Abstract
Vertically resolved multi-layer cloud distributions over the globe using 4 years of CloudSat/CALIPSO observations during 2007–2010 are discussed. The quantitative information on the frequency of occurrence of one- to five-layered clouds across the globe is established, which are of immense importance from the global climate standpoint. After segregating the CloudSat observations into different seasons, the 4 years of mean global maps of frequency of occurrence of one to five-layered clouds are discussed in details. These global maps provide much needed quantification of vertically resolved multi-layer clouds by revealing when and where the frequency of occurrence of multi-layer clouds are maximum including the number of layers. On an average, it is observed that over the globe one-, two-, three-, four- and five-layer clouds occur 53, 20, 3.5, 0.4 and 0.04 % of the time respectively. High fraction of single layer clouds is observed over the descending limbs of Hadley cell where relatively large lower tropospheric stability is found. The regions where multi-layer clouds are more frequent are identified and discussed along with large scale circulation. Apart from quantifying the frequency of occurrence of multi-layer clouds, the latitudinal distribution of zonal mean occurrence of cloud base and top altitudes of each cloud layer is constructed for boreal winter and summer. These analyses provide the cloud base and top altitudes of one to five-layered clouds, which are important to understand the vertical structure of the multi-layered clouds. The significance of the present study lies in establishing the global distribution of vertically resolved multi-layer clouds and the role of large-scale dynamics in controlling their distribution for the first time.
Similar content being viewed by others
References
Baum et al (1995) Satellite remote sensing of multiple cloud layers. J Atmos Sci 52:4210–4230
Bender FAM, Ramanathan V, Tselioudis G (2011) Changes in extratropical storm track cloudiness 1983–2008: observational support for a poleward shift. Clim Dyn. doi:10.1007/s00382-011-1065-6
Bengtsson L, Hodges KI, Roeckner E (2006) Storm tracks and climate change. J Clim 19:3518–3543
Bhat GS, Chakraborty A, Nanjundiah RS, Srinivasan J (2002) Vertical thermal structure of the atmosphere during active and weak phases of convection over the north Bay of Bengal: observation and model results. Curr Sci 83(3):296–302
Chen T, Zhang Y, Rossow WB (2000) Sensitivity of atmospheric radiative heating rate profiles to variations of cloud layer overlap. J Clim 13:2941–2959
Dimri AP, Niyogi D, Barros AP, Ridley J, Mohanty UC, Yasunari T, Sikka DR (2015) Western disturbances: a review. Rev Geophys. doi:10.1002/2014RG000460
Dong B, Sutton RT, Woollings T, Hodges K (2013) Variability of the North Atlantic summer storm track: mechanisms and impacts on European climate. Environ Res Lett 8:034037
Gupta SK, Darnell WL, Wilber AC (1992) A parameterization for longwave surface radiation from satellite data: recent improvements. J Appl Meteorol 31:1361–1367
Haynes JM, Jakob C, Rossow WB, Tselioudis G, Brown J (2011) Major characteristics of Southern Ocean cloud regimes and their effects on the energy budget. J Clim 24:5061–5080
Hoskins BJ, Hodges K (2005) A new perspective on Southern Hemisphere storm tracks. J Clim 18:4108–4129
Houze RA Jr (1982) Cloud clusters and large-scale vertical motions in the tropics. J Meteorol Soc Jpn 60:396–410
Huang J et al (2005) Advanced retrievals of multilayered cloud properties using multispectral measurements. J Geophys Res. doi:10.1029/2004JD005101
Klein SA, Hartmann DL, Norris JR (1995) On the relationship among low-cloud structure, sea surface temperature, and atmospheric circulation in the summertime northeast Pacific. J Clim 8:1140–1155
Li J, Yi Y, Minnis P, Huang J, Yan H, Ma Y, Wang W, Kirk Ayers J (2011) Radiative effect differences between multi-layered and single-layer clouds derived from CERES, CALIPSO, and CloudSat data. J Quant Spectrosc Radiat Transf 112:361–375
Liu C, Zipser EJ (2005) Global distribution of convection penetrating the tropical tropopause. J Geophys Res 110:D23104. doi:10.1029/2005JD006063
Luo Y, Zhang R, Wang H (2009) Comparing occurrences and vertical structures of hydrometeors between Eastern China and the Indian Monsoon Region Using CloudSat/CALIPSO Data. J Clim 22(4):1052–1064
Mace GG, Marchand R, Zhang Q, Stephens G (2007) Global hydrometeor occurrence as observed by CloudSat: initial observations from summer 2006. Geophys Res Lett 34:L09808. doi:10.1029/2006GL029017
