SPARCStratosphere-troposphereProcesses

AndtheirRoleinClimate

SRIP–SPARCReanalysisIntercomparison Project

SusannTegtmeierGEOMAR,Kiel,Germany

SPARC• Promotes research on how chemical and physical processesin the atmosphere interact with climate variability andchange.• Historically concentrated on the role of the stratosphere inclimate, but now includes foci throughout the atmosphere.

SPARCImplementationPlan•Theme1.AtmosphericDynamicsandPredictability•Theme2.ChemistryandClimate•Theme3.Long-termRecordsforClimateUnderstanding

OCTAV-UTLS– ObservedCompositionTrendsAndVariabilityintheUTLSLOTUS– OzoneTrends

AtmosphericTemperatureChangesandtheirDrivers

New/emergingactivities:

SPARCTheme:Long-termRecordsforClimateUnderstanding

• VerticallyandspatiallyresolvedtrendsinSPARC-relevantECVs?

Ø Whichspeciesandstatevariablesareneeded,andwithwhatresolution,frequency,anduncertainty?

Ø Requirementsonobservingprogramme (uncertaintiesandsamplingregimens)forreliabletrenddetection?

• Istheatmosphere(chemistryanddynamics)evolvinginawaythatisconsistentwithourunderstanding?

• Temporalevolutionofglobalandregionalforcing(naturalandanthropogenic)oftheclimatesystem?

• Docurrentobservationstestourknowledgeofatmosphericcompositionanddynamics?Whichobservationswouldprovidemorerobusttests?

WDACActionsitemsfromlastyear

RegardingthesatellitemissiongapitwasdecidedtosendalettertoCEOS/CGMSWorkingGrouponClimate

• Atmosphericcomposition:limbsounders

Regardingthein-situobservingnetworksatriskitwasdecidedthatWDACwillpreparealetterforJSCtoWMO.

• Continuationofstationswithlong-termrecords,especiallylidar andozonesondes• Homogeneityacrossthegroundnetworks,e.g.O3S-DQAforozonesonde,GRUAN.• ObservationsintropicsandSouthernmid-latitudes

FISAPS- FineScaleAtmosphericProcessesandStructures

M.Geller,H.Chun,P.Love

• Focusonatmosphericprocessesimportantforlarge-scaledynamicsandchemicalcompositionthatoccuronverticalscalesoflessthan1km

• Goals:enhanceavailabilityofhighvertical-resolutionradiosondedata(HVRRD)

Radiosondereportssortedbyverticallevels

IncreasingneedforresearchaccesstoHVRRD(currentlygrowinguseinreal-timeforecasting)

EncouragedataproducerstoworktowardshighresolutionBUFRdata

CurrentdiscussionofavailabilitythroughIGRA(verypreliminary)

SRIP- SPARCReanalysisIntercomparison Project

Masatomo Fujiwara(HokkaidoUniv.,Japan),LesleyGray(OxfordUniv.,UK),GloriaManney (NWRA,USA)

http://s-rip.ees.hokudai.ac.jp/

Objectives• Compare all (or some of the newer) reanalysis data sets for key diagnostics• Identify and understand the causes of differences amongst reanalyses• Provide guidance on the appropriate usage of various reanalysis products in

scientific studies• Establish collaborative links between reanalysis centres and the SPARC

community• Contribute to future improvements in reanalysis products

S-RIP focuses on reanalysis outputs in the stratosphere, upper troposphere andlower mesosphere

Prime Output:• S-RIP “interim” Report (2016), four ‘basic’ chapters• S-RIP “full” Report (2018), twelve chapters in total

Motivation• Multiplestudieshaveidentifiedsubstantialdifferencesamongstreanalyses

withrespecttokeyvariablesanddiagnostics.

