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Climate Dynamics

, Volume 50, Issue 9–10, pp 3413–3439 | Cite as

Towards a realistic simulation of boreal summer tropical rainfall climatology in state-of-the-art coupled models: role of the background snow-free land albedo

  • P. Terray
  • K. P. Sooraj
  • S. Masson
  • R. P. M. Krishna
  • G. Samson
  • A. G. Prajeesh
Article

Abstract

State-of-the-art global coupled models used in seasonal prediction systems and climate projections still have important deficiencies in representing the boreal summer tropical rainfall climatology. These errors include prominently a severe dry bias over all the Northern Hemisphere monsoon regions, excessive rainfall over the ocean and an unrealistic double inter-tropical convergence zone (ITCZ) structure in the tropical Pacific. While these systematic errors can be partly reduced by increasing the horizontal atmospheric resolution of the models, they also illustrate our incomplete understanding of the key mechanisms controlling the position of the ITCZ during boreal summer. Using a large collection of coupled models and dedicated coupled experiments, we show that these tropical rainfall errors are partly associated with insufficient surface thermal forcing and incorrect representation of the surface albedo over the Northern Hemisphere continents. Improving the parameterization of the land albedo in two global coupled models leads to a large reduction of these systematic errors and further demonstrates that the Northern Hemisphere subtropical deserts play a seminal role in these improvements through a heat low mechanism.

Keywords

Tropical rainfall climatology Monsoons Global coupled models Surface albedo Heat low Deserts 

Notes

Acknowledgements

The authors gratefully acknowledge the financial support given by the Earth System Science Organization, Ministry of Earth Sciences, Government of India, to conduct this research under the National Monsoon Mission (Grant #MM/SERP/CNRS/2013/INT-10/002, Contribution #MM/PASCAL/RP/08). We sincerely thank Prof. Ravi Nanjundiah, Director, Indian Institute of Tropical Meteorology (IITM, India) and Dr. R Krishnan, executive Director, Centre for Climate Change Research (at IITM, India) for all the support during this research study. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in the Supplementary Materials) for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Inter-comparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Computer resources from Indian Institute of Tropical Meteorology (India) and GENCI-IDRIS (France, Grants 2015, 2016, 2017–016895) are also acknowledged.

