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Representation of tropical subseasonal variability of precipitation in global reanalyses

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Abstract

Tropical subseasonal variability of precipitation from five global reanalyses (RAs) is evaluated against Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) observations. The RAs include the three generations of global RAs from the National Center for Environmental Prediction (NCEP), and two other RAs from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Aeronautics and Space Administration/Goddard Space Flight Center (NASA/GSFC). The analysis includes comparisons of the seasonal means and subseasonal variances of precipitation, and probability densities of rain intensity in selected areas. In addition, the space–time power spectrum was computed to examine the tropical Madden-Julian Oscillation (MJO) and convectively coupled equatorial waves (CCEWs). The modern RAs show significant improvement in their representation of the mean state and subseasonal variability of precipitation when compared to the two older NCEP RAs: patterns of the seasonal mean state and the amplitude of subseasonal variability are more realistic in the modern RAs. However, the probability density of rain intensity in the modern RAs show discrepancies from observations that are similar to what the old RAs have. The modern RAs show higher coherence of CCEWs with observed variability and more realistic eastward propagation of the MJO precipitation. The modern RAs, however, exhibit common systematic deficiencies including: (1) variability of the CCEWs that tends to be either too weak or too strong, (2) limited coherence with observations for waves other than the MJO, and (3) a systematic phase lead or lag for the higher-frequency waves.

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Notes

  1. Precipitation is assimilated only in ERA-I and MERRA.

  2. When MERRA assimilates precipitation observation over oceans, it is weighted only very weakly so that it effectively has almost no impact.

References

  • Bechtold P, Bazile E, Guichard F, Mascart P, Richard E (2001) A mass-flux convection scheme for regional and global models. Q J R Meteorol Soc 127:869–886. doi:10.1002/qj.49712757309

    Article  Google Scholar 

  • Behrangi A, Lebsock M, Wong S, Lambrigtsen B (2012) On the quantification of oceanic rainfall using spaceborne sensors. J Geophys Res 117:D20105

    Google Scholar 

  • Bergman JW, Hendon HH, Weickmann KM (2001) Intraseasonal air-sea interactions at the onset of El Nin˜o. J Clim 14:1702–1719

    Article  Google Scholar 

  • Bessafi M, Wheeler MC (2006) Modulation of South Indian Ocean tropical cyclones by the Madden–Julian oscillation and convectively coupled equatorial waves. Mon Weather Rev 134:638–656

    Article  Google Scholar 

  • Bloom SC, Takacs LL, da Silva AM, Ledvina D (1996) Data assimilation using incremental analysis updates. Mon Weather Rev 124:1256–1271

    Article  Google Scholar 

  • Compo GP et al (2011) The twentieth century reanalysis project. Q J R Meteorol Soc 137:1–28

    Article  Google Scholar 

  • Dee DP et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597

    Article  Google Scholar 

  • Derber JC, Parrish DF, Lord SJ (1991) The new global operational analysis system at the national meteorological center. Weather Forecast 6:538–547

    Article  Google Scholar 

  • Frank WM, Roundy PE (2006) The role of tropical waves in tropical cyclogenesis. Mon Weather Rev 134:2397–2417

    Article  Google Scholar 

  • Frierson DMW, Kim D, Kang I-S, Lee M-I, Lin JL (2011) Structure of AGCM-simulated convectively coupled kelvin waves and sensitivity to convective parameterization. J Atmos Sci 68:26–45

    Article  Google Scholar 

  • Hendon HH, Wheeler MC (2008) Some space–time spectral analyses of tropical convection and planetary-scale waves. J Atmos Sci 65:2936–2948

    Article  Google Scholar 

  • Hodges KI, Lee RW, Bengtsson L (2011) A comparison of extratropical cyclones in recent reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25. J Climate 24:4888–4906

    Article  Google Scholar 

  • Hong S-Y, Pan H-L (1998) Convective trigger function for a mass-flux cumulus parameterization scheme. Mon Weather Rev 126:2599–2620

    Article  Google Scholar 

  • Huffman GJ et al (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeor 8:38–55. doi:http://dx.doi.org/10.1175/JHM560.1

    Google Scholar 

  • Huffman GJ, Adler RF, Morrissey M, Bolvin DT, Curtis S, Joyce R, McGavock B, Susskind J (2001) Global precipitation at one-degree daily resolution from multisatellite observations. J Hydrometeor 2:36–50

