Advertisement

Climate Dynamics

, Volume 47, Issue 1–2, pp 249–269 | Cite as

Cloud cover climatologies in the Mediterranean obtained from satellites, surface observations, reanalyses, and CMIP5 simulations: validation and future scenarios

  • Aaron Enriquez-AlonsoEmail author
  • Arturo Sanchez-Lorenzo
  • Josep Calbó
  • Josep-Abel González
  • Joel R. Norris
Article

Abstract

Clouds are an important regulator of climate due to their connection to the water balance of the atmosphere and their interaction with solar and infrared radiation. In this study, monthly total cloud cover (TCC) records from different sources have been inter-compared on annual and seasonal basis for the Mediterranean region and the period 1984–2005. Specifically, gridded databases from satellite projects (ISCCP, CLARA, PATMOS-x), from reanalysis products (ERA-Interim, MERRA), and from surface observations over land (EECRA) and ocean (ICOADS) have been examined. Then, simulations from 44 climate runs of the Coupled Model Intercomparison Project phase 5 corresponding to the historical scenario have been compared against the observations. Overall, we find good agreement between the mean values of TCC estimated from the three satellite products and from surface observations, while reanalysis products show much lower values across the region. Nevertheless, all datasets show similar behavior regarding the annual cycle of TCC. In addition, our results indicate an underestimation of TCC from climate model simulations as compared to the satellite products, especially during summertime, although the annual cycle is well simulated by most models. This result is quite general and apparently independent of the cloud parameterizations included in each particular model. Equally, similar results are obtained if the ISCCP simulator included in the Cloud Feedback Model Intercomparison Project Observation Simulator Package is considered, despite only few models provide the post-processed results. Finally, GCM projections of TCC over the Mediterranean are presented. These projections predict a reduction of TCC during the 21st century in the Mediterranean. Specifically, for an extreme emission scenario (RCP8.5) the projected relative rate of TCC decrease is larger than 10 % by the end of the century.

Keywords

Total cloud cover Mediterranean Observations Reanalysis Climate model simulations Projections 

Notes

Acknowledgments

This research was supported by the Spanish Ministry of Science and Innovation (currently Ministry of Economy and Competitiveness) Projects CGL2010-18546, CGL2014-55976-R, and CGL2014-52135-C3-1-R. The first author enjoys a Grant by the FPI program (BES-2011-049095) of the same ministry. The second author was supported by the “Secretaria per a Universitats i Recerca del Departament d’Economia i Coneixement, de la Generalitat de Catalunya i del programa Cofund de les Accions Marie Curie del 7è Programa marc d’R + D de la Unió Europea” (2011 BP-B 00078) and the postdoctoral fellowship JCI-2012-12508. The ISCCP-D2 data were obtained from the International Satellite Cloud Climatology Project web site http://isccp.giss.nasa.gov, maintained by the NASA Goddard Institute for Space Studies, New York. Data from EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF) were used. ERA-Interim data is supported by the ECMWF. PATMOS-x data is available via ftp from the University of Wisconsin, Space Science and Engineering Center (SSEC) and the Cooperative Institute for Meteorological Satellite Studies (CIMSS). MERRA files were obtained from the NASA Goddard Earth Sciences Data and Information Services Center. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 2 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Supplementary material

382_2015_2834_MOESM1_ESM.docx (3.2 mb)
Supplementary material 1 (DOCX 3325 kb)