References

  1. Alessandri A, Gualdi S, Polcher J, Navarra A (2007) Effects of land surface-vegetation on the boreal summer surface climate of a GCM. J Clim 20:255–278CrossRefGoogle Scholar
  2. Annamalai H et al (2015) Persistence of systematic errors in the Asian-Australian monsoon precipitation in climate models: a way forward. Clivar Exch 66:19–22Google Scholar
  3. Ashfaq M, Rastogi D, Mei R, Touma D, Leung RL (2016) Sources of errors in the simulation of south Asian summer monsoon in CMIP5 GCMs. Clim Dyn Online, doi: 10.1007/s00382-016-3337-7 Google Scholar
  4. Biasutti M (2013) Forced Sahel rainfall trends in the CMIP5 archive. J Geophys Res 118:1613–1623Google Scholar
  5. Bollasina MA, Ming Y (2013) The general circulation model precipitation bias over the southwestern equatorial Indian Ocean and its implications for simulating the South Asian monsoon. Clim Dyn 40:823–838CrossRefGoogle Scholar
  6. Bony S et al (2015) Clouds, circulation and climate sensitivity. Nat Geosci 8:261–268CrossRefGoogle Scholar
  7. Boos WR, Hurley JV (2013) Thermodynamic bias in the multimodel mean boreal summer monsoon. J Clim 26:2279–2287CrossRefGoogle Scholar
  8. Boos WR, Kuang Z (2010) Dominant control of the South Asian monsoon by orographic insulation versus plateau heating. Nature 463:218–222CrossRefGoogle Scholar
  9. Chakraborty A (2002) Role of Asian and African orography in Indian summer monsoon. Geophys Res Lett 29:1989CrossRefGoogle Scholar
  10. Charney J, Quirk WJ, Chow S, Kornfield J (1977) A comparative study of the effects of albedo change on drought in Semi–arid regions. J Atmos Sci 34:1366–1385CrossRefGoogle Scholar
  11. Chen T-C (2003) Maintenance of summer monsoon circulations: a planetary-scale perspective. J Climate 16:2022–2037CrossRefGoogle Scholar
  12. Cook KH, Vizy EK (2015) Detection and analysis of an amplified warming of the Sahara desert. J Climate 28:6560–6580CrossRefGoogle Scholar
  13. Dai A (2006) Precipitation characteristics in eighteen coupled climate models. J Climate 19:4605–4630CrossRefGoogle Scholar
  14. Dai A et al (2013) The relative roles of upper and lower tropospheric thermal contrasts and tropical influences in driving Asian summer monsoons. J Geophys Res 118:7024–7045CrossRefGoogle Scholar
  15. Deardorff JW (1978) Efficient prediction of ground surface temperature and moisture with inclusion of a layer of vegetation. J Geophys Res 83:1889–1903CrossRefGoogle Scholar
  16. Dee DP et al (2011) The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597CrossRefGoogle Scholar
  17. Dickinson RE (1983) Land surface processes and climate surface Albedos and energy-balance. Adv Geophys 25:305-353Google Scholar
  18. Dirmeyer PA (1998) Land-sea geometry and its effect on monsoon circulations. J Geophys Res 103(D10):11,555–11,572CrossRefGoogle Scholar
  19. Doi T, Behera SK, Yamagata T (2016) Improved seasonal prediction using the SINTEX-F2 coupled model. J Adv Model Earth Syst 8:1847–1867. doi: 10.1002/2016MS000744
  20. Frierson DM et al (2013) Contribution of ocean overturning circulation to tropical rainfall peak in the Northern Hemisphere. Nat Geosci 6:940–944CrossRefGoogle Scholar
  21. Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J Roy Meteorol Soc 106:447–462CrossRefGoogle Scholar
  22. Goswami BB, Deshpande M, Mukhopadhyay P, Saha SK, Rao SA, Murthugudde R, Goswami BN (2014) Simulation of monsoon intraseasonal variability in NCEP CFSv2 and its role on systematic bias. Clim Dyn 43:2725–2745CrossRefGoogle Scholar
  23. Hawcroft M, Haywood J, Collins M, Jones A, Jones AC, Stephens G (2017) Southern albedo, interhemispheric energy transports and the ITCZ: global impacts of biases in a coupled model. Clim Dyn 48:2279–2295CrossRefGoogle Scholar
