The evolution of sub-monsoon systems in the Afro-Asian monsoon region during the Holocene

22 Pages·2015·4.02 MB·English

Clim.Past,11,305–326,2015
www.clim-past.net/11/305/2015/
doi:10.5194/cp-11-305-2015
©Author(s)2015.CCAttribution3.0License.
The evolution of sub-monsoon systems in the Afro-Asian monsoon
region during the Holocene – comparison of different transient
climate model simulations
A.Dallmeyer1,M.Claussen1,2,N.Fischer1,K.Haberkorn2,S.Wagner3,M.Pfeiffer4,L.Jin5,V.Khon6,7,Y.Wang8,
andU.Herzschuh8,9
1MaxPlanckInstituteforMeteorology,Bundesstrasse53,20146Hamburg,Germany
2MeteorologicalInstitute,CentrumfürErdsystemforschungundNachhaltigkeit(CEN),UniversitätHamburg,
Bundesstrasse55,20146Hamburg,Germany
3HelmholtzCenterGeesthacht,InstituteforCoastalResearch,21502Geesthacht,Germany
4AlfredWegenerInstituteforPolarandMarineResearch,27568Bremerhaven,Germany
5KeyLaboratoryofWesternChina’sEnvironmentalSystems,LanzhouUniversity,ResearchSchoolofAridEnvironmentand
ClimateChange,Lanzhou730000,China
6InstituteofGeosciences,Christian-AlbrechtsUniversitätzuKiel,Ludewig-Meyn-Str.10-14,24118Kiel,Germany
7A.M.ObukhovInstituteofAtmosphericPhysicsRAS,Pyzhevsky3,117019Moscow,Russia
8AlfredWegenerInstituteforPolarandMarineResearch,TelegrafenbergA43,14473Potsdam,Germany
9InstituteofEarthandEnvironmentalScience,UniversityofPotsdam,Karl-Liebknecht-Strasse24–25,
14476Potsdam,Germany
Correspondenceto:A.Dallmeyer([email protected])
Received:29March2014–PublishedinClim.PastDiscuss.:15May2014
Revised:22January2015–Accepted:26January2015–Published:19February2015
Abstract. The recently proposed global monsoon hypothe- The East Asian monsoon changes independently during the
sis interprets monsoon systems as part of one global-scale Holocene.Thedissimilaritiesintheseasonalityofthemon-
atmospheric overturning circulation, implying a connection soon sub-systems lead to a stronger response of the North
between the regional monsoon systems and an in-phase be- African and Indian monsoon systems to the Holocene inso-
haviour of all northern hemispheric monsoons on annual lationforcingthanoftheEastAsianmonsoonandaffectthe
timescales (Trenberth et al., 2000). Whether this concept seasonaldistributionofHolocenerainfallvariations.Within
can be applied to past climates and variability on longer the Indian and North African monsoon domain, precipita-
timescales is still under debate, because the monsoon sys- tion solely changes during the summer months, showing a
temsexhibitdifferentregionalcharacteristicssuchasdiffer- decreasing Holocene precipitation trend. In the East Asian
entseasonality(i.e.onset,peakandwithdrawal).Toinvesti- monsoonregion,theprecipitationsignalisdeterminedbyan
gate the interconnection of different monsoon systems dur- increasingprecipitationtrendduringspringandadecreasing
ingthepre-industrialHolocene,fivetransientglobalclimate precipitation change during summer, partly balancing each
model simulations have been analysed with respect to the other. A synthesis of reconstructions and the model results
rainfalltrendandvariabilityindifferentsub-domainsofthe do not reveal an impact of the different seasonality on the
Afro-Asian monsoon region. Our analysis suggests that on timingoftheHolocenerainfalloptimuminthedifferentsub-
millennialtimescaleswithvaryingorbitalforcing,themon- monsoon systems. Rather they indicate locally inhomoge-
soons do not behave as a tightly connected global system. neous rainfall changes and show that single palaeo-records
Accordingtothemodels,theIndianandNorthAfricanmon- should not be used to characterise the rainfall change and
soonsarecoupled,showingsimilarrainfalltrendandmoder- monsoonevolutionforentiremonsoonsub-systems.
atecorrelationincentennialrainfallvariabilityinallmodels.
PublishedbyCopernicusPublicationsonbehalfoftheEuropeanGeosciencesUnion.
306 A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion
1 Introduction insolationchange.Thiswouldimplyanintensificationofthe
summermonsoonstrengthandanincreasedsummerprecip-
Monsoonsystemsarecoupledatmosphere–ocean–landphe- itationintheearlyandmid-Holocenefollowedbyagradual
nomenathatareprimarilydrivenbyseasonalandlatitudinal decrease of both climate variables in the course of the time
differencesinincomingsolarradiation.Thedifferentheatca- towardsthepresentday.
pacitiesofoceansandcontinentsleadtostrongthermalcon- Indeed, many palaeoenvironmental records reveal en-
trasts forming large-scale atmospheric circulations that re- hancednorthernhemisphericmonsooncirculationsandmore
verse seasonally and are characteristically accompanied by rainfallduringtheearlyand/ormid-Holocene(e.g.Fleitmann
summer rainfall and winter dryness (Webster et al., 1998). et al., 2003; Jolly et al., 1998; Peyron et al., 2006; Prasad
Changes in any component of the climate system affect the andEnzel,2006;Wangetal.,2005).However,notallrecon-
monsoon circulations and result in strong temporal climate structions show a synchronous trend within and among the
variability on all timescales (e.g. Ding, 2007; Lau et al., differentsub-monsoonregions.FortheNorthAfricanmon-
2000;Wang,2006).Themostpronouncedmonsoonsystems soon area, for instance, some records are indicative of an
aretheNorthAfricanandAsianmonsoon,incorporatingthe abrupt end of the humid period around 5k (e.g. deMeno-
IndianandEastAsianmonsoonsub-systems. cal et al., 2000), whereas other records suggest a gradual
Prior to the satellite era, observational data of monsoon decline in annual precipitation during the Holocene (e.g.
