegionalClimateModelor

RCM),sometimestakingintoaccounttheveryspecificcharacteristics

of the surroundings.51Thealreadyapparentincreaseintheprobabilityof

occurrenceofextremeweathereventscanbederivedvisuallywiththehelp

offigure4,whichshowsrealclimatedataandpredictions.

Figure 4: Sample wind hazard function for a location in Northwest Germany, present vs. future

Source:IRE|BS,UniversityofRegensburgwithreferencetoBienert/Hirsch/Braun,

2013,p.1ff:ImmoRiskToolforBMVBS/seealsoHofherretal.,2010,p.105ff.

Inthecontextofvulnerabilityanalyses,functionalrelationshipsbetween

theintensityoftheextremeweathereventandtheresultingmonetary

lossesmustbeobtainedforeveryevent.Thelossfunctionthendescribes

therelationshipthatisdetermined,basedontheanalysisofalargenumber

of historical losses. Loss functions thus represent the connection between

theintensityofaneventandtheresultinglossinthevalueobserved

(vulnerabilityfunction).52Forexample,experienceindicatesthatacertain

windspeedcanmeanthat30percentofaparticulartypeofbuildingcould

bedestroyed.Thisisgenerallydeterminedbyempirically-basedevidence

fromhistoricalinsurancedataorbyanexpert’sopinion.53Oncerelative

lossesareestablished,monetarylossesonlyariseincombinationwiththe

valueofaspecificproperty.

Figure 5: Loss function which correlates intensity with storm damage.

Source:IRE|BS,UniversityofRegensburgwithreferencetoHeneka,2006,p.724

/seealsoUnanwaetal.,2000,p.146.

Thedeterminationoftheexpectedlossresultingfromtheinteraction

betweenindividualelementsisillustratedbyfigure6.

Figure 6: Integrative calculation of the risk of natural hazards in the case of uncertainty on all levels of observation.

Source:Bienert/Hirsch/Braun,2013,p.1ff:ImmoRiskToolforBMVBSwith

referencetowww.cedim.deandHenekaetal.

Closerinspectionrevealsthatan(expected)totallossmustalwaysbe

relatedtoonespecifictimeinterval(e.g.,oneyear)andincludeallpossible

riskscenariosofaparticularextremeweatherphenomenon(e.g.,wind)

-thatis,itmustbeweightedaccordingtoitsindividualprobabilityof

occurrence.

50 IPCC,2013,p.10,14f/Khanetal.,2009:Stormriskfunctions/Leckebuschetal.,2007,p.165ff/Mohretal.,2011/ Waldvogeletal.,1978,p.1680ff.51 Fleischbeinetal.,2006,p.79f/Linkeetal.,2010,p.1ff/Orlowskyetal.,2008,p.209/Rehmetal.,2009,p.290f: Modelforwindeffectsofburningstructures/Rockeletal.,2007,p.267f/Sauer,2010/Thiekenatal.,2006,p.485ff: Approachesforlarge-scaleriskassessments.

52 Cortietal.,2009,p.1739f/Cortietal.,2011,p.3335f/Granger,2003,p.183/Pinelloetal.,2004,p.1685f/Sparkset al.,1994,p.145ff.53 Golzetal.,2011,p.1f:Approachestoderivevulnerabilityfunctions./Hohl,2001,p.73f:Damagefunctionforhail./ICE, 2001:Source-Pathway-Receptor-Consequence-Concept/Jainetal.,2009/Jainetal.,2010/Kafali,2011/Klawaetal., 2003,p.725f/Matson,1980,p.1107/Naumannetal.,2009a,p.249f/Naumannetal.,2009b:Flooddamagefunctions. /Naumannetal.,2011/Penning-Rowselletal.,2005/Schanze,2009,p.3ff.

Dam

age

[S]

1

0G G crit tot

Intensity of extreme weather [G]

g(v)

Monetary Loss in Euro

Intensity of hazard (for ex. wind speed in m/s)

Probability in %

Risk-function Cost Value

Vulnerability-function Hazard-function

Damage Ratio in %

1971-2000 2071-2100

Annual exceedance probability (in %) 10-1 10-2

20 10 -10

25

30

35

40

45

Win

d sp

eed

(in m

/S)

15


Inthiscontext,itwouldbeexpedienttocalculateanannualexpectedloss

(AEL)-i.e.,todefineoneyearasarelevanttimeinterval.Asthehazard

cantakeonnotonlysingle,discretecharacteristics-forexample,“in

4%ofthecasesthewindspeedreaches8metres/second”-butalso

constitutepartofacontinualdistribution,thehazardfunctionmustbe

integrated:54

ƒ =probabilitydensityfunctionofthehazard(hazardfunction)

S = loss function

W =valueofbuildingproperty

x =intensity/formofhazard(e.g.,windforceorwaterdepth)

xmin =lowerintegrationlimit,abovewhichdamageistobeexpected

p =probabilityofreoccurrence

AEL(j) =annualexpectedloss(inaspecificextremeweatherevent,j)55

To obtain a complete picture of the AELofaparticularproperty,allpartial

resultsofthedifferentextremeweatherevents(e.g.,wind,hail,flood,etc.)

are added up:

with AEL=annualexpectedloss(sum),andAEL(j)=annualexpectedloss

(inaspecificextremeweatherevent,j).

Fromarealestatevaluationperspective,theannualexpectedlosscould

nowbesubjecttopresentvalueconsiderationsbyimplementingarisk-

adequatecaprate(i):

with PV=presentvalue(oftherisk),andAEL=annualexpectedloss

(here,identicalforallyears)withi= cap rate.

Toaccountforthemostrealisticcaseinwhich(atleast)thehazard

changes,itisusefultodifferentiatebetweendifferentAELassumptions,

anddifferenttimeframes.Incontrasttoperpetuity,itwouldthenmake

sensetodothecalculationwithonereversionaryannuityfordifferent

annualexpectedlosses:

with PV=presentvalue(ofallexpectedlosses)representingtherisk,and

AEL=annualexpectedloss(int)withd= discount rate.

Thisvaluecouldalsobeusedaspartofapropertyvaluation,andinrisk

managementandportfoliomanagement.Asclimateriskshavebeen

implicitlytakenintoaccountintheinputparametersofvaluationstodate,

caremustbetakentoavoidredundancies;torefertothetotalpresent

valueasadeductionwouldthereforeprobablynotbeconstructive.On

theotherhand,itwouldmakesensetotakethepresentvalueofafuture

increaseintheannualexpectedlossescomparedtotheinitialvalue-such

astheaverageofthepreviousperiods,forexample.

with PV=presentvalue(ofallexpectedlossesthatexceedthehistorical

benchmark)representingtherisk,andAEL=annualexpectedloss(int)with d= discount rate.

