Transcript
Page 1: The Madden-Julian Oscillation moist static energy budget

11.AcknowledgementsThisworkhasbeensupportedbytheNationalScienceFoundationResearchExperiencesforUndergraduatesSiteinClimateScienceatColoradoStateUniversityunderthecooperativeagreementNo.AGS-1461270.

TheMadden-JulianOscillationmoiststaticenergybudgetinCMIP5models

ShannonBohman1,CharlotteDeMott2,DavidRandall2StonyBrookUniversity,StonyBrook,NY1 andColoradoStateUniversity,FortCollins,CO2

Process metric CorrelationwithMJOskillVerticallongwaveheatingregressedontoMSEtendency -0.4866HorizontalMSEadvectionregressedonto MSE -0.4603AreaaveragedU850ineasternregion 0.7755PatterncorrelationbetweenmodelandERAIV850 0.7047Zonaldifferenceincolumnwatervapor 0.6051σ LH flux 0.6406σ wind-drivenLHflux 0.6350σthermodynamicSHflux 0.6316σ thermodynamicLHflux 0.5841σ wind-drivenSHflux 0.4560

Figure1.SchematicoftheMadden-JulianOscillation.3

• TheMadden-JulianOscillation(MJO)isasystemofalternatingenhancedandsuppressedatmosphericconvectionthatpropagateseastwardat5ms-1.OriginatinginthetropicalIndianOceanevery30-70days,theMJOaffectsmonsoons,tropicalcyclones,andjetstreamactivity.

• ClimatemodelswithcoupledoceanfeedbacksareknowntosimulatetheMJOmoreaccuratelythanuncoupledmodels.

1.Introduction

Freetroposphericterms Surfacefluxterms

Horizontaladvection

Verticaladvection

Longwaveheating

Shortwaveheating

Latentheating

Sensibleheating

• 14coupledCMIP5models:BCC,BNU,CCCMA,CNRM,FGOALS-g2,GFDL,GFDL-CM3,GFDL-ESM2M,IPSL,IPSL-MR,MIROC5,MPI,MRI,NCC• 2othercoupledmodels:CESM2_265_B1850,SPCCSM• Observationaldata:EuropeanCentreforMediumRangeForecasting(ECMWF)InterimReanalysis(ERAI)

4.DataSources

5.ModelsrankedbyMJOskill 6.MSEbudgetanalysis

Figure3.Regressingbudgettermsontomaintenance(MSE)ortendency(dMSE/dt)revealswhichtermscontributetoeachprocess.Sinceprocessmetric1isinphasewithMSE,itcontributestoMJOmaintenance.Sinceprocessmetric2isinphasewithdMSE/dt,itcontributestoMJOpropagation.

3.MSEbudget

2.MeasuringMJOskill• Generatetimelagvslongitudeplotsfor±20daysfrom60-180Efor90Eand150Ebasepoints.

• Mask±15degreesabouteachbasepoint.• Computeregressioncoefficientsbetween

modelandERAIplotsat90Eand150E.• Averagethe90Eand150Eregression

coefficientstogetskillscore.

• Moiststaticenergy(MSE):energyreleasedifallwatervaporinanairparcelcondenses.

• Conservedduringmoistadiabaticprocesses.4

12.References3Gottschalck,J.(2014,December31).WhatistheMJO,andwhydowecare?|NOAAClimate.gov.Retrievedfromhttps://www.climate.gov/news-features/blogs/enso/what-mjo-and-why-do-we-care4Yanai,M.,Esbensen,S.,&Chu,J.(1973). DeterminationofBulkPropertiesofTropicalCloudClustersfromLarge-ScaleHeatandMoistureBudgets (Vol.30,pp.611-627,Rep.).AmericanMeteorologicalSociety5Ahn,M.,Kim,D.,Sperber,K.R.,Kang,I.,Maloney,E.,Waliser,D.,&Hendon,H.(2017,March23).MJOsimulationinCMIP5climatemodels:MJOskillmetricsandprocess-orienteddiagnosis(Rep.).doi:10.1007/s00382-017-3558-4

7.MSEadvection 8.Oceansurfacefluxes

Figure10.Analysisperformedover15S-15Nand30-180E.Latentheatfluxanditswind-drivencomponentarepositivelycorrelatedwithMJOskillsignificantlyatthe99%levelandthethermodynamicLHfluxispositivelycorrelatedatthe95%level.ThermodynamicsensibleheatfluxispositivelycorrelatedwithMJOskillsignificantlyatthe99%level,butthereisnosignificantcorrelationbetweenMJOskillandsensibleheatfluxasawhole.