  24. Haywood JM et al (2016) The impact of equilibrating hemispheric albedos on tropical performance in the HadGEM2-ES coupled climate model. Geophys Res Lett 43:395–403CrossRefGoogle Scholar
  25. Hou Y-T, Moorthi S, Campana KA (2002) Parameterization of solar radiation transfer in the NCEP models. NCEP Office Note 441Google Scholar
  26. Houldcroft CJ, Grey WMF, Barnsley M, Taylor CM, Los SO, North PRJ (2009) New vegetation albedo parameters and global fields of soil background albedo derived from MODIS for use in a climate model. J of Hydrometeorology 10:183–198CrossRefGoogle Scholar
  27. Hourdin F, Gainusa-Bogdan A, Braconnot P, Dufresne J-L, Traore A-K, Rio C (2015) Air moisture control on ocean surface temperature, hidden key to the warm bias enigma. Geophys Res Lett 42:10,885–10,893Google Scholar
  28. Huffman GJ, Adler RF, Bolvin DT, Gu G (2009) Improving the global precipitation record: GPCP Version 2.1. Geophys Res Lett 36:L17808CrossRefGoogle Scholar
  29. IPCC Fifth Assessment Report of the Intergovernmental Panel on Climate Change (2013) http://www.ipcc.ch/ipccreports/ar4-wg1.htm
  30. Jiang XN, Li T, Wang B (2004) Structures and mechanisms of the northward propagating boreal summer intraseasonal oscillation. J Climate 17:1022–1039CrossRefGoogle Scholar
  31. Johnson SJ, Levine RC, Turner AG et al (2016) The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global _0.35° AGCM. Clim Dyn 46:807–831. doi: 10.1007/s00382-015-2614-1 CrossRefGoogle Scholar
  32. Kang SM, Held IM, Frierson DMW, Zhao M (2008) The response of the ITCZ to extratropical thermal forcing: Idealized slab-ocean experiments with a GCM. J Climate 21:3521–3532CrossRefGoogle Scholar
  33. Karlsson J, Svenson G (2013) Consequences of poor representation of Arctic sea-ice albedo and cloud-radiation interactions in the CMIP5 model ensemble. Geophys Res Lett 40:4374–4379CrossRefGoogle Scholar
  34. Kato S et al (2013) Surface irradiances consistent with ceres-derived top-of-atmosphere shortwave and longwave Irradiances. J Clim 26:2719–2740CrossRefGoogle Scholar
  35. Kay JE, Wall C, Yettella V, Medeiros B, Hannay C, Caldwell P, Bitz C (2016) Global climate impacts of fixing the Southern Ocean shortwave radiation bias in the Community Earth System Model. J Clim 29:4617–4636. doi: 10.1175/JCLI-D-15-0358.1 CrossRefGoogle Scholar
  36. Kelly P, Mapes B (2010) Land surface heating and the north american monsoon anticyclone: model evaluation from diurnal to seasonal. J Clim 23:4096–4106CrossRefGoogle Scholar
  37. Kelly P, Mapes B (2013) Asian monsoon forcing of subtropical easterlies in the community atmosphere model: summer climate implications for the western Atlantic. J Clim 26:2741–2755CrossRefGoogle Scholar
  38. Kim HM, Webster PJ, Curry JA, Toma VE (2013) Asian summer monsoon prediction in ECMWF system 4 and NCEP CFSv2 retrospective seasonal forecasts. Clim Dyn 39:2975–2991CrossRefGoogle Scholar
  39. Kumar P, Podzun R, Hagemann S, Jacob D (2014) Impact of modified soil thermal characteristic on the simulated monsoon climate over south Asia. J Earth Syst Sci 123:151–160CrossRefGoogle Scholar
  40. Lavaysse C (2015) Warming trends: Saharan desert warming. Nat Clim Change 5:807–808CrossRefGoogle Scholar
  41. Lavaysse C, Flamant C, Evan A, Janicot S, Gaetani M (2016) Recent climatological trend of the Saharan heat low and its impact on the West African climate. Clim Dyn 47:3479–3498CrossRefGoogle Scholar
  42. Levine RC, Turner AG, Marathayil D, Martin GM (2013) The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future predictions of Indian summer monsoon rainfall. Clim Dyn 41:155–172CrossRefGoogle Scholar
  43. Liang X, Liu Y, Wu G (2005a) The role of land-sea distribution in the formation of the Asian summer monsoon. Geophys Res Lett 32:L03708Google Scholar