The meaningful aggregation of hazard, vulnerability, and cost data elements in an annual expected loss as a present value involves a great deal of computing time and requires an extensive database.

Itshouldbenotedthat“cost”-andthereforealsoAEL-donot

automaticallyequal“value”andthisiswhypropertyvalueisoften

calculated using hedonic pricing models. These models attempt to

separatethegivenpropertypricesintotheirvaluedriversbyusing

multipleregressionmodels.Untilnow,however,researchershavemainly

focusedontheinfluenceofinfrastructure,populationdensity,and

othersocio-economicaspectswithintheframeworkofhedonicpricing

models,althoughsomeenvironmentalfactorssuchascrime,typesof

neighbourhood,earthquakerisk,airpollution,andclimatehavealsobeen

analysed.HarrisonandRubinfeld(1978)andlaterSmith(1995),aswell

asCostaandKahn(2003)andothers,haveinvestigatedhowthehedonic

priceofanon-marketgoodlike"climate"canbeestimated.(Thisfield

ofresearchthatfocusesonrealestatecanbecalled"cross-cityhedonic

qualityoflifeliterature".56)

Evenso,therearereasonswhytheuseofhedonicpricingmodelsto

estimate the cost and impact of climate change has so far remained

untouchedasaresearchfield.Theyaremainlybecause(1)hedonicpricing

modelsanalysehistoricaldata,andclimatechangeisadynamicprocess

withmanyofitsresultsonlyvisibleinthefuture,(2)climatechangeisa

complextopicwitharangeofinteractingvariables,and(3)uncertaintyis

inherentwhentalkingaboutclimatechange.

54 Kaplan,Garrick,1997,p.109:Therefore,informationaboutthehazardisaccompaniedbyastatementinregardtothe relevantstatisticalcertaintyinordertoshowthecertainty(e.g.,95percent)withwhichadefineddegreeofdamagewill notbeexceeded.55 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.56 Craggetal.,1997,p.261f/Craggetal.,1999,p.519f/Kahn,2004.

AEL(j) = ſ ƒ(x)S(x)Wdx = ſ S(p)Wdpxmin 0

1

AEL = Ʃ AEL(j)n

j=1

PV (Risk)= AEL

i

PV (Risk) = Ʃn

t=1

AELt

(1+d)t

PV (Increased Risk) = Ʃn

t=1

(AELt - AEL0)(1+d)t

16

However,hedonicpricingmodelscanhelpagreatdeal.Astheycan

disclosethevalueof“manyseverestorms”inonecityand“nostorms”

inanother,therearepossibilitiesforestablishinga“price”foranaspect

ofclimate.Combiningthemodelsforclimatechangewithaprojection

offutureeventsenablesacalculationoftheimpactofincreasingrisks

ofextremeweathereventsonthehousingmarketinthegivenlocation.

Nevertheless,theproblemsofinteraction,uncertainty,timepreference,

and changing consumer preferences still need to be addressed.

Inthiscontext,thecalculationmodelpresentedabovecanonlybe

understoodasafirststeptowardsthedeeperexplorationofnatural

hazards.Asyetitdoesnotallowforseveralnaturalhazardsoccurring

simultaneouslyandperhapsbeingsubjecttocorrelations57-forexample,

droughtincombinationwithveryhightemperaturesandlowhumidity

typicallyincreasestheriskofwildfire.Italsodoesnottakeintoaccount

thatlossfunctionscanalsobesubjecttodynamicsovertimeandcan

thereforechange;extremeweathereventstodaypossiblyincreasethe

vulnerabilityofagivenpropertytofutureextremeeventsduetoalower

resilience.Ontheotherhand,investmentstoincreasetheresilience

typicallyoccurafterafirstdisasterhastakenplace.Asaresult,extreme

weathereventswillaffectthecapabilityofthepropertytoadaptinvarious

ways.Furthermore,aswellastheverycomplexmodelingofthefunctional

relationships,thelimitedavailabilityofdatarepresentsafurtherrestriction

onderivingexpectedlosses,andthisgenerallyexposesclimatemodelsto

various uncertainties.58

Figure 7: Elements for the derivation of expected losses

Source:IRE|BS,UniversityofRegensburg,2013.

The analysis is restricted by data availability and complex functional modeling of the facts.

Itisthereforenoeasytasktoperformariskanalysisofextremeweather

eventsinrelationtopropertyvalues.Theaforementionedtopicsmust

bedealtwithinastructuredmanner,andthefundamentalrelationships

inrespecttoriskmanagementmustbeconsidered.Someofthekey

questionsthatariseare:

•Whatistheexactshapeofthedistributionofthespecifichazardfunction

foragivenkindofextremeweathertoday?Whichkindofdistributionfits

besttomodelthehazard,andwhichriskfunctionsandextremevalue

statisticsmightapply?

•Howwilltheriskchangeinthefutureinregardtotheintensityand

frequencyofextremeweatherevents?Howcandensityfunctionsbe

derivedtodaythatarerelevantforthefuture(e.g.,2020-2030)in

thisregard?

•Howisdamagecausedtoindividualpropertiesrelatedtotheintensity

ofanextremeweatherevent?Howcancorrespondingdamagefunctions

bederived?

•Whatinfluencedotechnicalprogressandadaptationtoexpectedlosses

haveonfuturevulnerability?

Inthenextsectionofthisreport,theelementsofvulnerabilityfunctionand

hazard function59areintroduced.Figure7givesanoverviewoftheorigins

of the data.

57 Buznaetal.,2006,p.132f.58 Cruzetal.,2007,p.495f/Lindenschmidtetal.,2005,p.99f/Merzetal.,2004,p.153f/Merzetal,2009,p.437f/Sachs, 2007,p.6ff.59 Note:AmoredetailedscientificexplanationofthetwoelementscanbefoundintheImmoRiskprojectreports.

Hazard Vulnerability Value

Database Historical events, modelled data for the distribution

Data based on historical losses (empirical loss events) or data derived by experts for a specific building type (engineering aproaches)

Typical replacement costs for specific building type, comparative data

Forecast Global and Regional Climate Models are the basis from which extreme value statistics are derived.

Only a few approaches exist to date. Changes of vulnerability are dependent on technical progress, adaptation measures, etc.

Cost inflation of given data for today’s replacement costs are possible.

17


Outlook on the future development of extreme weather events

Intermsofstrategicrealestateinvestmentdecisions,aswellas

observationofthecurrentsituation,itisimportanttoanalysethe

developmentofallfactorsthatpotentiallyaffectfuturereturnsandvalues

aswellastheunderlyingdrivingforces.Inthisrespect,extremeweather

eventswillbecomeincreasinglyrelevantand,inlightofcurrentresearch,it

isassumedthatthetotalnumberandintensityofdifferentextremeweather

events will continue to grow.60

Figure 8: Impact of projected climate change

Source:IPCC,2012/Bouwer,2010.