precipitationandcirculationswerescarce,particularlyabove Kropelin et al., 2008; Francus et al., 2013). The timing of
the oceans. By the use of remote sensing, monitoring of maximum Holocene rainfall in the Asian monsoon region
allmonsoonsystemshasbeenenabled.Thein-phasemove- strongly depends on the location (e.g. An et al., 2000) and
ment of the global monsoon systems partly visible in the theaffectingmonsoonsub-system(Maher,2008;Maherand
seasonal migration of the Intertropical Convergence Zone Hu,2006).WhilemoisturelevelsintheIndianmonsoonre-
(ITCZ) led to the development of a new monsoon concept, gion are highest during the early Holocene, the East Asian
i.e. the global monsoon hypothesis (Trenberth et al., 2000). monsoon did not reach maximum strength before the mid-
This concept suggests that all monsoon systems are part of Holocene (Herzschuh et al., 2006; Wang et al., 2010). On
one seasonal varying global-scale atmospheric overturning longer timescales, the precessional cycle is shared by most
circulationinthetropicsandsubtropicsforcedbytheannual monsoon systems, but Chinese speleothems lag the insola-
cycleofinsolationandtheresultantglobaldivergentmotion. tion curve by 4ka, northern African records by 2.6ka and
Furthermore, for instance, the African and Indian monsoon Indianrecordsby8ka(cf.Caleyetal.,2011andreferences
share similar decadal variability (Feudale and Kucharski, therein),showingnouniformresponsetotheinsolationforc-
2013).Whethertheglobalmonsoonconceptcanbeapplied ing.
to past climates and variability on longer timescales is not Varioussuggestionsofpossibleexplanationsforthedevi-
yet clear (Trenberth et al., 2000), although palaeomonsoon atingprecipitationtrendsexist,butsofarthecausalrelation-
studiesrevealsimilaritiestothemodernglobalmonsooncon- ships are not clear. Among other reasons, the differences in
cept regarding palaeomonsoon evolution, e.g. similar long- rainfalltrendscouldbeattributedtopreviousmisinterpreta-
term monsoon intensity oscillations in different monsoon- tion of the data (Cheng et al., 2012 and references therein;
subdomains(Chengetal.,2012). MaherandThompson,2012)and/ordifferencesinthechar-
During the early Holocene, the main changes in surface acteristics of the monsoon sub-systems: at least partly, the
boundary conditions compared to the present day were the monsoonresponsetotheorbitallycontrolledinsolationforc-
remnant Laurentide ice sheet and differences in the sea- ing is affected by differences in the land–sea settings (e.g.
sonalincomingsolarradiation.Forinstance,9000yearsago Wangetal.,2003,2013;Wang,2009)thatprobablyalsohave
(9k), the cyclic variations in the Earth’s orbital configura- animpactonthestrengthoftheinvolvedocean–atmosphere
tion (mainly the precession) led to a 10% higher summer feedbacks. The Indian and North African monsoon circula-
insolation on the Northern Hemisphere compared to today tions are determined by a meridional and interhemispheric
(Berger, 1978). In contrast, winter insolation was decreased land–oceancontrast,whiletheEastAsianmonsoonischar-
by10%yieldingonlysmallchangesintheannualmeanin- acterised by a zonal land–sea contrast (Wang et al., 2001).
solation,butanincreaseoftheamplitudeoftheseasonalin- Furthermore,theimpactofotherlarge-scalecirculationsys-
solationcycle.Whiletheinsolationdifferenceshavecontinu- tems (e.g. the Westerly wind system) varies among the dif-
ouslydecreasedthroughouttheHolocene,thepresentextent ferent monsoon sub-systems. For instance, the Indian mon-
of the Northern Hemisphere ice sheet was already reached soon system is less affected by mid- and high-latitude cli-
duringmid-Holocene.Accordingtotheglobalmonsooncon- mate processes than the East Asian monsoon (Huang et al.,
cept (Trenberth et al., 2000) and Kutzbach’s orbital mon- 2012). All monsoon systems show differences in the sea-
soonhypothesisofnorthernhemisphericsummerinsolation sonalcycle,particularlyinthetimingofonset,rainfallpeak
drivingthesummermonsoonevolutionatprecessionalscale and withdrawal. These differences in the seasonality of the
(Kutzbach, 1981; Ruddiman, 2006), one would expect that sub-monsoonsmayleadtodifferencesintheresponseofthe
all boreal summer monsoon systems react similarly to this
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A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion 307
monsoonsystemtotheHolocenechangeinseasonalinsola- 2.1.1 COSMOSandCOSMOSacc
tion.
Thus,whetherthemonsoonsystemsevolvesynchronously COSMOS is the model of the Community Earth System
or asynchronously during the Holocene, i.e. if the global models network, initiated by the Max Planck Institute for
or regional aspect of monsoons predominates on millennial Meteorology, Hamburg, Germany. The model consists of
timescales,isstillunderdebate.ToinvestigateHolocenepre- the general circulation model for the atmosphere ECHAM5
cipitation trends in different parts of the Afro-Asian mon- (Roeckner et al., 2003) coupled to the land-surface scheme
soonregionandtotesttheconnectivityofthedifferentmon- JSBACH(Raddatzetal.,2007)andtheoceanmodelMPIOM
soonsub-systemsinthisregion,weanalysefivetransientcli- (Marslandetal.,2003).Intheversionusedinthisstudy,JS-
mate simulations covering the last 6000 years, which have BACH included the dynamic vegetation module of Brovkin
been performed using various coupled atmosphere–ocean– et al. (2009) representing eight different plant functional
(vegetation) models. We focus on the following research types. MPIOM was integrated with a horizontal resolution
questions: ofapproximately3◦ and40levelsinthevertical.ECHAM5
wassetupinaspectralresolutionofT31L19corresponding
1. Can state-of-the-art climate models capture the recon- to a longitudinal distance of approx. 3.75◦ on a great circle
structedprecipitationtrendsintheAfro-Asianmonsoon and19levelsinthevertical.
region,e.g.retrievedfromspeleothemrecords? In this setup, two transient experiments have been per-
formed.Thefirst(COSMOS)wasconductedbyFischerand
2. Do the simulations reveal a synchronous precipitation
Jungclaus (2011) and started at mid-Holocene climate con-
responsetotheHoloceneinsolationforcingforallsub-
ditions(6000yearsago).Themodelwasbroughttoaquasi-
domains,supportingtheglobalmonsoonhypothesison
equilibrium climate state prescribing mid-Holocene insola-
longertime-scales?
tion forcing and pre-industrial atmospheric conditions (e.g.