ReanalysisCentre

Products Contacts for S-RIP

ECMWF ERA-40, ERA-Interim, ERA-20C, [ERA5] Rossana DraganiJMA (&CRIEPI) JRA-25/JCDAS, JRA-55 Yayoi Harada &

Kazutoshi OnogiNASA MERRA, MERRA-2 Krzysztof Wargan

NOAANCEP NCEP/NCAR (R-1), NCEP/DOE (R-2),NCEP-CFSR

Craig Long &Wesley Ebisuzaki

NOAA&Univ.Colorado

20CR Gilbert Compo &Jeffrey S. Whitaker

GlobalAtmosphericReanalysisDataSets

• Focusonnewerreanalysissystemsthatassimilateupper-airmeasurements(ERA-Interim,JRA-55,MERRA,MERRA-2,CFSR)

• ERA5 willnotbeincluded(sincetimeperiod1979-2009notavailableuntil2018)• Whereappropriate,includeotherreanalyses:

• Long-term,surface-inputreanalyses (e.g.NOAA-CIRES20CRandERA-20C)• Olderreanalyses (NCEP-NCARR1,NCEP-DOER2,ERA-40,andJRA-25/JCDAS)

• Theintercomparison periodcommontoallchapters:1979-2012• Somechapterswillalsoconsiderthepre-satelliteeraand/orincluderesultsforrecentyears.

Chapter Title Chapter Co-leads1 Introduction Masatomo Fujiwara, Gloria Manney,

Lesley Gray2 Description of the Reanalysis Systems Jonathon Wright, Masatomo Fujiwara,

Craig Long3 Climatology and Inter-annual Variability

of Dynamical VariablesCraig Long, Masatomo Fujiwara

4 Climatology and Inter-annual Variabilityof Ozone and Water Vapour

Michaela Hegglin, Sean Davis

5 Brewer-Dobson Circulation Thomas Birner, Beatriz Monge-Sanz6 Stratosphere-Troposphere Coupling Edwin Gerber, Patrick Martineau7 Extratropical UTLS Cameron Homeyer, Gloria Manney8 Tropical Tropopause Layer Susann Tegtmeier, Kirstin Krüger9 QBO and Tropical Variability James Anstey, Lesley Gray10 Polar Processes Michelle Santee, Alyn Lambert,

Gloria Manney11 Upper Strato. Lower Mesosphere Lynn Harvey, John Knox12 Synthesis Summary Fujiwara, Manney, Gray

Chapters1-4:Basicchapters2016(nowearly2017)Chapters5-11:Advancedchapters(end2018)

ChaptersoftheS-RIPReport

S-RIP2017InterimSPARCReport(Basicchapters)• Editors:M.Fujiwara,J.Wright,G.Manney,andL.Gray• Technicaleditors:FionaTummon andSPARCOfficecolleagues• Reportstatus:firstrevisionphase• Reviewprocessissimilartothatofjournalpublications

• minimum3-4reviewersperchapter• tworoundsofreviews

• Willbepublishedin2017

S-RIP2018FinalSPARCReport(Advancedchapters)• ZeroorderdraftsofeachchapterinOctober2016• FinaldraftsplannedforOctober2017• Beginningofreviewprocessendof2017

Chapter1:Introduction• Motivation,goals,scope,outline,communication,prospectsetc.

Chapter2:DescriptionoftheReanalysisSystems• Referenceforreanalysisusers• Understandhowreanalyses workusingsimpleterms• Comparethestructuresoftwoormorereanalyses• Sourcesofadditionalinformation,extensiveuseoftables/figures• Informationonpotentialtemporaldiscontinuities

S-RIP2017InterimSPARCReport(Basicchapters)

2.1Introduction

2.2Forecastmodels(includingmajorphysicalparametrizations andboundaryconditions)

2.3 Assimilationschemes(basicsandapplicationsinreanalysissystems

2.4Observationaldata(includingkeyupperairobservations,watervapour)

