Can Regional Climate Models Represent the Indian Monsoon?

Philippe Lucas-Picher Centre National de Recherches Météorologiques (CNRM-GAME), Météo-France, Toulouse, France, and Danish Meteorological Institute, Copenhagen, Denmark

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Jens H. Christensen Danish Meteorological Institute, Copenhagen, Denmark

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Fahad Saeed Max Planck Institute for Meteorology, Hamburg, Germany

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Pankaj Kumar Max Planck Institute for Meteorology, Hamburg, Germany

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Shakeel Asharaf Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany

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Bodo Ahrens Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany

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Andrew J. Wiltshire Met Office Hadley Centre for Climate Prediction and Research, Exeter, United Kingdom

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Daniela Jacob Max Planck Institute for Meteorology, Hamburg, Germany

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Stefan Hagemann Max Planck Institute for Meteorology, Hamburg, Germany

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Abstract

The ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981–2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land–sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from observationally based gridded datasets, while the monsoon withdrawal is less well simulated. A Hovmöller diagram representation of the mean annual cycle of precipitation reveals that the meridional motion of the precipitation simulated by the RCMs is comparable to the one observed, but the precipitation amounts and the regional distribution differ substantially between the four RCMs. In summary, the spread at the regional scale between the RCMs indicates that important feedbacks and processes are poorly, or not, taken into account in the state-of-the-art regional climate models.

Corresponding author address: Philippe Lucas-Picher, Centre National de Recherches Météorologiques (CNRM-GAME), Météo-France, 42 av. Gaspard Coriolis, 31057 Toulouse CEDEX, France. E-mail: philippe.lucas-picher@meteo.fr

This article is included in the Water and Global Change (WATCH) special collection.

Abstract

The ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981–2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land–sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from observationally based gridded datasets, while the monsoon withdrawal is less well simulated. A Hovmöller diagram representation of the mean annual cycle of precipitation reveals that the meridional motion of the precipitation simulated by the RCMs is comparable to the one observed, but the precipitation amounts and the regional distribution differ substantially between the four RCMs. In summary, the spread at the regional scale between the RCMs indicates that important feedbacks and processes are poorly, or not, taken into account in the state-of-the-art regional climate models.

Corresponding author address: Philippe Lucas-Picher, Centre National de Recherches Météorologiques (CNRM-GAME), Météo-France, 42 av. Gaspard Coriolis, 31057 Toulouse CEDEX, France. E-mail: philippe.lucas-picher@meteo.fr

This article is included in the Water and Global Change (WATCH) special collection.

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  • Bhaskaran, B., Jones R. G. , Murphy J. M. , and Noguer M. , 1996: Simulations of the Indian summer monsoon using a nested regional climate model: Domain size experiments. Climate Dyn., 12, 573587.

    • Search Google Scholar
    • Export Citation
  • Bhaskaran, B., Murphy J. M. , and Jones R. G. , 1998: Intraseasonal oscillation in the Indian summer monsoon simulated by global and nested regional climate models. Mon. Wea. Rev., 126, 31243134.

    • Search Google Scholar
    • Export Citation
  • Buonomo, E., Jones R. , Huntingford C. , and Hannaford J. , 2007: On the robustness of changes in extreme precipitation over Europe from two high resolution climate change simulations. Quart. J. Roy. Meteor. Soc., 133, 6581.

    • Search Google Scholar
    • Export Citation
  • Chang, H.-I., Niyogi D. , Kumar A. , Kishtawal C. M. , Dudhia J. , Chen F. , Mohanty U. C. , and Shepherd M. , 2009: Possible relation between land surface feedback and the post-landfall structure of monsoon depressions. Geophys. Res. Lett., 36, L15826, doi:10.1029/2009GL037781.

    • Search Google Scholar
    • Export Citation
  • Christensen, J. H., and Coauthors, 2007: Regional climate projections. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 847–940.

    • Search Google Scholar
    • Export Citation
  • Christensen, O. B., Drews M. , Christensen J. H. , Dethloff K. , Ketelsen K. , Hebestadt I. , and Rinke A. , 2006: The HIRHAM regional climate model, version 5. DMI Tech. Rep. 06-17, 22 pp. [Available online at http://www.dmi.dk/dmi/tr06-17.pdf.]

    • Search Google Scholar
    • Export Citation
  • Cox, P. M., Betts R. A. , Bunton C. B. , Essery R. L. H. , Rowntree P. R. , and Smith J. , 1999: The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Climate Dyn., 15, 183203.

    • Search Google Scholar
    • Export Citation
  • Dash, S. K., Shekhar M. S. , and Singh G. P. , 2006: Simulation of Indian summer monsoon circulation and rainfall using RegCM3. Theor. Appl. Climatol., 86, 161172.