CO composition of 280ppm). Afterwards, the orbital con-
2
3. If differences in the precipitation trend among sub-
figuration was changed yearly until present-day conditions
domainsexist,whichcontrollingmechanismscanbere-
werereached.Thechemical compositionoftheatmosphere
trievedfromthemodelresults,forinstanceinthecon-
stayedconstantduringtheentiresimulation.Thissimulation
textofchangesintheseasonalinsolationcycleanddif-
covers the last 6000 years. The data of this simulation are
ferencesintheseasonalityofthemonsoonsub-systems?
available as snapshots (every 50 years) in the PANGAEA
database(FischerandJungclaus,2012).
After a short description of the models, simulations and
The second simulation (COSMOSacc) was performed
methods used in this study, we first assess the performance
by Pfeiffer et al. (2013) (Varma et al., 2012; Pfeiffer and
of the models concerning the representation of the modern
Lohmann,2013)inthesamewayasthefirstsimulation,but
precipitationdistributionintheAfro-Asianmonsoondomain
using an orbital forcing accelerated by a factor of 10. This
(Sect.3.1).Thesecondpartoftheresultsdealswiththepre-
meansthattheperiodbetweenthemid-Holoceneandthepre-
cipitation change from mid-Holocene to present-day times
industrialperiodisrepresentedbyonly600insteadof6000
includingacomparisonoftheprecipitationtrendsinthedif-
model years. The chemical composition of the atmosphere
ferent models (Sects. 3.2–3.4). Based on these results, we
wasfixedtopre-industrialvalues.Similarexperimentswere
discusswhetherthetransientsimulationssupporttheglobal
also carried out by Lorenz and Lohmann (2004) with the
monsoon hypothesis for the Holocene monsoon evolution
ECHO-Gmodelusingtheaccelerationtechniqueforinvesti-
(4.2) and analyse the effect of the differences in seasonal-
gationsoftheclimateoftheHolocene.
ity on the Holocene monsoon response (4.3) as this is the
onlyhypothesisforthedeviatingprecipitationtrendswecan
2.1.2 ECHO-G
analysewiththissetupofsimulations.
ECHO-G (Legutke and Voss, 1999) consists of the atmo-
2 Methods sphericgeneralcirculationmodelECHAM4(Roeckneretal.,
1996) and the ocean model HOPE-G (Wolff et al., 1997).
2.1 Modeldescriptionandexperimentaldesign Adynamicvegetationmodelwasnotincludedinthissetup.
The vegetation is set to present-day conditions throughout
ToinvestigatetheHolocenerainfalltrendintheAfro-Asian the entirety of the simulations. ECHAM4 had a numerical
monsoon system, we analyse five transient climate model resolution of T31L19 corresponding to approx. 3.75◦ on a
simulations that have been performed in a wide spectrum great circle and 19 levels in the vertical. HOPE-G had 20
of coupled atmosphere–ocean–(vegetation) models (cf. Ta- irregularly spaced vertical levels and an effective horizon-
ble1).Inthefollowing,themodelsandsimulationsareintro- tal resolution of 2.8◦×2.8◦ increasing to 0.5◦ towards the
ducedbriefly;forfurtherdetailsonthesimulationswerefer Equator. In contrast to the newer COSMOS generation the
totheoriginalmanuscripts. ECHO-G model is flux corrected for heat and fresh water
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308 A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion
Table1.Overviewofalltransientclimatesimulationsconsideredinthisstudy,includingresolution(Res.),applicationoftheforcing(Acc.),
i.e.acceleratedornot,andhandlingofdynamicvegetationinthemodel.
Simulation Model Reference Res. Forcing Acc. Dyn.veg.
COSMOS ECHAM5/JSBACH-MPIOM FischerandJungclaus(2011) T31L19 Orbit No Yes
ECHO-G ECHAM4-HOPE-G Wagneretal.(2007) T31L19 Orbit No No
PLASIM PlaSim-LSGocean-Simba Haberkorn(2013) T21L10 Orbit+GHG No Yes
COSMOSacc ECHAM5/JSBACH-MPIOM Varmaetal.(2012); T31L19 Orbit Yes Yes
PfeifferandLohmann(2013)
KCM ECHAM5-NEMO Jinetal.(2014) T31L19 Orbit Yes No
in order to avoid climate drift. The model was brought to a Thecoupledmodelhadbeenbroughttoaquasi-equilibrium
quasi-equilibrium climate state using a mid-Holocene (7k) climate state with the early Holocene orbital configuration
orbital configuration (Wagner et al., 2007). Afterwards, the (9.5k) before the transient simulation started using orbital
insolationforcingwaschangedaftereachmodelyear.Inthe forcing only (Jin et al., 2014). The forcing, i.e. change in
transientsimulationusedinthisstudy,thechemicalcompo- orbital parameters, was accelerated by a factor of 10. The
sition of the atmosphere was kept constant at pre-industrial chemicalcompositionoftheatmospherewassettoconstant
levels.Thefirstpartofthissimulation(7000BP–4500BP)is pre-industrialvaluesthroughoutthesimulation.KCMshows
availableontheCERAdatabase(Wagner,2007). good agreement between simulated precipitation and obser-