CalculationsmadebytheImmoRiskprojectconcerningfuturetimeframes

havereachedthesameconclusion,whileallforecastsregardingthe

change in different hazard functions indicate a growing threat over time.61

Figure9illustratesthisresultbasedontheexampleofachangeindensity

function.

Leading scientists are highly likely to assume in

their scenarios that the overall risks from extreme

weather events will continue to increase, ultimately

leading to even higher losses. The corresponding

risk functions are generally composed of the

future hazard functions and the vulnerability of the

affected properties.

In these scenarios, increasing losses will be driven

in particular by the rising number of extreme

events (hazard). There is no clear conclusion,

however, regarding the development of the

vulnerability of buildings and infrastructure. On

one hand, resilience may improve due to major

investments in adaptation measures; on the other,

there are many reasons to believe the vulnerability

of the property stock in general will rise further,

such as the continued zoning for new construction

in heavily affected areas.

In developing strategies to address the threat of

extreme weather events for individual properties,

a strong, regional differentiation is essential when

considering the risks.

Furthermore, when it comes to real estate, it is

increasingly important to pay attention to relevant

psychological impacts. Even if people often do not

give up their property until they have been hit by

natural disasters repeatedly, these situations will

occur more frequently in the future, and migration

will intensify accordingly.

In regard to the vegetation in affected areas, trees

and other plants with a long growth phase, in

particular, will die out first, and this may happen

more rapidly.

Number of studies

Hazard type

Median estimated increase in loss in 2040 from 2000

9 Tropical storms 30%

6 Other storms 15%

6 Flooding 65%

60 Donatetal.,2011,p.1351ff/Donatetal.,2010,p.27ff/Naumann,2010,p.53/WorldBank,2013,p.XVff/Guyattetal., 2011,p.58:Physicalimpactswillincreasefrom2050on./Howelletal.,2013,p.4ff/IPCC,2013,p.4/Kunzetal.,2009, p.2294/Pintoetal.,2007,p.165f.61 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.

18

Figure 9: Change in the density function of extreme weather events

Source:IPCC,2013,p.7

Note: The top graph shows the effects of a simple shift of the entire distribution

toward a warmer climate. The bottom graph shows the effects of an increase in

temperature variability with no shift in the mean.

Generalisedstatementsarenotconstructive,however,because

“confidenceinprojectingchangesinthedirectionandmagnitudeofclimate

extremesdependsonmanyfactors,includingthetypeofextreme,the

regionandseason,theamountandqualityofobservationaldata,thelevel

ofunderstandingoftheunderlyingprocesses,andthereliabilityoftheir

simulationinmodels.”62

Global trends are obvious; regional differentiation is necessary, however.

If substantial conclusions are to be drawn for individual properties or

portfolios,furtherregionaldifferentiationmustbeappliedtothefollowing

statements that refer to general developments:63

•Indevelopedcountries“...exposuretoclimate-andweather-related

hazardshasincreased,whereasvulnerabilityhasdecreasedasa

resultofimplementationofpolicy,regulations,andriskpreventionand

management(EEA,2008;UNISDR,2009).”64Thistrendwillprobably

continue,whereasvulnerabilitymightyetincreaseforlessdeveloped

countries.65

•“Modelsprojectsubstantialwarmingintemperatureextremesbytheend

ofthe21stcentury.Itisvirtuallycertainthatincreasesinthefrequency

andmagnitudeofwarmdailytemperatureextremesanddecreasesincold

extremeswilloccurinthe21stcenturyattheglobalscale.”

“AcrosslargepartsofEurope,the1961-1990100-yeardroughtdeficit

volumeisprojectedtohaveareturnperiodoflessthan10yearsbythe

2070s.”66

InMediterraneancountriesinparticular,droughtswillleadtoincreased

economiclosses(particularlywhenrelatedtothedangerofmore

intensiveforestfiresintermsoflength,frequency,andseverity)while

heatextremesinAsiawillalsoproliferateinthenearfuture.Across

theworld,globalwarmingwillalsoputaddedpressureonagricultural

yields.67Inthiscontextexpertsalsopointtothemountingconcerns

aboutincreasingheatintensityandotherclimate-relatedthreatsinmajor

Europeancities.68

Warmingwillleadtoanincreaseinthelackofwaterintheaffected

regions69andcausetheArcticicemassandglacierstoretreatfurther.70

•“Itislikelythatthefrequencyofheavyprecipitationortheproportion

oftotalrainfallfromheavyfallswillincreaseinthe21stcenturyover

manyareasoftheglobe....[F]uturefloodlossesinmanylocationswill

increase.”71

“Heavyrainfallsassociatedwithtropicalcyclonesarelikelytoincrease

withcontinuedwarming.”72

“Itisverylikelythatmeansealevelriseswillcontributetoupwardtrends

inextremecoastalhighwaterlevelsinthefuture.”73

ForEurope,thesealevelcanbeexpectedtorisebyanother0.46metre

by2080,leadingtofurtherseveredamagetopropertyandinfrastructure

incoastalregions.Totalmonetarydamageduetoflooding,salinity

intrusion,landerosion,andmigrationcouldrisefromacurrent€1.9

billion to €25.3billionin2080annually.74ForAsia,expertswarnthatthe

sea-levelrisecouldbeasmuchas1metreby2100ifthetemperature

risesby4°C.75

“Thereishighconfidencethatchangesinheatwaves,glacialretreat,

and/orpermafrostdegradationwillaffecthighmountainphenomena

suchasslopeinstabilities,movementsofmass,andglaciallakeoutburst

floods.Thereisalsohighconfidencethatchangesinheavyprecipitation

willaffectlandslidesinsomeregions.”76

62 IPCC,2012,p.9/Guyattetal.,2011,p.62.63 IPCC,2012,p.12ff/IPCC,2013,p.15ff.64 IPCC,2012,p.255/Schmidtetal.,2010,p.13ff.65 Satterthwaiteetal.,2007,p.15ff.

66 IPCC,2012,p.242/Lehneretal.,2006,p.1ff.67 WorldBank,2013,p.XVII.68 Wilby,2003,p.251ff.69 WorldBank,2013,p.XVII.70 IPCC,2013,p.17.71 IPCC,2013,p.13.72 IPCC,2013,p.19.73 IPCC,2013,p.120.74 Brownetal.,2011,p.31.75 WorldBank,2013,p.XVII/Leurigetal.,2013,p.4.76 IPCC,2013,p.114.

ShiftedMean

IncreasedVariability

Prob

abili

tyo

fOcc

urre

nce

Prob

abili

tyo

fOcc

urre

nce

19


Lowland in coastal countries - below 5m elevation.

