Documentation of CAMS Climate Forcing products, version 0

ECMWFCOPERNICUSREPORT

Copernicus Atmosphere Monitoring Service

DocumentationofCAMSClimateForcingproducts,version0

Issuedby:UniversityofReading/NicolasBellouinandco-authors

Date:29/12/2016

Ref:CAMS74_2016SC1_D74.1-1_201612_Documentation_v1

ThisdocumenthasbeenproducedinthecontextoftheCopernicusAtmosphereMonitoringService(CAMS).TheactivitiesleadingtotheseresultshavebeencontractedbytheEuropeanCentreforMedium-RangeWeatherForecasts,operatorofCAMSonbehalfoftheEuropeanUnion(DelegationAgreementsignedon11/11/2014).Allinformationinthisdocumentisprovided"asis"andnoguaranteeorwarrantyisgiventhattheinformationisfitforanyparticularpurpose.Theuserthereofusestheinformationatitssoleriskandliability.Fortheavoidanceofalldoubts,theEuropeanCommissionandtheEuropeanCentreforMedium-RangeWeatherForecastshasnoliabilityinrespectofthisdocument,whichismerelyrepresentingtheauthorsview.

CopernicusAtmosphereMonitoringService

CAMS74_2016SC1-DocumentationofCAMSClimateForcingproducts,version0 Page3of41

Contributors

UNIVERSITYOFREADINGN.BellouinW.DaviesK.Shine

UNIVERSITYOFLEIPZIGK.BlockJ.MuelmenstaedtJ.QuaasUNIVERSITYOFLEEDSP.ForsterL.RegayreC.Smith



TableofContents

1. Alphabeticallistofproducts 9

2. Fileaccessandnamingconvention 13

3. Carbondioxideandmethane 16

3.1Productspecifications 163.1.1Carbondioxide 163.1.2Methane 173.2Methods 183.2.1Radiativetransfercalculations 183.2.2Inputstotheradiativetransfercode 203.2.3Pre-industrialatmosphericconcentrations 233.3Uncertainties 23

4. Troposphericandstratosphericozone 23

4.1Productspecifications 234.2Methods 244.2.1Radiativetransfercalculations 244.2.2Inputstotheradiativetransfercode 244.2.3Pre-industrialatmosphericconcentrations 244.3Uncertainties 25

5. Speciatedaerosolopticaldepths 25

5.1Productspecifications 255.2Methods 265.2.1Identificationofaerosolorigin 265.2.2Inputstothealgorithm 285.3Uncertainties 28

6. Aerosol-radiationinteractions 29

6.1Productspecifications 296.2Methods 306.2.1Inputstothealgorithm 326.2.2Pre-industrialaerosolopticaldepths 326.3Uncertainties 32

7. Aerosol-cloudinteractions 34

7.1Productspecifications 347.2Methods 347.2.1Cloudcondensationnuclei 35



7.2.2Clouddropletnumberconcentrations 357.2.3CalculationofRFaci 367.3Uncertainties 37

8. Listofacronyms 38

9. References 39

10. Usersupportandcontacts 40



IntroductionPleaserefertosection8forthedefinitionofallacronyms.

Radiative forcing (RF) measures the imbalance in the Earth’s energy budget caused by aperturbation of the climate system, for example changes in atmospheric composition driven byhuman activities (Myhre et al., 2013). RF is a useful predictor of globally-averaged temperaturechange,especiallywhenrapidadjustmentsofatmospheric temperatureandmoistureprofilesaretaken into account (Boucher et al., 2013). RF has therefore become a quantitative metric tocompare the potential climate response to different perturbations. Increases in greenhouse gasconcentrationsovertheindustrialeraexertedapositiveRF,causingagainofenergyintheclimatesystem.Incontrast,concurrentchangesinatmosphericaerosolconcentrationsarethoughttoexertanegativeRFleadingtoalossofenergy.Chapter8oftheIPCCAR5estimatesnettotalindustrial-eraRFat+2.3Wm−2withabroadconfidenceintervalof+1.1to+3.3Wm−2(Myhreetal.,2013).EstimatesforkeyforcingagentsfromtheIPCCAR5aresummarisedinTableI.1below.Themethodsused to estimate RF of different species in the IPCC AR5 are diverse: global modelling ofatmospheric composition, line-by-line radiative transfer calculations, simplified calculations, orobservational-basedcalculations.TheCAMSClimateForcingserviceaimsatrefiningthoseestimatesbyproviding inaconsistentway thedistributions,globalaverages,anduncertaintiesof theRFofkeyatmosphericconstituent.

TableI.1-EstimatesofRadiativeForcingandEffectiveRadiativeForcingforchangesinatmosphericcompositionbetween1750and2011,takenfromTables8.2and8.6oftheIPCCAR5(Myhreetal.,2013).

Forcingagent RadiativeForcingRF(Wm−2)

EffectiveRadiativeForcingERF(Wm−2)

CO2 +1.82±0.19 CH4 +0.48±0.05 N2O +0.17±0.03 Halocarbons +0.360±0.036 Totalwell-mixedgreenhousegases +2.83(2.54to3.12) +2.83(2.26to3.40)Troposphericozone +0.40(0.20to0.60) Stratosphericozone −0.05(−0.15to+0.05) Stratospheric water vapour frommethane

+0.07(+0.02to+0.12)

Aerosol-radiationinteractions −0.35(−0.85to+0.15) −0.45(−0.95to+0.05)Aerosol-cloudinteractions −0.45(−1.2to0.0)

CAMSClimateForcingprovidesRFseparatelyfor:

• carbondioxide• methane• troposphericozone



• stratosphericozone• interactionsbetweenanthropogenicaerosolsandradiation• interactionsbetweenanthropogenicaerosolsandclouds

andtheiruncertainties.Foraerosols,CAMSClimateForcingalsoproducesdistributionsofaerosolopticaldepths,distinguishingnaturalfromanthropogenicaerosols.

This documentation describes “version 0” RF estimates,which are essentially a first draft of theactualproducts,whichwillbepublishedinmid-2017.Version0productsincludeseveralsimplifyingassumptionsthatwillbeimproveduponinthefuture:needsforfurtherimprovementsareclearlylistedintheboxeslabelled“Futureimprovements”inthisdocument.Therefore,version0productsshouldbeusedwithcaution,becausetheyarenotnecessarilybasedonstate-of-the-artmethods,theyarenotyetatthelevelofconsistencytargetedbyCAMS,andmaycontainmistakes.

CAMS Climate Forcing estimates follow the definitions for instantaneous and stratospherically-adjustedRFgivenintheIPCCAR5(Myhreetal.,2013):

• Instantaneous RF is the “instantaneous change in net (down minus up) radiative flux(shortwavepluslongwave;inWm–2)duetoanimposedchange.”

• Stratospherically-adjustedRF,hereafterreferredtosimplyasadjustedRF,is“thechangeinnetirradianceatthetropopauseafterallowingforstratospherictemperaturestoreadjusttoradiative equilibrium, while holding surface and tropospheric temperatures and statevariablessuchaswatervapourandcloudcoverfixedattheunperturbedvalues”.

ThereferencestateistakenbyCAMSClimateForcingproductstobeyear1750,exceptforaerosolRF, which is defined with respect to present-day natural aerosol and scaled to pre-industrialconditions.(Seesection6.)Radiativeeffect(RE)isalsoquantifiedforaerosols:thedifferencewithRFisthatREisdefinedwithrespecttoanatmospherethatcontainsnoaerosols.

CAMS instantaneous forcing is quantified in terms of flux changes at the top of the atmosphere(TOA)andthesurfaceforallspecies,butalsoattheclimatologicaltropopauseforcarbondioxide,methane,andozone.CAMSadjustedRFiscurrentlyonlyquantifiedattheclimatologicaltropopausefor carbon dioxide, methane, and ozone. Adjusted RF is not yet given for aerosol perturbationsbecauseitdiffersonlyslightlyfrominstantaneousRFattheTOA.

CAMSClimateForcingproductsarequantifiedbydefault in“all-sky”conditions,meaningthattheradiative effects of clouds are included in the radiative transfer calculations. Products denoted“clear-sky”arecomputedbyexcludingcloudsintheradiativetransfercalculations.

IPCC AR5 further defines effective radiative forcing (ERF) as “the change in net TOA downwardradiativefluxafterallowingforatmospherictemperatures,watervapourandcloudstoadjust,butwithsurfacetemperatureoraportionofsurfaceconditionsunchanged.”ERFestimatesbytheIPCCAR5aregiveninTableI.1above.ERFestimatesbyCAMSClimateForcingareplannedaspartofanevolutionofRFproductsin2018.



FigureI.1illustratestheRFproductionchainthatwillbeinplaceforversion1RFproductsin2017.Version0productsarebasedonadevelopmentalversionofthatproductionchain.

FigureI.1-Diagramoftheradiativeforcingproductionchain(lightorange),whichtakesinputsfromthe the CAMS Global Reanalysis (blue) and produces radiative forcing estimates and theiruncertainties(darkorange).Greenboxesindicateobservationalconstraints.BBstandsforbiomassburning,AODforaerosolopticaldepth,andCCNforcloudcondensationnuclei.RRTMGistheRapidRadiativeTransferModelforGeneralCirculationModels.Redboxesandlinesindicateaspectsthatdifferorareyettobeimplementedinversion0,asdiscussedinthetext.

