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Monsoons in a changing world: A regional perspective in aglobal context
Akio Kitoh,1 Hirokazu Endo,1 K. Krishna Kumar,2 Iracema F. A. Cavalcanti,3
Prashant Goswami,4 and Tianjun Zhou5
Received 15 September 2012; revised 8 February 2013; accepted 11 February 2013.
 We provide a new view of global and regional monsoonal rainfall, and their changes inthe 21st century under RCP4.5 and RCP8.5 scenarios as projected by 29 climate modelsthat participated in the Coupled Model Intercomparison Project phase 5. The model resultsshow that the global monsoon area defined by the annual range in precipitation is projectedto expand mainly over the central to eastern tropical Pacific, the southern Indian Ocean,and eastern Asia. The global monsoon precipitation intensity and the global monsoon totalprecipitation are also projected to increase. Indices of heavy precipitation are projected toincrease much more than those for mean precipitation. Over the Asian monsoon domain,projected changes in extreme precipitation indices are larger than over other monsoondomains, indicating the strong sensitivity of Asian monsoon to global warming. Over theAmerican and African monsoon regions, projected future changes in mean precipitation arerather modest, but those in precipitation extremes are large. Models project that monsoonretreat dates will delay, while onset dates will either advance or show no change, resultingin lengthening of the monsoon season. However, models limited ability to reproduce thepresent monsoon climate and the large scatter among the model projections limit theconfidence in the results. The projected increase of the global monsoon precipitation can beattributed to an increase of moisture convergence due to increased surface evaporation andwater vapor in the air column although offset to a certain extent by the weakening of themonsoon circulation.
Citation: Kitoh, A., H. Endo, K. Krishna Kumar, I. F. A. Cavalcanti, P. Goswami, and T. Zhou (2013), Monsoons in achanging world: A regional perspective in a global context, J. Geophys. Res. Atmos., 118, doi:10.1002/jgrd.50258.
 The monsoon is conventionally defined as a seasonalreversal of prevailing surface winds, driven by the seasonalcycle of solar heating and difference in thermal inertias ofland and ocean that establish a land-sea temperaturedifference [Webster and coauthors, 1998]. This large-scalewind reversal creates favorable conditions for the occurrenceof convection in the summer hemisphere. As the monsoonseason matures, latent heat released by convection highabove the land surface helps to draw additional moisture overthe land from nearby oceans, maintaining the wet season.
Monsoons are responsible for the majority of summer rainfallwithin the tropics, where billions of people depend on themonsoon-related rainfall. Patterns of projected global-scalechanges in the surface temperatures are robust among models,with greater warming over land than over ocean and at mosthigh latitudes [Meehl and coauthors, 2007]. Therefore, theland-sea temperature contrast is projected to become largerin summer, together with ample moisture available in awarming world, leading to a more intense monsoon. However,in spite of their common basic mechanism, monsoons overdifferent regions are subject to diverse forcing; thus theresponses of the various regional monsoons to a changingclimate are expected to vary [Meehl et al., 2007; Turner andAnnamalai, 2012]. The monsoon region is distributed over all the tropical
continents, and over the tropical oceans in the western NorthPacific, eastern North Pacific, and the southern Indian Ocean[Wang and Ding, 2006]. Although the American monsoonsare not characterized by a seasonal reversal of wind, thereare large differences in precipitation, humidity, andatmospheric circulation between summer and winter [Veraand coauthors, 2006; Raia and Cavalcanti, 2008; Marengoand coauthors, 2010]. While different indices have beenused to identify the lifecycle of monsoons, the definition ofthe monsoon in terms of the precipitation characteristics[Wang and LinHo, 2002; Wang and Ding, 2006] rather than
1Meteorological Research Institute, Tsukuba, Ibaraki, Japan.2Indian Institute of Tropical Meteorology, Pune, India.3Center for Weather Forecasting and Climate Studies (CPTEC), National
Institute for Space Research (INPE), Cachoeira Paulista, SP, Brazil.4CSIR Centre for Mathematical Modelling and Computer Simulations
(C-MMACS), Bangalore, India.5LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences,
Corresponding author: A. Kitoh, Climate Research Department, Meteoro-logical Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan.(firstname.lastname@example.org)
2013. American Geophysical Union. All Rights Reserved.2169-897X/13/10.1002/jgrd.50258
JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES, VOL. 118, 113, doi:10.1002/jgrd.50258, 2013
the wind reversal, permits the use of similar monsoon indi-ces for all the monsoon regions (keeping in mind that rainfallis the lifeline for billions of people living there). Thus, froma global point of view, precipitation characteristics overSouth Asia, East Asia, Australia, Africa, and the Americascan be viewed as an integrated global monsoon system, asso-ciated with a global-scale persistent atmospheric overturningcirculation [Trenberth et al., 2000]. Wang and Ding have demonstrated that the global monsoon is the dominantmode of the annual variation of the tropical circulation,characterizing the seasonality of the tropical climate. Examination of historical precipitation records over
the monsoon regions around the globe reveals a decreasingtrend in the global land monsoon precipitation over the lasthalf of the 20th century (19482003), with primary contribu-tions from a weakening of the summer monsoon systems inthe Northern Hemisphere (NH) [Wang and Ding, 2006;Ramesh and Goswami, 2007; Zhou et al., 2008b]. Changesin both the monsoon area and monsoon intensity contributeto this decreasing tendency [Zhou et al., 2008a]. However,the combined (oceanic and land) monsoon precipitationhas increased for the more recent 19792008 epoch mainlydue to a significant upward trend in the NH summermonsoon precipitation [Wang et al., 2012]. When thechange in monsoon-affected domain is considered, thefractional increase in monsoon area is greater than in totalprecipitation, so that the ratio of these two measures (whichserves as an index of the global monsoon intensity) exhibitsa decreasing trend for the most recent 30 year (19792008)period [Hsu et al., 2011]. Kim et al.  investigated the reproducibility of
global monsoon climate variability simulated by the coupledglobal climate models (CGCM) that participated in theCoupled Model Intercomparison Project phase 3 (CMIP3).They found that the CMIP3 CGCM multimodel ensemblesimulates a reasonably realistic climatology of the globalmonsoon precipitation and circulation, but models have com-mon biases such as a northeastward shift of the IntertropicalConvergence Zone (ITCZ) over the tropical North Pacific.Kim et al.  also pointed out that models with higherresolution generally reproduced a better spatial pattern of theglobal monsoon precipitation compared to lower-resolutionmodels. Hsu et al.  investigated global monsoonarea and precipitation in the late 21st century using threehigh-resolution atmospheric GCMs (40 km MPI ECHAM5,20 kmMRI/JMA, and 50 kmGFDLHiRAM) that were forcedby different future sea surface temperature (SST) warmingpatterns. They found a consistent increase in the globalmonsoon area, precipitation, and intensity among the modelprojections. Recently, many climate modeling groups around
the world have participated in the Coupled ModelIntercomparison Project phase 5 (CMIP5), under which aseries of experiments including the 20th century historicalsimulation and 21st century climate projections with fourdifferent representative concentration pathway (RCP)scenarios were performed [Taylor et al., 2012]. There isevidence that the CMIP5 models are better than the CMIP3models in simulating the Asian-Australian monsoon system.Several works [Li et al., 2012; Sperber et al., 2012] havereported that the CMIP5 multimodel mean is more skillfulthan the CMIP3 multimodel mean; however, the CMIP5
models simulation of El Nio-Southern Oscillation-monsoonrelationships is still found to be poor (correlation is too weak).Lee and Wang  and Hsu et al.  found an increaseof global monsoon area and precipitation intensity under theRCP4.5 scenario in CMIP5 model simulations of futurechanges in the global monsoon. These results are essentiallyconsistent with CMIP3 model results [Hsu et al., 2012,2013] but with some regional differences [Lee and Wang,2012]. The objective of this paper is to provide an updatedview of global and regional monsoonal rainfall and changesin the 21st century as projected by 29 CMIP5 models underthe RCP4.5 and RCP8.5 scenarios: our analysis includes notonly mean precipitation but also some precipitation extremeindices and monsoon seasonality changes for seven landmonsoon regions across the world.
2.1. Global Climate Model Data
 Table 1 lists the models used in our analysis. We usedmonthly mean data from 29 CMIP5 models and dailyprecipitation data from 21 CMIP5 models. Results fromhistorical (19862005), RCP4.5 (20802099), and RCP8.5(20802099) experiments were investigated. Only oneensemble member from each model was used. The gridsquares where the land fraction exceeds 10% were regardedas land area in the analysis. Further information on theexperiments and the models is available from the CMIP5web site (http://cmip-pcmdi.llnl.gov/cmip5/).
