AirTemperatureSensorSitingClassificationinNordicCountries
MareileWolff1,InnaHaapa2,MinnaHuuskonen2,PetraJohansson3,Juho‐PekkaKaukoranta2,
GabrielKielland1,MiinaKrabbi4,SibyllevonLöwis5,AslaugvanNes1,HildegunnNygård1,Maria
Santanen2,ArniSigurdsson5,TedTorfoss1,CristofferWittskog3
1NorwegianMeteorologicalInstitute,Oslo,Norway
2FinnishMeteorologicalInstitute,Helsinki,Finland
3SwedishMeteorologicalandHydrologicalInstitute,Norrköping,Sweden
4EstonianEnvironmentAgency,Tallinn,Estonia
5IcelandicMeteorologicalOffice,Reykjavík,Iceland
Introduction
Airtemperatureisoneofthemostimportantclimateparameterandismeasuredbyalmostall
standardautomaticweatherstationsaroundtheworld.Theaccuracyofthemeasurementis
determinedbytheinstrumentquality,itsuncertaintyandoverallperformanceaswellas
calibrationandmaintenanceroutines.Furthermore,thetemperaturemeasurementsare
influencedbytheirimmediatevicinity.Thedistancetoartificialandnaturalheatsourcesor
sinks,topography,vegetationandshadingeffectsareallfactorswhichmayaffectthe
representativenessofthemeasurements.TheWorldMeteorologicalOrganization'sCommission
forInstrumentsandMethodsofObservation(WMOCIMO)givessuggestionsonthesitingofa
temperaturesensor(WMO,2008)andalsorecommendsasitingclassificationsystemtoclassify
thosestationswhicharenotperfectlylocatedforeasierevaluationoftheexpecteddataquality
(CIMO/WMO,2010).TheCIMOsitingclassificationsystemisadaptedfromaschemedeveloped
atMeteoFrance(Leroy,1998andLeroy,2006).
Withintheco‐operationbetweentheNordicnationalmeteorologicalservicesinthefieldof
Observations(NordObs),aworkinggroupwasestablishedtoworktowardsacommonapproach
ofmetadatacollectionandsiteclassificationoftheirnetworks.
FirstexperienceswiththeWMOCIMOsitingclassificationbytheparticipatingcountrieshad
shownacoupleofcommonchallengeswhenimplementingitforstationsathigherlatitudes.For
example,thecombinationoflowelevationandveryvaryingazimuthanglesofthesun
throughoutayear,typicallandscapeformsandvegetationtypesoftenresultinasitingclass
unsuitedforclimatologicalassessmentofthetemperature.
Twenty‐fivestationsinEstonia,Finland,Iceland,Norway,andSwedenwereevaluatedand
classifiedapplyingacommonmetadatascheme.ThefourcriteriaoftheWMOCIMOsiting
classification(slope,vegetation,distancetoheatsourcesandwaterbodiesandshading)were
analysedseparatelyforthosestations.Siteswereadditionallyevaluatedbasedonthe
experiencesofthestationholdersandtheentireNordobs‐team.Forafewselectedstations,
moredetailedanalyseswereperformed.
Thispapersummarizesandconcludesontheevaluationresults.Thecommonmetadataschemes
forallstations,thedetailedanalysesoftheselectedstationsandanextendeddiscussionofthe
resultswillbepublishedinareportbytheNordObsco‐operationinautumn2016andwillalso
beprovidedtotheWMO/CIMOexpertteamcurrentlyworkingonthattopic.
Results
Duringsummer2015,25stationsinallfivecountrieswereevaluated,applyingthecommon
metadatascheme.Foreachstation,theCIMOclassificationwasperformed.Theresultsare
showninthehistograminFigure1.Thefirstfourbarsforeachclassindicatethenumberof
stationsseparatelyforeachcriterion.
At20of25stations,thevegetationwasevaluatedasclass1(greenbars).Twostationswere
classifiedasclass3andthreestationswereclassifiedasclass4.All25stationsaresituatedon
flatterrainorslopeswithananglelessthan19°(yellowbars).Thedistancetoheatsourcesand
waterbodiesislargeenoughforclass1(>100m)at11stations(redbars),about30m(class2)
at8stationsandabout10m(class3)at5stations.Only1stationiscloserthan10mtoheat
sources,justifyingaclass4.
Theshadecriterionistheonlycriterionforwhichasignificantamountofhighclasses(class4
and5)weregiven.At15stationsintotal,shadeonthetemperaturesensorisexperiencedifthe
sunishigherthan7°or20°(purplebar).
Thelast(blue)barshowstheoverallevaluation.Thesiteclassisequaltothehighestclass
numbergivenforanycriterion.Formoststationsreceivingclass4or5,theshadecriterionwas
determiningthehighclass.Nostationwasclassifiedasclass3.Fivestationswereclassifiedas
class1andfourasclass2.
