Advertisement

Climate Dynamics

, Volume 39, Issue 5, pp 1149–1168 | Cite as

A comparative study of the Indian summer monsoon hydroclimate and its variations in three reanalyses

  • Vasubandhu Misra
  • P. Pantina
  • S. C. Chan
  • S. DiNapoli
Article

Abstract

This study examines the Indian summer monsoon hydroclimate in the National Centers for Environmental Prediction (NCEP)-Department of Energy (DOE) Reanalysis (R2), the Climate Forecast System Reanalysis (CFSR), and the Modern Era Retrospective-Analysis for Research and Applications (MERRA). The three reanalyses show significant differences in the climatology of evaporation, low-level winds, and precipitable water fields over India. For example, the continental evaporation is significantly less in CFSR compared to R2 and MERRA. Likewise the mean boreal summer 925 hPa westerly winds in the northern Indian Ocean are stronger in R2. Similarly the continental precipitable water in R2 is much less while it is higher and comparable in MERRA and CFSR. Despite these climatological differences between the reanalyses, the climatological evaporative sources for rain events over central India show some qualitative similarities. Major differences however appear when interannual variations of the Indian summer monsoon are analyzed. The anomalous oceanic sources of moisture from the adjacent Bay of Bengal and Arabian Sea play a significant role in determining the wet or dry year of the Indian monsoon in CFSR. However in R2 the local evaporative sources from the continental region play a more significant role. We also find that the interannual variability of the evaporative sources in the break spells of the intraseasonal variations of the Indian monsoon is stronger than in the wet spells. We therefore claim that instead of rainfall, evaporative sources may be a more appropriate metric to observe the relationship between the seasonal monsoon strength and intraseasonal activity. These findings are consistent across the reanalyses and provide a basis to improve the predictability of intraseasonal variability of the Indian monsoon. This study also has a bearing on improving weather prediction for tropical cyclones in that we suggest targeting enhanced observations in the Bay of Bengal (where it is drawing the most moisture from) for improved analysis during active spells of the intraseasonal variability of the Indian monsoon. The analysis suggests that the land–atmosphere interactions contribute significant uncertainty to the Indian monsoon in the reanalyses, which is consistent with the fact that most of the global reanalyses do not assimilate any land-surface data because the data are not available. Therefore, the land–atmosphere interaction in the reanalyses is highly dependent on the land-surface model and it’s coupling with the atmospheric model.

Keywords

Monsoon Intraseasonal Interannual 

Notes

Acknowledgments

The authors would like to acknowledge the expert guidance of Kathy Fearon of COAPS for her editorial corrections on an earlier version of the manuscript. We acknowledge the resources of the Computational and Information Systems Laboratory of NCAR to obtain some of the observational datasets used for verification in this study. We also thank Dr. Paul Dirmeyer of Center for Ocean, Land and Atmosphere Studies (COLA) for sharing the Fortran code of the back trajectory program. The useful review comments and suggestions of three anonymous reviewers on an earlier version of the manuscript is also acknowledged. This work is supported by NOAA grant NA070AR4310221 and the USDA.

