What controls the variability of springtime fine dust in the...

WhatcontrolsthevariabilityofspringtimefinedustinthewesternUnitedStates?

ImplicationsfortherecentdustincreaseintheSouthwest

PloyPattanun AchakulwisutLuShen

LorettaJ.MickleyHarvardUniversity

PMandRelatedPollutantsinaChangingWorldEPARTP,6-7April2017

Phoenixduststorm,2015Ploy(nearlyallwork) Lu(guidance)

ClimatechangecouldhavealargeimpactondustandwildfirePMinthewesternUS.

DuststorminSanJoaquinValley,California RimFireinCalifornia,August2013.

Dry,hot,windyconditionscanleadtobothduststormsandwildfires.• Howwillchangingclimatechangethefrequencyofdusteventsandwildfires?• Whataretheimplicationsforairquality?

Yueetal.,(2013,2014,2015),Liu(2016….)

ClimatechangecouldhavealargeimpactondustandwildfirePMinthewesternUS.

DuststorminSanJoaquinValley,California

Dry,hot,windyconditionscanleadtobothduststormsandwildfires.• Howwillchangingclimatechangethefrequencyofdusteventsandwildfires?• Whataretheimplicationsforairquality?

AreaburnedinthewesternUS

Newinventory

GFED4GFED3

Wedevelopanewemissionsinventoryusingon-the-groundinteragencyfirereports.Yueinpreparation.

WestandSouthwestwilllikelyexperiencewarmeranddrierconditionsinthefutureclimate,withimplicationsfordust.

Anomaliesinprecipitationminusevaporation(P-E)

medianP-E

medianevap

medianprecip

ResultsovertheSouthwestfromanensembleof19climatemodels.

Seager etal.,2007

Reasonsfortrend:• ExpansionofHadleycell• Poleward shiftofpolarjet• Slowerwesterlies,lessmoisturedeliveredtomountains

drier

wetter

Drierconditions+landusechangecouldenhancedustconcentrations,withimplicationsforhumanhealth.

Hahnenberger etal.,2012ArrivalofaduststorminSaltLakeCity,Utah.

DusteventsinSaltLakeCityexceedtheNAAQSforPM10aboutonceperyear.

22August2010,3:30p.m.

20minuteslater

Dustcarriesmicroorganismsharmfultohumanhealth– e.g.,Cocciodiodes,thecauseofCocciodioidomycosis (a.k.a.valleyfever).

ValleyFevercanbefatalifsporesreachthebrain.ThediseaseismostcommoninArizonaandpartsofSouthernCalifornia.

NumberofreportedcasesinUS,1998-2015

CDC

OverseascontributiontoUS“worstdustdays”

%

PreviousstudiesonUSdust

Transpacificsourcesaccountfor~40%ofworstdustdaysintheWest.Fairlie etal.,2007

IMPROVEsitesshowdustincreasinginMarchintheWest,+5%yr-1.Handetal.,2016

UsingdatafromIMPROVEsites,ourstudyconfirmsthereportedtrendinMarchspringdust.

2002-2015TrendsindustatIMPROVEsitesintheWestMARCH

125W 115W 105W30N

40N

50NAPRIL

125W 115W 105W

MAY

125W 115W 105W

−0.4 −0.2 0.0 0.2 0.4(µg m−3 y−1)

March MayApril

Boxesindicatestatistically

significanttrends.

Weseektounderstand:• DriversofvariabilityofdustconcentrationsacrosstheWest.• CausesofMarchtrendindust.

Usingthisknowledge,wewillexaminetheimplicationsofclimatechangefordustinthewesternUS.

Approachoffirstdustproject.1.UseEOFanalysistodeterminethedominantpatternsofdustconcentrationsacrossthewest.

2.ProbetheEOFresultstoidentifymeteorologicaldriversthatdrivethevariabilityofdust.

3.Usinginfofrom#2,buildstatisticalmodelsthatrelatemeteorologyandteleconnectionpatternstodustconcentrations.

4.ApplythesemodelstoarchivedoutputfromIPCC.