Source:EuropeanEnvironmentAgency

Theoverallpicturefromthismostrecentresearchisclear:extreme

weathereventswillriseinnumber,nomatterwhatkindofnaturalhazard

isdiscussed.Inparticular,theincidenceofforestfires,heatwaves,and

droughtswillcontinuetoincreaseinmanyregions,whilefloods,hail,and

severestormswilloccurwithgreaterfrequency.Likewisemudslides,

avalanches,andotherexamplesofsevereerosionwillbecomeevenmore

common,especiallyinmountainousareas,whileflashfloodswillgrowin

regularityandthemigrationofpeoplefromseverelyaffectedareaswill

escalate.

Expertsassumethat,aboveall,Russia77andtheUnitedStates78 will be

affectedtoanincreasingextent.Ofspecificnoteareheatwaves,their

accompanyingdroughtsandforestfires,andtheresultinglossesfor

forestryandagriculture,asdiscussedearlier.FortheWesternUnited

States,forexample,Spracklenetal.(2009)assumethattheaveragearea

burnedinforestfireseachyearwillmorethandoublewithinthenext40

years.Ifrainfalldecreases,thedrynessofthesoilwillincrease,especially

inthoseareasthatrelyonmountainmeltwater.

The rise in wildfires reports in the last 30 years

Source:ClimateCentral

It is widely accepted that a significant increase in frequency and intensity of extreme events - and therefore in damage - is highly likely.

Itisalsoexpectedthatdisastersassociatedwithclimateextremeswillhave

anincreasinginfluenceonpopulationmobilityandrelocation.Evenso,it

shouldbenotedthatpeoplemightnotimmediatelygiveuptheirhomesas

aresultofadisaster,butmaychoosetodosoiftheeventhappensagain.

Forexample,inpartsofAustriaanincreaseinrealestatesaleswasonly

noticedwhenthesameregionwasfloodedforasecondtime-acoupleof

yearsafterthefirstoccurrence.

Assevereweathereventsoccurwithgreaterfrequencyormagnitude,or

both,somelocalitiesmaybeconsideredincreasinglymarginalasplaces

tolive.Intensityandrecurrenceofnaturaldisasterswillthereforehavea

greatinfluenceonlocationdecisionsmadebypeople,yetonlywhencertain

tolerancelevelshavebeenreached.Theresultingmigrationwillnotonly

impacttheplacesbeingleftbehind,butclearlyalsotheareasthatpeople

moveto.Itislikelythattheareasmostaffectedbythelossofpopulation

willbecoastalsettlements,smallislands,mega-deltas,andmountain

settlements.79

77 MüRe,2013,p.40.78 Brandes,2013,p.4:basedonthe“DraftNationalClimateAssessmentReport”,U.S.GlobalChangeResearchProgram, January2013.

79 IPCC,2012,p.234f.

20

Studieshavealsodemonstratedthatperiodsofseveredroughtcanalso

leadtotherapidlocalextinctionofcertainplantsinaffectedareas-a

developmentthatissettointensify.80Inparticular,thisaffectstrees

with a long growth phase that cannot adapt fast enough to the changing

environment,asshownbythecaseoftheColoradopinyon(Pinusedulis)in

the2000-2003U.S.drought.81

Frequently recurring extreme weather will intensify human migratory flows. In the plant world, trees with a long growth phase will die out first.

InGreenland,thepresenceofheatislandswithincreasinglyrising

temperatures could cause the ice cover to continue to recede on a large

scale.However,itisquestionablewhethertheiceintheArcticwillcontinue

toretreatatitsveryhighaveragerateof11.3percentperdecadein

summer(basedontheoveralldifferenceinicecoverin2012compared

with1980).IntheSouthernHemisphereitcanbeassumedthattheannual

seaiceextent(Antarcticwithoutinlandice)willcontinuetoincrease-

althoughattheslowerrateof2.8percentperdecadeinthesouthern

summer,asrecordedtodate(basedonthechangefrom1980to2012).

The rising temperatures will also cause stronger winds around the Poles.

TheIntergovernmentalPanelonClimateChange(IPCC)assertsthat

various alternative emission scenarios and the climate models based on

themrepresent“asubstantialmulti-centuryclimatechangecommitment

createdbypast,presentandfutureemissionsofCO2.”82Becausemost

oftheimpactsrelatedtoclimatechangewillpersistovermanycenturies,

evenifemissionsarestoppedtoday,itisclearthatmanyconsequencesof

climatechangearenotforeseeable,despitestate-of-the-artforecasting

techniques.Forexample,thepossibilitythattheAtlanticMeridional

OverturningCirculation(AMOC)-thelarge-scaleoceancirculationcreated

bysurfaceheatandfreshwaterfluxes-mightcollapseafterthe21st

century,cannotbeignored.83

The limits of climate models are reached when thresholds and tipping

pointsrelatedtosocialand/ornaturalsystemsareexceeded.84For

example,Fischlinetal.(2007)analysed19studiesandconcludedthatup

to30percentofplantaswellasanimalspeciesmightbeatanincreased

riskoffastextinctioniftemperatureriseexceeds2°Cto3°C-whichisa

realistic scenario.85Suchfundamentalchangestotheenvironmentwillhave

significantbut,asyet,unpredictableeffectsontheeconomy.

The continuous deterioration of the ecosystem and ongoing climate change could lead to critical tipping points being reached more frequently.

Thus,acleartrendtowardsmoresevereandmorefrequentextreme

weatherevents-withcorrespondingeffectsonrealestateandthe

broadereconomy-mustbeanticipated.Incontrast,nouniformtrends

canbederivedconcerningvulnerabilityofrealestatetoextremeweather.

Itisgenerallytobeexpectedthattheexposureofrealestateportfolios

toextremeweathereventswillseearelativedecreaseworldwidedue

toadaptationmeasurestocombatsuchevents-thoughtheadaptation

neededwillprobablybesimultaneouslyconnectedtosubstantial

investments.

Theexposureofrealestatetoclimatechange-relatedriskisclosely

connectedtosocio-economicdevelopments,suchasthecontinuedrisein

populationandeconomicgrowth,improvedsocialwelfare,andthelocation

ofnewsettlementareas.Inthisregard,itwillbenecessaryinthefuture

tobemuchmoresensitivewhendesignatingexistingnaturalareasas

building zones.86Positiveactionsinthisdirectioncanalreadybeobserved

indevelopingcountries,wherebuildingregulationsandland-useplanning

areincreasinglytakingintoaccounttheneedtoreducethevulnerabilityof

buildings to the effects of climate change.87Intelligentwarningsystemsare

alsoincreasinglybeinginstalledthatcanhelpprotectpeopleandprevent

propertydamage.