References

  1. Wang B et al. (2005) Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys Res Lett L15711. doi: 10.1029/2005GL022734
  2. Ek MB et al (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geo Res Letters 108:12-1–12-16Google Scholar
  3. Mitchell KE et al (2004) The multi-institution North American Land Data Assimilation System (NLDAS): utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J Geophys Res 109:D07S90. doi: 10.1029/2003JD003823
  4. Bamzai AS, Shukla J (1999) Relation between Eurasian snow cover, snow depth, and the Indian summer monsoon: an observational study. J Climate 12:3117–3132CrossRefGoogle Scholar
  5. Benton GS et al (1950) The role of the atmosphere in the hydrologic cycle. Trans Am Geophsy Union 31:61–73Google Scholar
  6. Betts AK, Chen F, Mitchell KE, Janjic Z (1997) Assessment of the land surface and boundary layer models in the two operational versions of the NCEP Eta model using FIFE data. Mon Weather Rev 125:2896–2916CrossRefGoogle Scholar
  7. Bloom S, Takacs L, DaSilva A, Ledvina D (1996) Data assimilation using incremental analysis updates. Mon Wea Rev 124:1256–1271CrossRefGoogle Scholar
  8. Bosilovich MG et al (2008) Evaluation of precipitation in reanalyses. J Appl Meteorol Climatol 47:2279–2299CrossRefGoogle Scholar
  9. Brubaker KL et al (1993) Estimation of continental precipitation recycling. J Climate 6:1077–1089CrossRefGoogle Scholar
  10. Budyko MI (1974) Climate and life. Academic Press, LondonGoogle Scholar
  11. Cadet D, Reverdin G (1981) Water vapour transport over the Indian ocean during summer 1975. Tellus 33:476–487CrossRefGoogle Scholar
  12. Chan SC, Misra V (2009) A diagnosis of the 1979–2005 extreme rainfall events in the Southeast US with isentropic moisture tracing. Mon Wea Rev 138:1172–1185CrossRefGoogle Scholar
  13. Delworth TL, Manabe S (1988) The influence of potential evaporation on the variabilities of simulated soil wetness and climate. J Climate 1:523–547CrossRefGoogle Scholar
  14. Delworth TL, Manabe S (1989) The influence of soil wetness on near-surface atmospheric variability. J Climate 2:1447–1462CrossRefGoogle Scholar
  15. Derber JD, Parrish DF, Lord SJ (1991) The new global operational analysis system at the National Meteorological Center. Weather Forecast 6:538–547CrossRefGoogle Scholar
  16. Dirmeyer PA, Brubaker KL (1999) Contrasting evaporative moisture sources during the drought of 1988 and the flood of 1993. J Geophysical Res 104:19383–19397CrossRefGoogle Scholar
  17. Dirmeyer PA, Schlosser CA, Brubaker KL (2009) Precipitation, recycling and land memory: an integrated analysis. J Hydrometeorol 10:278–288. doi: 10.1175/2008JHM1016.1 CrossRefGoogle Scholar
  18. Dirmeyer PA, Schlosser CA, Brubaker KL (2011) The terrestrial segment of soil moisture-climate coupling. Geophys Res Lett L16702, doi: 10.1029/2011GL048268
  19. Ek MB, Mahrt L (1991) OSU 1-D PBL model user’s guide. Dep. of Atmos. Sci., Oreg. State University, Corvallis, OregonGoogle Scholar
  20. Gadgil S (2003) The Indian monsoon and its variability. Annu Rev Earth Planet Sci 31:429–467CrossRefGoogle Scholar
  21. Goswami BN, Ajayamohan RS (2001) Intraseasonal oscillations and interannual variability of the Indian monsoon. J Climate 14:1180–1198CrossRefGoogle Scholar
  22. Guo Z et al (2006) GLACE: the global land atmosphere coupling experiment. Part II Anal J Hydrometeor 7:611–625CrossRefGoogle Scholar
  23. Jones C et al (2004) Climatology of tropical intraseasonal convection anomalies: 1979–2002. J Climate 17:523–539CrossRefGoogle Scholar
  24. Joyce RJ et al (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeor 5:487–503CrossRefGoogle Scholar
  25. Kanamitsu M et al (2002) NCEP-DOE AMIP-II reanalysis (R-2). Bull Amer Meteor Soc 83:1631–1643CrossRefGoogle Scholar
  26. Kang I-S, Shukla J (2005) Dynamical seasonal prediction and predictability of monsoon. In: Wang B (ed) The Asian monsoon. Praxis Publishers Ltd, Chichester, pp 585–612Google Scholar
  27. Kerr JM (1996) Sustainable development of rainfed agriculture in India. EPTD discussion paper no. 20Google Scholar