    Article  Google Scholar 

  • Hung M-P, Lin J-L, Wang W, Kim D, Shinoda T, Weaver SJ (2013) MJO and convectively coupled equatorial waves simulated by CMIP5 climate models. J Climate (in press)

  • Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Amer Meteor Soc 77:437–471

    Article  Google Scholar 

  • Kanamitsu M, Ebisuzaki W, Woolen J, Yang S-K, Hnilo JJ, Fiorino M, Potter GL (2002) NCEP-DOE AMIP-II reanalysis (R-2). Bull Amer Meteor Soc 83:1631–1643

    Article  Google Scholar 

  • Kessler WS (2001) EOF representations of the Madden–Julian oscillation and its connection with ENSO. J Clim 14:3055–3061

    Google Scholar 

  • Kiladis GN, Wheeler MC, Haertel PT, Straub KH, Roundy PE (2009) Convectively coupled equatorial waves. Rev Geophys 47, RG2003, doi:10.1029/2008RG000266

  • Kim D et al (2009) Application of MJO simulation diagnostics to climate models. J Climate 22:6413–6436. doi:http://dx.doi.org/10.1175/2009JCLI3063.1

    Google Scholar 

  • Kim D, Sobel AH, Maloney ED, Frierson DMW, Kang I-S (2011) A systematic relationship between intraseasonal variability and mean state bias in AGCM simulations. J Climate 24:5506–5520. doi:http://dx.doi.org/10.1175/2011JCLI4177.1

    Google Scholar 

  • Kleist DT, Parrish DF, Derber JC, Treadon R, Wu W-S, Lord S (2009) Introduction of the GSI into the NCEP global data assimilation system. Weather Forecast 24:1691–1705

    Article  Google Scholar 

  • Liebmann B, Hendon HH, Glick JD (1994) The relationship between tropical cyclones of the western Pacific and Indian Oceans and the Madden–Julian oscillation. J Meteor Soc Jpn 72:401–412

    Google Scholar 

  • Lin J-L et al (2006) Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: convective signals. J Climate 19:2665–2690

    Article  Google Scholar 

  • Madden RA, Julian PR (1972) Description of global-scale circulation cells in the tropics with a 40–50 day period. J Atmos Sci 29:1109–1123

    Article  Google Scholar 

  • Majda A, Stechmann S (2011) Multi-scale theories for the MJO. In Lau WKM, Waliser DE (eds) Intraseasonal variability of the atmosphere-ocean climate system, 2nd edn. Springer, Heidelberg, p. 613

  • Maloney ED, Hartmann DL (2000a) Modulation of hurricane activity in the Gulf of Mexico by the Madden–Julian oscillation. Science 287:2002–2004

    Article  Google Scholar 

  • Maloney ED, Hartmann DL (2000b) Modulation of eastern North Pacific hurricanes by the Madden–Julian oscillation. J Climate 13:1451–1460

    Article  Google Scholar 

  • Matsuno T (1966) Quasi-geostrophic motions in the equatorial area. J Meteorol Soc Jpn 44:25–43

    Google Scholar 

  • Molinari J, Lombardo K, Vollaro D (2007) Tropical cyclogenesis within an equatorial Rossby wave packet. J Atmos Sci 64:1301–1317

    Article  Google Scholar 

  • Moorthi S, Suarez MJ (1992) Relaxed Arakawa-Schubert. A parameterization of moist convection for general circulation models. Mon Weather Rev 120:978–1002

    Article  Google Scholar 

  • Onogi K et al (2007) The JRA-25 reanalysis. J Meteor Soc Jpn 85:369–432. doi:10.2151/jmsj.85.369

    Article  Google Scholar 

  • Pan H-L, Wu W-S (1994) Implementing a mass-flux convective parameterization package for the NMC medium range forecast model. Preprints, 10th Conference on numerical weather prediction, Portland, OR. Amer Meteor Soc 96–98

  • Parrish DF, Derber JC (1992) The national meteorological center’s spectral statistical interpolation analysis system. Mon Weather Rev 120:1747–1763

    Article  Google Scholar 

  • Rancic M, Derber JC, Parrish D, Treadon R, Kleist DT (2008) The development of the first-order time extrapolation to the observation (FOTO) method and its application in the NCEP global data assimilation system. Proceedings of 12th conference IOAS-AOLS, New Orleans, LA. Amer Meteor Soc 6.1. http://ams.confex.com/ams/88Annual/techprogram/paper_131816.htm

  • Rienecker MM et al (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Climate 24:3624–3648. doi:10.1175/JCLI-D-11-00015.1