Thesourceofatmosphericcompositiondata isaGlobalReanalysisperformedbytheECMWFIFS.That reanalysis includes assimilation of satellite retrievals of atmospheric composition, thusimproving RF estimates compared to free-running models. Improvements derive directly fromobservational constraints on reactive gas columns and aerosol optical depths and, for ozone,verticalprofiles.Dataassimilationalsoconstrainsgaseousandbiomass-burningaerosolemissions,leading to indirect improvements in the simulation of atmospheric concentrations. The RFproductionchainthereforereliesinpriorityonvariablesimprovedbythedataassimilationprocess(gas mixing ratios, total aerosol optical depth). However, it is not possible to solely rely onassimilatedvariablesbecauseothercharacteristicsofthemodelaffectRFdirectly(verticalprofilesofaerosolsandgases, speciationof totalaerosolmass)or indirectly (cloudcoverandcloud type,surface albedo, temperature and moisture profiles). Inaddition, parameters required by the RFestimatebutnotsimulatedbytheGlobalReanalysis(e.g.aerosolsizedistributions)areprovidedbyancillarydatasets.



Version0differs fromthe finalproductionchaindepicted inFigure I.1 in four importantaspects.ThosedifferencesarehighlightedinredinFigureI.1,anddescribedasfollows.Themainobjectiveofdevelopmentstowardsversion1productswillbetoremovethosedifferences.

1. Version 0 takes most distributions of atmospheric properties from the MACC GlobalReanalysis dataset, which covers 2003—2012. Concentrations of carbon dioxide andmethanearetakenfromthird-partydatasetsbecausetheMACCreanalysisisstronglybiasedin those two variables. The version1 production chain will use the new CAMS GlobalReanalysis,andwillbeabletorelyonsimulatedcarbondioxideandmethanedistributionsbecauseofimprovementsinthemodellinganddataassimilationsystems.

2. Version0definesRFagainstapre-industrial state that isspecified ina ratherad-hocway,with no consistency between forcing agents. The version 1 production chain will rely ondedicatedsimulationsofthepre-industrialatmosphere,consistentforallspeciesandusingthemodelthatprovidesthepresent-dayCAMSGlobalReanalysis.

3. Version0computesRFusingthreedifferentradiativetransfercodes:o Streamer(KeyandSchweiger1988),awrappertoDISORT,foraerosol-radiationRF;o theECHAMradiativetransfercode(Stevensetal.2015),foraerosol-cloudRF;o the IFS radiative transfer code (see section 3.2.1), which is a dedicated version of

RRTMG(Mlaweretal.1997).

Theversion1productionchainwillusetheIFSRRTMGforallforcingagents.

4. Version0usesasimplifieduncertaintyanalysis.Foraerosol-radiationandaerosol-cloudRF,uncertaintiesarebasedonaperturbedphysicsensembleappliedtoaglobalaerosolmodel.It is here assumed that those uncertainties are representative of uncertainties associatedwith the IFSGlobal Reanalysis. For greenhouse gas andozoneRF, uncertainties are takenfrom the IPCC AR5. Uncertainties in the version 1 production chain will be morerepresentativeoftheradiativetransfercodeused,andmadeconsistentacrossspecies.

1. AlphabeticallistofproductsAsofDecember2016,theCAMSClimateForcingservicepublishes47differentproducts:

- 13forcarbondioxide;- 7formethane;- 22 for aerosol-radiation interactions, including speciated aerosol optical depths and

radiativeeffects;- 5foraerosol-cloudinteractions.

Table1.1liststhemaincharacteristicsoftheCAMSClimateForcingproductsandthesectioninthisdocumentwheremoredetailedinformationcanbefoundabouteachproduct.



Table 1.1 -Alphabetical listby variablenameofCAMSClimateForcingproducts,asofDecember2016.# Variablename Forcingagent Description RE/RF

type andspectrum

Periodcovered

Section

1 abs550anth Aerosols AnthropogenicabsorptionAOD

N/A 2003—2012 5

2 abs550dust Aerosols Mineral dustabsorptionAOD

N/A 2003—2012 5

3 abs550landnat Aerosols Land-basednaturalabsorptionAOD

N/A 2003—2012 5

4 abs550marine Aerosols MarineabsorptionAOD

N/A 2003—2012 5

5 arf_ch4_trop_lw Methane RF attropopause

Adjusted,LW

2003—2012 3

6 arf_co2_trop_lw Carbondioxide RF attropopause

Adjusted,LW

2003—2012 3

7 od550aer Aerosols TotalAOD N/A 2003—2012 58 od550anth Aerosols Anthropogenic

AODN/A 2003—2012 5

9 od550dust Aerosols Mineral dustAOD

N/A 2003—2012 5

10 od550landnat Aerosols Land-basednaturalAOD

N/A 2003—2012 5

11 od550marine Aerosols MarineAOD N/A 2003—2012 512 reari_anth_srfcs Aerosols Clear-sky

anthropogenicaerosol-radiation RE atsurface

Instant,SW

2003—2012 6

13 reari_anth_toacs Aerosols Clear-skyanthropogenicaerosol-radiation RE atTOA

Instant,SW

2003—2012 6

14 reari_dust_srfcs Aerosols Clear-skymineral dustaerosol-radiation RE atsurface

Instant,SW

2003—2012 6

15 reari_dust_toacs Aerosols Clear-skymineral dustaerosol-

Instant,SW

2003—2012 6



radiation RE atTOA

16 reari_landnat_srfcs Aerosols Clear-sky land-based naturalaerosol-radiation RE atsurface

Instant,SW

2003—2012 6

17 reari_landnat_toacs Aerosols Clear-sky land-based naturalaerosol-radiation RE atTOA

Instant,SW

2003—2012 6

18 reari_marine_srfcs Aerosols Clear-skymarine aerosol-radiation RE atsurface

Instant,SW

2003—2012 6

19 reari_marine_toacs Aerosols Clear-skymarine aerosol-radiation RE atTOA

Instant,SW

2003—2012 6

20 rfaci_srf_lw Aerosols Aerosol-cloudRFatsurface

Instanta,LW

2007—2010 7

21 rfaci_srf_sw Aerosols Aerosol-cloudRFatsurface

Instanta,SW

2007—2010 7

22 rfaci_toa_lw Aerosols Aerosol-cloudRFatTOA

Instanta,LW

2007—2010 7

23 rfaci_toa_sw Aerosols Aerosol-cloudRFatTOA

Instanta,SW

2007—2010 7

24 rfari_srfcs Aerosols Clear-skyaerosol-radiation RF atsurface

Instanta,SW

2003—2012 6

25 rfari_srf Aerosols Aerosol-radiation RF atsurface

Instanta,SW

2003—2012 6

26 rfari_toacs Aerosols Clear-skyaerosol-radiation RF atTOA

Instanta,SW

2003—2012 6

27 rfari_toa Aerosols Aerosol-radiation RF atTOA

Instanta,SW

2003—2012 6

28 rf_ch4_srf_lw_cs Methane Clear-sky RF atsurface

Instant,LW

2003—2012 3



29 rf_ch4_srf_lw Methane RFatsurface Instant,LW

2003—2012 3

30 rf_ch4_toa_lw_cs Methane Clear-sky RF atTOA

Instant,LW

2003—2012 3

31 rf_ch4_toa_lw Methane RFatTOA Instant,LW

2003—2012 3

32 rf_ch4_trop_lw_cs Methane Clear-sky RF attropopause

Instant,LW

2003—2012 3

33 rf_ch4_trop_lw Methane RF attropopause

Instant,LW

2003—2012 3

34 rf_co2_srf_lw_cs Carbondioxide Clear-sky RF atsurface

Instant,LW

2003—2012 3

35 rf_co2_srf_lw Carbondioxide RFatsurface Instant,LW

2003—2012 3

36 rf_co2_srf_sw_cs Carbondioxide Clear-sky RF atsurface

Instant,SW

2003—2012 3

37 rf_co2_srf_sw Carbondioxide RFatsurface Instant,SW

2003—2012 3

38 rf_co2_toa_lw_cs Carbondioxide Clear-sky RF atTOA

Instant,LW

2003—2012 3

39 rf_co2_toa_lw Carbondioxide RFatTOA Instant,LW

2003—2012 3

40 rf_co2_toa_sw_cs Carbondioxide Clear-sky RF atTOA

Instant,SW

2003—2012 3

41 rf_co2_toa_sw Carbondioxide RFatTOA Instant,SW

2003—2012 3

42 rf_co2_trop_lw_cs Carbondioxide Clear-sky RF atthetropopause

Instant,LW

2003—2012 3

43 rf_co2_trop_lw Carbondioxide RF at thetropopause

Instant,LW

2003—2012 3

44 rf_co2_trop_sw_cs Carbondioxide Clear-sky RF atthetropopause

Instant,SW

2003—2012 3

45 rf_co2_trop_sw Carbondioxide RF at thetropopause

Instant,SW

2003—2012 3

46 std_rfaci_toa Aerosols Standarddeviation ofaerosol-cloudRFatTOA

Instanta,SW

2003—2012 7

47 std_rfari_toa Aerosols Standarddeviation ofaerosol-radiation RF atTOA

Instanta,SW

2003—2012 6



Notes:a. Stratosphericadjustmentisnegligiblefortroposphericaerosolperturbations,soforaerosols

instantaneousandadjustedRFsareequal.