References

  1. Allen RJ, Sherwood SC, Norris JR, Zender CS (2012) Recent Northern Hemisphere tropical expansion primarily driven by black carbon and tropospheric ozone. Nature 485:350–354. doi: 10.1038/nature11097 CrossRefGoogle Scholar
  2. Azorin-Molina C, Baena-Calatrava R, Echave-Calvo I et al (2013) A daytime over land algorithm for computing AVHRR convective cloud climatologies for the Iberian Peninsula and the Balearic Islands. Int J Climatol 33:2113–2128. doi: 10.1002/joc.3572 CrossRefGoogle Scholar
  3. Bedacht E, Gulev SK, Macke A (2007) Intercomparison of global cloud cover fields over oceans from the VOS observations and NCEP/NCAR reanalysis. Int J Climatol 27:1707–1719. doi: 10.1002/joc.1490 CrossRefGoogle Scholar
  4. Betts AK, Zhao M, Dirmeyer PA, Beljaars ACM (2006) Comparison of ERA40 and NCEP/DOE near-surface data sets with other ISLSCP-II data sets. J Geophys Res Atmos 111:D22S04. doi: 10.1029/2006JD007174 CrossRefGoogle Scholar
  5. Bodas-Salcedo A, Webb MJ, Bony S et al (2011) COSP: satellite simulation software for model assessment. Bull Am Meteorol Soc 92:1023–1043. doi: 10.1175/2011BAMS2856.1 CrossRefGoogle Scholar
  6. Bony S, Stevens B, Frierson DMW et al (2015) Clouds, circulation and climate sensitivity. Nat Geosci 8:261–268. doi: 10.1038/ngeo2398 CrossRefGoogle Scholar
  7. Calbó J, Sanchez-Lorenzo A (2009) Cloudiness climatology in the Iberian Peninsula from three global gridded datasets (ISCCP, CRU TS 2.1, ERA-40). Theor Appl Climatol 96:105–115. doi: 10.1007/s00704-008-0039-z CrossRefGoogle Scholar
  8. Cermak J, Wild M, Knutti R et al (2010) Consistency of global satellite-derived aerosol and cloud data sets with recent brightening observations. Geophys Res Lett 37:L21704. doi: 10.1029/2010GL044632 CrossRefGoogle Scholar
  9. Chernokulsky A, Mokhov II (2012) Climatology of total cloudiness in the arctic: an intercomparison of observations and reanalyses. Adv Meteorol 2012:1–15. doi: 10.1155/2012/542093 CrossRefGoogle Scholar
  10. Christensen JH, Hewitson B, Busuioc A et al (2007) Regional climate projections. In: Solomon S, Qin D, Manning M et al (eds) Climate change 2007: the physical science basis. Contribution of working group I to Fourth assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 847–940Google Scholar
  11. Christensen J, Kjellström E, Giorgi F et al (2010) Weight assignment in regional climate models. Clim Res 44:179–194. doi: 10.3354/cr00916 CrossRefGoogle Scholar
  12. Christensen JH, Krishna Kumar K, Aldrian E et al (2013) Climate phenomena and their relevance for future regional climate change. In: Stocker TF, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Contribution of working group I to Fifth assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 1217–1308Google Scholar
  13. Collins M, Knutti R, Arblaster J et al (2013) Long-term Climate Change: Projections, Commitments and Irreversibility. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to Fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 1029–1136Google Scholar
  14. Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  15. Diffenbaugh NS, Pal JS, Giorgi F, Gao X (2007) Heat stress intensification in the Mediterranean climate change hotspot. Geophys Res Lett 34:L11706. doi: 10.1029/2007GL030000 CrossRefGoogle Scholar
  16. Dubois C, Somot S, Calmanti S et al (2012) Future projections of the surface heat and water budgets of the Mediterranean Sea in an ensemble of coupled atmosphere–ocean regional climate models. Clim Dyn 39:1859–1884. doi: 10.1007/s00382-011-1261-4 CrossRefGoogle Scholar
  17. Dufresne J-L, Bony S (2008) An assessment of the primary sources of spread of global warming estimates from coupled atmosphere–ocean models. J Clim 21:5135–5144. doi: 10.1175/2008JCLI2239.1 CrossRefGoogle Scholar
  18. Eastman R, Warren SG (2013) A 39-Yr survey of cloud changes from land stations worldwide 1971–2009: long-term trends, relation to aerosols, and expansion of the tropical belt. J Clim 26:1286–1303. doi: 10.1175/JCLI-D-12-00280.1 CrossRefGoogle Scholar