  44. Liang X-Z et al (2005b) Development of land surface albedo parameterization based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. J Geophys Res 110:D11107. doi: 10.1029/2004JD005579 CrossRefGoogle Scholar
  45. Lin JL (2007) The double-ITCZ problem in IPCC AR4 coupled GCMs: Ocean-atmosphere feedback analysis. J Clim 20:4497–4525CrossRefGoogle Scholar
  46. Loeb NG et al (2012) Advances in understanding top-of-atmosphere radiation variability from satellite observations. Surv Geophys 33:359–385CrossRefGoogle Scholar
  47. Masson S, Terray P, Madec G, Luo J–J, Yamagata T, Takahashi K (2012) Impact of intra-daily SST variability on ENSO characteristics in a coupled model. Clim Dyn 39:681–707CrossRefGoogle Scholar
  48. Mishra SK, Salvekar PS (1980) Role of barotropic instability in the development of monsoon disturbances. J Atmos Sci 37:383–394CrossRefGoogle Scholar
  49. Nicholson SE, Barcilon AI, Challa M, Baum M (2007) Wave Activity on the Tropical Easterly Jet. J Atmos Sci 64:2756–2763CrossRefGoogle Scholar
  50. Nie J, Boos WR, Kuang Z (2010) Observational evaluation of a convective quasi-equilibrium view of monsoons. J Climate 23:4416–4428CrossRefGoogle Scholar
  51. Noreen EW (1989) Computer-intensive methods for testing hypotheses: an introduction. Wiley, New YorkGoogle Scholar
  52. Prodhomme C et al (2014) Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model. Clim Dyn 42:271–290CrossRefGoogle Scholar
  53. Prodhomme C et al. (2016) Benefits of increasing the model resolution for the seasonal forecast quality in EC-Earth. J. Climate online.Google Scholar
  54. Rai A, Saha SK (2017) Evaluation of energy fluxes in the NCEP climate forecast system version 2.0 (CFSv2). Clim Dyn. doi: 10.1007/s00382-017-3587-z Google Scholar
  55. Reichler T, Kim J (2008) How well do coupled models simulate today’s climate? Bull Amer Meteorol Soc 89:303–311CrossRefGoogle Scholar
  56. Richter I (2015) Climate model biases in the eastern tropical oceans: Causes, impacts and ways forward. Clim Change 6:345–358Google Scholar
  57. Richter I, Xie S-P, Wittenberg AT, Masumoto Y (2012) Tropical Atlantic biases and their relation to surface wind stress and terrestrial precipitation. Clim Dyn 38:985–1001CrossRefGoogle Scholar
  58. Rodwell MJ, Hoskins BJ (1996) Monsoons and the dynamics of deserts. Q J Roy Meteorol Soc 122:1385–1404CrossRefGoogle Scholar
  59. Rodwell MJ, Hoskins BJ (2001) Subtropical Anticyclones and Summer Monsoons. J Climate 14:3192–3211CrossRefGoogle Scholar
  60. Roeckner E et al. (2003) The atmospheric general circulation model ECHAM5: Part 1: model description. Max-Planck-Institut fur Meteorologie, Hamburg, MPI-Report 349.Google Scholar
  61. Roehrig R, Bouniol D, Guichard F, Hourdin F, Redelsperger JL (2013) The present and future of the West African monsoon: a process-oriented assessment of CMIP5 simulations along the AMMA Transect. J Clim 26:6471–6505CrossRefGoogle Scholar
  62. Sabeerali CT, Rao SA, Dhakate AR, Salunke K, Goswami BN (2015) Why ensemble mean projection of south Asian monsoon rainfall by CMIP5 models is not reliable? Clim Dyn 45:161–174CrossRefGoogle Scholar
  63. Saha S et al (2014) The NCEP climate forecast system version 2. J Climate 27:2185–2208CrossRefGoogle Scholar
  64. Samson G, Masson S, Durand F, Terray P, Berthet S, Jullien S (2016) Role of land surface albedo and horizontal resolution on the Indian Summer Monsoon biases in a coupled ocean-atmosphere tropical-channel model. Clim DynGoogle Scholar
  65. Sandeep S, Ajayamohan RS (2014) Origin of the cold bias over the Arabian Sea in climate models. Sci Rep 4:6043Google Scholar
  66. Schaaf CB, Liu J, Gao F, Strahler AH (2011) Land remote sensing and global environmental change. L Rem Sens Glob Environ Chang 11:549–561CrossRefGoogle Scholar
  67. Schneider T, Bischoff T, Haug GH (2014) Migration and dynamics of the inter-tropical convergence zone. Nature 513:45–53CrossRefGoogle Scholar