2. FileaccessandnamingconventionFilesarecurrentlystoredonECMWFsystems.AsofDecember2016,aweb-baseddownloadtoolisbeingfinalised.Itsaddressislikelytobe http://apps.ecmwf.int/datasets/data/cams-climate-forcings/AsofDecember2016,thereare47differentvariables(“products”)available.(SeeSection1forfulllist.) Products are made from the MACC Global Reanalysis of atmospheric composition, andthereforecovertheperiod2003—2012thatthereanalysisprovides.Aerosol-cloudRFproductsarelimited to the period 2007—2010 however. (See section 8.) Spatial and temporal resolutionsdependonthevariable.Thereisonefilepervariableandpermonth.Forvariablesgivenatmonthlytemporal resolution, there is only one distribution per file. For variables given at daily temporalresolution,thereareasmanydistributionsinamonthlyfileastherearedaysinthatmonth.FilesnamesfollowtheWorldMeteorologicalOrganization’srecommendationavailableat

https://www.wmo.int/pages/prog/www/WDM/ET-IDM-3/Doc-4%281%29.docThefilenameconventionofCAMSClimateForcingversion0products: z_cams_l_uor_<YYYY><MM>_v0_<varname>.ncwhereYYYYisthe4-digityearcorrespondingtothedistributionstoredinthefile; MMisthe2-digityearmonthcorrespondingtothedistributionstoredinthefile; varnameisthenameofthemainnetCDFvariablestoredinthefile.Files are innetCDF formatand follow theClimateandForecastmetadata convention version1.6(CF-1.6). Version 0 files are in netCDF3 format, except for carbon dioxide andmethane RF files,whichareinnetCDF4format.

Futureimprovement:Allversion1productswillbeinnetCDF4format.

ThenetCDFheader formethaneLW instantaneousRFat the surface for themonthofDecember2012 isgivenbelowasanexample for the file structureusedbyCAMSClimateForcingproducts.Aspectsthatmaybedifferentforotherproductsarehighlightedinred:refertothecorrespondingnotefordetails.netcdf z_cams_l_uor_201212_v0_rf_ch4_srf_lwa { dimensions: latitude = 61b ; longitude = 120b ; time = UNLIMITED ; // (1c currently)



variables: floatd latitude(latitude) ; latitude:units = "degrees_north" ; latitude:long_name = "latitude" ; latitude:standard_name = "latitude" ; latitude:point_spacing = "evene" ; floatd longitude(longitude) ; longitude:units = "degrees_east" ; longitude:long_name = "longitude" ; longitude:standard_name = "longitude" ; longitude:modulo = ; longitude:point_spacing = "evene" ; float rf_ch4_srf_lwa(time, latitude, longitude) ; rf_ch4_srf_lwa:units = "W m-2f" ; rf_ch4_srf_lwa:long_name = "Methane_lw_instantaneous_radiative_forcing_at_surfaceg" ; rf_ch4_srf_lwa:standard_name = "surface_instantaneous_longwave_forcingh" ; rf_ch4_srf_lw:species = "ch4i" ; floatd time(time) ; time:units = "hours since 1900j-01-01 00:00:0.0" ; time:long_name = "time" ; time:standard_name = "time" ; time:calendar = "gregorian" ; // global attributes: :Conventions = "CF-1.6" ; :title = "Copernicus Atmosphere Monitoring Service 74 Climate Forcings" ; :description = "CAMS 74 production chain : Monthly mean Methane radiative forcing for year 2012. Will Davies UoR 2016, [email protected]" ; k :references = "Update to Bellouin et al., doi:10.5194/acp-13-2045-2013, 2013l" ; :source = "model-generated, CAMS74 using MACC reanalysis, version 0 . $Rev: 52 $ . 1m" ; :institution = "Department of Meteorology, University of Readingn" ; :history = "Thu Nov 3 14:18:27 2016: ncks -d time,11 /export/cloud/cams74/users/gn907779/outputs/Rev52/cams74_rf_ch4_srf_lw_2012.nc /glusterfs/cams74/users/pv904464/version0/z_cams_l_uor_201212_v0_rf_ch4_srf_lw.nc\nwriteMonthlyMean.py -o ch4 -y 2012 run on 2016-10-20 19:25:13o" ; :NCO = "4.2.0" ;p }



Notes:a. EachproductisassociatedwithadifferentnetCDFvariablename;b. Thenumberofgridboxesdependsontheproduct:61x120forcarbondioxideandmethane

products,320x161foraerosolproducts,96x73foraerosolRFuncertaintydistributions;c. Aerosol-radiationproductsareatdailyresolution,givingfrom28to31distributionsperfile.

Otherproductsareatmonthlyresolution,giving1distributionperfile;d. Dimensionvariablesinaerosol-cloudRFproductsaredoubleprecision;e. ThehorizontalgridusedforaerosolRFuncertaintyproductsisuneven;f. Radiative effects and forcings and their uncertainties are in W m−2. Absorption and

extinctionAODsaredimensionless.g. Thelongnameisafree-formnamethattriestogiveasmuchinformationaspossibleonthe

variable’smeaning.h. The standard name is taken, as much as possible, from the CMIP standard output table

available at http://cmip-pcmdi.llnl.gov/cmip5/data_description.html . When a new nameneededtobecreated,itfollowstheCMIPnamingconvention.

i. Variableattributesspeciesand,foraerosolRF,forcing_mechanism,areusedtoidentifytheforcingagentandmechanismwhendifferentvariableshappentosharethesamestandardname;

j. Thereferenceyearvariesdependingonproduct:1900forcarbondioxideandmethaneRFproducts,currentyearfortheotherproducts;

k. The short description and contact email address are currently available only for carbondioxideandmethaneRFproducts.Seesection10forcontactinformationforallproducts;

l. Products aremade by applying a series of differentmethods and their updates, some ofwhicharepublished,othernot.Wherepossible,areferenceisgiven;

m. Themain sourceofdata for version0products is theMACCGlobalReanalysis, butotherdatasetshavebeenused.Seesections3to7fordetailsabouteachproducts;

n. The CAMS Climate Forcing service is delivered by three main partners: the University ofReading (UK), University of Leeds, and Universität Leipzig (Germany). Each partner isresponsibleforspecificproducts.TheserviceisledbytheUniversityofReading,whichisthemaincontactforusers(seesection10);

o. The history attribute lists the commands issued to generate the products and thecorrespondingtimestamps;

p. Some products have undergone slight post-processing using the netCDF operators(http://nco.sourceforge.net/nco.html).

Futureimprovement:

- Latitude,longitude,andtimeboundarieswillbeaddedtoclarifygridboxdimensionsandtimeaveragingperiods.

- Differencesinfilestructurebetweentheproductswillberemoved.



3. Carbondioxideandmethane

3.1 Productspecifications

3.1.1 CarbondioxideVariableName SpatialResolution TemporalResolution Unitsarf_co2_trop_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_adjusted_longwave_forcingLongname CarbonDioxide_lw_adjusted_radiative_forcing_at_tropopauseVariableName SpatialResolution TemporalResolution Unitsrf_co2_srf_lw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname surface_instantaneous_longwave_forcing_assuming_clear_skyLongname CarbonDioxide_lw_instantaneous_radiative_forcing_at_surface_

assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_co2_srf_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname surface_instantaneous_longwave_forcingLongname CarbonDioxide_lw_instantaneous_radiative_forcing_at_surfaceVariableName SpatialResolution TemporalResolution Unitsrf_co2_srf_sw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname surface_instantaneous_shortwave_forcing_assuming_clear_skyLongname CarbonDioxide_sw_instantaneous_radiative_forcing_at_surface_

assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_co2_srf_sw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname surface_instantaneous_shortwave_forcingLongname CarbonDioxide_sw_instantaneous_radiative_forcing_at_surfaceVariableName SpatialResolution TemporalResolution Unitsrf_co2_toa_lw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname toa_instantaneous_longwave_forcing_assuming_clear_skyLongname CarbonDioxide_lw_instantaneous_radiative_forcing_at_toa_

assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_co2_toa_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname toa_instantaneous_longwave_forcingLongname CarbonDioxide_lw_instantaneous_radiative_forcing_at_toa



VariableName SpatialResolution TemporalResolution Unitsrf_co2_toa_sw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname toa_instantaneous_shortwave_forcing_assuming_clear_skyLongname CarbonDioxide_sw_instantaneous_radiative_forcing_at_toa_

assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_co2_toa_sw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname toa_instantaneous_shortwave_forcingLongname CarbonDioxide_sw_instantaneous_radiative_forcing_at_toaVariableName SpatialResolution TemporalResolution Unitsrf_co2_trop_lw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_instantaneous_longwave_forcing_assuming_clear_skyLongname CarbonDioxide_lw_instantaneous_radiative_forcing_at_tropopause_

assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_co2_trop_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_instantaneous_longwave_forcingLongname CarbonDioxide_lw_instantaneous_radiative_forcing_at_tropopauseVariableName SpatialResolution TemporalResolution Unitsrf_co2_trop_sw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_instantaneous_shortwave_forcing_assuming_clear_skyLongname CarbonDioxide_sw_instantaneous_radiative_forcing_at_tropopause_

assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_co2_trop_sw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_instantaneous_shortwave_forcingLongname CarbonDioxide_sw_instantaneous_radiative_forcing_at_tropopause