    • Search Google Scholar
    • Export Citation
  • Davies, H. C., 1976: A lateral boundary formulation for multi-level prediction models. Quart. J. Roy. Meteor. Soc., 102, 405418.

  • Dobler, A., and Ahrens B. , 2008: Precipitation by a regional climate model and bias correction in Europe and South Asia. Meteor. Z., 17, 499509, doi:10.1127/0941-2948/2008/0306.

    • Search Google Scholar
    • Export Citation
  • Dobler, A., and Ahrens B. , 2010: Analysis of the Indian summer monsoon system in the regional climate model COSMO-CLM. J. Geophys. Res., 115, D16101, doi:10.1029/2009JD013497.

    • Search Google Scholar
    • Export Citation
  • Douglas, E. M., Beltràn-Przekurat A. , Niyogi D. S. , Pielke R. A. Sr., and Vörösmarty C. J. , 2009: The impact of agricultural intensification and irrigation on land–atmosphere interactions and Indian monsoon precipitation—A mesoscale modeling perspective. Global Planet. Change, 67, 117128.

    • Search Google Scholar
    • Export Citation
  • Dümenil, L., and Todini E. , 1992: A rainfall–runoff scheme for use in the Hamburg climate model. Advances in Theoretical Hydrology, J. P. O’Kane, Ed., EGS Series of Hydrological Sciences, Vol. 1, Elsevier, 129–157.

    • Search Google Scholar
    • Export Citation
  • Feng, J., and Fu C. , 2006: Inter-comparison of 10-year precipitation simulated by several RCMs for Asia. Adv. Atmos. Sci., 23, 531542.

    • Search Google Scholar
    • Export Citation
  • Fu, C., and Coauthors, 2005: Regional Climate Model Intercomparison Project for Asia. Bull. Amer. Meteor. Soc., 86, 257266.

  • Giorgi, F., 2006: Regional climate modeling: Status and perspectives. J. Phys. IV Fr., 139, 101118, doi:10.1051/jp4:2006139008.

  • Giorgi, F., Jones C. , and Asrar G. , 2009: Addressing climate information needs at the regional level: The CORDEX framework. WMO Bull., 58, 175183.

    • Search Google Scholar
    • Export Citation
  • Goswami, B. N., 2005: South Asian summer monsoon: An overview. The global monsoon system: Research and forecast, World Meteorological Organization Tech. Doc. WMO/TD 1266, 47–71.

    • Search Google Scholar
    • Export Citation
  • Graham, S. T., Famiglietti J. S. , and Maidment D. R. , 1999: Five-minute, 1/2°, and 1° data sets of continental watersheds and river networks for use in regional and global hydrologic and climate system modeling studies. Water Resour. Res., 35, 583587.

    • Search Google Scholar
    • Export Citation
  • Gregory, D., and Rowntree P. R. , 1990: A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev., 118, 14831506.

    • Search Google Scholar
    • Export Citation
  • Hagemann, S., and Gates L. D. , 2003: Improving a subgrid runoff parameterization scheme for climate models by the use of high resolution data derived from satellite observations. Climate Dyn., 21, 349359.

    • Search Google Scholar
    • Export Citation
  • Jacob, D., and Podzun R. , 1997: Sensitivity studies with the regional climate model REMO. Meteor. Atmos. Phys., 63, 119129.

  • Jacob, D., and Coauthors, 2007: An inter-comparison of regional climate models for Europe: Model performance in present-day climate. Climatic Change, 81, 3152.

    • Search Google Scholar
    • Export Citation
  • Ji, Y., and Vernekar A. D. , 1997: Simulation of the Asian monsoons of 1987 and 1988 with a regional model nested in a global GCM. J. Climate, 10, 19651979.

    • Search Google Scholar
    • Export Citation
  • Jones, R. G., Murphy J. M. , and Noguer M. , 1995: Simulation of climate change over Europe using a nested regional-climate model. I: Assessment of control climate, including sensitivity to location of lateral boundaries. Quart. J. Roy. Meteor. Soc., 121, 14131449.

    • Search Google Scholar
    • Export Citation
  • Kessler, E., 1969: On the Distribution and Continuity of Water Substance in the Atmospheric Circulations. Meteor. Monogr., No. 32, Amer. Meteor. Soc., 84 pp.

    • Search Google Scholar
    • Export Citation
  • Kishtawal, C. M., Niyogi D. , Tewari M. , Pielke R. A. , and Shepherd J. M. , 2010: Urbanization signature in the observed heavy rainfall climatology over India. Int. J. Climatol., 30, 19081916, doi:10.1002/joc.2044.