vationsforcontemporaryclimate,aswellaswiththehydro-
2.1.3 PLASIM logicalchangesduringthemid-Holocene(Khonetal.,2010).
PlaSim is an atmosphere model of medium complexity 2.2 Analysesmethodsofmodelresults
(Fraedrich et al., 2005) and was used in a horizontal reso-
lution of T21 (approx. 5.6◦×5.6◦ on a Gaussian grid) and Precipitation in monsoon regions has a strong seasonality
10 levels in the vertical. In the simulation used for this and usually the summer (i.e. June–September) precipitation
study (Haberkorn, 2013), PlaSim was coupled to the ocean is taken to analyse changes in the monsoon intensity and to
model LSG (Maier-Reimer et al., 1993) and the vegeta- discussrainfallvariationsinmonsoondomains.Wedecided
tion module SimBA (Kleidon, 2006). The model had been touseannualprecipitationbecausewealsoincludetheEast
broughttoquasi-equilibriuminearlyHoloceneclimatecon- Asian monsoon region in which precipitation is not solely
ditions (10k orbit and atmospheric composition). Then the related to the summer season. Here, more than 30% of an-
transient simulation was started using yearly adapted or- nual rainfall already falls during the months February–May
bital forcing (Berger, 1978). Holocene variations in atmo- (cf.YihuiandZunja,2008).Furthermore,reconstructionsof-
sphericCO concentrationwereadditionallyprescribedfrom ten integrate over a longer period and therefore an annual
2
Taylor Dome reconstructions (Indermuhle, 1999). For in- signal rather than a monthly or seasonal signal is recorded.
stance, atmospheric CO content was changed from 265– Forexampleplants(pollenproxy)canusemoisturestoredin
2
269ppmduringthemid-Holocenetothepre-industriallevel the soil or lake level changes (various sedimentary proxies)
(280ppm). The effect of increasing CO during the pre- record the annual balance. We do not want to exclude the
2
industrialHoloceneisrelativelysmallcomparedtochanges pre-monsoon precipitation in East Asia from our analysis.
inorbitalforcing.Therefore,wedonotexpectanysubstan- In all other regions considered here, annual precipitation is
tialimpactofthevaryingCO concentrationontheresultsof highly correlated with summer precipitation. Therefore tak-
2
this study. Here, the last 6000 years of this simulation were ingannualrainfallinsteadofsummerrainfalldoesnotaffect
used. the results in these regions. Moreover, defining a meaning-
fultimeperiod(intheformofmonths)forthesummermon-
2.1.4 KCM soonseasonisdifficultinpalaeo-studiesbecausethesummer
monsoonseasonmaybevariableoverthetime.
TheKielClimateModel(KCM,Parketal.,2009)isacou-
pled atmosphere–ocean–sea ice general circulation model. 2.2.1 Definitionofthetime-slices
The atmosphere is represented by ECHAM5 (Roeckner et
al., 2003) that ran in the numerical resolution T31L19 cor- We compare the simulated climate of the mid-Holocene
responding to 3.75◦ on a great circle. ECHAM5 is cou- (6000yearsago,furtherreferredtoas6k)andpre-industrial
pledtotheocean–seaicemodelNEMO(Madec,2006)that time-slice(herereferredtoas0k).Theresultsarebasedon
ran with a horizontal resolution of approx. 2◦×2◦ and in- climatological means of 120 years, i.e. 120 model years in
creased meridional resolution (0.5◦) close to the Equator. the non-accelerated experiments and 12 model years in the
Clim.Past,11,305–326,2015 www.clim-past.net/11/305/2015/
A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion 309
onthelast1000yearsofthesimulations.Forthiscalculation,
thetimeserieshavebeenfilteredbya10-yearrunningmean
andhavebeendetrendedbya500-yearrunningmean.Only
thenon-acceleratedsimulationsareconsidered.
The rainfall trend series in the different sub-regions are
based on 100-year running means to filter out interannual
and interdecadal variability. Only the non-accelerated sim-
ulations have been considered since the accelerated simu-
lations reveal a strong year-to-year variability. The signifi-
cance of the trend is estimated by the signal-to-noise ratio.
Figure1.Definitionofthedifferentmonsoonsub-regionsusedin
The time series are displayed as anomalies with respect to
thisstudy(shaded)andthelocationsofcavesintheEastAsianmon-
thelasttime-steprepresentingthepre-industrialclimate.To
soonregion(letters)forwhichspeleothemrecordsexist,i.e.Dongge
cave(D,25.32◦N,108.09◦E;Wangetal.,2005),HeshangCave(H, calculatethecorrelationsamongrainfallinthedifferentmon-
30.45◦N,110.42◦E;Huetal.,2008),LianhuaCave(L,29.29◦N, soonsub-regions,thetimeserieshavebeendetrendedbythe
109.32◦E; Cosford et al., 2008), and Jiuxian Cave (J, 33.34◦N, 500-yearmovingaverageoftheannualtimeseries.Therain-
◦
109.6 E;Caietal.,2010). falltrendseriesareprovidedassupplementarymaterialinthe
PANGAEAdatabase(http://dx.doi.org/10.1594/PANGAEA.
837442). Sliding correlations are performed for annual and
accelerated experiments. We are aware of the short period decadal time series to assess if the teleconnections among
usedtorepresenttheacceleratedsimulations.Therefore,we thesub-systemsarestableandiftheregionalmonsoontele-
calculated the statistical significance of the rainfall change connectionsweakenedorstrengthenedundervaryingorbital
using the student’s t test and only show results that are sig- parameters.
nificant at the 95% level in the case of the non-accelerated Similarly, as for the time-slice results, the seasonal cy-
simulationsandsignificantatthe90%levelinthecaseofthe cleineachsub-regionhasbeencalculatedonclimatological
acceleratedsimulations.Thereby,themainaimistheassess- monthlymeansof120years.
mentofthephysicalsignificanceoftherainfallchange.
Global fields of precipitation (in netCDF) for both
3 Results
time-slices are provided as supplementary material in the
PANGAEAdatabase(http://dx.doi.org/10.1594/PANGAEA.