3.1.2 MethaneVariableName SpatialResolution TemporalResolution Unitsarf_ch4_trop_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_adjusted_longwave_forcingLongname Methane_lw_adjusted_radiative_forcing_at_tropopause



VariableName SpatialResolution TemporalResolution Unitsrf_ch4_srf_lw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname

surface_instantaneous_longwave_forcing_assuming_clear_sky

Longname Methane_lw_instantaneous_radiative_forcing_at_surface_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_ch4_srf_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname surface_instantaneous_longwave_forcingLongname Methane_lw_instantaneous_radiative_forcing_at_surfaceVariableName SpatialResolution TemporalResolution Unitsrf_ch4_toa_lw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname toa_instantaneous_longwave_forcing_assuming_clear_skyLongname Methane_lw_instantaneous_radiative_forcing_at_toa_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_ch4_toa_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname toa_instantaneous_longwave_forcingLongname Methane_lw_instantaneous_radiative_forcing_at_toaVariableName SpatialResolution TemporalResolution Unitsrf_ch4_trop_lw_cs 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_instantaneous_longwave_forcing_assuming_clear_skyLongname Methane_lw_instantaneous_radiative_forcing_at_tropopause_

assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrf_ch4_trop_lw 3°x3° Monthly(2003–2012) Wm−2CMIPStandardname tropopause_instantaneous_longwave_forcingLongname Methane_lw_instantaneous_radiative_forcing_at_tropopause

3.2 Methods

3.2.1 RadiativetransfercalculationsTheradiativetransfermodelusedisastandaloneversionoftheECMWFIFS,configuredlikeincycle36r1,which is theversionusedtocreatetheMACCGlobalReanalysis.Gaseousopticalpropertiesare computed by RRTMG (Mlawer et al., 1997) while cloud and aerosol optical properties arecomputedbyschemesdevelopedatECMWF.TheLWandSWsolversarebasedonMcICA(Pincusetal.,2003).Cloudoverlapisassumedtobeexponential-random.Scatteringbycloudsandaerosolsinthe LW spectrum is neglected. The calculations of radiative fluxes by the CAMS Climate Forcing



radiativetransfercodehavebeencomparedagainstobservationalestimates(Katoetal.,2013)andfoundtobeaccuratewithinafewpercents(Table3.2).Fluxeswithsizeableaerosolcontributions,suchassurfaceandclear-skyfluxes,arelessaccuratebecauseaerosolswerenotincludedinthosebenchmarktests.

Table 3.1 – Comparison of globally- and annually-averaged radiative fluxes computed by thestandaloneECMWFIFSradiativetransfercodeagainstobservationalestimatesbyKatoetal.(2013).

Radiativeflux Katoetal.(2013)(Wm−2)

ECMWFIFSradiativetransfercalculations

(Wm−2)

Difference(Wm−2,%)

TOAincomingsolar 340 341.5 1.5(0.5%)

Allsky

TOAoutgoingSW 99to100 97.7 1.3(1.4%)

TOAoutgoingLW 237to240 239.0 0.0(0.0%)

SurfSWdownward 187 195.8 8.8(4.5%)

SurfSWupward 23to24 25.9 1.9(7.5%)

SurfLWdownward 342to344 341.9 0.1(0.0)

SurfLWupward 398 396.8 1.2(0.3)

Clearsky(cloudfree)

TOAoutgoingSW 53 48.7 4.3(8.7%)

TOAoutgoingLW 264to266 263.9 0.1(0.0%)

SurfSWdownward 242to243 254.1 11.1(4.4%)

SurfSWupward 29to30 31.9 1.9(6.0%)

SurfLWdownward 314 314.6 0.6(0.2%)

SurfLWupward 397to398 396.4 0.6(0.2%)

Radiativefluxesarecalculatedat61modelhalf-levelsbutforRFpurposes,threelevelsareretained:surface,TOA,andtropopause.Thetropopauseiscurrentlysettobeat200hPaatallpoints.



Futureimprovement:Inversion1products,thetropopauselevelwillbedefinedaccordingtolocalconditions.

As of version 0, adjustment of LW radiative fluxes to account for changes in stratospherictemperaturesisdoneinaverysimplifiedway,followingShineetal.(1995)andHansenetal.(2005).Forcarbondioxide,adjustedLWRFiscomputedatthetropopausebydecreasinginstantaneousLWRFatthetropopauseby7.5%.Fortroposphericozone,thedecreaseis23%(Table7ofBerntsenetal.1997;Table4ofStevensonetal.2013).Formethane,theimpactofstratosphericadjustmentismuch smaller and is neglected, so adjusted methane LW RF at the tropopause is equal toinstantaneousRFatthetropopause.Forstratosphericozone,adjustmentcannotbedoneinsuchasimplifiedwayandisnotimposedforversion0products.

Future improvement:Adjustment inversion1productswillbeachievedusingseasonally-varyingfixed-dynamicalheating(Forsteretal.,1997).

MethaneRFisonlygivenintheLWspectrum,althoughit isnowknownthattheSWcontributioncanbeaslargeas15%(Etminanetal.,2016).ThedecisionnottopublishmethaneRFestimatesintheSWstemsfromtheinabilityofRRTMG–andmostotherradiativetransfercodes–toproperlyhandlemethaneabsorptionbandsintheSWpartofthespectrum.

Futureimprovement:Forversion1products,itwillbeattemptedtocomputemethaneRFintheSWbyimprovingRRMTGorusingscalingfactorsbasedonline-by-linecalculations.

3.2.2 InputstotheradiativetransfercodeTheradiativetransfercodeisrunondistributionsofatmosphericvariablessimulatedbytheMACCGlobal Reanalysis (Table 3.1) and taken fromECMWFMARS and corresponding to data availablefromthedownloadtoolathttp://apps.ecmwf.int/datasets/data/macc-reanalysis.Thedistributionsareusedasthemeanof4timesteps(0Z,6Z,12Z,and18Z)forthereanalysisdated0Zdaily.Thedistributionsareusedatthedegradedhorizontalresolutionof3.0°by3.0°,downfrom0.75°x0.75°,to reduce computational cost. That decrease in resolution causes negligible (third decimal place)changesinglobally-averagedRF.



Table 3.2 –Variables taken from theMACCGlobal Reanalysis andusedas input to the radiationscheme.Variablename MARSParameterNumber LevelsFractionofCloudCover 248.128 60levelsForecastAlbedo 243.128 SurfaceonlyGEMSozone 203.210 60levelsLogarithmofsurfacepressure 152.128 SurfaceonlySpecificcloudicewatercontent 247.128 60levelsSpecificcloudliquidwatercontent 246.128 60levelsSkintemperature 235.128 SurfaceonlySnowdepth 141.128 SurfaceonlySpecifichumidity 133.128 60levelsPressure on 61 half levels is calculated from the logarithmof the surface pressure following thedefinition and coefficients of the 60-level IFS configuration, as described athttp://www.ecmwf.int/en/forecasts/documentation-and-support/60-model-levels. The radiativetransfercodealsorequirestemperatureon61half levels,whicharecomputedfromtemperatureon60modellevelsusingpressure-weightedlinearinterpolationfollowingtheequation:

𝑇"𝑃" = 1 −𝑃" −𝑃()

𝑃(* −𝑃()𝑃()𝑇() +

𝑃" −𝑃()

𝑃(* −𝑃()𝑃(*𝑇(*

where𝑇"and𝑃"are temperature and pressure at the half-level,𝑇()and𝑃()are the pressure andtemperature for themodel level above, and𝑇(*and𝑃(*are thepressure and temperature for thelevelbelow.Temperatureatthetop-mosthalf-levelisobtainedbylinearextrapolation.LWsurfaceemissivity iscomputedasdone intheECMWFIFSbasedonsimulatedsnowandsandcovers.Itsvalueiscomputedbyaveragingtheemissivityoffoursurfacetilesinproportiontotheircoverage of each gridbox. Surface emissivities used in that calculation are listed in Table 3.3.Outsidethewindowregion,thevalueforseaisused.Table3.3–ValuesofLWsurfaceemissivityusedinradiativetransfercalculations.

Surfacetype LWemissivityLand 0.96Sand 0.93Sea 0.99Snow 0.98

RFisintegrateddiurnallybyintegratingover6solarzenithangles,computedasafunctionoflocallatitudeanddayoftheyearandsymmetricallydistributedaroundlocalnoon.Concentrations of carbon dioxide andmethane are taken from third-party datasets because theMACC reanalysis is strongly biased in those two variables. Present-day carbon dioxide



concentrations are taken from the globally-averaged marine surface monthly mean recordmaintainedbyNOAAESRLathttps://www.esrl.noaa.gov/gmd/ccgg/trends/global.html#global_dataandspecificallythefileatftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_mm_gl.txtThe resulting time series for 2003—2012 is shown in Figure 3.2.a. Present-day methaneconcentrationsaretakenfromtheglobally-averagedmonthlymeanrecordmaintainedbyAGAGEathttps://agage.mit.edu/data/agage-dataandspecificallythefileathttp://agage.eas.gatech.edu/data_archive/global_mean/global_mean_md.txtTheresultingtimeseriesfor2003—2012isshowninFigure3.2.b.Figure3.2–Timeseriesofglobally-andmonthly-averagedmolefractionsofcarbondioxide(a,ppm)andmethane(b,ppb)fortheMACCGlobalReanalysisperiod2003—2012.