It is impossible to derive clear information regarding the development of vulnerability.

Meanwhile,threatstorealestatefromsevereweatherremainintheform

ofunbridledgrowth,uncontrolledconstructionofsettlementsinpoor

countries,anduseofmodernconstructionmaterialsandelements,such

as certain facades or fragile solar panels on roofs that could be damaged

byhailorotherstormdamage.Moreover,recentstudiesfocusingonport

citieswithmorethan1millioninhabitants,forexample,haveestimated

thatrealestateassetsinthesecitiesthatmightbeexposedtoaonce-a-

centuryextremeeventcouldgrowtenfoldtoaroundUS$35trillionby2070

(€25.5trillion).88

80 WorldBank,2013,p.XVII.:Drought-induceddie-offofplantsandtrees.81 IPCC,2012,p.244./Granieretal.,2007,p.124f.82 IPCC,2013,p.19.83 IPCC,2013,p.17.84 Dawsonetal.,2009,p.9685 Dawsonetal.,2009,p.244.

86 Cruzetal.,2007,p.491f:Weaklanduseplanningandenforcementareincreasingvulnerabilitytoextremeweatheraswell as climate change in general.87 Feyenetal.,2009,p217f.88 Nichollsetal.,2008,p.8ff/WorldBank,2013,p.XXI,p.33ff,p.82ff:Regardingcoastalcitiesingeneral.

21


Case Study: Increased insurance premiums / annual expected loss

Inthiscasestudy,ahypotheticalpropertyisprocessedwiththedata

ofdamagefunctionsaswellas(future)hazardfunctionstoderivean

annualexpectedloss(AEL)ofthepropertyfordifferenttimeperiods.The

characteristicsofthehypotheticalpropertyareshowninfigure10.89

Figure 10: Property details

Source:IRE|BS,UniversityofRegensburg.

Theriskofwindstormhazardsistypicallyexpressedasthefrequency

oftheoccurrenceofstormeventswhichexceedacertainwindspeed

([exceedance]probability).Atthisproperty’slocation,weassumethereisa

stormeventevery10years(returnperiod),withsqualls(windgusts)ofup

to31.6metrespersecond(114km/h)tobeexpected.Thecorresponding

functiondescribingthisrelationship-thatis,thereturnperiodofwindstorm

intensities(windspeeds)-canbestatedasfollows:90

Here,x is the wind speed and Tistherecurrenceinterval.Inthisexample,

α (3.31)andβ(24.12)aretheextremevaluestatisticalparametersofthe

Gumbel-distribution91reflectingthecurrentsituation(basedasaproxyon

the latest available data set regarding hazards that occurred within the time

period1971-2000).

Takingintoaccountthespecificbuildingandlocationcharacteristics,the

followingempiricallyderivedstorm-damagefunctioncanbeapplied.Thisis

a power function of

with Sastherelativedamagetothepropertycausedbyagivenwind

speed,x. The parameters a and b are derived from empirical damage

functions(basedonrealinsurancedataofhistoricallossesthatoccurredin

connectionwithcertainstormeventsinthepast).Inthiscase,

a =3.3*10-19 and b =10.0//92

Thefunctionsalsoaccountforthefactthatthedamagesforverylowwind

speeds(uptoabout30metrespersecond)areclosetozero.However,

withhigherwindspeeds,theyincreasestrongly.Otherfactors-suchas

howlongthewindstormlasts,gustiness,93 or trees that might surround the

building-arenotexplicitlymodelledhere.

Accordingtothisdamagefunction,thestormforareturnperiodof100

years,withwindspeedsofabout39.3metrespersecond,would,for

example,leadtodamagesofabout0.377percentofthetotalbuilding’s

costvalue;thepercentagerelatedtotheoverallvaluereflectsmainly

therepairworkneededforthepartiallydestroyedroofcover,damaged

windows,andotherrelativelyfragilebuildingpartsthatwillbeexposedto

stormevents.Itshouldbenotedthatbecauseofthehigh-quality,robust

constructionofpropertiesinGermany,severe,structuraldamagesare

usuallytheexceptioninstorms.

Todeducetheannualexpectedloss(AEL*)inallpossiblestormevents,

this formula involving all recurrence intervals or probabilities must be

integrated as follows94:

Hazard Type Windstorm

Property type Single-family house (detached)

Construction Solid construction/stone

Year of construction 2010

Gross external area 250 sq metres

Levels above ground 1

Height of building 3.25 metres

Type of roof Flat

Roofing Soft roofing

Standard of fittings Very high

Special exposure to hazards None

Year of assessment 2013

x(T)= β - α * ( ln (-ln(1- )))1T

S (x) = a * ( 1 + x )b

89 Note: Case study was calculated by Jens Hirsch and Sven Bienert. The case study is for illustration only.90 SeeAugter/Roos,2010,p.21f.91 Markoseetal.,2011,p.35ff:GeneralizedExtremeValue(GEV)distribution./Rootzenetal.,1997,p.70f/Singhetal., 1995,p.165ff.

92 Thisdamagefunctionisforthepurposesofillustrationonly,withreferencetorealdatafromtheinsuranceindustry.93 Wieringa,1973,p.424:Differentiationofgustfactors.94 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.

= 0.637

= 0.637

AEL* = 0.637* ſ S(x(p))dp1

0

=0.637 * 0.293‰ = 0.187‰

* ſ a*(1+β-α*(ln (-ln(1-p))))b dp1

0

1

0* ſ a*(1 + x(p))b dp

22

Duetoproperty-specificelements,95 this result is adapted in regards to

typeofuse,age,construction,androofing,basedonempiricalvaluesfrom

theinsuranceindustry;theresultingcorrectionfactorhereis0.637,andis

integratedaccordinglyintheformulaabove.

Here,theannualexpectedlossis0.187‰ofthevalueofthebuilding.The

AEL(ineuros)isthereforecalculatedbymultiplyingtheobtainedAEL*

bythepropertyvalue(basedoncostdataforthebuildingonly).

SincebenchmarkdataisavailableinGermany(NHK,normalised

replacementcost,2010,whichrepresentstheaveragebuildingcostsper

squaremetre),96itispossibletoderivereplacementcostspersquare

metreforagivenbuilding;thebenchmarksalreadyincludeconstruction

costs,value-addedtax,and17percentforrelatedcosts(e.g.,design,

planningapproval,projectmanagement,etc.).Aftertakingintoaccountthe

building-costindexforinflation,andadjustingthefiguresaccordingtolocal

andregionalpricinglevels,theadjustednormalreplacementcostsroundto

€1,950persquaremetregrossexternalarea.Thereplacementcostofthe

property(withoutland),therefore,encompasses

Theannualexpectedlossthusamountsto:

Thisvaluelargelycorrespondstotoday’sinsurancepremiums,butshould

beclassifiedas“veryhigh”.