2.2. Observed Precipitation Data for Validation
 We used Climate Prediction Center Merged Analysisof Precipitation (CMAP) [Xie and Arkin, 1997], GlobalPrecipitation Climatology Project (GPCP) [Huffman et al.,2009], Climatic Research Unit Time-Series 3.1 (updatedfrom Mitchell and Jones ), Global PrecipitationClimatology Centre Full Reanalysis version 6 (GPCC v.6)(updated from Rudolf et al. ), Variability Analysis ofSurface Climate Observations (GPCC-VASClimO) [Becket al., 2005], GPGP One-Degree Daily data (GPCP 1DD)Version 1.2 [Huffman et al., 2001], and Tropical RainfallMeasuring Mission (TRMM) 3B42 product in version 6[Huffman et al., 2007]. Note that GPCC-VASClimO isgridded data (0.5 degrees 0.5 degrees) designed forclimate variability and trend studies, based on timeseries of 9343 stations covering at least 90% of the period19512000. All the observational data were first regriddedonto a common 2.5 degree 2.5 degree resolution(but GPCP 1DD and TRMM 3B42 were regridded onto2.0 degree 2.0 degree resolution).2.3. Definition of Monsoon Domains, Onset, Retreat,and Duration
 A monsoon domain is defined where the annual rangeof precipitation exceeds 2.5 mm d1, based on the definitionof Wang et al. . Here the annual range is defined asthe difference between the May-September (MJJAS) meanand the November-March (NDJFM) mean. Monsoon onsetdate, retreat date, and its duration are determined using thecriteria proposed by Wang and LinHo  utilizing onlyprecipitation data. Based on the regionally averaged relative cli-matological mean daily precipitation, which is the difference
KITOH ET AL.: GLOBAL MONSOONS IN CMIP5 MODELS
between the climatological daily precipitation and dry month(January in NH and July in the Southern Hemisphere (SH))mean precipitation, the onset (retreat) date is defined as thedate when the relative precipitation first exceeds (last dropsbelow) 5 mm d1, and the duration is defined as their differ-ence. The daily climatology of precipitation was defined asthe sum of the first 12 harmonics of daily average precipitation.
2.4. Extreme Precipitation Indices
 We used four precipitation indices: average precipita-tion (Pav), simple precipitation daily intensity index (SDII),
seasonal maximum 5 day precipitation total (R5d), andseasonal maximum consecutive dry days (CDD). Here SDIIis defined as the total precipitation divided by the number ofdays with precipitation greater than or equal to 1 mm. R5d isdefined as the seasonal maximum precipitation total in fiveconsecutive days. CDD is defined as the seasonal maximumnumber of consecutive dry days with precipitation less than1 mm. These indices were calculated for the summer season(MJJAS in NH and NDJFM in SH). All the extreme precip-itation indices for the models were at first calculated for theiroriginal grid, and then averaged over each monsoon domain.
Figure 1. Observed (thick contour) and simulated (shading) global monsoon domain, based on thedefinition by Wang et al. . The observation is based on GPCP data, and the simulations are basedon 29 CMIP5 multimodel mean precipitation with a common 2.5 by 2.5 degree grid in the present-day(19862005) and the future (20802099; RCP8.5 scenario). Warm yellow (dark blue) shading: monsoondomain only in the present-day (future). Blue shading: monsoon domain in the both periods.
Table 1. List of CMIP5 Models Used in This Study
Model ID Institute ID Country Horizontal (Lon. Lat.) Monthly DailyACCESS1-0 CAWCR Australia 192145 1.8751.25 ACCESS1-3 CAWCR Australia 192145 1.8751.25 bcc-csm1-1 BCC China 12864 T42 CanESM2 CCCMA Canada 12864 T63 (TL63) CCSM4 NCAR USA 288192 1.250.942 CESM1-BGC NCAR USA 288192 1.250.942 CESM1-CAM5 NCAR USA 288192 1.250.942 CNRM-CM5 CNRM/CERFACS France 256128 TL127 CSIRO-Mk3-6-0 CSIRO/QCCCE Australia 19296 T63 FGOALS-g2 LASG/IAP China 12860 2.83.1 FGOALS-s2 LASG/IAP China 128108 R42 GFDL-CM3 GFDL USA 14490 2.52 GFDL-ESM2G GFDL USA 14490 2.52 GFDL-ESM2M GFDL USA 14490 2.52 GISS-E2-R GISS USA 14490 2.52 HadGEM2-CC MOHC UK 192145 1.8751.25 HadGEM2-ES MOHC UK 192145 1.8751.25 INM-CM4 INM Russia 180120 21.5 IPSL-CM5A-LR IPSL France 9696 3.751.895 IPSL-CM5A-MR IPSL France 144143 2.51.268 IPSL-CM5B-LR IPSL France 9696 3.751.895 MIROC-ESM MIROC Japan 12864 T42 MIROC-ESM-CHEM MIROC Japan 12864 T42 MIROC5 MIROC Japan 256128 T85 MPI-ESM-LR MPI-M Germany 19296 T63 MPI-ESM-MR MPI-M Germany 19296 T63 MRI-CGCM3 MRI Japan 320160 TL159 NorESM1-M NCC Norway 14496 2.51.895 NorESM1-ME NCC Norway 14496 2.51.895
KITOH ET AL.: GLOBAL MONSOONS IN CMIP5 MODELS
3. Global Monsoon: Area and Intensity
 Figure 1 shows the observed and simulated globalmonsoon domains for the present climate. The multimodelensemble mean of 29 CMIP5 models generally reproducesthe observed global monsoon domain, although it tends tooverestimate the areal extent in the NH and underestimateit in the SH, except in the African monsoon region(overestimate) and in North American monsoon region (un-derestimate). Models also have some difficulty in reproduc-ing monsoon rainfall in East Asia. This underestimation ofmonsoon domain in East Asia was pointed out by Kim etal.  for the CMIP3 models,...