Future improvement: Version 1 products will be based on the CAMS Global Reanalysis,which is expected to have much reduced biases in its simulation of carbon dioxide andmethanedistributions.

For the moment, the radiative transfer calculations for carbon dioxide and methane RF do notincludeaerosol.Theeffectiveradiusofcloudliquiddropletsandicecrystalsarefixedat10μmand50μm,respectively.OpticallyactivegasesaresettotheirPIvalues,seesection3.2.3.

Future improvement: Radiative transfer calculations for version 1 products will useconsistentrepresentationsofaerosolsandcloudsforallforcingagents.

The3Dradiativetransfercapabilitiesofthecodearenotused,andtherearenoplanstousetheminthefuture.



3.2.3 Pre-industrialatmosphericconcentrationsPre-industrialvolumemixingratiosofcarbondioxide,methane,andnitrousoxidearetakenfromtheIPCCAR5(Myhreetal.,2013)andgiveninTable3.3.Thosemixingratiosareusedasglobalandannualsinglenumbers,i.e.areuniformhorizontallyandverticallyandwithoutmonthlycycles.

Future improvement: Version 1 products will be based on several estimates of the pre-industrial atmosphere and will resolve horizontal, vertical, and monthly variations ofmethane,andifpossiblealsocarbondioxide,volumemixingratios.

Table 3.4 -Volumemixing ratios used to represent pre-industrial conditions in radiative transfercalculations.TakenfromIPCCAR5Table8.2(Myhreetal.,2013).

Species VolumemixingratioCO2 278ppmCH4 722ppbN2O 270ppbCFC11 0CFC12 0

3.3 UncertaintiesForversion0products,uncertaintiesincarbondioxideandmethaneRFaretakenat±10%followingIPCCAR5(Myhreetal.,2013),whichassesseduncertaintiesduetospectroscopy,radiativetransfercalculations,andrepresentationofclouds.

Future improvement: Version 1 product uncertainties will be derived for the radiativetransfer code used in the service, and will include both structural and parametricuncertainties.

4. Troposphericandstratosphericozone4.1 ProductspecificationsAs of December 2016, tropospheric and stratospheric ozone products have not been finalisedbecause of difficulties in correcting for biases in MACC Global Reanalysis ozone against bothpresent-dayandpre-industrialstates(Section4.2.3).

Ozoneproductsexistatversion0atanexperimentalstagebutarenotdistributedpublicly.



4.2 Methods

4.2.1 RadiativetransfercalculationsTheradiativetransfercalculationsmadeforcomputingozoneRFareidenticaltothosedescribedinsection3.2.1forcarbondioxideandmethaneRF,withtheexceptionofstratosphericadjustmentofLWtroposphericozoneRF,whichisachievedbydecreasinginstantaneousLWtroposphericozoneRFby25%.

Future improvement:Adjustment inversion1productswillbeachievedusingseasonally-varyingfixed-dynamicalheating(Forsteretal.,1997).

4.2.2 InputstotheradiativetransfercodeCalculationsaremade ina similarway to those for carbondioxideandmethane, asdescribed insection 3.2.2. In version 0 products, the ozone distributions are taken from the MACC GlobalReanalysis (variable “GEMS ozone” in Table 3.1). The distinction between tropospheric andstratosphericozoneismadebysettingthetropopauselevelfollowingHansenetal.(2005),wherethetropopauselevelissetat100hPaforlatitudeswithin±30°,(100+(110/15)*(|latitude|−30))for30°<|latitude|<45°,and210hPaforlatitudeslargerthan±45°.

Futureimprovement:Inversion1products,thetropopauselevelwillbedefinedaccordingtolocalconditions.

4.2.3 Pre-industrialatmosphericconcentrationsPre-industrial ozone conditions are taken as three-dimensional, monthly-averaged distributionsfrom the CMIP6 dataset derived from CCMI models with representations of stratosphere-tropospherechemistry.Theyear representedby thatdataset is1850and it isassumedhere thatozone distributions have not changed between 1750 and 1850. That assumption is reasonable,although contributions from wildfires and anthropogenic activities linked to the start of theindustrialrevolutionmayhaveintroducedsmallvariations.

CMIP6 ozone files used by CAMS Climate Forcing were obtained fromhttps://pcmdi.llnl.gov/search/input4mips/.TheCMIP6datasetisgivenasvolumemixingratiosandare converted tomass-mixing ratiosbymultiplyingby1.66. Toensure that this PI distributionofozoneisconsistentwiththePDdistributiontakenfromtheMACCGlobalReanalysis(seeprevioussection),abiascorrectionisappliedwheremonthlyCMIPPIaveragesarescaledbythePDMACC-to-CMIP6 ratios for the samemonth.Unfortunately, that bias correctiondoesnot reduce knownbiasesintheMACCGlobalReanalysis(Innessetal.2013).

Futureimprovement:Pre-industrialozonedistributionsforversion1productswillbebasedonseveralsimulationsofthepre-industrialatmosphereusingtheECMWFIFS.



4.3 UncertaintiesForversion0products,uncertaintiesinozoneRFaretakenat±50%followingIPCCAR5(Myhreetal.,2013),whichassesseduncertaintiesduetothepre-industrialozoneconcentrations,inter-modelspreadinpresent-dayozonedistributions,andradiativetransfercalculations.

Future improvement: Version 1 product uncertainties will be derived for the radiativetransfer code used in the service, and will include both structural and parametricuncertainties.

5. Speciatedaerosolopticaldepths5.1 ProductspecificationsVariableName SpatialResolution TemporalResolution Unitsabs550anth 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname

atmosphere_absorption_optical_thickness_due_to_ambient_aerosol_particles

Longname anthropogenic_aerosol_absorption_optical_depth_at_550_nmVariableName SpatialResolution TemporalResolution Unitsabs550dust 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname


Longname mineral_dust_aerosol_absorption_optical_depth_at_550nmVariableName SpatialResolution TemporalResolution Unitsabs550landnat 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname


Longname non-dust_land_natural_aerosol_absorption_optical_depth_at_550nmVariableName SpatialResolution TemporalResolution Unitsabs550marine 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname


Longname marine_aerosol_absorption_optical_depth_at_550_nmVariableName SpatialResolution TemporalResolution Unitsod550aer 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname atmosphere_optical_thickness_due_to_ambient_aerosol_particlesLongname total_aerosol_optical_depth_at_550_nm



VariableName SpatialResolution TemporalResolution Unitsod550anth 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname atmosphere_optical_thickness_due_to_ambient_aerosol_particlesLongname anthropogenic_aerosol_optical_depth_at_550_nmVariableName SpatialResolution TemporalResolution Unitsod550dust 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname atmosphere_optical_thickness_due_to_ambient_aerosol_particlesLongname mineral_dust_aerosol_optical_depth_at_550nmVariableName SpatialResolution TemporalResolution Unitsod550landnat 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname atmosphere_optical_thickness_due_to_ambient_aerosol_particlesLongname non-dust_land_natural_aerosol_optical_depth_at_550nmVariableName SpatialResolution TemporalResolution Unitsod550marine 1.125°x1.125° Daily(2003–2012) 1CMIPStandardname atmosphere_optical_thickness_due_to_ambient_aerosol_particlesLongname marine_aerosol_optical_depth_at_550_nm

5.2 Methods

5.2.1 Identificationofaerosolorigin

ToobtainaerosolRF,itisnecessarytodistinguishbetweenaerosolsofnaturaloriginandaerosolsofanthropogenicorigin.TheECMWFIFSdoesnotkeeptrackoftheaerosoloriginmainlytokeepcomputational cost reasonable but also because aerosol origin is not always given in emissioninventories,becausethesameaerosolparticlemaybeaninternalmixturewithanthropogenicandnatural contributions, and because data assimilation cannot constrain natural and anthropogenicaerosolsindependently.InsteadtheaerosoloriginisobtainedusingthealgorithmdescribedbyBellouin et al. (2013) where aerosol size is used as a proxy for aerosol origin. The algorithmidentifies four aerosol origins: anthropogenic, mineral dust, marine, and land-based fine-modenatural aerosol. That last origin mostly includes biogenic aerosols. The reader is referred tosection3ofBellouinetal.(2013)fordetailsofthealgorithm.ThepresentdocumentationdescribestwoupdatesmadetothealgorithmsincethepublicationofBellouinetal.(2013).The first update is the replacement of continental-wide anthropogenic fractions used over landsurfaces by a fully gridded dataset that includes seasonal variations. Over land, identification ofcomponentAODsstartswith removing thecontributionofmineraldustaerosols fromtotalAOD.The remaining non-dust AOD, τnon-dust, is then distributed between anthropogenic and fine-modenaturalcomponents,notedτanthandτfine-natural,respectively,following:

τanth=fanth.τnon-dustτfine-natural=(1–fanth).τnon-dust



wherefanthistheanthropogenicfractionofthenon-dustAOD.Inversion0products,fanthisgivenbymonthly distributions on a 1x1-degree grid projected onto the 1.1°x1.1° grid used by theMACCGlobalReanalysis.ThisnewdatasetderivesfromananalysisofAeroCom2numericalmodels(Kinneetal.,2013).ItsannualaverageisshowninFigure5.1.AnthropogenicfractionsshowaNorth-Southgradient, as expected from the location of population and industrial activities. Anthropogenicfractionsare larger than0.8overmost industrialisedregionsofNorthAmerica,Europe,andAsia.ThelargestfractionsarelocatedoverChina,wheremorethan90%ofnon-dustAODisattributedtoanthropogenicaerosols. Inthesouthernhemisphere,anthropogenicfractionsaretypicallysmallerthan0.7onanannualaverage.Intermsofseasonality,anthropogenicfractionsremainlargerthan0.7 throughout the year in the northern hemisphere, with a peak in winter when energyconsumptionishigh.Inthesouthernhemisphere,seasonalityisdrivenbybiomass-burningaerosols,whichareconsideredpurelyanthropogenic intheCAMSClimateForcingproducts.AnthropogenicfractionsthereforepeakinlatesummerinSouthAmericaandsouthernAfrica.

Figure5.1-Annually-averagedanthropogenicfractionofnon-dustaerosolopticaldepthoverland.

Thesecondchangeconcernsthefine-modefraction(FMF)ofmarineAODat0.55μm,whichgivesthefractionofmarineAODthatisexertedbyparticleswithradiismallerthan0.5μm.InBellouinetal. (2013), that fraction was set to a fixed value of 0.3. In version 0 products, that fraction isdetermined by a gridded dataset that includes monthly variations. The dataset is obtained byapplyingthemethodofYuetal. (2009)todailyMODISCollection6aerosolretrievalsofAODandFMF.First,themarineaerosolbackgroundis isolatedbyselectingonlyocean-basedsceneswheretotalAODat0.55μmisbetween0.03and0.10.Then,anAOD-weightedaveragedFMFiscomputed.The analysis has been applied to retrievals fromMODIS instruments on both the Terra (datasetcovering2001—2015)andAqua (datasetcovering2003—2015)platforms.Both instrumentsyieldverysimilarmarineFMFdistributions,andthedistributionsusedinversion0productarethemulti-annualmonthlyaveragesof the two instruments.Figure5.2shows themarineFMFderived fromMODIS/Terra for themonthsof Januaryand July. It suggests thatmarineFMFvariesoverawiderangeofvalues.Regionsofhighwindspeeds,around40-50° inbothhemispheres,areassociatedwith largeFMFs indicatingthat themarineaerosolsizedistribution includesasizeable fractionofsmaller particles there. There are indications of contamination by fine-mode anthropogenic and



mineral dust aerosols in coastal areas, but the impact on speciated AODs is small because theaerosolidentificationalgorithmusesbroadFMFcategoriesratherthanabsolutevalues.

Figure 5.1 – Fine-mode fraction of marine aerosol optical depth at 0.55 μm as derived fromMODIS/TerraCollection6aerosolretrievalsforthemonthsofJanuary(left)andJuly(right).

Infact,theimpactofusingmonthly-varyingdistributionsinsteadofaglobal,annualmarineFMFissmall.AnthropogenicAODdecreasesslightlyintheroaringfortiesintheSouthernOcean,buttendstoincreaseslightlyintheNorthernAtlanticandPacificoceans.Onaglobalaverage,thechangeinanthropogenicAODduetotheimprovedspecificationofmarineFMFis+0.001(+1.4%).

5.2.2 Inputstothealgorithm

The list of input distributions from the MACC Global Reanalysis used by the aerosol originidentificationalgorithmisgiveninTable5.1.

Table5.1–VariablestakenfromtheMACCGlobalReanalysisandusedasinputtotheaerosoloriginidentificationalgorithm.Variablename MARSParameterNumber Levels10metreUwindcomponent Surfaceonly10metreVwindcomponent SurfaceonlyBlackCarbonAerosolOpticalDepthat550nm 210.211 ColumnDustAerosolOpticalDepthat550nm 210.209 ColumnLand-seamask SurfaceonlyOrganicMatterAerosolOpticalDepthat550nm 210.210 ColumnSeaSaltAerosolOpticalDepthat550nm 210.208 ColumnSulphateAerosolOpticalDepthat550nm 210.212 ColumnTotalAerosolOpticalDepthat550nm 210.207 Column

5.3 Uncertainties

UncertaintiesonspeciatedAODsaregiveninTable2ofBellouinetal.(2013)andcorrespondtoarelativeuncertaintyofabout20%onaglobalaverage.



6. Aerosol-radiationinteractions6.1 ProductspecificationsVariableName SpatialResolution TemporalResolution Unitsreari_anth_srfcs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname

surface_shortwave_aerosol_radiative_effect_assuming_clear_sky

Longname anthropogenic_sw_radiative_effect_of_ari_at_surface_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsreari_anth_toacs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname toa_shortwave_aerosol_radiative_effect_assuming_clear_skyLongname anthropogenic_sw_radiative_effect_of_ari_at_toa_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsreari_dust_srfcs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname surface_shortwave_aerosol_radiative_effect_assuming_clear_skyLongname mineral_dust_sw_radiative_effect_of_ari_at_surface_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsreari_dust_toacs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname toa_shortwave_aerosol_radiative_effect_assuming_clear_skyLongname mineral_dust_sw_radiative_effect_of_ari_at_toa_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsreari_landnat_srfcs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname surface_shortwave_aerosol_radiative_effect_assuming_clear_skyLongname non-dust_land_natural_aerosol_sw_radiative_effect_of_ari_

at_surface_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsreari_landnat_toacs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname surface_shortwave_aerosol_radiative_effect_assuming_clear_skyLongname non-dust_land_natural_aerosol_sw_radiative_effect_of_ari_

at_toa_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsreari_marine_srfcs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname surface_shortwave_aerosol_radiative_effect_assuming_clear_skyLongname marine_sw_radiative_effect_of_ari_at_surface_assuming_clear_sky



VariableName SpatialResolution TemporalResolution Unitsreari_marine_toacs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname surface_shortwave_aerosol_radiative_effect_assuming_clear_skyLongname marine_sw_radiative_effect_of_ari_at_toa_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrfari_srfcs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname

surface_instantaneous_shortwave_forcing_assuming_clear_sky

Longname anthropogenic_sw_radiative_forcing_of_ari_at_surface_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrfari_srf 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname surface_instantaneous_shortwave_forcingLongname sw_radiative_forcing_of_ari_at_surface_allskyVariableName SpatialResolution TemporalResolution Unitsrfari_toacs 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname toa_instantaneous_shortwave_forcing_assuming_clear_skyLongname anthropogenic_sw_radiative_forcing_of_ari_at_toa_assuming_clear_skyVariableName SpatialResolution TemporalResolution Unitsrfari_toa 1.125°x1.125° Daily(2003–2012) Wm−2CMIPStandardname toa_instantaneous_shortwave_forcingLongname sw_radiative_forcing_of_ari_at_toa_allskyVariableName SpatialResolution TemporalResolution Unitsstd_rfari 2.5°x3.75° Monthly(2003–2012)* Wm−2CMIPStandardname standard_deviation_of_toa_instantaneous_shortwave_forcingLongname standard_deviation_of_sw_radiative_forcing_of_ari_at_toa_allsky*Standarddeviationsaredeterminedforagivenyearandassumedtoapplytoallyears.

6.2 Methods

Radiative effect and forcing of aerosol-radiation interactions are computed by radiative transfercalculationsthatcombinethespeciatedAODsderivedinSection5withprescriptionsofaerosolsizedistributionandsingle-scatteringalbedo.ThemethodsareasdescribedinSection4ofBellouinetal. (2013)withoneexception: theprescriptionof single-scatteringhasbeenupdated froma few,continental-widenumberstogriddedmonthlyclimatologies.Thisupdateddataset introducestwomajor improvements compared to Bellouin et al. (2013). First, the new dataset provides themonthlycycleoffine-modeabsorption.Second,thedatasetisprovidedona1x1-degreegrid,laterprojectedonto the coarser grid usedby theMACC re-analysis. Themethodused to produce thedatasetisdescribedinKinneetal.(2013).First,distributionsoffine-modeextinctionandabsorption



AODs are obtained from a selection of global aerosol numericalmodels that participated in theAeroCom 1 simulations using a common set of aerosol and precursor emissions for present-dayconditions (Kinne et al. 2006). In order to include an observational constraint, those modelleddistributionsarethenmergedwithretrievalsofaerosolSSAfortheperiod1996–2011atmorethan300 AERONET sites. The merging is based on a subjective assessment of the quality of themeasurementsateachoftheAERONETsitesused,alongwiththeirabilitytorepresentaerosolsinawider region around the site location. The main impact of merging observed SSAs is to makeaerosolsinAfricaandSouthAsiamoreabsorbingthannumericalmodelspredicted.Thedistributionofannual-averagedaerosolSSAisshowninFigure6.1.Thedatasetrepresentsthelocalmaximumofabsorption over California and the change in absorption as biomass-burning aerosols duringtransport, which is visible over Africa. Over Asia, Europe, and South America, absorption is alsolargernearsourceregions,withlessabsorptionelsewhere.