Wenowchangetheinputparametersbasedontheinformationderived

fromRegionalClimateModels(RCMs)regardingthehazarddata,anduse

theextremestatisticsparameterα (now3.56)andβ(now25.82)asinput

for the Gumbel distribution applied in this case for the time period

2021-2050.

The new AEL* is 0.637 * 0.578‰ = 0.368‰; the new AEL = 0.368‰ * €487,500 = €179.49

Inthiscase,theinsurancepremiumwillthereforealmostdoubleinthe

medium term based on latest climate data.

Whena3percentinterestrateisapplied,asimplifiedconsiderationofa

pure capitalisation of the annual difference results in97

with PV=presentvalue(ofallexpectedlossesthatexceedthehistorical

benchmark)representingtherisk,andAEL=annualexpectedloss(int)with i= cap rate.

Therefore,althoughtheincreasedriskseemsrelativelymoderateand,

whenrounded,amountstoonlylessthan1percentofthetotalbuilding

value,onemusttakeacoupleoffactorsintoaccount.First,severalother

hazardtypesrelatedtoextremeweathereventsmustalsobeconsidered

-hail,flooding,etc.-andthesehazardfunctionsmightevencorrelate.

Furthermore,besidesdirectlossesduetoextremeweather,therealso

areeffectsduetothegradualclimatechangethatneedtobereflected,

asshouldindirecteffectsandconsequentiallossesrelatedtoextreme

weather.Ifallthese(increasing)risksaretakenintoaccount,theoverall

impactontoday’svaluemightbesignificantenoughtocatchthe

owner’sattention.

NHK = 1,950 * 250.0m2 = €487,500€m2

AEL = AEL* * NHK = 0.187‰ * €487,500 = €91.16

PV (Increased Risk) = (AELt - AEL0)

i

PV (Increased Risk) = (179.49 - 91.16)

0,03

PV (Increased Risk) = €2,944.33

95 Databasedonexperience:GesamtverbandderDeutschenVersicherungswirtschaft(GDV),Germaninsurancecompanies association.96 SeeBundesministeriumfürVerkehr,BauundStadtentwicklung,SW-RL,2012,p.12ff.

97 Note:Thelaterincreasebasedonthereferenceperiodswasnotincludedinthisillustrationoftheeffect.

23


Conclusions

Thisreportverymuchconfirmsthatclimatechangeisarealityandthat

itsnear-termconsequences-intheformofextremeweatherevents-are

growinginscale,intensityandfrequency.Fortherealestateindustry,

whichisalreadyadaptingtotacklethecausesofclimatechange(ofwhich

itisamaincontributor)inareassuchasemissionsandenvironmental

controls,addressingtheseweather-relatednaturalhazardsand

correspondingthreatsshouldnotjustbeviewedasthe‘nextchallenge’

on the agenda. It should be part of a wider mindset that considers how

climatechangeandallitseffectswillinfluencerealestatelocation,building

specificationandcost,operatingcostsand,ultimately,value.

Ashighlighted,extremeweathereventsarenowhaving,insomecases,

a devastating effect on particular regions of the world with spectacular

economiclosses–andtheimpactsarenotjustbeingrepeatedmore

frequentlybutarewideningtotouchnewgeographies.Withfinancial

returnsalreadybeingaffected,adeeperunderstandingofthescience

ofclimatechangeanditsimpactonpropertyvalueisthereforerapidly

required;asistheadoptionofnewcriteriawithintheinvestment-decision

makingprocess.

Therealestateindustry,critically,shouldnotattempttomitigatethe

increaseinextremeweathereventsandtheresultingincreaseinrisk

bymerelyrelyingonpotentiallyrising(andnon-allocable)insurance

premiums.Thedirectandindirecteffectsonspecificregionsandasset

classesmaybesoenormous,thatinvestmentlocationscurrentlyseenas

“safehavens”mustbereconsidered.Theresultwillbere-evaluations,

buildingadaptationcosts,andfundamentallydifferentallocationsof

investmentfunds.Moreover,thedramaticregionaldifferencesinthe

expectedimpactfromclimatechangerequiresananalysisoftherealestate

inventoryineachregion,andthenindividualrecommendationsmadeonit.

Aspartofthechangeinmindset,itisalsoessentialthatclimatechange

anditsrisksarethoroughlyunderstoodand,whererelevant,actedonat

everystageofthepropertylifecycle.Forexample,planningeffortsthat

integrateclimatechangeriskswillbeincreasinglyimportantforinvestors.

Atthesametime,fromanurbanplanningperspective,theextenttowhich

the public sector adopts building adaptation measures and implements

broaderspatialplanningconceptstoaddressriskswillbecomemore

importantinaworldofincreasinglycompetitiveinternationalcitymarkets.

Ininvestmentmarkets,managingclimateriskwill,amongotherthings,

mostlikelyleadtoanincreasedallocationofinvestmenttorealestate

assetsthatarealreadyfuture-proofed.Investorsmustthereforetake

significantstepstowardsimprovingtheresilienceoftheirportfolioswhile

integratingriskassessmentsrelatedtoclimatechangeintheirportfolio

management.Simultaneously,advisersandassociatedindustryplayers

willneedtobeatthesamepoint,ifnotfurtheruptheclimatechange

intelligence curve.

Atpresent,researchintothefutureofpropertyvaluesinthefaceof

increasingweather-relatednaturalhazards,andtheimplicationsfor

riskandportfoliomanagement,isstillinitsinfancy.Thisreportis

therefore a contribution towards heightening awareness and opening up

discussiontoalargeraudienceintherealestateindustry.Pivotaltothe

debateishowweather-relatedlossescanbeaccuratelycalculatedand

therisksassessed;thenewlosscalculationmethodologyfeaturedin

thispaperseekstoprovidetheindustrywithatoolthatwillenablereal

estateinvestorstomakefar-reachingconclusionsinregardtothefuture

developmentofpropertyvaluesinaspecificsituation.

Extremeweathereventswillcontinuetomultiplyandintensify,and

althoughimprovedforecastingwillbecomestronger,therewillalwaysbe

anelementofunpredictabilityintheirnatureandlocation.Inreality,as

thesethreatscontinuetoescalatenoonewillbetrulyinvulnerable.Acting

nowtofuture-proofassets,improveresilienceandreducerisksisvitalfor

therealestateindustryacrosstheworld.

24

Appendix: Overview of the present state of research

Existingstudiesrelatedtoclimatechange,andthatfocusonextreme

events,mainlydealwithempiricalvaluesinspecificregionsorcities.