Benefitsofapproach:• Strongrelianceonobserved

relationships.• Useofanensembleofclimate

modelsandscenariostoobtainrobustresults.

29%

(a) 1st EOF loading

30% 45%

26%

(b) 2nd EOF loading

MARCH

20%

APRIL

16%

MAY

−0.2 −0.1 0.0 0.1 0.2

29%

(a) 1st EOF loading

30% 45%

26%

(b) 2nd EOF loading

MARCH

20%

APRIL

16%

MAY

−0.2 −0.1 0.0 0.1 0.2

EOFanalysisofMarchdustshowstwopatternsthattogetherexplain55%ofdustvariability:• Northwest-Southwestdipole• Uniformpattern

Whatdrivesthesepatterns?

HerewefocusonresultsforMarchdustinthewesternUS.

withJFMSSTs

2002 2004 2006 2008 2010 2012 2014−8

−4

0

4

8

12

−2

−1

0

1

2

3

JFM ENSO, r=0.74JFM PDO, r=0.69

(a) March PC1 time series (29%)

−1.0

−0.5

0.0

0.5

1.0

(b) Homogeneous corr map

−1.0

−0.5

0.0

0.5

1.0(c) Corr(PC, JFM SST)

−1.0

−0.5

0.0

0.5

1.0(d) Corr(PC, JFM Tmax)

−1.0

−0.5

0.0

0.5

1.0(e) Corr(PC, JFM precip)withJFMmaxTemps withJFMPrecip

CorrelationsofPC1withmeteorologicalvariables.

PC1ofMarchdustpatternscorrelateswellwithENSOindexandwiththePacificDecadalOscillation.

2002 2004 2006 2008 2010 2012 2014−8

−4

0

4

8

12

−2

−1

0

1

2

3

JFM ENSO, r=0.74JFM PDO, r=0.69

(a) March PC1 time series (29%)

−1.0

−0.5

0.0

0.5

1.0

(b) Homogeneous corr map

−1.0

−0.5

0.0

0.5

1.0(c) Corr(PC, JFM SST)

−1.0

−0.5

0.0

0.5

1.0(d) Corr(PC, JFM Tmax)

−1.0

−0.5

0.0

0.5

1.0(e) Corr(PC, JFM precip)

Timeseries ofPC1inMarch CorrelationofPC1withdust

ENSO

PDOPC1r =0.69, r =0.74

ElNinowintersareassociatedwithdecreaseddustinthedesertSouthwest.

OppositeoccursduringLaNinawinters,whensubtropicaljetisweaker.LaNinaleadstoincreasedsubsidenceoverSouthwestandgreaterdustconcentrations.

ElNiñoconditions:• Southwardshiftof

Pacificstormtrack.

• IncreasedwinterprecipitationacrossthesouthernUS.

• ReducednortherlyflowofcoldairfromCanadainNorthwest.

2002 2004 2006 2008 2010 2012 2014−8

−4

0

4

8

−100

0

100

200MGI, r=0.81AOD, r=0.62

(a) March PC2 time series (26%) (m)x 10−2

−1.0

−0.5

0.0

0.5

1.0

(b) Homogeneous corr map

−1.0

−0.5

0.0

0.5

1.0

(c) Corr(PC, Mar 500 mbar gph)

2002 2004 2006 2008 2010 2012 2014−8

−4

0

4

8

−100

0

100

200MGI, r=0.81AOD, r=0.62

(a) March PC2 time series (26%) (m)x 10−2

−1.0

−0.5

0.0

0.5

1.0

(b) Homogeneous corr map

−1.0

−0.5

0.0

0.5

1.0

(c) Corr(PC, Mar 500 mbar gph)

CorrelationofPC2withdust

CorrelationofPC2withMarch500mb heights

AOD

PC2ofMarchdustpatternsappearsrelatedwithtransportofAsiandustacrossthePacific.