Figure 6.1 – Annually-averaged distribution of single-scattering albedo at 0.55 μm used tocharacterizeabsorptionofanthropogenicaerosols.

It isworth noting that the SSAdistribution characterises absorptionof fine-mode aerosols but isused to provide the absorption of anthropogenic aerosols, which is not fully consistent. Theinconsistencyishowevermitigatedbytwofactors.First,fine-modeaerosolsarethemainproxyforanthropogenicaerosolsintheMACCalgorithmthatidentifiesaerosolorigin,andtheirdistributionsarebroadlysimilar.Second,regionswherenaturalaerosolssuchasmarineandmineraldustmaycontaminatethefine-modeAODoftencorrespondtominimainanthropogenicAOD.

LikeinBellouinetal.(2013),REariandRFariareestimatedinclear-sky(cloud-freesky)thenscaledby the complement of the cloud fraction in each gridbox to represent all-sky conditions, thusassumingthatcloudy-skyaerosol-radiation interactionsarezero.However,experimentalproductsthatincludeestimatesofcloudy-skyRFexistbutarebasedonasimplifiedaccountofcloudalbedo,which limits theirusefulness.For2003,globally-averagedabove-cloudanthropogenicandmineraldustAODsweightedbycloud fraction,are0.005and0.003, respectively,or8%of their clear-skycounterparts.Above-cloudmarineand fine-modenaturalAODsarenegligible.Thoseabove-cloudaerosolsexertapositiveREaribecauseoftheirabsorbingnatureandthehighreflectanceofclouds.REari commonly reach +5 to +10Wm−2 during the biomass-burning season that lasts from late



AugusttoOctoberoverthesouth-easternAtlanticstratocumulusdeck.Thatwouldtranslateintoacloudy-sky anthropogenic RFari of +0.01 Wm−2. Neglecting above-cloud aerosols thereforeintroduces a small uncertainty on the global average, but leads to larger errors regionally andseasonally.

Future improvement:Version1productswill use theECMWF IFS radiation codeandwilltherefore properly account for impact of clouds on all-sky radiative forcing of aerosol-radiationinteractions.

6.2.1 Inputstothealgorithm

The list of input distributions from the MACC Global Reanalysis used by the radiative transfercalculationstoobtainREariandRFariisgiveninTable6.1.

Table 6.1 – Variables taken from the MACC Global Reanalysis and used to compute aerosol-radiationinteractions.Variablename LevelsNearIRalbedofordiffuseradiation SurfaceonlyNearIRalbedofordirectradiation SurfaceonlyTotalcloudcover ColumnUVvisiblealbedofordiffuseradiation SurfaceonlyUVvisiblealbedofordirectradiation Surfaceonly

6.2.2 Pre-industrialaerosolopticaldepths

Version 0 products are not defined with respect to PI conditions. Rather, RFari is defined withrespect to PD aerosols, which is a different reference to PI so a correction is required. Thatcorrection factor is taken from Bellouin et al. (2013) and is equal to 0.8, i.e. RFari definedwithrespecttoPIis80%ofRFaridefinedwithrespecttoPDaerosols.

Future improvement: Pre-industrial aerosol optical depth distributions for version 1productswill be based on several simulations of the pre-industrial atmosphere using theECMWFIFS.

6.3 UncertaintiesUncertainties are derived from a Perturbed Parameter Ensemble (PPE) run at the University ofLeedswiththeGLOMAPglobalaerosolmodelembedded inHadGEM3(Yoshiokaetal.2017). It isthereforeassumedthattheuncertaintiesthatcharacteriseRFari inanumericalaerosolmodelarethe same than the uncertainties that would characterise the combination of modelling, dataassimilation,andradiativetransfercalculationsthatmakeuptheCAMSRFariestimates.



Future improvement:For version1products, thisassumptionwill be supportedbyaPPEderivedfromtheECMWFIFSandaccountingforuncertaintiesininputdistributions.

FortheGLOMAPPPE,priorprobabilitydistributionsofuncertainparametersweregeneratedusingan expert elicitation process that lasted from February 2015 to October 2016. To avoid overlycentralising the sample for individual parameters compared to expert beliefs, trapezoidaldistributions are used here to represent parameter uncertainty. Experts also converged onagreementaboutparameteruncertaintyusingtrapezoidaldistributionsfasterthantheydidwhenattemptingtouseothertypesofdistribution.Foreacheliciteddistributionaliteraturereviewandanalysisofthemodelsensitivitytoindividualparameterperturbationswasconducted.ThesetofuncertainparametersisgiveninTable6.3.ItisanupdateandextensionofthesetusedinLeeetal.(2013).Uncertaintiesarecalculatedforagenericyearandassumedtoapplytoallyears.Table 6.3 – List of parameters perturbed in the HadGEM3-GLOMAP Perturbed Physics EnsembleusedtoestimateRFariandRFaciuncertainties# Parameter # Parameter1 Boundarylayernucleation 14 Seaspraymassflux(coarse/accumulation)2 Ageingratefrominsolubletosoluble 15 SO2emissionflux(anthropogenic)3 Modal width (accumulation

soluble/insoluble)16 SO2emissionflux(volcanic)

4 Modalwidth(Aitkensoluble/insoluble) 17 BiogenicmonoterpeneproductionofSOA5 pHofclouddrops 18 DMSemissionflux6 BC/OCmassemissionrate(fossilfuel) 19 DrydepositionvelocityofAitkenmode

Aerosol7 BC/OC mass emission rate (biomass

burning)20 Dry deposition velocity of accumulation

modeaerosol8 BC/OCmassemissionrate(biofuel) 21 DrydepositionvelocityofSO29 BC/OCemittedmodediameter(fossilfuel) 22 Hygroscopicity parameter Kappa for

organicaerosols10 BC/OC emitted mode diameter (biomass

burning)23 Standarddeviationofupdraftvelocity.

11 BC/OCemittedmodediameter(biofuel) 24 Tuningfactortothedustemissionflux.12 Mass fraction of SO2 converted to new

SO42− particles in sub-grid power plant

plumes

25 Fraction of the cloudy part of the gridboxwhererainisformingandhencescavengingtakesplace.

13 Mode diameter of new sub-grid SO42−

particles26 Scavenging threshold for both cloud liquid

andicewaterscavenging



7. Aerosol-cloudinteractions7.1 ProductspecificationsVariableName SpatialResolution TemporalResolution Unitsrfaci_srf_lw 1.125°x1.125° Monthly(2007–2010) Wm−2CMIPStandardname surface_instantaneous_longwave_forcingLongname lw_radiative_forcing_of_aci_at_surface_allskyVariableName SpatialResolution TemporalResolution Unitsrfaci_srf_sw 1.125°x1.125° Monthly(2007–2010) Wm−2CMIPStandardname surface_instantaneous_shortwave_forcingLongname sw_radiative_forcing_of_aci_at_surface_allskyVariableName SpatialResolution TemporalResolution Unitsrfaci_toa_lw 1.125°x1.125° Monthly(2007–2010) Wm−2CMIPStandardname toa_instantaneous_longwave_forcingLongname lw_radiative_forcing_of_aci_at_toa_allskyVariableName SpatialResolution TemporalResolution Unitsrfaci_toa_sw 1.125°x1.125° Monthly(2007–2010) Wm−2CMIPStandardname toa_instantaneous_shortwave_forcingLongname sw_radiative_forcing_of_aci_at_toa_allskyVariableName SpatialResolution TemporalResolution Unitsstd_rfaci 2.5°x3.75° Monthly(2003–2012)* Wm−2CMIPStandardname standard_deviation_of_toa_instantaneous_shortwave_forcingLongname standard_deviation_of_sw_radiative_forcing_of_aci_at_toa_allsky*Standarddeviationsaredeterminedforagivenyearandassumedtoapplytoallyears.

7.2 Methods

Theaerosol-cloudRFestimationalgorithmproceedsinthreesteps:

1. DeriveCCNconcentrationsfromtheMACCGlobalReanalysis,usingaerosolpropertiesasprescribedintheIFSradiativetransfercode;

2. EstimateCDNCfromcloudpropertiesderivedfromA-Trainsatelliteinstrumentsandassumptionsofupdraftvelocitydistributions;

3. ComputetheanthropogenicfractionofCDNCbasedonAODspeciation.

The four steps are described below. Aerosol-cloud RFs are estimated as monthly distributionsbecauseoflimitationsofthemethodabove.



Future improvement: Inversion1products,cloudpropertieswillbetakenfromtheCAMSGlobalReanalysis,allowingdailyestimatesofaerosol-cloudRF.