Amongthese,forexample,aretheUNDROsurveyforManila(1977);the

KATANOSreportforSwitzerland(1995);theAustralianAGSOCitiesproject

withitsemphasisongeohazards(1999);andstudiesregardingTurrialba,

CostaRica(2002),andToronto(2003).Inadditiontotheirregionalfocus,

mostofthestudiesconcentrateonsingle-hazardresearch-thatisan

isolated consideration of a single natural hazard. 98Inparticular,several

studies from different regions have focused on the economic losses

withrespecttoflooddamage(e.g.,L.M.Bouwer’s2010studyofthe

Netherlands).Simultaneousconsiderationofseveralextreme-weather

hazards-forexample,inthemanneroftheAustralianresearchofBlong

(2003)-has,uptonow,beenanexception.Inviewofthepractical

relevanceofclimatechange,thisissurprising.99

Inregardtohazardresearch,thefewstudiesthathaveaddressed

economiclossesfromhaildamagehaveyieldedmixedresults.McMaster

(1999)andNiallandWalsh(2005)foundnosignificanteffectonhailstorm

lossesforAustralia,whileBotzenetal.(2010)predictedasignificant

increase(upto200percentby2050)fordamagesintheagricultural

sectorintheNetherlands-theapproachesusedbythetwostudiesvaried

considerably.TheRosenzweigetal.(2002)studyreportedonapossible

doublingoflossestocropsduetoexcesssoilmoisturecausedbymore

intense rainfall.100

Invulnerabilityresearch,DodmanandSatterthwaite(2008)havefocused

onthevulnerabilityofresidentialproperty,andSatterthwaitehasalso

analysedtheeffectsofclimatechangeonareaswherethepoorlivein

veryelementaryhousing.IncommonwithDouglas(2008),hefoundsuch

housingtobehighlyvulnerable.Furthermore,Wilby(2003,2007)has

intensivelyexaminedtheimpactofclimatechangeonhighlydeveloped

cities such as London.

Climatechangeandpopulationdensityhasbeenespeciallyaddressedby

Cutteretal.(2008),whileEndlicheretal.(2008)havealsofocusedon

largecities,althoughthereportconcentratedonprospectiveheatwaves

thatwillposespecificchallengesforsuchareas.Morespecifically,

McGranahanetal.(2007)haveexploredtherelationshipbetween

windstormsanddenselypopulatedareasincoastalregionsandfoundan

increasing threat.

RiskManagementSolutions(2000,2012)hasconcentratedoncertain

constructionmaterialsandtheirvulnerabilityincaseofwindstorms,and

Witharanaetal.(2010)haveusedsoftwaretoquantifybuilding-content

vulnerability.

98 Grünthaletal.,2006,p.21.99 DiMauroetal.,2006,p.1.100 IPCC,2012,p.272.

25


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Footnotes

1 MüRe,2013,p.40ff/IPCC,2013,p.4.

2 Petersonetal.,2013,p.20/IPCC,2013,p.5.

3 Rahmstorf,2007,p.1ff/IPCC,2013,p.6.

4 MüRe,2008,p.6/Latif,2009,p.153/Petersonetal.,2013,p.IV/IPCC,2013,p.8f,p.12f./Bouwer,2011,p.39f.

5 MüRe,2013,p.40.

6 NationalOceanicandAtmosphericAdministration(NOAA),10.Mai2013/IPCC,2013,p.7.

7 Note:“DohaClimateGateway”negotiationswithmandatoryregulationsfrom2020onstillrefertothe2degreeCelsiusgoalattheDohaclimateconferenceinDecember2012.

8 Brandes,2013,p.9:EstimatedValueofInsuredCoastalPropertiesamountintheUnitedStatestoUS$27.000billionin2012.

9 WBCSD,2009,p.6.

10 Bosteelsetal.,2013,p.6.

11 Guyattetal.,2011,p.15:Realestateisverysensitivetoclimateimpacts./Leurigetal.,2013,pp.5,7

12 WorldBank,2013,p.94:Reducedpropertyvalues.

13 Guyattetal.,2011,p.61/Cruzetal.,2007,p.492:Effectsontourismmightbemassive./Lamond,2009.

14 ULI,2013,p.14ff:Recommendation16:Accuratelypriceclimateriskintopropertyvalueandinsurance.

15 Guyattetal.,2011,p.58.

16 MüRe,2013,p.53.

17 Kronetal.,2012,p.542:Directlossesareimmediatelyvisibleandcountable(lossofhomes,householdproperty,schools,vehicles,machinery,livestock,etc.).

18 IPCC,2013,p.270.

19 Kronetal.,2012,p.535f,p.542f.

20 MüRe,2013,p.42

21 Note:Theassumptionofaperpetuityservesonlytoillustratetheextentofthesituationanddoesnotclaimtobescientificallyconclusiveastothefacts.

22 MüRe,2010,p.33,p.37.

23 Cruzetal.,2007,p.488.

24 IPCC,2012,p.7:Inregardtothechangeswhichhaveoccurredsofar,theIPCChasdeterminedthat“atleastmediumconfidencehasbeenstatedforanoveralldecreaseinthenumberofcolddaysandnightsandanoverallincreaseinthenumberofwarmdaysandnightsattheglobalscale,lengthornumberofwarmspellsorheatwaveshasincreased,PolewardshiftinthemainNorthernandSouthernHemisphereextratropicalstormtracks,therehasbeenanincreaseinextremecoastalhighwaterrelatedtoincreasesinmeansealevel.”

25 GDV,2011,p.1/MüRe,2013,p.52/Mechleretal.,2010,p.611ff.

26 MüRe,2013,p.3ff.

27 MüRe,2013,p.52.

28 IPCC,2012,p.270/Guyattetal.,2011,p.14:CostofphysicalclimatechangeimpactcouldreachUS$180billionperyearby2030(€131.4billionpa)

29 Mills,2005,p.1040f/Mills,2012,p.1424f/Mechleretal.,2010,p.611ff.

30 Howelletal.,2013,p.46:Greaterconcentrationofpropertiesinriskzones.

31 Naumannetal.,2009,p.228/MüRe,2008,p.4.

32 MüRe,2013,p.58.

33 IPCC,2012,p.265.

34 Note:SeetheAppendixforanextendedoverviewofthecurrentstateofresearch.

35 IPCC,2012,p.266.

36 Wilby,2007,p.42/Guyattetal.,2011,p.1ff:Traditionalassetallocationdoesnot account for climate change. There is a small amount of research which focusesontheinvestmentimplicationsofclimatechange./Brandes,2013,p.12ff:Theriseofmodelingandfutureriskscenarios.

37 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.

38 Note:Anexternaleffectis,forexample,airpollutioncausedbyenergyconsumptionthataffectsathirdparty(e.g.,thesocietyingeneral)thatwasnotresponsibleforthatemission.Theexternalityis“uncompensated”forthepolluterbecausethecostwillbebornebyothersunlesstheexternalityis“internalised”throughregulation(e.g.,taxes).