3.1 Pre-industrialAsianandNorthAfricansummer
837442).
monsoonprecipitation
2.2.2 Inferenceofrainfalltrendsandcomparisonof
Inordertogetanoverviewoftherepresentationofthepre-
regionaltimeseries
industrialcontrolclimateinthedifferentmodelswecompare
the simulated precipitation with data of the Global Precipi-
Thedifferentsub-regionspresentedinthisstudy(cf.Fig.1)
tation Climatology Project (GPCP, 1979–2008, Adler et al.,
have been defined on the basis of the leading empirical
2003).Asthepre-industrialsimulationshavebeenperformed
orthogonal function (EOF) mode of the annual precipita-
with a CO concentration of 280ppm, considerably lower
2
tion variations. For this purpose, the ensemble mean of the
thanthoseobservedforthepresentday,weexpectsmallbi-
non-accelerated simulations (i.e. COSMOS, ECHO-G and
ases particularly in the strength of the monsoon system and
PLASIM)hasbeenstandardisedanddetrendedbya500-year
precipitationamountresultingfromthedifferentCO levels.
2
running mean. The EOF was calculated afterwards for the
African,IndianandeasternAsianregions.Themonsoonsub- 3.1.1 Evaluationoftheannualprecipitationpattern
systemsareselectedbasedontheareasshowingthehighest
loadings in the respective region. The East Asian monsoon Ingeneral,themodelsareabletocapturethesummermon-
domain is divided into two sub-regions, as it is commonly sooncirculation(seeAppendix).Theyshowsimilardiscrep-
characterisedbybipolarprecipitationpatterninpresent-day anciestotheobservedprecipitationpattern,buttheamplitude
observations, e.g. floods in the north, droughts in the south ofthebiasesdiffers(Fig.2).Allmodelstendtooverestimate
(e.g.Ding,2007). annualprecipitationintheEastAsianmonsoonregion.This
To test whether the different monsoon sub-systems are is particularly pronounced in the area between the Yangtze
connectedduringpre-industrialtimes,wecalculatethePear- andHuangheRiverineasternChina(100–120◦E,25–35◦N)
soncorrelationcoefficientbasedonthelast150yearsofthe wherepre-industrialannualprecipitationexceedsthemodern
annual mean precipitation time series (for interannual vari- observations by more than 750mmyear−1 in most simula-
ability).Forthispurpose,thetimeserieshavebeendetrended tionsandtheensemblemean.
by a 30-year running mean. In addition, we calculate the In contrast, precipitation in the Indian monsoon re-
Pearsoncorrelationcoefficientsfordecadaltimescalesbased gion is highly underestimated in all models, particularly in
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310 A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion
Table2.Absoluterainfall(mmyear−1)intheensemblemeanAfro-Asianmonsoonregion(includinglandandocean,cf.Fig.2)duringthe
pre-industrialperiodandinobservations.
GPCP COSMOS ECHO-G PLASIM COSMOSacc KCM ENSMEAN
Rainfall(mmyr−1) 941.7 1016.8 965.0 862.1 1052.2 998.2 978.9
Taylor Diagram precipitation
0.1 0.2
0.3 l KCM
0.4 l ECHO−G
0.5 l COSMOS
1.5 1.5 0.6 0C.7orrelation lll PCElNOaSSSMiMmEOASNacc
n 0.8
eviatio 1.0 1
d
d
ar 0.9
d
n
a
st lll
l 0.95
0.5 ll 0.5
0.99
0.0 l
0.0 0.5 1.0 1.5
standard deviation
Figure 3. Taylor diagram showing the pattern correlation, nor-
Figure 2. Biases in annual mean precipitation (mmyear−1) be- malisedstandarddeviationandnormalisedroot-mean-squareerror
(greycircles)ofthesimulatedprecipitationinthedifferentmodels
tweenthedifferenttransientsimulations(last100years,i.e.0k)and
(0k-time-slice)fortheAfro-Asianmonsoonregion.Referencedata
themodernobservedclimate,representedbytheprecipitationdata
set:GPCP,basedontheyears1979–2008(whitedot).
oftheGlobalPrecipitationClimatologyProject(GPCP,1979–2008,
Adleretal.,2003).Thegreylineintheplotoftheensemblemean
marksthesimulatedpre-industrialAfro-Asianmonsoonregion,i.e
the55%isolineofthesummertoannualprecipitation. totheobservation.Inaddition,itdisplaysthestandarddevia-
tionineachdatasetcomparingtheamplitudeofthetemporal
andspatialpatternvariations.Overall,ECHO-Ghasasimilar
Bangladesh, which exceeds by −750mmyear−1. With the spatial and temporal variation as observed precipitation and
exception of ECHO-G showing more precipitation than ob- agreesbestwiththeobservedprecipitationpattern.PLASIM
served, all other models also underestimate precipitation by underestimates the variation slightly and shows the lowest
more than 300mmyear−1 in large parts of northern Africa. correlation.KCM,COSMOSaccandCOSMOSdemonstrate
Above the tropical oceans, the models simulate consider- a very similar skill for simulating the North African and
ably higher precipitation compared to observations. How- Asianmonsoonprecipitation.Thosemodelsslightlyoveres-
ever,overtheseoceanicareas,precipitationobservationsare timate the amplitude in pattern variation, but show a good
alsoafflictedwithhigheruncertainty. patterncorrelation.Theensemblemeanrevealsthebestpat-
Averagedovertheentireensemblemeanmonsoonregion tern correlation and also the highest agreement in terms of
ofNorthAfricaandAsia(includingoceanicareas,cf.Fig.2), spatialandtemporalvariation.