    Article  Google Scholar 

  • Saha S et al (2010) The NCEP climate forecast system reanalysis. Bull Amer Meteor Soc 91(8):1015–1057

    Article  Google Scholar 

  • Sobel AH et al (2008) The role of surface heat fluxes in tropical intraseasonal oscillations. Nat Geosci 1:653–657. doi:10.1038/ngeo312

    Article  Google Scholar 

  • Sperber KR (2003) Propagation and the vertical structure of the madden–julian oscillation. Mon Weather Rev 131:3018–3037

    Article  Google Scholar 

  • Sperber KR, Kim D (2012) Simplified metrics for the identification of the Madden-Julian Oscillation in models. Atmos Sci Lett 13:187–193. doi:10.1002/asl.378

    Google Scholar 

  • Sperber K, Slingo J, Inness P (2011) Modeling Intraseasonal Variability. In Lau WKM, Waliser DE (eds) Intraseasonal variability of the atmosphere-ocean climate system, 2nd edn. Springer, Heidelberg, p 613

  • Takayabu YN (1994) Large-scale cloud disturbances associated with equatorial waves. Part I: spectral features of the cloud disturbances. J Meteor Soc Japan 72:433–449

    Google Scholar 

  • Takayabu YN, Iguchi T, Kachi M, Shibata A, Kanzawa H (1999) Abrupt termination of the 1997–1998 El Nino in response to a Madden-Julian oscillation. Nature 402:279–282

    Article  Google Scholar 

  • Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106(D7):7183–7192

    Article  Google Scholar 

  • Tian BJ, Waliser DE, Fetzer E (2006) Modulation of the diurnal cycle of deep convective clouds by the madden-julian oscillation. Geophys Res Lett 30:L20704. doi:10.1029/2006GL027752

    Article  Google Scholar 

  • Uppala S et al (2005) The ERA-40 Re-analysis. Q J R Meteorol Soc 131:2961–3012

    Article  Google Scholar 

  • Wang B (2011) Theory. In: Lau WKM, Waliser DE (eds) Intraseasonal variability of the atmosphere-ocean climate system, 2nd edn. Springer, Heidelberg, p 613

  • Wheeler MC, Kiladis GN (1999) Convectively coupled equatorial waves: analysis of clouds and temperature in the wavenumber–frequency domain. J Atmos Sci 56:374–399

    Article  Google Scholar 

  • Wheeler MC, McBride JL (2011) Australasian monsoon. In: Lau WKM, Waliser DE (eds) Intraseasonal variability in the atmosphere-ocean climate system, 2nd edn. Springer, Heidelberg, p 613

  • Yang G-Y, Hoskins B, Slingo J (2007) Convectively coupled equatorial waves. Part I: horizontal and vertical structures. J Atmos Sci 64:3406–3423

    Article  Google Scholar 

  • Yasunari T (1979) Cloudiness fluctuations associated with the northern hemisphere summer monsoon. J Metor Soc Jpn 57–3:227–242

    Google Scholar 

  • Zhang C (2005) Madden-Julian oscillation. Rev Geophys 43:RG2003, doi:10.1029/2004RG000158

  • Zhang MH et al (2005) Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements. J Geophys Res 110:D15S02, doi:10.1029/2004JD005021

Download references

Acknowledgments

This work was supported by the Korea Meteorological Administration Research and Development Program under Grant APCC 2013-3141. Also, this work was supported by the NASA grant NNX09AK34G for DK, and the NASA Modeling, Analysis, and Prediction (MAP) program for SDS. DEW’s and BT’s contribution to this research was performed at Jet Propulsion Laboratory (JPL), California Institute of Technology (Caltech), under a contract with National Aeronautics and Space Administration (NASA). The authors are grateful for the computing resources provided by NASA and the Supercomputing Center at Korea Institute of Science and Technology Information (KSC-2013-C2-011).

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Authors and Affiliations

  1. Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA

    Daehyun Kim

  2. School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan, 689-798, Republic of Korea

    Myong-In Lee & Dongmin Kim

  3. NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Siegfried D. Schubert

  4. NASA Jet Propulsion Laboratory, Pasadena, CA, USA

    Duane E. Waliser & Baijun Tian

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  1. Daehyun Kim
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Correspondence to Myong-In Lee.

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Kim, D., Lee, MI., Kim, D. et al. Representation of tropical subseasonal variability of precipitation in global reanalyses. Clim Dyn 43, 517–534 (2014). https://doi.org/10.1007/s00382-013-1890-x

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