An Atmospheric Modeling Tool for Site Characterization and Telescope Calibration using MERRA2

Andrew Wang, Denis Barkats, Scott Paine, Simon Radford, John Kovac

Abstract

UsingNASA’sMERRA2atmosphericreanalysisandtheamradia7vetransfermodel,wehavedevelopedanewtoolthatpredictstheskybrightnesstemperatureandopacityanywhereonEarthforanydatefrom1970tothepresent.WevalidateMERRA2bycomparingourpredic7onswithlong-baselineopacitymeasurementcampaignsandquan7fytheaccuracyofourpredic7ontool.Finally,wehavecreatedacommandlinetoolandwebinterfaceforresearcherstogeneratepredic7onsindependently.

Introduction

Method

Results

1  M. M. Rienecker, et al. 2011 “MERRA, NASA's Modern-Era Retrospective Analysis for Research and Applications.” J. Climate 24:3624. , https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/

2  Paine, Scott. (2017, March 29). The am atmospheric model (v. 9.2). Zenodo. http://doi.org/10.5281/zenodo.438726

3  Radford & Peterson, 2016, arXiv:1602.08795 4  Matsushita et al., 2017, PASP, 129, 025001 5  C-L. Kuo, arXiv: 1707.08400 6  NOAA/NCEP Global Forecast System (GFS) Atmospheric Model

Relevance to CMB-S4

•  SiteCharacteriza1on:Ourtoolcanprovidepredic7onsofanypoten7alsite’sopacityorbrightnesstemperaturetodetermineviabilityasafutureobservingloca7on.•  Recentworkhasbeendonetocompareexis7ngCMB

observingloca7onswithnewsites,includingSummitSta7on4inGreenland,Ali5ObservatoryinTibet,andDomeAinAntarc7ca.

•  TelescopeCalibra1on:Zenithbrightnesstemperature7mestreamcanbeusedtocalibrateores7matereal-7mesensi7vityatcurrentCMBobservatories(Figure5).

References

HowaccuratearetheMERRA2-basedpredic1ons?•  WecompareourMERRA2skybrightnesstemperaturepredic7onsto850GHz7ppermeasurements

takenfrom1998-2017atSouthPole(Fig2),ChajnantorPlateau,CerroChajnantor,andMaunaKea.

•  Themedian7pperuncertaintyis7-10K(5-6%)atallsites,andremainsbelow10%over93%ofthe7meatMaunaKeaandSouthPoleandover88%ofthe7meattheChajnantorsites.

•  WeassigntheMERRA2predic7onanuncertaintyrela7vetothe7pper’sknownuncertainty.Modelingtheresidual’svarianceasthesumofthe7pperσt2andtheMERRA2σm2variances,calcula7ngchi-squaredvaluesoftheresidualsallowsustosolvefortheunknownσm(Fig3):χ2=(7ppermeasurement-MERRA2modelpredic7on)2/(σt2+σm2)

•  IfMERRA2wereaperfectmodel,wewouldexpectχ2=1(i.e.σm=0).Forallsites,wefindχ2=2–6whichsuggeststheMERRA2modelhasbetween1and2.37mesthe7pperuncertainty(Fig4).

•  AtSouthPoleandMaunaKea,theMERRA2predic7onsareremarkablyclosetothemeasuredbrightnesstemperature.Predic7onsattheChajnantorsitesareslightlylessaccurate,buts7llwithin10-15%ofthemeasuredvalue.ThisisexpectedgiventhatthecomplexlocalweatherpajerninthemountainousChajnantorregionishardertospa7allyresolveaccuratelyonMERRA2’s50x50kmgrid.

•  Ground-basedCMBtelescopesobservethroughtheatmosphere,whichabsorbsasignificantfrac7onofthemm/sub-mmcosmicsignalandaddsthermalnoise.

•  Atmosphericturbulencealsoaddsnoisefluctua7onstoincomingradia7on.

•  WedeterminetheatmosphericstateusingMERRA2.MERRA2’sfocusontheatmosphericwatervaporisidealforthisapplica7on.

•  WevalidateMERRA2’spredic7onsbyquan7fyingitsuncertain7esagainstlong-baselinehistorical850GHzand225GHzopacity7pper3measurements.

•  Interpolate3-hourMERRA21dataproducts(e.g.ver7calprofilesofpressure,temperature,watermixingra7o,andotherrelevantquan77es)toanyposi7ononEarth.

•  Usethe2DMERRA2productstoobtaingroundvaluesoftheatmosphericprofiles.

•  Runtheamradia7vetransfermodel2ontheseprofilestogeneratefrequency-dependentatmospherictransmissionspectra,alongwithPWVvalue.

•  Integratethesespectraoveraninstrumentbandpasstopredicttheskybrightnesstemperatureforthatinstrument.

Publicly Available Tool

•  WebInterface(seebelow)andcommandlinetoolcurrentlyindevelopment;betaversionath$ps://goo.gl/czB24x

•  Userinputsaloca7on,daterange,andbandpass,andreceivesanoutputfileandplotswiththebrightnesstemperatureandPWVpredic7onsat3-hourintervals.

•  FutureWork:Weareaddingthecapabilitytomakepredic7onsforfuturedatesusingGFS6forecasts,touploadcustombandpassfiles.Wearealsoworkingonapaperdescribingthedetailedmethodsandvalida7onofthistool.

Figure1:Transmissionspectraoftheatmospherewithvaryinglevelsofprecipitablewatervapor(PWV).TransmissiondropssignificantlyasatmosphericPWVincreases,whichiswhyweneedtoiden7fylow-PWVsites.

Figure5:Brightnesstemperaturepredic7onsatSouthPolein2015fortheBICEP/KeckArray100/150/220/270GHzbands.

Figure2Le#:Time-seriescomparisonofMERRA2brightnesstemperaturepredic7onstoreal7pperdataevery3hoursfromFebruarytoApril2015atSouthPole.Right:One-to-onecomparisonandbest-fitlineforafullyear.

Figure3:ResidualsforFig2-lenatSouthPolefromFebruarytoApril2015,withaχ2of3.

Figure4(below):χ2valuesfortheaboveresidualsateachofthesites.Amedianχ2of2.9(asinSPandMK)meansthestandarddevia7onoftheMERRA2predic7onis1.47mesthatofthe7pper.Aχ2of6(asinChajnantor)impliesapredic7onuncertainty2.37mesthe7pper’suncertainty.