COSMOS, COSMOSacc and KCM simulate too much pre-
cipitation, and PLASIM too little precipitation. ECHO-G 3.1.2 Evaluationoftheseasonalprecipitationcycle
simulatessimilarrainfallasobserved(cf.Table2).Tofurther
quantifythebiasesbetweensimulatedandobservedprecipi- Toassesstheperformanceofthemodelswithrespecttothe
tation(hereGPCPdata),wechoseaTaylordiagram(Fig.3). seasonalprecipitationcycle,thesimulatedpre-industrialsea-
This diagram is based on the climatological monthly mean sonal precipitation cycle for each sub-region is compared
precipitationvaluesofeachsimulationandshowsthepattern to the seasonal cycle derived from present-day GPCP data
correlation of the simulated and observed precipitation and (Fig. 4): during the present-day times, the rainy season in
the centred root-mean-square difference of each simulation the North African monsoon region (NAM) starts in March
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A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion 311
is shifted by one month to August. Rainfall rates are much
lowercomparedtoobservations.
The observed seasonal precipitation cycle in the East
Asian monsoon area (EASM) is different to the cycle in
the tropical monsoon regions of Africa and India. Over this
region, precipitation occurs during the entire year reaching
rainfall rates of 1–2mmday−1 during winter and spring.
Nevertheless, the temporal rainfall distribution reflects a
monsoonal character with summer dominant rainfall and
much higher precipitation rates in summer than in win-
ter. Maximum rainfall is reached during June with approx.
6mmday−1.AllmodelsexceptPLASIMareabletosimulate
thisseasonalcycle.However,winterandspringprecipitation
isstronglyoverestimatedby1–2mmday−1leadingtoarain-
fall peak by May. During summer, simulated rainfall rates
areasobservedinmostmodels.ECHO-Gsimulatesrainfall
ratessimilartothoseobserveduntilMay;afterwardsprecip-
itation rates decrease and are underestimated until Septem-
ber. PLASIM strongly overestimates the late summer, au-
Figure 4. Simulated pre-industrial seasonal precipitation cycle tumnandwinterprecipitation.
comparedtoGPCPobservationaldata(inmmday−1,basedonthe The observed seasonal precipitation cycle in the north-
years 1979–2008), for different regions in the Afro-Asian mon- ern East Asian monsoon region (NEASM) is characterised
soon domain, i.e. the North African monsoon region (NAM), In- by weak winter/spring rainfall rates and high summer rain-
dianmonsoonregion(ISM),EastAsianmonsoonregion(EASM), fall rates, although much less than in the other parts of the
andthenorthernpartoftheEastAsianmonsoonregion(NEASM).
monsoondomain,withamaximumprecipitationrateofonly
Pleasenotethechangeinscale. 2.7mmday−1 inJuly.Mostmodelscapturetheseasonalcy-
cle, but slightly overestimate precipitation throughout the
yearbyapprox.0.5mmday−1.ECHO-Gsimulatestoolittle
summerprecipitation.Similarly,asfortheEastAsianmon-
with rainfall continuously increasing to a rainfall peak of soon region, PLASIM strongly overestimates precipitation
4mmday−1 in August. Afterwards, precipitation declines duringtheentireyear.
until October. This seasonal cycle is simulated correctly by
all models with the exception of ECHO-G which strongly 3.1.3 Connectivityofthedifferentsub-monsoon
overestimates precipitation during March–July, leading to systems
peak rainfall by July. COSMOS, COSMOSacc and KCM
Table3showsthePearsoncorrelationcoefficientsforthean-
simulate a similar seasonal cycle as observed, but underes-
nual and decadal (in brackets) precipitation time series of
timate rainfall rates during the entire rainy season (at sum-
mer peak by 1–2mmday−1). PLASIM reveals less than the different sub-regions considered here. Overall, only the
0.5mmday−1 as the precipitation peak, which is a typical COSMOSmodelshowsastrongpositivecorrelationamong
annual and decadal mean precipitation in the Indian and
rainfall rate in (semi-) arid regions. Thus, with respect to
the North African monsoon (r >0.8). In COSMOS, pre-
maximumprecipitationPLASIMdoesnotidentifytheNorth
cipitation variability over these regions is also moderately
Africanmonsoonasamonsoonregion.
correlated with precipitation over the northern part of the
The observed precipitation maximum over the Indian
EastAsianmonsoon(annual:r >0.6anddecadal:r >0.5).
monsoon region (ISM) is reached during July following a
These correlations stay at high levels throughout the entire
very rapid increase of rainfall starting in May. None of the
6000years(notshown).Fortheotherregionsandintheother
models captures this seasonal cycle: in PLASIM, the rainy
models,correlationsareveryweakandthereforechangeus-
season is very short. Precipitation starts to increase as late
ing different sliding windows. They remain mostly statisti-
as July and does not peak until September. Rainfall rates
callynon-significant(notshown).
are strongly underestimated during the entire rainy season.
COSMOS, COSMOSacc and KCM reveal a similar mon-
soon season length as observed, but simulate a double-peak
monsooninJulyandSeptember.However,thesemodelsalso
underestimate precipitation during the entire rainy season,
particularly KCM, by up to 3mmday−1. Precipitation rates
riseslowerinECHO-Gthanobservedandthemonsoonpeak
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312 A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion
Table3.Pearsoncorrelationcoefficientsforthe0krainfalltimeseries,basedonthelast150years(1000years)detrendedbya30-year
(500-year)runningmeanforannual(decadal)variability,fordifferentmonsoonsub-regions,i.e.theIndianmonsoonregion(ISM),North
Africanmonsoonregion(NAM),EastAsianmonsoonregion(EASM),andthenorthernpartoftheEastAsianmonsoonregion(NEASM).
Onlythenon-acceleratedsimulationshavebeenused.