  28. Kirtman BP, Shukla J (2000) Influence of the Indian summer monsoon on ENSO. Q J R Meteorl Soc 126:213–239CrossRefGoogle Scholar
  29. Kleist DT, Parrish DF, Derber JC, Treadon R, Errico RM, Yang R (2009) Improving incremental balance in the GSI 3DVAR analysis system. Mon Wea Rev 137:1046–1060CrossRefGoogle Scholar
  30. Koren V, Schaake JC, Mitchell KE, Duan QY, Chen F, Baker J (1999) A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J Geophys Res 104:19569–19585CrossRefGoogle Scholar
  31. Koster RD et al (2000) A catchment-based approach to modeling land surface processes in a general circulation model, 1: model structure. J Geophys Res 105:24809–24822CrossRefGoogle Scholar
  32. Koster RD et al (2004) Regions of strong coupling between soil moisture and precipitation. Science 305:1138–1140CrossRefGoogle Scholar
  33. Koster RD et al (2006) GLACE: the global land–atmosphere coupling experiment. Part I Overv J Hydrometeor 7:590–610CrossRefGoogle Scholar
  34. Koster RD, Guo Z, Dirmeyer PA, Yang R, Mitchell K, Puma MJ (2009) On the nature of soil moisture in land surface models. J Climate 22:4322–4335CrossRefGoogle Scholar
  35. Krishnamurthy V, Ajayamohan RS (2010) Composite structure of monsoon low pressure systems and its relation to Indian rainfall. J Clim 23:4285–4305CrossRefGoogle Scholar
  36. Krishnamurthy V, Kinter III JL (2003) The Indian monsoon and its relation to global climate variability. In: Rodó X, Comín F (eds) Global Climate: current research and uncertainties in the climate system. Springer, Berlin, pp 186–236Google Scholar
  37. Krishnamurthy V, Kirtman BP (2003) Variability of the Indian ocean: relation to monsoon and ENSO. Quart J Roy Meteor Soc 129:1623–1646CrossRefGoogle Scholar
  38. Krishnamurthy V, Kirtman BP (2009) Relation between Indian monsoon variability and SST. J Climate 22:4437–4458CrossRefGoogle Scholar
  39. Krishnamurthy V, Shukla J (2000) Intraseasonal and interannual variability of rainfall over India. J Climate 13:4366–4377CrossRefGoogle Scholar
  40. Krishnamurthy V, Shukla J (2006) Intraseasonal and seasonally persisting patterns of Indian monsoon rainfall. J Climate 20:3–20CrossRefGoogle Scholar
  41. Krishnamurti TN, Subrahmanyam D (1995) The 30–50 day mode at 850 mb during MONEX. J Atmos Sci 39:2088–2095CrossRefGoogle Scholar
  42. Kumar K et al (1999) On the weakening relationship between the Indian monsoon and ENSO. Science 284:2156–2159CrossRefGoogle Scholar
  43. Kumar SV et al (2008) A land surface data assimilation framework using the land information system: Description and application. Adv Water Resour 31:1419–1432CrossRefGoogle Scholar
  44. Lawrence DM, Webster PJ (2001) Interannual variations of the intraseasonal oscillation in the South Asian summer monsoon region. J Climate 14:2910–2922CrossRefGoogle Scholar
  45. Lim YK et al (2002) Temporal and spatial evolution of the Asian summer monsoon in the seasonal cycle of synoptic fields. J Climate 15:3630–3644CrossRefGoogle Scholar
  46. Meehl GA (1994) Coupled land–ocean–atmosphere processes and south Asian monsoon variability. Science 266:263–267CrossRefGoogle Scholar
  47. Meehl GA (1997) The South Asian monsoon and the tropospheric biennial oscillation. J Climate 10:1921–1943CrossRefGoogle Scholar
  48. Merrill JT (1989) Atmospheric long-range transport to the Pacific Ocean. Chemical Oceanogr 10:15–50Google Scholar
  49. Misra V (2008) Coupled interactions of the monsoons. Geophys Res Letters 35:L12705CrossRefGoogle Scholar
  50. Mooley DA, Parthasarathy B (1984) Fluctuations in All-India summer monsoon rainfall during 1871–1978. Clim Change 6:287–301CrossRefGoogle Scholar
  51. Nigam S, Ruiz-Barradas A (2006) Seasonal hydroclimate variability over North America in global and regional reanalyses and AMIP simulations: varied representation. J Climate 15:815–837CrossRefGoogle Scholar
  52. Pan HL, Mahrt L (1987) Interaction between soil hydrology and boundary-layer development. Bound-Layer Meteorol 38:185–202CrossRefGoogle Scholar