2.5Executionstreams

2.6Archiveddata

Chapter2:DescriptionoftheReanalysisSystemsJ.Wright,M.Fujiwara,C.Long

Chapter2Tables/Figures• Reanalysisdatasetwithdatesandjournalpapers• Horizontalresolution,verticallevels,modeltop• Radiativetransferschemes,cloudscheme,gravitywavescheme• SST/seaicetreatment,solarvariabilitytreatment• Ozonetreatment,aerosolschemes,CO2 +otherGHGstreatments• Assimilationschemeemployed,satelliteradianceassimilationschemeemployed• Satellitedatasetsandotherdatasets(e.g.aircraft)assimilated• Watervapour treatment

AssimilatedsatelliteradiancedatasetsSimplifiedschematicfordataassimilationstrategies

1980 2015

TOVS

ATOVS

Execution‘streams’employedtoproducethevariousreanalysisdatasets1979-2016

ERA-I

JRA-55

MERRA

MERRA-2

CFSR

• AnintroductiontoS-RIP(motivation,objectives,reportstructure)• descriptionofelevencurrentorrecentreanalyses:

• ERA-40,ERA-Interim,ERA-20C• JRA-25/JCDAS,JRA-55• MERRA,MERRA-2• NCEP-NCARR1,NCEP-DOER2,CFSR,NOAA-CIRES20CRv2

• Forecastmodelspecs(grids,dynamicalcores,parametrizations,boundaryconditions)• Dataassimilationoverview(briefaccountofmethodsemployed)• Inputobservations(conventionalandsatellite-based,changesintime,keydatasourcesandarchives,

qualitycontrolandbiascorrectionprocedures)• Ozoneandwatervapour (relevantparametrizations,detailsofdataassimilation)

AcknowledgementsandthankstothemanyS-RIPparticipantswhoprovidedinputandfeedbackforthispaper— thiswastrulyacollaborativeeffort

S-RIPoverviewpaperinACP:IntroductiontotheSPARCReanalysisIntercomparisonProject(SRIP)andOverviewoftheReanalysisSystems

Fujiwaraetal.

SpecialIssueintheAtmosphericChemistryandPhysics(ACP):

“TheSPARCReanalysisIntercomparison Project(S-RIP)”Editors:P.Haynes,G.Stiller,andW.Lahoz

• IntendedtocollectresearchwithrelevancetoS-RIP

• ParticipationinS-RIPisnotaprerequisiteforsubmission

• 10paperssofar,includinganS-RIPoverviewpaper,with8publishedand5atdiscussionstage

• Fujiwaraetal.(ACP,2017):IntroductionS-RIPandoverviewofthereanalysissystems• Hoffmannetal.,(ACPD,2017)ValidationofmeteorologicalanalysesandtrajectoriesintheAntarcticlowerstratosphere

usingConcordiasi superpressure balloonobservations• Nützel etal.,(ACP,2016)Movement,driversandbimodalityoftheSouthAsianHigh• Boothe andHomeyer (ACPD,2016)Globallarge-scalestratosphere-troposphereexchangeinmodernreanalyses• KimandChun,(ACP,2015)Momentumforcingofthequasi-biennialoscillationbyequatorialwavesinrecentreanalyses• Fujiwaraetal.(ACP,2015):Globaltemperatureresponsetothemajorvolcaniceruptionsinmultiplereanalysisdatasets• Kawatani etal.(ACP,2016):Representationofthetropicalstratosphericzonalwindinglobalatmosphericreanalyses• Miyazakietal.(ACP,2016):Inter-comparisonofstratosphericmean-meridional circulationandeddymixingamongsix

reanalysisdatasets• Friedrichetal.(ACP,2017):AcomparisonofLoonballoonobservationsandstratosphericreanalyses products• Wunderlich &Mitchell(ACP,2017):Revisitingtheobservedsurfaceclimateresponsetolargevolcaniceruptions

• Reanalysestemperaturevariabilitywithtime• Reanalysesensemblemean• Intercomparison ofthereanalyses(temperature,zonalwind)• Polarannualtemperaturecycle• Comparisonwithindependentobservations(MLS,HIRLDS,Ozonesondes,Balloons,Rocketsondes)

• Effectsofvolcaniceruptionsonreanalysestemperaturesandwind• Majorconclusions

• Reanalyes shouldNOTbeusedfortrends.• Thereisnoone'perfect'reanalyses. Theyallhaveissues.• Reanayses havetemperatureandwindbiasesinthemiddleandupperstratospherewithrespect toeachother.Witheachgenerationofreanalysesthesebiaseshavebeengettingsmaller.