COSMOS ISM NAM EASM NEASM
ISM 1.00(1.00) – – –
NAM 0.83(0.83) 1.00(1.00) – –
EASM 0.19(0.00) 0.10(−0.01) 1.00(1.00) –
NEASM 0.62(0.57) 0.67(0.51) 0.14(0.03) 1.00(1.00)
ECHO-G ISM NAM EASM NEASM
ISM 1.00(1.00) – – –
NAM 0.0(−0.12) 1.00(1.00) – –
EASM −0.06(−0.12) −0.11(0.02) 1.00(1.00) –
NEASM 0.12(0.09) 0.06(0.00) 0.22(0.26) 1.00(1.00)
PLASIM ISM NAM EASM NEASM
ISM 1.00(1.00) – – –
NAM 0.04(0.01) 1.00(1.00) – –
EASM 0.05(0.01) 0.10(0.01) 1.00(1.00) –
NEASM 0.10(0.11) 0.08(0.08) 0.01(0.09) 1.00(1.00)
3.2 Mid-Holoceneclimate
3.2.1 Changesinannualprecipitationpattern
Figure 5 shows the simulated mean annual precipitation
difference between the mid-Holocene and pre-industrial.
All models simulate an increase in precipitation in the
North African and Indian monsoon regions during the mid-
Holocene compared to the pre-industrial climate. In most
models, these changes are connected with a shift in the
ITCZ, indicated by the bipolar difference in precipitation
pattern between ocean and land, particularly in northern
Africa.ThispatternisconsistentwiththeincreaseinNorth-
ern Hemisphere summer insolation (Kutzbach, 1981). The
largestchangesoccurinCOSMOSandKCMrevealinganin-
creaseinprecipitationbymorethan500mmyear−1 inlarge
partsofthemonsoonregion.
IntheNorthAfricanmonsoonarea,thesimulatedmagni-
tudeofprecipitationchangediffersstronglyamongthemod-
Figure5.Simulatedmeanannualprecipitationdifference(shaded,
els. ECHO-G reveals a relatively weak response to the in- mmyear−1)betweenmid-Holocene(6k)andpre-industrialclimate
solation change with an increased mid-Holocene precipita- (0k).Onlysignificantvaluesareshown,i.e.significantatthe95%
tion by less than 200mmyear−1. PLASIM shows a signifi- level(student’st test)forthenon-acceleratedexperiments(ECHO-
cantriseinrainfallintheentiretyofnorthernAfricainclud- G,COSMOS,PLASIM)andsignificantatthe90%levelfortheac-
ing the Sahara, but the strongest changes are concentrated celeratedexperiments(COSMOSacc,KCM).Theensemblemean
around the Equator. COSMOS, COSMOSacc and KCM in- (ENSMEAN)isdefinedassignificantifallsimulationsagreeinthe
signoftheprecipitationchangeintheindividualgrid-boxes.There-
dicatethestrongestincreaseinprecipitationinabroadarea
between the Equator and 20◦N (by up to 400mmday−1). constructionsofBartleinetal.(2010)areadditionallyshown(dots,
samelegendasthesimulateddata).
Regarding the precipitation increase in the Indian monsoon
region, the models are in better agreement with each other.
All models show a relatively strong response in a broad re- to650mmyear−1 inKCM).COSMOSaccistheonlymodel
gionextendingfromIndiatothecentralTibetanPlateau(up revealingnosignificantsignal.
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A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion 313
IncontrasttotheincreasedNorthAfricanandIndianmon-
soon rainfall during the mid-Holocene, the models tend to
simulate less precipitation in the core regions of the East
Asianmonsoondomain.InPLASIM,precipitationdecreases
byapprox.200mmyear−1 inIndochina,easternChina,and
overthewesternPacificOcean.COSMOSandCOSMOSacc
revealasignificantreductionofprecipitationonlyincentral-
eastern China (up to 300mmyear−1). In ECHO-G, the de-
creaseinprecipitationislimitedtotheIndochinesePeninsula
andthewesternPacific.Thestronginter-modeldiscrepancies
concerningtherainfallchangeintheEastAsianmonsoonre-
gionleadtoanon-significantsignalintheensemblemean.
Figure5additionallyshowspollen-basedprecipitationre-
constructions(Bartleinetal.,2010)plottedontopofthesim-
ulated precipitation changes. Overall, the simulated rainfall
difference between the mid-Holocene and the pre-industrial
agreewellwithreconstructionswhichrevealsubstantiallyin-
creased mid-Holocene precipitation at most sites. However,
the models tend to underestimate the precipitation change,
Figure6.Simulatedchangeintheseasonalprecipitationcyclebe-
particularlyinnorthernAfricaandeasternChina. tweenmid-Holoceneandpre-industrialclimate(mmday−1)fordif-
ferent regions in the Afro-Asian monsoon domain, i.e. the North
3.2.2 Changeintheseasonalprecipitationcycle
African monsoon region (NAM), Indian monsoon region (ISM),
EastAsianmonsoonregion(EASM),andthenorthernpartofthe
Figure6showsthesimulatedchangeintheseasonalprecipi- East Asian monsoon region (NEASM). Please note the change in
tationcyclebetweenthemid-Holoceneandthepre-industrial scale.
forthedifferentmonsoonsub-regions.
Forthemid-Holocenetime-slice,themodelsrevealacon-
sistent picture regarding the shape of change in the North solation forcing throughout the year. In most models, win-
African seasonal precipitation cycle (NAM), but they vary ter and spring precipitation are substantially reduced by
regarding the amplitude. Precipitation is increased from up to 1mmday−1 (1.5mmday−1 in KCM). Summer mon-
June to November revealing the strongest signal in August soon rainfall is increased by 0.5mmday−1 (PLASIM) to
(PLASIM,ECHO-GandKCM)andSeptember(COSMOS, 1.3mmday−1 (COSMOS) at most. The strongest enhance-
COSMOSacc). The most intense response is shown in mentofrainfalloccursinJuly(ECHO-G,PLASIM),August
COSMOS with a peak signal of up to 3.5mmday−1. The (KCM)andSeptember(COSMOS).
weakestresponseoccursinPLASIMwithmaximumvalues Most models simulate slightly decreased precipitation in
of0.5mmday−1atmost.Themaximumprecipitationdiffer- the northern East Asian monsoon region (NEASM) dur-
encebetweenthemid-Holoceneandthepre-industrialtime- ing the mid-Holocene winter and spring. This signal is par-
sliceintheNorthAfricanmonsoonregioncoincideswiththe ticularly pronounced in PLASIM (0.5mmday−1 at most).