  68. Shaw TA, Voigt A, Kang SM, Seo J (2015) Response of the intertropical convergence zone to zonally asymmetric subtropical surface forcings. Geophys Res Lett 42:9961–9969CrossRefGoogle Scholar
  69. Sooraj KP, Terray P, Mujumdar M (2015) Global warming and the weakening of the Asian summer monsoon circulation: assessments from the CMIP5 models. Clim Dyn 45:233–252CrossRefGoogle Scholar
  70. Sperber KR et al (2013) The Asian summer monsoon: an inter-comparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41:2711–2744CrossRefGoogle Scholar
  71. Stephens GL et al (2010) Dreary state of precipitation in global models. J Geophys Res 115:D24211CrossRefGoogle Scholar
  72. Stephens GL, O’Brien D, Webster PJ, Pilewski P, Kato S, Li J-I (2015) The Albedo of Earth. Rev Geophys 53:141–163CrossRefGoogle Scholar
  73. Sud YC, Smith WE (1985) Influence of local land surface processes on the Indian monsoon: a numerical study. J Clim Appl Meteor 24:1015–1036CrossRefGoogle Scholar
  74. Swapna et al (2015) The IITM earth system model. Bull Amer Meteor Soc 96:1351–1367. doi: 10.1175/BAMS-D-13-00276.1
  75. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498CrossRefGoogle Scholar
  76. Terray P, Delecluse P, Labattu S, Terray L (2003) Sea surface temperature associations with the late Indian summer monsoon. Clim Dyn 21:593–618CrossRefGoogle Scholar
  77. Thackeray CW, Fletcher CG, Derksen C (2015) Quantifying the skill of CMIP5 models in simulating seasonal albedo and snow cover evolution. J Geophys Res 120:5831–5849Google Scholar
  78. Vamborg FSE, Brovkin V, Claussen M (2014) Background albedo dynamics improve simulated precipitation variability in the Sahel region. Earth Syst Dynam 5:89–101CrossRefGoogle Scholar
  79. Voigt A, Stevens B, Bader J, Mauritsen T (2014) Compensation of hemispheric albedo asymmetries by shifts of the ITCZ and tropical clouds. J Climate 27:1029–1045CrossRefGoogle Scholar
  80. Wang S, Trishchenko AP, Khlopenkov KV, Davidson A (2006) Comparison of International Panel on Climate Change Fourth Assessment Report climate model simulations of surface albedo with satellite products over northern latitudes. J Geophys Res 111:D21108CrossRefGoogle Scholar
  81. Wang C, Zhang L, Lee SK, Wu L, Mechoso CR (2014) A global perspective on CMIP5 climate model biases. Nat Clim Change 4:201–205CrossRefGoogle Scholar
  82. Wang B (2006) The Asian monsoon. Springer-Verlag, p 870Google Scholar
  83. Wild M et al (2015) The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models. Clim Dyn 44:3393–3429CrossRefGoogle Scholar
  84. Wu G et al (2012) Thermal Controls on the Asian Summer Monsoon. Scientific Rep 2:1–7Google Scholar
  85. Xie P, Arkin PA (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Amer Meteor Soc 78:2539–2558CrossRefGoogle Scholar
  86. Yang F, Mitchell K, Hou Y-T, Dai Y, Zeng X, Wang Z, Liang X-Z (2008) Dependence of land surface albedo on solar zenith angle: observations and model parameterization. J Appl Meteo Clim 47:2963–2982CrossRefGoogle Scholar
  87. Yin et al (2004) Comparison of the GPCP and CMAP Merged Gauge–Satellite Monthly Precipitation Products for the Period 1979–2001. J of Hydrometeorology 5:1207–1222Google Scholar

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© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Indo-French Cell for Water Sciences, IISc-NIO-IITM–IRD Joint International LaboratoryIndian Institute of Tropical Meteorology (IITM)PuneIndia
  2. 2.Sorbonne Universites (UPMC, Univ Paris 06)-CNRS-IRD-MNHN, LOCEAN LaboratoryParisFrance
  3. 3.Centre for Climate Change ResearchIndian Institute of Tropical MeteorologyPuneIndia
  4. 4.Indian Institute of Tropical MeteorologyPuneIndia
  5. 5.Mercator OcéanRamonville-Saint-AgneFrance

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