• Reanalyses allhave'issues'gettingthetropicalstratosphericwindscorrect.

Chapter3:ClimatologyandInterannual VariabilityofDynamicalVariables

C.Long,M.Fujiwara

• Reanalysestemperaturevariabilitywithtime

• Reanalysesensemblemean

• Intercomparison ofthereanalyses(temperature,zonalwind)

• Polarannualtemperaturecycle

• Comparisonwithindependentobservations(MLS,HIRLDS,Ozonesondes,Balloons,Rocketsondes)

• Effectsofvolcaniceruptionsonreanalysestemperaturesandwind• Reanalysistemperaturesagreewellbelow10hPa• Largediscontinuitiesassociatedwiththe~1998transitionfromTOVS(SSU+MSU)toATOVS(AMSU)• CFSR:severaldiscontinuitiesassociatedwithproductionstreamchangesandthechangeinmodelresolution• CFSRmodelimpartsawarmbiasintheupperstratosphere• JRA-55containsayear-roundcoldbiasintheupperstratosphere• ERA-Interimisbiasedwarminthesouthernpolarvortexnear7~5hPa• MERRAcontainsaslightcoldbiasat1hPa relativetoAuraMLS• AssimilationofAuraMLS temperatureretrievalsatpressureslessthan5hPa causesajumpinMERRA-2upper

stratospherictemperatures• Disagreementsamongstreanalyses arereducedduringtheATOVSperiod(post-1998)relativetotheTOVSperiod• Significantbiasesinearlierreanalyses (JRA-25,ERA-40,NCEPR1/R2)arelarger,morepersistent,andextend

throughadeeperverticallayer• EvaluationsagainstAuraMLS,ozonesondes,long-durationballoonexperiments,andun-assimilatedradio- and

rocketsondes

Chapter3:ClimatologyandInterannual VariabilityofDynamicalVariables

C.Long,M.Fujiwara

Global Temperature Anomalies1979-2016

CFSR MERRA

MERRA2ERA-I

JRA55Global temperature anomalies reveal discontinuities in the middle and upper stratosphere due to stream and data transitions. Most notably is the transition from TOVS to ATOVS observations in late 1998. Other features observed are: El Nino warm period in troposphere in 1998, 2010 and 2016, and the lower stratospheric warming due to El Chichón and Mt Pinatubo in 1982 and 1991, respectively.

Equatorialzonalwinds(10°S–10°N) anddifferencefromensemble-mean(ERA-I+JRA-55+MERRA)

CFSR

MERRA

ERA-Interim

JRA-55

MERRA-2

Seasonal cycle Time series(1979–2015)

Jan Dec

1hPa

1979 2015

1000

Overall1.Continuedimprovementinmeteorologicalreanalyses andpastrecords2.Continuationofexistingcoremeasurements– realfundingpressure

Specific• Lackofplannedsatelliteobservations(esp.limb)ofUTScomposition• Needup-to-dateAMSUandmergedSSU-AMSUclimatedatarecords• Availabilityofhighvertical-resolutionradiosondedata• Needformorereference-qualityglobal&long-termobservations,particularlyforreanalysisintercomparisons

• Noplannedcontinuationofmesosphericradiancefortemperatures•Needforquickresponsefieldcampaignsaftervolcaniceruptions• Datasharingisachallengeinthe‘AsianMonsoonregion’