    • Search Google Scholar
    • Export Citation
  • Kitoh, A., and Uchiyama T. , 2006: Changes in onset and withdrawal of the East Asian summer rainy season by multi-model global warming experiments. J. Meteor. Soc. Japan, 84, 247258.

    • Search Google Scholar
    • Export Citation
  • Kripalani, R. H., Oh J. H. , Kulkarni A. , Sabade S. S. , and Chaudhari H. S. , 2007: South Asian summer monsoon precipitation variability: Coupled climate model simulations and projections under IPCC AR4. Theor. Appl. Climatol., 90, 133159, doi:10.1007/s00704-006-0282-0.

    • Search Google Scholar
    • Export Citation
  • Krishnamurti, T. N., and Ramanathan Y. , 1982: Sensitivity of the monsoon onset to differential heating. J. Atmos. Sci., 39, 12901306.

    • Search Google Scholar
    • Export Citation
  • Lucas-Picher, P., Caya D. , Biner S. , and Laprise R. , 2008: Quantification of the lateral boundary forcing of a regional climate model using an aging tracer. Mon. Wea. Rev., 136, 49804996.

    • Search Google Scholar
    • Export Citation
  • Matsuura, K., and Willmott C. J. , cited 2009: Terrestrial air temperature and precipitation: Monthly and annual time series (1900–2008) version 2.01. [Available online at http://climate.geog.udel.edu/~climate/html_pages/Global2_Ts_2009/README.global_p_ts_2009.html.]

    • Search Google Scholar
    • Export Citation
  • May, W., 2002: Simulated changes of the Indian summer monsoon under enhanced greenhouse gas conditions in a global time-slice experiment. Geophys. Res. Lett., 29, 1118, doi:10.1029/2001GL013808.

    • Search Google Scholar
    • Export Citation
  • May, W., 2003: The Indian summer monsoon and its sensitivity to the mean SSTs: Simulations with the ECHAM4 AGCM at T106 horizontal resolution. J. Meteor. Soc. Japan, 81, 5783, doi:10.2151/jmsj.81.57.

    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., Arblaster J. M. , and Collins W. D. , 2008: Effects of black carbon aerosols on the Indian monsoon. J. Climate, 21, 28692882.

    • Search Google Scholar
    • Export Citation
  • Mitchell, T. D., and Jones P. D. , 2005: An improved method of constructing a database of monthly climate observations and associated high resolution grids. Int. J. Climatol., 25, 693712.

    • Search Google Scholar
    • Export Citation
  • Niyogi, D., Kishtawal C. , Tripathi S. , and Govindaraju R. S. , 2010: Observational evidence that agricultural intensification and land use change may be reducing the Indian summer monsoon rainfall. Water Resour. Res., 46, W03533, doi:10.1029/2008WR007082.

    • Search Google Scholar
    • Export Citation
  • Nordeng, T. E., 1994: Extended versions of the convective parameterization scheme at ECMWF and their impact on the mean and transient activity of the model in the tropics. ECMWF Tech. Memo. 206, 41 pp.

    • Search Google Scholar
    • Export Citation
  • Oki, T., and Sud Y. C. , 1998: Design of Total Runoff Integrating Pathways (TRIP)—A global river channel network. Earth Interact., 2, 137.

    • Search Google Scholar
    • Export Citation
  • Park, S., and Hong S.-Y. , 2004: The role of surface boundary forcing over South Asia in the Indian summer monsoon circulation: A regional climate model sensitivity study. Geophys. Res. Lett., 31, L12112, doi:10.1029/2004GL019729.

    • Search Google Scholar
    • Export Citation
  • Piani, C., Haerter J. O. , and Coppola E. , 2010: Statistical bias correction for daily precipitation in regional climate models over Europe. Theor. Appl. Climatol., 99, 187192, doi:10.1007/s00704-009-0134-9.

    • Search Google Scholar
    • Export Citation
  • Rajendran, K., and Kitoh A. , 2008: Indian summer monsoon in future climate projection by a super high-resolution global model. Curr. Sci., 95, 15601569.

    • Search Google Scholar
    • Export Citation
  • Rockel, B., and Geyer B. , 2008: The performance of the regional climate model CLM in different climate regions, based on the example of precipitation. Meteor. Z., 17, 487498.

    • Search Google Scholar
    • Export Citation
  • Rupa Kumar, K., Sahai A. K. , Krishna Kumar K. , Patwardhan S. K. , Mishra P. K. , Revadekar J. V. , Kamala K. , and Pant G. B. , 2006: High-resolution climate change scenarios for India. Curr. Sci., 90, 334345.