  19. Errasti I, Ezcurra A, Sáenz J, Ibarra-Berastegi G (2010) Validation of IPCC AR4 models over the Iberian Peninsula. Theor Appl Climatol 103:61–79. doi: 10.1007/s00704-010-0282-y CrossRefGoogle Scholar
  20. Evan AT, Heidinger AK, Vimont DJ (2007) Arguments against a physical long-term trend in global ISCCP cloud amounts. Geophys Res Lett 34:L04701. doi: 10.1029/2006GL028083 CrossRefGoogle Scholar
  21. Flato G, Marotzke J, Abiodun B et al (2013) Evaluation of climate models. In: Stocker TF, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Contribution of working group I to Fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 741–866Google Scholar
  22. Foster MJ, Heidinger A (2013) PATMOS-x: results from a diurnally corrected 30-yr satellite cloud climatology. J Clim 26:414–425. doi: 10.1175/JCLI-D-11-00666.1 CrossRefGoogle Scholar
  23. Geophysical Fluid Dynamics Laboratory Global Atmospheric Model Development Team G–G (2004) The new GFDL global atmosphere and land model AM2–LM2: evaluation with prescribed SST simulations. J Clim 17:4641–4673CrossRefGoogle Scholar
  24. Giorgi F (2006) Climate change hot-spots. Geophys Res Lett 33:L08707. doi: 10.1029/2006GL025734 CrossRefGoogle Scholar
  25. Griggs JA, Bamber JL (2008) Assessment of cloud cover characteristics in satellite datasets and reanalysis products for Greenland. J Clim 21:1837–1849. doi: 10.1175/2007JCLI1570.1 CrossRefGoogle Scholar
  26. Hahn CJ, Rossow WB, Warren SG (2001) ISCCP cloud properties associated with standard cloud types identified in individual surface observations. J Clim 14:11–28CrossRefGoogle Scholar
  27. Hartmann DL, Klein Tanki AMG, Rusticucci M et al (2013) Observations: atmosphere and surface. In: Stocker TF, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Contribution of working group I to Fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 159–254Google Scholar
  28. Hourdin F, Musat I, Bony S et al (2006) The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Clim Dyn 27:787–813. doi: 10.1007/s00382-006-0158-0 CrossRefGoogle Scholar
  29. Jakob C (1999) Validation and sensitivities of frontal clouds simulated by the ECMWF model. Mon Weather Rev 27:2514–2531Google Scholar
  30. Jiang JH, Su H, Zhai C et al (2012) Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA “A-Train” satellite observations. J Geophys Res. doi: 10.1029/2011JD017237 Google Scholar
  31. Kang SM, Lu J (2012) Expansion of the hadley cell under global warming: winter versus summer. J Clim 25:8387–8393. doi: 10.1175/JCLI-D-12-00323.1 CrossRefGoogle Scholar
  32. Karl TR, Steurer PM (1990) Increased cloudiness in the United States during the first half of the Twentieth Century: fact or fiction? Geophys Res Lett 17:1925–1928. doi: 10.1029/GL017i011p01925 CrossRefGoogle Scholar
  33. Karlsson K-G, Riihelä A, Müller R et al (2013) CLARA-A1: a cloud, albedo, and radiation dataset from 28 yr of global AVHRR data. Atmos Chem Phys 13:5351–5367. doi: 10.5194/acp-13-5351-2013 CrossRefGoogle Scholar
  34. Klein SA, Jakob C (1999) Validation and sensitivities of frontal clouds simulated by the ECMWF model. Mon Weather Rev 127:2514–2531CrossRefGoogle Scholar
  35. Klein SA, Zhang Y, Zelinka MD et al (2013) Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator. J Geophys Res Atmos 118:1329–1342. doi: 10.1002/jgrd.50141 CrossRefGoogle Scholar
  36. Knutti R, Furrer R, Tebaldi C, Cermak J, Meehl GA (2010) Challenges in combining projections from multiple climate models. J Clim 23:2739–2758. doi: 10.1175/2009JCLI3361.1
  37. Lacagnina C, Selten F (2014) Evaluation of clouds and radiative fluxes in the EC-Earth general circulation model. Clim Dyn 43:2777–2796. doi: 10.1007/s00382-014-2093-9 CrossRefGoogle Scholar
  38. Lauer A, Hamilton K (2013) Simulating clouds with global climate models: a comparison of CMIP5 results with CMIP3 and satellite data. J Clim 26:3823–3845. doi: 10.1175/JCLI-D-12-00451.1 CrossRefGoogle Scholar