Table1.CorrelationcoefficientsbetweendifferentprocessmetricsandMJOskill.Allcoefficientsaresignificantatthe90%level.Coefficientssignificantat95%arebolded.Coefficientssignificantatthe99%levelareboldedanditalicized.

9.Conclusions• PropagationofMJObeyondMaritimeContinentisimportanttoskillscore.

• VerticallongwaveheatingdominatesMSEmaintenance,butitdoesnothavesignificantbearingonMJOskill

• Consistentwithotherstudies5

• HorizontalMSEadvectiondrivesMSEpropagation.• NearlyallmodelsrelyonoverestimatingthezonalmoisturegradienttocompensateforunderestimatingtheU850winds.

• SimulationofMJOismostdependentonlargemeanstatemoisturegradientsandrealisticwindanomalies.

10.Futurework• FurtherstudythefeedbacksofsurfacefluxesonMJOtounderstandcausationinthoserelationships

• SSTeffectonMJOmaintenanceandpropagation

Zonaldifferenceincolumnwatervapor,𝛻𝑞

V850patterncorrelationbetweenmodelandERAI

V850

AreaaveragedU850ineasternregion

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BudgettermsregressedontoMSEmaintenance, 𝑚 BudgettermsregressedontoMSEtendency,% &%'

σLHflux σwind−drivenLHflux σthermodynamicLHflux

σSHflux σwind−drivenSHflux σthermodynamicSHflux

Figure4.Modelsrankedbyskillscore.

Figure2.ComparingMJOofonemodeltoobservations

Observatio

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Surfaceflux

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𝐿𝑊 regressedon 𝑚

𝐿𝐻regressedon 𝑚

𝑆𝐻regressedon 𝑚

Figure5.MSEbudgettermsregressedontoMSEmaintenance.VerticallongwaveradiationisthedominantterminmaintainingMJOconvection.ModelMJOskillandhorizontalMSEadvectionhaveacorrelationcoefficientof-0.4866significantatthe90%level.

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𝜔𝜕𝑞𝜕𝑝

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*Notedifferentscale

Figure6.MSEbudgettermsregressedontoMSEtendency.HorizontalMSEadvectionisthedominantterminMJOpropagation.ModelMJOskillandverticallongwaveheatinghaveacorrelationcoefficientof-0.4603significantatthe90%level.

𝑚 = 𝐶6𝑇 + 𝑔𝑍 + 𝐿;𝑞

𝜕 𝑚𝜕𝑡

= − 𝑉 * 𝛻𝑞 − 𝜔𝜕𝑞𝜕𝑝

+ 𝐿𝑊 + 𝑆𝑊 + 𝐿𝐻 + 𝑆𝐻

MJOskillranking:1. CNRM2. SPCCSM3. NCC4. MRI5. CESM2_265_B18506. GDFL-CM37. BCC8. MIROC59. BNU10. FGOALS-g211. MPI12. GDFL-ESM2M13. GDFL14. IPSL-MR15. CCCMA16. IPSL

ERAIdisplayedinblack

MSEmaintenance:

MSEtendency:

Longitude

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nwatervapor(kg/m

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Figure7.Zonaldifferenceincolumnwatervapor.Thewesternaveragingregionis15S-15Nand90-100E,andtheeasternaveragingregionis15S-15Nand155-165E.ModelMJOskillandzonaldifferenceincolumnwatervaporhaveacorrelationcoefficientof0.6051significantatthe95%level.

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Figure8.Zonalwindsaveragedover15S-15Nand100-150E.ModelMJOskillandareaaveragedU850haveacorrelationcoefficientof-0.7755significantatthe99%level.

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Figure9.Analysisperformedover15S-15Nand30-180E.PatternskillswerecalculatedbetweenthemeridionalwindsofeachmodelandERAI.ModelMJOskillandV850patterncorrelationhaveacorrelationcoefficientof0.7047significantatthe99%level.

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