    • Search Google Scholar
    • Export Citation
  • Saeed, F., Hagemann S. , and Jacob D. , 2009: Impact of irrigation on the South Asian summer monsoon. Geophys. Res. Lett., 36, L20711, doi:10.1029/2009GL040625.

    • Search Google Scholar
    • Export Citation
  • Saeed, F., Hagemann S. , and Jacob D. , 2011: A framework for the evaluation of the South Asian summer monsoon in a regional climate model applied to REMO. Int. J. Climatol., doi:10.1002/joc.2285, in press.

    • Search Google Scholar
    • Export Citation
  • Schneider, U., Fuchs T. , Meyer-Christoffer A. , and Rudolf B. , 2008: Global precipitation analysis products of the GPCC, Full Data Reanalysis Product version 4. Global Precipitation Climatology Centre Rep., 12 pp.

    • Search Google Scholar
    • Export Citation
  • Schrodin, E., and Heise E. , 2002: A new multi-layer soil model. COSMO Newsletter, No. 2, Consortium for Small-Scale Modelling, Offenbach, Germany, 149–151.

    • Search Google Scholar
    • Export Citation
  • Singh, N., and Ranade A. , 2010: The wet and dry spells across India during 1951–2007. J. Hydrometeor., 11, 2645.

  • Smith, R. N. B., 1990: A scheme for predicting layer clouds and their water content in a general circulation model. Quart. J. Roy. Meteor. Soc., 116, 435460.

    • Search Google Scholar
    • Export Citation
  • Sundquist, H., 1978: A parameterization scheme for non-convective condensation including prediction of cloud water content. Quart. J. Roy. Meteor. Soc., 104, 677690.

    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791800.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 29613012.

  • Venkata Ratnam, J., and Krishna Kumar K. , 2005: Sensitivity of the simulated monsoons of 1987 and 1988 to convective parameterization schemes in MM5. J. Climate, 18, 27242743.

    • Search Google Scholar
    • Export Citation
  • Venkata Ratnam, J., and Cox E. A. , 2006: Simulation of monsoon depressions using MM5: Sensitivity to cumulus parameterization schemes. Meteor. Atmos. Phys., 93, 5378, doi:10.1007/s00703-005-0160-9.

    • Search Google Scholar
    • Export Citation
  • Venkata Ratnam, J., Giorgi F. , Kaginalkar A. , and Cozzini S. , 2009: Simulation of the Indian monsoon using the RegCM3–ROMS regional coupled model. Climate Dyn., 33, 119139.

    • Search Google Scholar
    • Export Citation
  • Vernekar, A. D., and Ji Y. , 1999: Simulation of the onset and intraseasonal variability of two contrasting summer monsoons. J. Climate, 12, 17071725.

    • Search Google Scholar
    • Export Citation
  • Wang, B., and Yang H. , 2008: Hydrological issues in lateral boundary conditions for regional climate modeling: Simulation of East Asian summer monsoon in 1998. Climate Dyn., 31, 477490, doi:10.1007/s00382-008-0385-7.

    • Search Google Scholar
    • Export Citation
  • Wang, C., Kim D. , Ekman A. M. L. , Barth M. C. , and Rasch P. J. , 2009: Impact of anthropogenic aerosols on Indian summer monsoon. Geophys. Res. Lett., 36, L21704, doi:10.1029/2009GL040114.

    • Search Google Scholar
    • Export Citation
  • Xie, P., and Arkin P. A. , 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 25392558.

    • Search Google Scholar
    • Export Citation
  • Xie, P., Janowiak J. E. , Arkin P. A. , Adler R. F. , Gruber A. , Ferraro R. R. , Huffman G. J. , and Curtis S. , 2003: GPCP pentad precipitation analyses: An experimental dataset based on gauge observations and satellite estimates. J. Climate, 16, 21972214.

    • Search Google Scholar
    • Export Citation
  • Yatagai, A., Arakawa O. , Kamiguchi K. , Kawamoto H. , Nodzu M. I. , and Hamada A. , 2009: A 44-year daily gridded precipitation dataset for Asia based on a dense network of rain gauges. SOLA, 5, 137140, doi:10.2151/sola.2009-035.

    • Search Google Scholar
    • Export Citation
  • Yin, X., Gruber A. , and Arkin P. , 2004: Comparison of the GPCP and CMAP merged gauge–satellite monthly precipitation products for the period 1979–2001. J. Hydrometeor., 5, 12071222.

    • Search Google Scholar
    • Export Citation
  • Zeng, X., and Lu E. , 2004: Globally unified monsoon onset and retreat indexes. J. Climate, 17, 22412248.

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