40 IPCC,2013,p.10:climatefeedbacks.

41 Osbaldistonetal.,2002,p.46/Ozdemir,2012,p.1ff.

42 Wilby,2007,p.42:“Aboveall,thereisanurgentneedtotranslateawarenessof climate change impacts into tangible adaptation measures at all levels of governance.”/Guyattetal.,2011,p.1:Standardapproachesrelyheavilyonhistoricaldataanddonottacklefundamentalshifts.

43 Lechelt,2001,p.28.

44 Büchele,2006,p.485/Kaplan,Garrick,1997,p.93.

44 UNDHA,1992,p.64:“Riskareexpectedlosses(of...propertydamaged...)duetoaparticularhazardforagivenareaandreferenceperiod.Basedonmathematicalcalculations,riskistheproductofhazardandvulnerability.”


46 Thywissen,2006,p.36/UNDHA,1992,p.84:“Degreeofloss(from0%to100%)resultingfromapotentiallydamagingphenomenon.”

47 Heneka,2006,p.722/Büchele,2006,p.493.

48 InsurablevalueaccordingtoInternationalValuationStandards(IVS):Thevalueofapropertyprovidedbydefinitionscontainedinaninsurancecontractorpolicy.

49 EuropeanValuationStandards(EVS),2012.

50 IPCC,2013,p.10,14f/Khanetal.,2009:Stormriskfunctions/Leckebuschetal.,2007,p.165ff/Mohretal.,2011//Waldvogeletal.,1978,p.1680ff.

51 Fleischbeinetal.,2006,p.79f/Linkeetal.,2010,p.1ff/Orlowskyetal.,2008,p.209/Rehmetal.,2009,p.290f:Modelforwindeffectsofburningstructures/Rockeletal.,2007,p.267f/Sauer,2010/Thiekenatal.,2006,p.485ff:Approachesforlarge-scaleriskassessments.

52 Cortietal.,2009,p.1739f/Cortietal.,2011,p.3335f/Granger,2003,p.183/Pinelloetal.,2004,p.1685f/Sparksetal.,1994,p.145ff.

53 Golzetal.,2011,p.1f:Approachestoderivevulnerabilityfunctions./Hohl,2001,p.73f:Damagefunctionforhail./ICE,2001:Source-Pathway-Receptor-Consequence-Concept/Jainetal.,2009/Jainetal.,2010/Kafali,2011/Klawaetal.,2003,p.725f/Matson,1980,p.1107/Naumannetal.,2009a,p.249f/Naumannetal.,2009b:Flooddamagefunctions./Naumannetal.,2011/Penning-Rowselletal.,2005/Schanze,2009,p.3ff.

33


54 Kaplan,Garrick,1997,p.109:Therefore,informationaboutthehazardisaccompaniedbyastatementinregardtotherelevantstatisticalcertaintyinordertoshowthecertainty(e.g.,95percent)withwhichadefineddegreeofdamagewillnotbeexceeded.

55 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.

56 Craggetal.,1997,p.261f/Craggetal.,1999,p.519f/Kahn,2004.

57 Buznaetal.,2006,p.132f.

58 Cruzetal.,2007,p.495f/Lindenschmidtetal.,2005,p.99f/Merzetal.,2004,p.153f/Merzetal,2009,p.437f/Sachs,2007,p.6ff.

59 Note:AmoredetailedscientificexplanationofthetwoelementscanbefoundintheImmoRiskprojectreports.

60 Donatetal.,2011,p.1351ff/Donatetal.,2010,p.27ff/Naumann,2010,p.53/WorldBank,2013,p.XVff/Guyattetal.,2011,p.58:Physicalimpactswillincreasefrom2050on./Howelletal.,2013,p.4ff/IPCC,2013,p.4/Kunzetal.,2009,p.2294/Pintoetal.,2007,p.165f.

61 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.

62 IPCC,2012,p.9/Guyattetal.,2011,p.62.

63 IPCC,2012,p.12ff/IPCC,2013,p.15ff.

64 IPCC,2012,p.255/Schmidtetal.,2010,p.13ff.

65 Satterthwaiteetal.,2007,p.15ff.

66 IPCC,2012,p.242/Lehneretal.,2006,p.1ff.

67 WorldBank,2013,p.XVII.

68 Wilby,2003,p.251ff.

69 WorldBank,2013,p.XVII.

70 IPCC,2013,p.17.

71 IPCC,2013,p.13.

72 IPCC,2013,p.19.

73 IPCC,2013,p.120.

74 Brownetal.,2011,p.31.

75 WorldBank,2013,p.XVII/Leurigetal.,2013,p.4.

76 IPCC,2013,p.114.

77 MüRe,2013,p.40.

78 Brandes,2013,p.4:basedonthe“DraftNationalClimateAssessmentReport”,U.S.GlobalChangeResearchProgram,January2013.

79 IPCC,2012,p.234f.

80 WorldBank,2013,p.XVII.:Drought-induceddie-offofplantsandtrees.

81 IPCC,2012,p.244./Granieretal.,2007,p.124f.

82 IPCC,2013,p.19.

83 IPCC,2013,p.17.

84 Dawsonetal.,2009,p.96

85 Dawsonetal.,2009,p.244.

86 Cruzetal.,2007,p.491f:Weaklanduseplanningandenforcementareincreasingvulnerabilitytoextremeweatheraswellasclimatechangeingeneral.

87 Feyenetal.,2009,p217f.

88 Nichollsetal.,2008,p.8ff//WorldBank,2013,p.XXI,p.33ff,p.82ff:Regardingcoastalcitiesingeneral.

89 Note:CasestudywascalculatedbyJensHirschandSvenBienert.Thecasestudyisforillustrationonly.

90 SeeAugter/Roos,2010,p.21f.

91 Markoseetal.,2011,p.35ff:GeneralizedExtremeValue(GEV)distribution./Rootzenetal.,1997,p.70f/Singhetal.,1995,p.165ff.

92 Thisdamagefunctionisforthepurposesofillustrationonly,withreferencetorealdatafromtheinsuranceindustry.

93 Wieringa,1973,p.424:Differentiationofgustfactors.

94 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.

95 Databasedonexperience:GesamtverbandderDeutschenVersicherungswirtschaft(GDV),Germaninsurancecompaniesassociation.

96 SeeBundesministeriumfürVerkehr,BauundStadtentwicklung,SW-RL,2012,p.12ff.

97 Note:Thelaterincreasebasedonthereferenceperiodswasnotincludedinthis illustration of the effect.

98 Grünthaletal.,2006,p.21.

99 DiMauroetal.,2006,p.1.

100 IPCC,2012,p.272.

34

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