SPARCDataneedsandrequirements

Chapter4: Climatologyandinterannualvariabilityofozone

• Treatmentofozone• AllofthereanalysissystemsexceptforNCEPR1andR2includesomeformofprognosticozone

parametrizationandanalysis,butnoneoftheseincludeheterogeneouschemistry(usewithcautionforozoneholestudies)

• Todate,onlysatelliteozoneretrievalsareassimilated(noozonesondes)• Inputobservationsvarywidely,fromtotalcolumnonly(JRA-25andJRA-55)tocoarse-

resolutionprofileinformation(ERA-40,MERRA,CFSR)toabroadselectionofsatelliteproducts(ERA-Interim)

• ECMWFreanalysesuseclimatologiesratherthananalysesforradiationcalculations

• Keyconclusionsandobservationalevaluation• Climatologies,annualcyclesandinterannualvariabilitygenerallyagreewellwithobservational

data,despitesomeissuesinJRA-25andERA-40• Totalcolumnozoneismostlycapturedbyreanalyses,withsomelimitations(e.g.,noColumn

Ozone dataduringpolarnight)• Theozoneverticaldistributionisweaklyconstrainedbydataassimilation,sothatmeanbiases

inozoneproductsvarywithheight(10~50%instratosphere)• QBOsignalsarevastlyimprovedinJRA-55relativetoJRA-25• Allreanalysesfailtocapturethe“ozonevalley”associatedwiththeAsianmonsoonanticyclone

Height-latitudecolumnozoneclimatology:differencefromSBUV(DU)AlsoshownistheTOMS/OMIdifferencewithSBUV.

Ozoneverticaldistribution:%differencesofannual-av climatology(2005-2010)fromtheSPARCDataInitiativemulti-instrumentmean(MIM;i.e.Ri-MIM)/MIM*100.)

1hPa

100

S N

CFSR JRA-25 MERRA

ERA-I JRA-55 MERRA-2

OzoneQBOsignal2005-201010oS-10oN

2005 2010

1hPa

100hPa

Obs

ERA-I

JRA-55

JRA-25

CFSR

MERRA-2

MERRA

Chapter4: Climatologyandinterannualvariabilityofwatervapour

• Treatmentofwatervapour• ReanalysisWVisafunctionofdehydration,transport,andforsome

reanalysesmethaneoxidation(ERA-40,ERA-Interim,ERA-20C),icesupersaturation(ERA-InterimandERA-20C),and/orrelaxationtoclimatology(MERRAandMERRA-2)

• Dataassimilationhaslimitedornoinfluenceinthestratosphere(specificationandtreatmentoftheupperboundvaries)

• Fieldsusedforradiationcalculationsinthestratosphereoftendifferfromreanalysisproducts

• Keyconclusionsandobservationalevaluation• ModerateagreementamongstreanalysesintheUTLS• MajorissuesinJRA-55atmid–highlatitudesandpressureslessthan200

hPa• CFSRisverydry(withsomenegativemixingratios)inthestratosphere• Comparisonoftransportsimulationsandtaperecordersignalsreveals

severalimportantdiscrepanciesincirculationandtemperatures• ReanalysisstratosphericWVshouldnotbeusedinscientificstudies!

Multi-annualmeanzonalmeancross-sectionsofwatervapour (2005-2010)forSPARCDataInitiativemulti-instrumentmean(MIM;upperright)andvariousreanalysisdatasets

0.1hPa

100hPa

S N

Obs

CFSR MERRA

MERRA-2

JRA-25

JRA-55ERA-I

S-RIP2017workshop• Place:

• EuropeanCentreforMedium-RangeWeatherForecasts,ECMWF,U.K.• When (withjointDAworkshop)

• 23-27October2017

• Host:ECMWF• BeatrizMonge-Sanz,Rossana Dragani

• Facilities• LectureTheatre,meetingrooms,posterboards• Wi-Fi,cafeteria,restaurant• Parkingonsiteorpublictransportfromtown• Manyhotelsintown,offerspecialECMWFrates• Londonisreasonablyclosefor“commuting”• Twomajorairports(Heathrow,Gatwick)

• Costsestimate• Nocostformeetingroomsandequipment• Coffeebreakandlunchatextracostà registrationfee/smallSPARCcontribution

andself-fundedlunch?