  39. Levizzani V, Pinelli F, Pasqui M et al (2010) A 10-year climatology of warm-season cloud patterns over Europe and the Mediterranean from Meteosat IR observations. Atmos Res 97:555–576. doi: 10.1016/j.atmosres.2010.05.014 CrossRefGoogle Scholar
  40. Lu J, Vecchi GA, Reichler T (2007) Expansion of the Hadley cell under global warming. Geophys Res Lett 34:L06805. doi: 10.1029/2006GL028443 Google Scholar
  41. Lucas C, Timbal B, Nguyen H (2014) The expanding tropics: a critical assessment of the observational and modeling studies. Wiley Interdiscip Rev Clim Chang 5:89–112. doi: 10.1002/wcc.251 CrossRefGoogle Scholar
  42. Meerkötter R, König C, Bissolli P et al (2004) A 14-year European Cloud Climatology from NOAA/AVHRR data in comparison to surface observations. Geophys Res Lett 31:L15103. doi: 10.1029/2004GL020098 CrossRefGoogle Scholar
  43. Nam CCW, Quaas J (2012) Evaluation of clouds and precipitation in the ECHAM5 general circulation model using CALIPSO and CloudSat satellite data. J Clim 25:4975–4992. doi: 10.1175/JCLI-D-11-00347.1 CrossRefGoogle Scholar
  44. Nam C, Bony S, Dufresne J-L, Chepfer H (2012) The “too few, too bright” tropical low-cloud problem in CMIP5 models. Geophys Res Lett 39:L21801. doi: 10.1029/2012GL053421 CrossRefGoogle Scholar
  45. Naud CM, Booth JF (2014) Evaluation of ERA-Interim and MERRA Cloudiness in the Southern Ocean. J Clim 27:2109–2124CrossRefGoogle Scholar
  46. Norris JR (2000) What can cloud observations tell us about climate variability? Space Sci Rev 94:375–380CrossRefGoogle Scholar
  47. Norris JR, Evan AT (2015) Empirical removal of artifacts from the ISCCP and PATMOS-x satellite cloud records. J Atmos Ocean Technol 32:691–702. doi: 10.1175/JTECH-D-14-00058.1 CrossRefGoogle Scholar
  48. Perkins SE, Pitman AJ, Holbrook NJ, McAneney J (2007) Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over australia using probability density functions. J Clim 20:4356–4376. doi: 10.1175/JCLI4253.1 CrossRefGoogle Scholar
  49. Pincus R, Batstone CP, Hofmann RJP et al (2008) Evaluating the present-day simulation of clouds, precipitation, and radiation in climate models. J Geophys Res 113:D14209. doi: 10.1029/2007JD009334 CrossRefGoogle Scholar
  50. Probst P, Rizzi R, Tosi E et al (2012) Total cloud cover from satellite observations and climate models. Atmos Res 107:161–170. doi: 10.1016/j.atmosres.2012.01.005 CrossRefGoogle Scholar
  51. Qian Y, Long CN, Wang H et al (2012) Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations. Atmos Chem Phys 12:1785–1810. doi: 10.5194/acp-12-1785-2012 CrossRefGoogle Scholar
  52. Rajczak J, Pall P, Schär C (2013) Projections of extreme precipitation events in regional climate simulations for Europe and the Alpine Region. J Geophys Res Atmos 118:3610–3626. doi: 10.1002/jgrd.50297 CrossRefGoogle Scholar
  53. Randall DA (2013) Beyond deadlock. Geophys Res Lett 40:5970–5976. doi: 10.1002/2013GL057998 CrossRefGoogle Scholar
  54. Randall DA, Wood RA, Bony S et al (2007) Climate Models and Their Evaluation. In: Solomon S, Qin D, Manning M et al (eds) Climate change 2007: the physical science basis. Contribution of working group I to I to Fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 589–662Google Scholar
  55. Rienecker MM, Suarez MJ, Gelaro R 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 CrossRefGoogle Scholar
  56. Roeckner E, Arpe K, Bengtsson L et al (1996) The atmospheric general circulation model ECHAM-4: model description and simulation of present-day climate. Hamburg, GermanyGoogle Scholar
  57. Rojas M, Li LZ, Kanakidou M et al (2013) Winter weather regimes over the Mediterranean region: their role for the regional climate and projected changes in the twenty-first century. Clim Dyn 41:551–571. doi: 10.1007/s00382-013-1823-8 CrossRefGoogle Scholar
  58. Rossow WB, Dueñas EN (2004) The international satellite cloud climatology project (ISCCP) web site: an online resource for research. Bull Am Meteorol Soc 85:167–172. doi: 10.1175/BAMS-85-2-167 CrossRefGoogle Scholar
