Global monsoon, El Niño, and their interannual linkage simulated by MIROC5 and the CMIP3 CGCMs

Hyung-Jin Kim1 (hyungjin@jamstec.go.jp), Kumiko Takata1, Bin Wang2, Masahiro Watanabe3,Masahide Kimoto3, Tokuta Yokohata4, and Tetsuzo Yasunari1,5

1Global Hydro-climate Process Research Team/GCPRP/RIGC, JAMSTEC, Japan 2IPRC/SOEST, University of Hawaii, USA 3AORI, the University of Tokyo, Japan 4CGER, NIES, Japan 5HyARC, Nagoya University, Japan

Verifying and tracing the performance of a coupled global climate model (CGCM) are indispensable for its continuous improvement. These efforts more often focus on fundamental processes which may be reasonably categorized into two groups depending upon the type of impetus: forced responses to external forcings and self-recurrent phenomena due to internal feedbacks.

This study evaluates the capability of CGCMs in simulating the prime examples of the forced response (global monsoon) and internal feedback process (El Niño). Emphases are also placed on CGCMs’ fidelity of the year-to-year variability of global monsoon precipitation associated with the interannual tropical SST fluctuation.

1. Introduction

2. Proposed Concepts

(1) Global Monsoon

a. Domain: annual range (AR) of precipitation rate(westerly wind or poleward wind at 850 hPa) exceeds2.5 mm/day (2.5 m/s).AR = MJJAS (NDJFM) minus NDJFM (MJJAS) in NH (SH)

b. Intensity: AR/annual mean

(2) Monsoon Year: May to subsequent April.

Fig. 1 (a) Global monsoon precipitation domain (solid curves) and monsoon precipitation index (MPI, color shadings) defined using the GPCP data (1979-2008); (b)-(e) the model counterparts (1970-1999) derived from 20C3M MME, MIROC5, MIROC3hi, and MIROC3med, respectively.

Fig. 3 (a) Standard deviation and (b) asymmetry (˚C2) of the monthly Niño 3 index. The ±20 % limits of the observed value are denoted by red lines.

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Fig. 2 Evaluation of the CGCMs’ performance on the climatological global monsoon index (left) and domain (right). The regression coefficient is shown in lower-right corner of each panel. The domain used is 0˚-360˚E, 40˚S-45˚N.

(1) Observation- GPCP version 2: 1979-2008- NCEP/DOE Reanalysis 2: 1980-2009 - NOAA ERSST version 3: 1979-2008

(2) Model- CMIP3 20C3M simulation: 20 CGCMs, 1970–1999- MIROC3med (T42) and MIROC3hi (T106)- MIROC5: T85 atmospheric and 1-degree ocean models

3. Data and Model

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(1) Coefficient of Determination: SquareOf pattern correlation coefficient (PCC)

(2) Threat Score: hit/(hit+missed+false)

3.1 Evaluation: Global Monsoon

(1) Amplitude: Standard deviation of the monthly Niño 3 index (90W-150W, 5S-5N)

(2) Asymmetry: Skewness, a measure of the asymmetry of a probability distribution function defined as the normalized third statistical moment

(3) Periodicity: dominant periods of the monthly Niño 3 index that pass the red noise test with 95% confidence level

3.2 Evaluation: El Niño Properties

Fig. 4 Dominant periods of the monthly Niño 3 index. Only periods that pass the red noise test with 95% confidence level are plotted. In the observation (ERSST), annual-to-quasi-biennial mode (1-2.5 years) and El Niño mode (3-5 years) are observed.

(1) Coupled Mode: Maximum Covariance Analysis (MCA) between global monsoon rainfall and tropical SST

(2) Leading Mode of Global Monsoon Precipitation: To see whether the precipitation patterns that are concatenated with El Niño are also visible in the year-to-year global monsoon precipitation variability, the EOF analysis is applied to the global monsoon precipitation itself. In observation, pattern and temporal correlation coefficients between PR MCA1 and PR EOF1 are 0.96 and 0.99, respectively.

3.3 Evaluation: Interannual Variability

Fig. 5 Spatial patterns of (a)-(b) global monsoon precipitation and SST obtained from MCA1 and (c) global monsoon precipitation obtained from EOF1, and (d) the corresponding time expansion coefficients. For comparison, the Niño 3 SST anomaly averaged over the monsoon year are shown in panel (d). The data period is 1979-2008.