present-day monsoon season peak, suggesting a strong in- During summer, rainfall increases in all models by up
tensitychangeoftheNorthAfricanmonsoonandnotapost- to 0.8mmday−1 (COSMOS). Maximum precipitation is
ponementofthemonsoonseason. reached in July (KCM) or August. PLASIM shows a very
Similar to the North African monsoon region, all mod- weakresponsetochangesinthesummerinsolationandsim-
els simulate increased precipitation during summer and au- ulatesonlyslightlymoreprecipitationduringOctober.
tumn(May–November)intheIndianmonsoonregion(ISM) Theseasonalprecipitationchangeindicatesthattheannual
during the mid-Holocene with maximum precipitation val- rainfallsignalsintheAfricanandIndianmonsoonregionare
uesinAugust(PLASIM,KCMandECHO-G)andSeptem- mostly related to the increased summer monsoon precipita-
ber (COSMOS, COSMOSacc). PLASIM and KCM reveal tionat6k.Incontrast,thedecreasedmid-Holocenerainfallin
the strongest response with 2.5 and 2.2mmday−1 at most, parts of the East Asian monsoon area (cf. Fig. 5) cannot be
respectively. In the other models, the magnitude of rain- explainedbysummermonsoonchanges.Withtheexception
fall change is similar with maxima ranging from 1.2 to of PLASIM, precipitation is increased in most parts of the
1.6mmday−1. EastAsianmonsoondomainduringthemid-Holocenesum-
The simulated seasonal precipitation change in the East mermonsoonseason(notshown)revealingthatthedecrease
Asian monsoon region (EASM) from the mid-Holocene to inprecipitationisrelatedtochangesinthepre-monsoonsea-
thepre-industrialisverydifferenttothechangeinthetrop- son as previously pointed out in Dallmeyer et al. (2013). In
icalmonsoon domainbecauseprecipitation reactsto thein- this region, the Holocene summer monsoon signal is over-
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314 A.Dallmeyeretal.:Theevolutionofsub-monsoonsystemsintheAfro-Asianmonsoonregion
Table 4. Pearson correlation coefficients for the rainfall time se-
riesinthedifferentmonsoonsub-regions,i.e.theIndianmonsoon
region (ISM), North African monsoon region (NAM), East Asian
monsoonregion(EASM),andthenorthernpartoftheEastAsian
monsoonregion(NEASM).Thetimeserieshavebeendetrendedby
a500-yearmovingaveragebeforecalculatingthecorrelationcoef-
ficients.Onlythenon-acceleratedsimulationshavebeenused.
COSMOS ISM NAM EASM NEASM
ISM 1.00 – – –
NAM 0.38 1.00 – –
EASM −0.08 −0.02 1.00 –
NEASM 0.50 0.36 0.19 1.00
ECHO-G ISM NAM EASM NEASM
ISM 1.00 – – –
NAM 0.31 1.00 – –
EASM −0.19 −0.02 1.00 –
NEASM 0.12 0.20 0.17 1.00
PLASIM ISM NAM EASM NEASM
ISM 1.00 – – –
NAM 0.27 1.00 – –
EASM −0.08 0.03 1.00 –
NEASM −0.11 0.09 0.17 1.00
compensatedbythepre-monsoonsignal.Incomparisonwith
thereconstructionsofBartleinetal.(2010),whichshowin-
creased precipitation in East Asia, COSMOS and ECHO-G
may overestimate the decreased pre-monsoon precipitation
at6k.
Figure 7. Simulated rainfall trend (100-year running mean, in
mmyear−1) in different sub-regions of the Afro-Asian monsoon
3.3 Rainfalltrend
domain, displayed as an anomaly to the last time-step represent-
ing the pre-industrial climate. The regions are: the North African
Figure7showstheevolutionofrainfallinthedifferentsub-
monsoonregion(NAM),Indianmonsoonregion(ISM),EastAsian
monsoonregionsbasedonthenon-acceleratedclimatesimu-
monsoonregion(EASM),andthenorthernpartoftheEastAsian
lations.FortheNorthAfricanregion,allmodelsshowasta-
monsoonregion(NEASM).
tisticallysignificant(>99%)negativerainfalltrendranging
from 40mm/6000 years (PLASIM) to 280mm/6000 years
(COSMOS). The trends are relatively linear, but all models
suggest a stronger trend in the first 4000 years, i.e. from 6 for some periods in the last 2000 years. The evolution of
to 2k, than in the last 2000 years of the simulations. Both theprecipitationsignalsimulatedbyCOSMOSshowsmod-
ECHO-G and COSMOS reveal periods of long-lasting dry erate positive correlation with the precipitation variability
and wet phases interrupting the general trend. The non- overnorthernAfrica(r =+0.38,Table4).InECHO-Gand
linearity of the trends is consistent with changes in orbital PLASIM,Indianrainfallisonlyweaklycorrelatedwithrain-
forcing, i.e. the rate of change in the decline of northern fallovernorthernAfrica(r =+0.31andr =+0.27,respec-
hemisphericsummerinsolationislargerinthemid-Holocene tively).
comparedtothelateHolocene. The models disagree regarding the sign of the precipita-
FortheIndianmonsoonregion,allmodelsindicateasim- tion trend over the East Asian monsoon region. COSMOS
ilardecreasingtrendof130–160mm/6000years.Thistrend and PLASIM indicate a slightly increasing trend during the
is statistically significant (>99%) and linear, but superim- Holoceneof20mm/6000years(significantatthe90%level)
posed by several long-lasting dry and wet periods. For in- and 80mmyear−1 (significant at the 99% level), respec-
stance, COSMOS, and to a minor extent ECHO-G, reveal tively. In contrast, ECHO-G reveals a slightly decreasing
a prominent long-lasting dry period around 2k. PLASIM trend of 20mm/6000 years (significant at the 95% level).
simulateslessprecipitationcomparedtopre-industrialtimes Thetrendsaregenerallylinear,buttheareaischaracterised
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