  59. Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Am Meteorol Soc 80:2261–2287. doi: 10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2 CrossRefGoogle Scholar
  60. Ruosteenoja K, Räisänen P (2013) Seasonal changes in solar radiation and relative humidity in Europe in response to global Warming*. J Clim 26:2467–2481. doi: 10.1175/JCLI-D-12-00007.1 CrossRefGoogle Scholar
  61. Sanchez-Lorenzo A, Calbó J, Wild M (2012) Increasing cloud cover in the 20th century: review and new findings in Spain. Clim Past Discuss 8:1133–1167. doi: 10.5194/cpd-8-1133-2012 CrossRefGoogle Scholar
  62. Schlemmer L, Hohenegger C, Schmidli J, Schär C (2012) Diurnal equilibrium convection and land surface–atmosphere interactions in an idealized cloud-resolving model. Q J R Meteorol Soc 138:1526–1539. doi: 10.1002/qj.1892 CrossRefGoogle Scholar
  63. Schneider A, Wallace DWR, Körtzinger A (2007) Alkalinity of the Mediterranean Sea. Geophys Res Lett 34:L15608. doi: 10.1029/2006GL028842 CrossRefGoogle Scholar
  64. Stanfield RE, Dong X, Xi B et al (2014) Assessment of NASA GISS CMIP5 and Post-CMIP5 simulated clouds and TOA radiation budgets using satellite observations. Part I: cloud fraction and properties. J Clim 27:4189–4208. doi: 10.1175/JCLI-D-13-00558.1 CrossRefGoogle Scholar
  65. Stevens B, Bony S (2013) What are climate models missing? Science 340(6136):1053–1054. doi: 10.1126/science.1237554 CrossRefGoogle Scholar
  66. Stubenrauch CJ, Rossow WB, Kinne S et al (2013) Assessment of global cloud datasets from satellites: project and database initiated by the GEWEX Radiation Panel. Bull Am Meteorol Soc 94:1031–1049. doi: 10.1175/BAMS-D-12-00117.1 CrossRefGoogle Scholar
  67. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. 106:7183–7192Google Scholar
  68. Taylor KE, Stouffer RJ, Meehl G, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. doi: 10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  69. Tiedtke M (1993) Representation of clouds in large-scale models. Mon Weather Rev 121:3040–3061CrossRefGoogle Scholar
  70. Tompkins AM (2002) A prognostic parameterization for the subgrid-scale variability of water vapor and clouds in large-scale models and its use to diagnose cloud cover. J Atmos Sci 59:1917–1942CrossRefGoogle Scholar
  71. Town MS, Walden VP, Warren SG (2007) Cloud cover over the South Pole from visual observations, satellite retrievals, and surface-based infrared radiation measurements. J Clim 20:544–559CrossRefGoogle Scholar
  72. Wang H, Su W (2013) Evaluating and understanding top of the atmosphere cloud radiative effects in intergovernmental panel on climate change (IPCC) Fifth Assessment Report (AR5) Coupled Model Intercomparison Project Phase 5 (CMIP5) models using satellite observations. J Geophys Res Atmos 118:683–699. doi: 10.1029/2012JD018619 CrossRefGoogle Scholar
  73. Webb M, Senior C, Bony S, Morcrette J-J (2001) Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Clim Dyn 17:905–922. doi: 10.1007/s003820100157 CrossRefGoogle Scholar
  74. Woodruff SD, Worley SJ, Lubker SJ et al (2011) ICOADS Release 2.5: extensions and enhancements to the surface marine meteorological archive. Int J Climatol 31:951–967. doi: 10.1002/joc.2103 CrossRefGoogle Scholar
  75. Wu W, Liu Y, Betts AK (2012) Observationally based evaluation of NWP reanalyses in modeling cloud properties over the Southern Great Plains. J Geophys Res Atmos 117:D12202. doi: 10.1029/2011JD016971 Google Scholar
  76. Zhang MH, Lin WY, Klein SA 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 Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Aaron Enriquez-Alonso
    • 1
    Email author
  • Arturo Sanchez-Lorenzo
    • 2
  • Josep Calbó
    • 1
  • Josep-Abel González
    • 1
  • Joel R. Norris
    • 3
  1. 1.Department of PhysicsUniversity of GironaGironaSpain
  2. 2.Instituto Pirenaico de EcologíaConsejo Superior de Investigaciones Científicas (IPE–CSIC)ZaragozaSpain
  3. 3.Scripps Institution of OceanographyUniversity of California, San DiegoLa JollaUSA

Personalised recommendations