3.3 Continued

(1) How robust is theyear-to-year coupling inthe CMIP3 CGCMs?In MIROC5, spatiotemporalpatterns of PR EOF1 are virtuallyidentical to those of PR MCA1.Among the CMIP3 CGCMs,19 (12) models out of 22 modelsthat have El Niño amplitudegreater than 50 (80)% of theobserved show a PCC betweenPR EOF1 and PR MCA1 higherthan 0.66 (0.80).

(2) Does the improvedEl Niño simulation entailmore realistic monsoonprecipitation in a CGCM?The skill of global monsoon variability is linearly related with that of tropical SST variability with a regression coefficient of 0.51 (0.69 without one outlier at middle left. See Fig. 6). This suggests that the fidelity of the global monsoon rainfall indeed depends upon the reality of the tropical SST (i.e. El Niño).

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Fig. 6 Evaluation of the CGCMs’ performance on the spatial similarity between the observation and model simulations for SST MCA1 (abscissa) and PR EOF1 (ordinate).

For the MIROC simulations, the PCCs between the simulated and observed SST MCA1 are increased from MIROC3 (0.68 for MIROC3hi and 0.70 for MIROC3med, respectively) to MIROC5 (0.84). As a result, the PR EOF1 simulation of MIROC5 is improved to a PCC of 0.56 compared with that of the two MIROC3 versions, of which PCCs are below 0.25.

Possible mechanism for the improved simulation of El Niño in MIROC5: Enhanced convection amplifies the Bjerknes feedback

4. ENSO simulation in MIROC5

Fig. 7 (a) Lead-lag correlation coefficients of the monthly precipitation anomalies over the maximum upward branch of the climatological Walker circulation (115˚-120˚E, 5˚S-5˚N) with respect to the monthly Niño 3 index obtained from the observations (scale on the left) and MIROC simulations (scale on the right). Red line denotes the 95% confidence level with scale on the right. (b) Scatter plots of monthly SST (abscissa) and precipitation (ordinate) over the equatorial central Pacific (160˚E-200˚E, 5˚S-5˚N) obtained from the observation. Results imply that El Niño events are often triggered by the slowing down of the Walker circulation at rising branch and, once established, convective activity over the central Pacific is a key to amplify the Bjerknes feedback.

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Fig. 7 (c)-(e) Same as Fig. 7(b) except for (c) MIROC5, (d) MIROC3hi, and (e) MIROC3med, respectively.

Owing to the improved physical parameterizations, MIROC5 outperforms MIROC3 and is generally superior to the CMIP3 CGCMs in replicating the domain and intensity of global monsoon precipitation and circulations.

El Niño amplitude and periodicity are simulated better in MIROC5 than in MIROC3. Yet the reality of nonlinear El Niño dynamics measured by the SST skewness is unsatisfactory in the majority of the CMIP3 models.

MCA shows that on interannual timescale, a significant fraction of the global monsoon rainfall variability is in concert with El Niño.Such coupling is robust in the CMIP3 CGCMs. In addition, the fidelity of the global monsoon precipitation relies on the realism of El Niño.

Comparison among the MIROC models suggests that improved El Niño is likely attributable to the more realistic Bjerknes feedback loop, which results from the intensified convective activity over the equatorial central Pacific.

5. Conclusions

<References>1. Key Papers(1) Kim et al., 2011, Global monsoon, El Niño, and their interannual linkage simulated by MIROC5 and the CMIP3 CGCMs, J. Climate, revised.(2) Wang B., J. Liu, H.-J. Kim, P. J. Webster, and T. A. Schroeder, 2011, Recent intensification of global monsoon precipitation, Nature, revised.2. Global Monsoon Papers(1) Kim et al., 2008, J. Climate, 21, 5271-5294.(2) Wang, B., H.-J. Kim, K. Kikuchi, and A. Kitoh, 2010, Climate Dyn., DOI 10.1007/ s00382-010-0877-0, Online First.

OBS Model

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3. MIROC5 Description Papers(1) Watanabe et al., 2010, J. Climate, 23, 6312-6335.(2) Chikira, M, and M. Sugiyama, 2010, J. Atmos. Sci., 67, 2171–2193.(3) Chikira, M., 2010, J. Atmos. Sci., 67, 2194–2211.

<Acknowledgements>This work was performed under the auspices of the MEXT, Japan, under theEnvironment Research & Technology Development Fund (A0902). MW, MK and TYwere supported from the Kakushin Program from the MEXT, Japan. BW was supported by APCC. The MIROC simulations were carried out on the Earth Simulator.

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