Mace GG, Zhang Q, Vaughan M, Marchand R, Stephens G, Trepte C, Winker D (2009) A description of hydrometeor layer occurrence statistics derived from the first year of merged CloudSat and CALIPSO data. J Geophys Res 114:D00A26. doi:10.1029/2007JD009755
Narendra Babu AN, Nee JB, Kumar KK (2010) Seasonal and diurnal variation of convective available potential energy (CAPE) using COSMIC/FORMOSAT-3 observations over the tropics. J Geophys Res 115:D04102. doi:10.1029/2009JD012535
Randall DA, DA Harshvardhan D, Corsetti TG (1989) Interactions among radiation, convection, and large-scale dynamics in a general circulation model. J Atmos Sci 46:1943–1970
Randall DA et al (2007) Climate models and their evaluation. In: Solomon S et al (eds) Climate Change 2007: the physical sciences basis, contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, chap 4. Cambridge University Press, Cambridge, pp 589–662
Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim GK, Bloom S, Chen J, Collins D, Conaty A, Da Silva A et al (2011) MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J Clim 24:3624–3648. doi:10.1175/JCLI-D-11-00015.1
Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Am Meteorol Soc 80:2261–2287
Rossow W, Zhang Y, Wang J (2005) A statistical model of cloud vertical structure based on reconciling cloud layer amounts inferred from satellites and radiosonde humidity profiles. J Clim 18:3587–3605
Sathiyamoorthy V, Pal PK, Joshi PC (2004) Influence of the upper-tropospheric wind shear upon cloud radiative forcing in the Asian Monsoon Region. J Clim 17(14):2725–2735
Simpson J, Robert FA, Gerald RN (1988) A proposed Tropical Rainfall Measuring Mission (TRMM) Satellite. Bull Am Meteorol Soc 69:278–295
Slingo A, Slingo JM (1988) The response of a general circulation model to cloud longwave radiative forcing. I. Introduction and initial experiments. Q J R Meteorol Soc 114:1027–1062
Stephens GL (2005) Cloud feedback in the climate system: a critical review. J Clim 18:237–273
Stephens GL, Vane DG, Boain RJ, Mace GG, Sassen K, Wang Z, Illingworth AJ, O’Connor EJ, Rossow WB, Durden SL, Miller SD, Austin RT, Benedetti A, Mitrescu C (2002) The CloudSat mission and the A-Train. Bull Am Meterorol Soc 83:1771–1790
Stephens GL, Vane DG, Taneli S (2008) CloudSat mission: performance and early science after the first year of operation. J Geophys Res 113:D00A18. doi:10.1029/2008JD009982
Subrahmanyam KV, Kumar KK (2013) CloudSat observations of cloud-type distribution over the Indian summer monsoon region. Ann Geophys 31:1155–1162. doi:10.5194/angeo-31-1155-2013
Trenberth KE, Fasullo JT (2010) Tracking earth’s energy. Science 328:316–317
Wang J, Rossow WB (1995) Determination of cloud vertical structure from upper-air observations. J Appl Meteorol 34:2243–2258
Wang J, Rossow WB (1998) Effects of cloud vertical structure on atmospheric circulation in the GISS GCM. J Clim 11:3010–3029
Wang J, Rossow WB, Zhang Y (2000) Cloud vertical structure and its variations from a 20-yr global rawinsonde dataset. J Clim 13:3041–3056
Webster PJ, Stephens GL (1984) Cloud–radiation interaction and the climate problem. In: Houghton J (ed) The global climate. Cambridge University Press, Cambridge, pp 63–78
Wielicki BA, Cess RD, King MD, Randall DA, Harrison EF (1995) Mission to Planet Earth: role of clouds and radiation in climate. Bull Am Meteorol Soc 76:2125–2153
Winker DM, Hunt WH, McGill MJ (2007) Initial performance assessment of CALIOP. Geophys Res Lett 34:L19803. doi:10.1029/2007GL030135
Wu DL, Ackerman SA, Davies R, Diner DJ, Garay MJ, Kahn BH, Maddux BC, Moroney CM, Stephens GL, Veefkind JP, Vaughan A (2009) Vertical distributions and relationships of cloud occurrence frequency as observed by MISR, AIRS, MODIS, OMI, CALIPSO, and CloudSat. Geophys Res Lett 36:L09821. doi:10.1029/2009GL037464
Yuan X, Patoux J, Li C (2009) Satellite-based midlatitude cyclone statistics over the Southern Ocean: 2. Tracks and surface fluxes. J Geophys Res 114:D04106. doi:10.1029/2008JD010874
Zipser EJ, Cecil D, Liu C, Nesbitt S, Yorty D (2006) Where are the most intense thunderstorms on earth? Bull Am Meteorol Soc 87:1057–1071
Acknowledgments
The authors are greatly thankful to CloudSat and CALIPSO team for 2B-GEPROF LIDAR product, which was obtained from the website http://www.cloudsat.cira.colostate.edu.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Subrahmanyam, K.V., Kumar, K.K. CloudSat observations of multi layered clouds across the globe. Clim Dyn 49, 327–341 (2017). https://doi.org/10.1007/s00382-016-3345-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-016-3345-7