Number of Stations per class Vegetasjon
Slope
HS/WB
Shade
WMO
25
20
11
9
9 9
8
5
4
1
0 0
1
2
6
5
7
3
2
0
0 0
3
0
1
4
0 0 0
5
Figure1.SiteclassificationresultsforNordobsstations.Thebars/numbersindicatethenumberofstationsperclassfor
eachcriterionandfortheoverallsiteclassification,seecoloredlegend.Totally,25stationswereclassified.
Figure2comparestheresultsoftheCIMOsiteclassificationwiththeevaluationofeachstation,
basedontheopinionandexperiencesfromtheNordObsgroup.Colorsareusedforindicating
theinfluenceoftheexposureontemperaturemeasurements.Onlythreecolorsareusedfor
simplicity,indicatingnoinfluence(green=class1),littleinfluence(yellow=classes2and3)anda
lotofinfluence(red=classes4and5).
Whilethesitingclassificationclassifieshighinfluenceontemperaturemeasurementson16
stations,theNordobsgroupevaluatesonlytemperaturemeasurementsatfivestationstobe
highlyinfluenced.
18
16
14
12
10
Red
Yellow
8
Green
6
4
2
0
WMO
NordObs
Figure 2: Evaluation of temperature influence of siting exposure on temperature measurements by WMO siting classification and
by Nordobs
Conclusions
Generally,theimplementationofaclassificationofsitingisveryuseful.Currently,theavailable
metadataaboutsitesdifferalotfordifferentcountriesastheyhavebeendevelopedindividually
andoftenreflectverylocalcharacteristicsofthetypicallandscapesandevenculturalaspects.
Theusedvocabularymaybeunderstooddifferently,i.e.theterm“suburban”isverydependent
onthetypicalsizeanddensityofthecitiesineachcountry.
Beingabletocharacterizethesitingofasensorbyoneorseveralnumbersmakesitpossibleto
comparetheinfluenceofthesitingwithinthenetwork,betweendifferentnetworksandover
time.Sitescanbemoreobjectivelyassessedanditiseasytoidentifypossibleimprovementsand
theirimpact.Lastbutnotleast,communicationabouttheimportanceofsitingbothinternaland
externalwasnoticeablesimplifiedbythesuggestedclassificationsystem.
Estimateduncertainty
Theestimateduncertaintyofthetemperaturemeasurementduetositingisgivenforclasses3,4
and5intheWMOSitingclassificationfortemperature.Theadditionalestimateduncertainty
addedbysitingisupto1°Cforclass3,upto2°Cforclass4andupto5°Cforclass5,
CIMO/WMO2010.
Foraspecificclass,theinfluenceontemperatureduetoslope,vegetation,heatsources/water
bodiesorshadowshouldgivethesameestimateduncertainty,butthisdoesnotseemcorrectfor
allcases.
AlotofstationsintheNordiccountriesgetclass4or5duetoshadowduringashortperiodof
theyear.Accordingtothesitingclassificationthisisexpectedtogivethesameestimated
uncertaintyasanearbyheatsourcethatwillgiveaninfluenceonthetemperaturemostofthe
year.Withoutdoubt,shadehasaninfluenceonthetemperatureandthecomparisonbetween
twoneighboredNorwegianstationsshowedatemperaturedifferencepossiblycausedbya
prolongedperiodwithshadeonthesensorofabout2°C,categorizedasclass5.However,results
fromthesamestudyandsimilarstudiesfromFinlandandEstoniaalsoshowedthatasignificant
effectontemperaturecouldnotbeseenforshortshadingperiods.
Bothfromliteratureresearch(i.e.Kumamoto,2012;Jinaxia,2014)andownstudiesitcouldalso
beenshown,thatdifferentkindofheatsourcesmayhaveverydifferentimpactsontheair
temperaturenearby:



Waterbodiesseemtohavealargerimpactthanflatheatsourcesduringday.
Theinfluenceofelevatedheatsourcesdependsverymuchonthedirectionofthesite–
anobstacleintheNorthofthesensorscanchangethetemperatureofthesensorby
severaldegrees(forclasses4and5),whileanobstacleintheSouthhardlyhaveany
effect.
Lotsofheatsourcesactsasheatsinksduringnightandthateffectseemstobelarger
thanthewarmingeffectduringday.
Amorereliablequantificationoftheestimatedaddeduncertaintyofthetemperature
measurementsandapossibleadjustmentoftheclass‐limitsarerequired.Bothwouldraisethe
valueofthesitingclassificationschemetremendously.
Theperformedanalysesofselectedstationsshowedthedifficultiesofjustcomparingdatafrom
existingstations.Firstly,itishardtofindsuitablesitesincloseenoughvicinitythathomogenous
temperaturedataseriescanbeassumed.Further,influencesareoftencombined:Aheatsource
mightalsogiveshadeandslopesareoftenconnectedtochangesinelevationwhichhaveamuch
higherimpactontemperature.