Figure 1: Plot showing current isentropic level offerings from CFSR (green), ERA-I (blue), JRA-55 (purple), along with our minimum (light gray), reduced (dark gray) and full (black) recommendations up to 1500 K.

Figure 2: Plot showing sampling of our minimum (light gray), reduced (dark gray) and full (black) recommendations above 1000 K.

Motivation for Above Recommendations The full, reduced, and minimum recommendations outlined above are designed with balance in mind such that reanalysis centers could independently choose from among the three and still provide many overlapping levels throughout the atmosphere, as well as providing data for previously unrepresented regions (i.e., the USLM). As a result, two evident motivations come to mind:

1. While it would be ideal to have all datasets use the same isentropic levels, these recommendations should give the data-providers some leeway to fit their own time/space constraints.

2. There is plenty of overlap between each recommendation, which will facilitate intercomparisons, and encourage data-users to make use of multiple datasets in their analyses and studies.

We also note that there are other considerable benefits of data-providers making more isentropic levels available. One reason, in particular, is that the data-providers/reanalysis centers already have the

Figure 1: Plot showing current isentropic level offerings from CFSR (green), ERA-I (blue), JRA-55 (purple), along with our minimum (light gray), reduced (dark gray) and full (black) recommendations up to 1500 K.

Figure 2: Plot showing sampling of our minimum (light gray), reduced (dark gray) and full (black) recommendations above 1000 K.

Motivation for Above Recommendations The full, reduced, and minimum recommendations outlined above are designed with balance in mind such that reanalysis centers could independently choose from among the three and still provide many overlapping levels throughout the atmosphere, as well as providing data for previously unrepresented regions (i.e., the USLM). As a result, two evident motivations come to mind:

1. While it would be ideal to have all datasets use the same isentropic levels, these recommendations should give the data-providers some leeway to fit their own time/space constraints.

2. There is plenty of overlap between each recommendation, which will facilitate intercomparisons, and encourage data-users to make use of multiple datasets in their analyses and studies.

We also note that there are other considerable benefits of data-providers making more isentropic levels available. One reason, in particular, is that the data-providers/reanalysis centers already have the

RequestforPVonIsentropicSurfaces:conductaquicksurveytoascertainthattheserecommendationswillprovidewhatisrequiredbythecommunity?

CommentsreceivedattheSSGmeetingreportedbyLesleyGray

• TherewassomediscussionabouttherelationshipbetweenS-RIPandthetroposphericreanalysisintercomparisonthatmightfallundertheTIRAinitiative.• Therewasgreatsupportforthereanalysisinter-comparisonsgoingonwithinS-RIPanda

needtoextendthemmoretodirecttroposphericcomparisons(e.g.howwelldothereanalyses comparewithregardtospecifictroposphericfeaturessuchascirculationpatternsandfeatureslikethemonsoons)- anditwasfeltthatthiswaswhatTIRAwouldbeplanning.

• Therewassupportfortheideaofcollectinguserrequirementse.g.PVonisentropicsurfacesandfeedingthemthroughtotheReanalysisCentres.

• Therewasstrongencouragementforourideaofpullingtogetherthevarioustablesofinformationoneachreanalysisdataset,toencouragetheCentres toprovideastandardsetofinformationforeachfuturedataset.Theyhelpfullysuggestedthatthismightbeturnedintoa'livingdocument'onaweb-site(SPARC?S-RIP?)thatcouldcontinuetobeupdatedintothefuture.

• FionaTummon saidsheishappytobethehandlingeditor,sothatreviewerscanbeanonymous.