7.2.1 Cloudcondensationnuclei

Three-dimensional, daily distributions of CCN are computed for 3 supersaturations (0.2, 0.4, and1%)fortheperiod2003—2012.CCNarecalculateddiagnosticallyinaboxmodel(Daviesetal.2005)asfunctionoftemperature,pressure,specifichumidityandaerosolmassmixingratios.Thoseinputdistributions are all taken from the MACC Global Reanalysis. Aerosol mass mixing ratios areconvertedtoaerosolnumberconcentrationsbyassumingthatsizedistributionsarelognormal,withtheparametersgiveninTable7.1.NotethatCCNconcentrationsresultonlyfromhydrophilicblackcarbonandorganicmatter,sulfateandsea-saltcomponents.Dustistreatedentirelyasaninsolubleaerosolspeciesandnoageingorcoatingeffectsareconsideredinthemodel.

Table 7.1 – Properties of the lognormal size distributions of MACC Global Reanalysis aerosolcomponents: median radius r0 (μm) and geometric standard deviation σg. Also given is the drydensityρp(kgm−3).FromBenedettietal.(2009)andReddyetal.(2005).Aerosolcomponent r0(μm) σg ρp(kgm−3)Dust(small) 0.135 2.0 2160Dust(medium) 0.704 2.0 2160Dust(large) 4.4 2.0 2160Sea-salt(small) 0.125 2.0 2600Sea-salt(medium) 1.6 2.0 2600Sea-salt(large) 10 2.0 2600Sulfate 0.0355 2.0 1840Blackcarbon 0.0118 2.0 1800Organicmatter 0.0355 2.0 1760

7.2.2 Clouddropletnumberconcentrations

Two-dimensional,dailydistributionsofCDNCatcloudbaseheightarecomputedfor6categoriesofliquidwater cloudsover theperiod2007—2010. This dataset is producedusing a joint satellite-reanalysis approach. TheMACCGlobal Reanalysis aerosol distributions are first collocated to thetrackoftheCALIPSOlidarusinganearestneighbourapproach.Thedataisthenfilteredforliquid,single-layerandnon-precipitatingcloudsusingthesatelliteretrievalsgatheredinCCCM(Katoetal.2014).MACCGlobalReanalysisaerosolmassmixingratiosaretakenatcloudbaseheight,whichisdetermined approximately from the CALIOP lidar retrievalswithin the CCCMdataset. Finally, co-located aerosol mass mixing ratios at cloud base heights are used in a box model, whichdiagnostically computesCDNCusing aparameterizationof aerosol activation, asdescribed in thenextsubsection.



CDNC isestimatedfromaerosolcomposition,sizedistribution,andhygroscopicity (seeTable7.1).Theparameterizationofmaximumsupersaturation,Smax,whichdependsontemperature,pressure,humidity,andupdraftvelocity,istakenfromAbdul-RazzakandGhan(2000).Thisparameterisationaccounts for the competition between aerosol particles for available water vapour and for thedependence of this competition on particle sizes, chemical properties and also on thesupersaturationforcingratewhichisdeterminedbytheupdraftvelocity.

AnimportantaspectinthecomputationofSmaxistheupdraftvelocity.Toaccountforsub-gridscalevariability within the CERES footprint (20 by 20 km), the updraft velocity is assumed to bedistributedaccordingtothefollowingPDF:

𝑓 𝑤 = 1

2𝜋𝜎1exp −

𝑤 −𝑤 *

2𝜎1*

where𝑤isthemeanlarge-scaleverticalvelocity,takenat0ms−1andσwisthestandarddeviation.ThePDF is composedof 20updraft bins from0 to2m s−1.Only thepositivepart of the verticalvelocitydistributionistakenintoaccounttoensurethatonlyupdraftsandnotdowndraftsareusedforthecomputationofSmax.

Thevalueofσwdependsoncloudregime,whichitselfdependsoncloudbaseheightandcloudtopheightvariability.CloudregimesandcorrespondingσwvaluesaregiveninTable7.2.

Table7.2–Standarddeviation,inms−1,ofcloudupdraftvelocityusedforeachcloudregime.Hcbisthecloudbaseheight(m).VHtop(%)isthevariabilityincloudtopheight.Cloudbase/variability VHtop<11%

(homogeneous/stratiform)VHtop>11%

(inhomogeneous/cumuliform)Hcb<350m 0.2 0.4350m<Hcb<950m 0.4 0.8Hcb>950m 0.6 1.2

7.2.3 CalculationofRFaci

Radiative fluxes are calculated using the standalone version of the RRTM-G (Iacono et al., 2008)implementationintheECHAM6generalcirculationmodel(Stevensetal.,2013).Inputdistributionstothecodearethefixed-σwCDNCdescribedinsection7.2.2;distributionsofsurfacetemperature,surfaceemissivity,atmospherictemperatureandpressureprofiles,cloudcover,cloudliquidandicewater mixing ratios, specific humidity, and ozone mixing ratio taken from the MACC GlobalReanalysis,andclimatologicalglobally-averagedcarbondioxide,methane,andnitrousoxidemixingratios.

The calculation of the anthropogenic perturbation in CDNCuses the anthropogenicAOD fractionfanthderivedinSection5.

ΔCDNC=fanthxCDNC



RFaciisthencalculatedas

RFaci=F(CDNC)–F(CDNC–ΔCDNC)

whereFistheTOAall-skyradiativefluxcalculatedbytheradiativetransfercode.CDNCistheonlydifference between the calculations of the two sets of radiative fluxes. Radiative transfercalculationsareperformed foreachCERES footprintusing theCDNCcalculated for that footprintandtheCAMSfanthofthegridboxandatthetimecorrespondingtotheCERESfootprint.IfnoCDNChasbeenretrieved,theradiativefluxperturbationforthatfootprint issetzero.RFaci isthereforethatduetoliquid,non-precipitatingcloudsonly.

ToproducethemonthlygriddedCAMSRFaci,theradiativefluxineachCERESfootprintiscorrectedforthediurnalcycleininsolation.Thiscorrectionisperformedbyscalingthefluxbytheratio

cosθ/<cosθ>

where θ is the instantaneous zenith angle at the CERES overpass time and brackets indicate thediurnalmean at the location of the CERES footprint. The RFaci product is then regridded to the1.125°-gridusedbytheCAMSanthropogenicAODproduct.

7.2.4 Pre-industrialreferencestate

Like for RFari (section 6.2.2), version 0 products of RFaci are not defined with respect to PIconditions.Rather,RFaciisdefinedwithrespecttoPDaerosols,whichisadifferentreferencetoPIso a correction is required. That correction factor is assumed to be the same as for RFari at 0.8(Bellouinetal.2013).SoRFacidefinedwithrespecttoPIis80%ofRFacidefinedwithrespecttoPDaerosols.

Future improvement: Pre-industrial aerosol optical depth distributions for version 1productswill be based on several simulations of the pre-industrial atmosphere using theECMWFIFS.

7.3 Uncertainties

UncertaintiesonRFaci are calculated in the samewayasuncertaintiesonRFari. See section6.3.Uncertaintiesarecalculatedforagenericyearandassumedtoapplytoallyears.



8. ListofacronymsAcronym MeaningAGAGE AdvancedGlobalAtmosphericGasesExperimentAOD AerosolOpticalDepthCALIOP Cloud-AerosolLidarwithOrthogonalPolarizationCALIPSO Cloud-AerosolLidarandInfraredPathfinderSatelliteObservationCAMS CopernicusAtmosphereMonitoringServiceCCCM CERESCALIPSOCloudsatMODISCCN CloudCondensationNucleiCDNC CloudDropletNumberConcentrationCERES CloudsandtheEarth'sRadiantEnergySystemCMIP6 CoupledModelIntercomparisonProject,phase6DISORT DiscreteOrdinatesRadiativeTransferECHAM ECMWFHamburg(theclimatemodelofMaxInstituteforMeteorologyinHamburg)ECMWF EuropeanCentreforMedium-rangeWeatherForecastsESRL EarthSystemResearchLaboratoryERF EffectiveRadiativeForcingFMF Fine-ModeFractionIFS IntegratedForecastSystemIPCCAR5 IntergovernmentalPanelonClimateChangeFifthAssessmentReportLW Long-wavepartoftheelectromagneticspectrumMACC MonitoringAtmosphericCompositionandClimateMODIS ModerateResolutionImagingSpectroradiometerNOAA NationalOceanicandAtmosphericAdministrationPD PresentDayPDF ProbabilityDensityFunctionPI Pre-IndustrialPPE PerturbedParameterEnsembleRE RadiativeEffectRF RadiativeForcingRFaci RadiativeForcingofaerosol-cloudinteractionsRFari RadiativeForcingofaerosol-radiationinteractionsRRTMG RapidRadiativeTransferModelforGeneralCirculationModelsSW Short-wavepartoftheelectromagneticspectrumTOA TopOfAtmosphere



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10. UsersupportandcontactsFor questions regarding the CAMS Climate Forcing products or this documentation, it isrecommended to raise a query through the CAMS user support system athttps://atmosphere.copernicus.eu/user-support-0 . You can also contact Nicolas Bellouin (CAMSClimateForcingPI,UniversityofReading)[email protected].

Copernicus Atmosphere Monitoring Service

atmosphere.copernicus.eu copernicus.eu ecmwf.int

ECMWF - Shinfield Park, Reading RG2 9AX, UK Contact: [email protected]

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Documentation of CAMS Climate Forcing products, version 0