Therefore,TheNordiccountrieshighlyrecommendfurtherstudieswithexistingandespecially
withdedicatedstationsandsensorconfigurationstoquantifytheeffectofdifferenttypeofheat
sources,shade,slopesandvegetation.Oneinitiativeperformingcurrentlysuchstudiesisthe
METEOMET‐projectwhichalsocollaborateswiththetheWMO/CIMOexpertteam.
Further,modelstudiescanbeaveryhelpfulandcomplimentarytooltothiseffort.Different
influencescanbeassessedindependentlyfromeachotherandthedistancetothesensororthe
sizeofthefeaturecanbechangedstepless.Forexample,Kinoshita(2014)havesuccessfully
appliedthemodelENVI‐metforsiteexposurestudies.
Additionaleffectsnotyetconsidered
Severalaspectsoftheexposureofasensorarenotyetconsideredinthesitingclassification.
Basedonthegeneralliteratureinmicrometeorology(i.e.Geiger,1995)andmorefocused
studieswithinforest/agricultural(i.e.Dobrowski,2009)andurbanclimatology(Eliassonand
Svennson,2003;Grimmond,2001;Oke,1981;Oke,2006;Shudo,1997;Sailor,1995),itis
suggestedthatthefollowingfeaturesmayhavesignificantinfluenceontemperaturesensors:





Thedirectionoftheslope
Thepositionofthesensorontheslope(withinorwithoutcold‐airdrainageareaor
ratherontopofthehill)
Night‐timeeffects:
o Reductionoflongwaveradiationfromthegroundduetoobstaclesreducingthe
skyview
o Strongercoolingoftypicalflatheatsources(parkinglot,etc)
Obstacles(naturalandartificial)intheNorthwhichchangetheradiationbalanceofthe
areaandthusmayinfluencethetemperaturemeasurementsnearby
Changesinsnowheightandthusthechangingdistancebetweenthesensorandthe
ground.
Offcourse,itisimportanttonotoverloadthesitingschemetoguaranteeitsapplication.The
Nordiccountriessuggesttocooperatewithrelatedscientificcommunities(asforest/agricultural
andurbanclimatology)whendevelopingfurthercategories.
AdaptionofthesiteclassificationintheNordiccountriesTheNordiccountrieswill
continueusingthedevelopedcommonmetadataschemeforevaluatingtheirsites.Bythat,
additionalinformationiscollectedinacomparablewaywhichmayallowadaptingthesiting
classificationtofuturemodifications.
InsteadofreportingonlyonenumberasaresultoftheWMO/CIMOsitingclassification,the
Nordiccountrieswillreportallfournumbersforthefourcategoriesallowingforamore
balancedevaluationofthesite.
TheNordiccountrieswillapplytheWMO/CIMOsitingclassificationwiththefollowing
adaptions:
1. Asimpletime‐parameterwillbeusedadditionaltothesunelevationintheshade‐criterion.
TheNordiccountrieswillneglectshadowingfromobstacleswhichlastslessthan1hour
(equaltoanobstaclewidthof30°).Consequently,theseparationbetweenshadeonsensor
whenthesunishigherthan5°and7°isnotnecessary.
Class1
Awayfrom
projectedshade
whenthesunis
higherthan7°or
shadeonsensor
forlessthan1
hourperday.
Class2
Awayfrom
projectedshade
whenthesunis
higherthan7°or
shadeonsensor
forlessthan1
hourperday.
Class3
Awayfrom
projectedshade
whenthesunis
higherthan7°or
shadeonsensor
forlessthan1
hourperday.
Class4
Awayfromall
projectedshade
whenthesunis
higherthan20°or
shadeonsensor
forlessthan1
hourperday.
Class5
Sitenotmeeting
requirementsfor
class4
2. BecauseofthewidespreadtypicalheathlandvegetationintheNordiccountries,whichis
sparseandoftenreachesanaturallowheightofabout40cm,thevegetationcriterionwillbe
relaxed.Especially,whenthetemperaturesensorismountedin2mheight,theslightly
highervegetationisnotexpectedtohaveanimpactonthetemperaturemeasurements.
Class1
Groundcovered
withnaturaland
lowvegetation
(<10cm)
representativeof
theregion
Class2
Groundcovered
withnaturaland
lowvegetation
(<10cm)
representativeof
theregion
Class3
Groundcovered
withnaturaland
lowvegetation
(<45cm)
representativeof
theregion
Class4
Class5
‐
‐
3. FollowingthepracticeinFinland,forareaswheretheabundanceofwaterincreases30%
withinaradiusof1km,waterbodiesbetween10and100mawayfromtothesensorarenot
consideredforthesitingclassification.
Further,ifalowvegetationareaneedstobemaintained,i.e.withinafieldofcropsorinanurban
area,aplotsizeof6mtimes9misrecommended,inaccordancewiththeGuideto
ClimatologicalPractices(WMO,2011).
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