PC2correlateswith:1. MeridionalGradientIndex

(differenceinheightsbetweenthetwoboxes)

2. AODincentralPacific.

2002 2004 2006 2008 2010 2012 2014−8

−4

0

4

8

−100

0

100

200MGI, r=0.81AOD, r=0.82

(a) March PC2 time series (26%) (m)x 10−2

−1.0

−0.5

0.0

0.5

1.0

(b) Homogeneous corr map

−1.0

−0.5

0.0

0.5

1.0

(c) Corr(PC, Mar 500 mbar gph)

Timeseries ofPC2inMarch

AOD

Meridionalgradientindex

PC2 r =0.62r =0.81

120W 115W 110W 105W32N

36N

40N

Trends and concentrations in March fine dust, 2002−2015 average

California Southwest

−0.30

−0.15

0.00

0.15

0.30(µg m−3 y−1) (µg m−3)

1

1

1

1

1

< 1.5

< 2.5

< 3.5

< 4.5

< 5.5

WelookmorecloselyatrecenttrendsinMarchdustinCaliforniaandSouthwest.

Weuseastepwiseapproachtobuildalinearregressionmodeltounderstandobservedincreases.

UsinginformationfromEOFanalysis,weconsiderthesevariables:ENSO,PDO,localmeteorologicalvariables,droughtindices….

Size=meanconcentrationBox=significanttrend

2002-2015Trendsandmeanconcentrationsoffinedust

Phoenix

2002 2004 2006 2008 2010 2012 20140.5

1.5

2.5

3.5 Observed (Trend = 0.11 µg m−3 y−1)Modeled (R2 = 0.76)

(a) Southwest regional−mean March fine dust conc. (µg m−3) time series

−3−2−1

012

−1.5−1−0.500.51

2002 2004 2006 2008 2010 2012 2014

PDOSPEI48

(b) JFM PDO and SPEI48 time series

MarchvariabilityindustintheSouthwestcanbeexplainedbyvariationsinPDOanddrought.

Timeseries ofregionalmeandustintheSouthwestinMarch

Timeseries ofpredictors

PDO

SPEI48

Droughtindex

observations

model

CoolPacific+increasingdrought,increasingdust

WarmPacific+littledrought,lowdust?

Dustco

ncentrationµg

m-3

R2 =0.76

2002 2004 2006 2008 2010 2012 20140.5

1.5

2.5Observed (Trend = 0.05 µg m−3 y−1)Modeled (R2 = 0.81)

(a) California regional−mean March fine dust conc. (µg m−3) time series

−2

−1

0

1

2

2002 2004 2006 2008 2010 2012 2014

SPEI48SMGIRH

(b) JFM SPEI48, March SMGI and RH (%) time series

45

55

65

75

MarchvariabilityinCaliforniadustcanbeexplainedbyvariationsinrelativehumidity,transportfromAsia,anddrought.

Timeseries ofCaliforniaregionalmeandust

Dustco

ncentrationµg

m-3

Timeseries ofpredictors

RH

SPEI48Meridionalgradientindex

Droughtindex

model

observationsR2 =0.81

NextstepwillbetoapplyourstatisticalmodelofmonthlymeandusttotheensembleofCMIP5models.

2000 2002 2004 2006 2008 2010 2012 2014

0

20

40

60

80

100 None D0 D1 D2 D3 D4

Area (%) of different drought types averaged over AZ, NM, TX, and OK for Jan−MarPercentofSouthweststatesindifferentstatesofdrought

nodrought

Extremedrought

Severedrought

Southwesthasseenshifttowardincreaseddroughtsince2000.Willthistrendcontinue?IsitrelatedtotoexpansionofHadleyCell?

Policyrelevantmessages.

• ObserveddustincreaseinMarchinSouthwestandCaliforniaappearsrelatedtonaturalvariability– i.e.,thesignalofclimatechangehasnotemergedfromthenoise.

• Projectionsoflikelydroughtintheregioncouldleadtogreaterfrequencyofduststorms,withimplicationsforhumanhealth.

WearecurrentlyinvestigatingtrendsinfuturedustandsmokeconcentrationsacrosstheWest,usingbothstatisticalanddynamicmodels.

Ourresearchgroup,spring2016