  53. Parrish DF, Derber JC (1992) The National Meteorological Center’s spectral statistical interpolation system. Mon Wea Rev 120:1747–1763CrossRefGoogle Scholar
  54. Rajeevan M et al (2006) High resolution daily gridded rainfall data for the Indian region: analysis of break and active monsoon spells. Curr Sci 91:296–306Google Scholar
  55. Reale O, Lau WK, Susskind J, Brin E, Liu E, Risshojgaard LP, Fuentes M, Rosenberg R (2009) AIRS impact on the analysis and forecast track of tropical cyclone Nargis in a global data assimilation and forecasting system. Geophys Res Lett 36:L06812. doi: 10.1029/2008GL037122 CrossRefGoogle Scholar
  56. Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis. J Climate 15:1609–1625CrossRefGoogle Scholar
  57. Rienecker MM et al (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Climate 24:3624–3648CrossRefGoogle Scholar
  58. Roads J, Kanamitsu M, Stewart R (2002) CSE water and energy budgets in the NCEP-DOE reanalysis-II. J Hydrometeor 3:227–248CrossRefGoogle Scholar
  59. Robock A et al (2003) Evaluation of the North American land data assimilation system over the southern great plains during the warm season. J Geophys Res 108:8846. doi: 10.1029/2002JD003245 CrossRefGoogle Scholar
  60. Ruiz-Barradas A, Nigam S (2004) Warm season rainfall variability over the US great plains in observations, NCEP and ERA-40 reanalyses, and NCAR and NASA atmospheric model simulations. J Climate 18:1808–1830CrossRefGoogle Scholar
  61. Saha S et al (2006) The climate forecast system at NCEP. J Clim 19:3483–3517. doi: 10.1175/JCLI3812.1 CrossRefGoogle Scholar
  62. Saha S et al (2010) The NCEP climate forecast reanalysis. Bull Amer Meteor Soc 91:1015–1057CrossRefGoogle Scholar
  63. Saji NH et al (1999) A dipole mode in the tropical Indian Ocean. Nature 401:360–363Google Scholar
  64. Shepard D (1968) A two-dimensional interpolation function for irregularly spaced data. Proceedings of the 1968 23rd ACM National Conference 517–524Google Scholar
  65. Singh SV et al (1992) Interannual variability of the Madden-Julian Oscillations in Indian summer monsoon rainfall. J Climate 5:973–978CrossRefGoogle Scholar
  66. Trenberth KE, Guillemot CJ (1998) Evaluation of the atmospheric moisture and hydrological cycle in the NCEP/NCAR reanalyses. Climate Dyn 14:213–231CrossRefGoogle Scholar
  67. Trenberth KE, Dai A, Rasmussen RM, Parsons DB (1999) Atmospheric moisture recycling: role of advection and local evaporation. J Climate 12:1368–1381CrossRefGoogle Scholar
  68. Trenberth KE, Dai A, Rasmussen RM, Parsons DB (2003) The changing character of precipitation. Bull Amer Soc 84:1205–1217CrossRefGoogle Scholar
  69. Wang B, Lee J-Y et al. (2009) Advance and prospect of seasonal prediction: Assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004). Clim Dyn 33. doi: 10.1007/s00382-008-0460-0
  70. Wang B et al (2001) Interannual variability of the Asian summer monsoon: contrasts between the Indian and the western North Pacific-East Asian monsoons. J Climate 14:4073–4090CrossRefGoogle Scholar
  71. Zhang L, Dirmeyer PA, Wei J, Guo Z, Lu C-H (2011) Land-atmosphere coupling strength in the global forecast system. J Hydromet 12:147–156CrossRefGoogle Scholar
  72. Zhou Y, Lau WK, Reale O, Rosenberg R (2010) AIRS impact on precipitation analysis and forecast of tropical cyclones in a global data assimilation and forecasting system. Geophys Res Lett 37:L02806. doi: 10.102/2009GL041494 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Vasubandhu Misra
    • 1
    • 2
  • P. Pantina
    • 3
    • 4
  • S. C. Chan
    • 5
    • 6
  • S. DiNapoli
    • 2
  1. 1.Department of Earth, Ocean and Atmospheric ScienceFlorida State UniversityTallahasseeUSA
  2. 2.Center for Ocean-Atmospheric Prediction StudiesFlorida State UniversityTallahasseeUSA
  3. 3.Science Systems and Application, Inc.LanhamUSA
  4. 4.Cloud and Radiation LaboratoryNASA/GSFCGreenbeltUSA
  5. 5.School of Civil Engineering and GeosciencesNewcastle UniversityNewcastle upon TyneUK
  6. 6.Met Office Hadley CenterExeterUK

Personalised recommendations