Open Access
Issue
EPJ Web of Conferences
Volume 119, 2016
The 27th International Laser Radar Conference (ILRC 27)
Article Number 04009
Number of page(s) 4
Section Poster Session (Spaceborne Lidar)
DOI https://doi.org/10.1051/epjconf/201611904009
Published online 07 June 2016
  1. Bacmeister, J. T, and G. L. Stephens (2011), Spatial statistics of likely convective clouds in CloudSat data, J. Geophys. Res., 116, D04104, doi:10.1029/2010JD014444 [CrossRef] [Google Scholar]
  2. Chen, S. S, and R. A. Houze Jr., 1997: Diurnal variation and lifecycle of deep convective systems over the Pacific warm pool. Quart. J. Roy. Meteor. Soc.,123, 357–388. [CrossRef] [Google Scholar]
  3. Chou C. J. D. Neelin (1999) Cirrus detrainment-temperature feedback. Geophysical Research Letter, 26, 1295-1298. [CrossRef] [Google Scholar]
  4. Cetrone J. and R. A. Houze Jr. 2009: anvil clouds of tropical mesoscale convective systems in monsoon regions. Quart. J. Roy. Meteor. Soc.135: 305–317 [CrossRef] [Google Scholar]
  5. Deng, M., G. G. Mace, Z. Wang, and H. Okamoto, 2010: Tropical Composition, Cloud and Climate Coupling Experiment validation for cirrus cloud profiling retrieval using CloudSat radar and CALIPSO lidar, J. Geophys. Res., 115, D00J15, doi:10.1029/2009JD013104 (6) [CrossRef] [Google Scholar]
  6. Futyan J, Del Genio A. 2007. Deep convective system evolution over Africa and the tropical Atlantic., J. Clim 20: 5041–5060 [CrossRef] [Google Scholar]
  7. Fu, R., A. D. Del Genio, and B. Rossow, 1990: Behavior of deep convective clouds in the tropical Pacific deduced from IPSSP radiance, J. Clim, 3, 1129-1152. 1990. [CrossRef] [Google Scholar]
  8. Gamache, J. F, and R. A. Houze (1983), Water budget of a mesoscale convective system in the tropics, J. Atmos. Sci., 40(7), 1835 – 1850. [CrossRef] [Google Scholar]
  9. Hartmann, D. L, M. E. Ockert-Bell, and M. L. Michelsen (1992), The effect of cloud type on Earth’s energy balance: Global analysis, J. Clim., 5, 1281 – 1304. [CrossRef] [Google Scholar]
  10. Houze, R. A, Jr., 1977: Structure and dynamics of a tropical squall line system observed during GATE. Mon. Wea. Rev., 105, 1540–1567. [CrossRef] [Google Scholar]
  11. Houze, R. A, Jr., 2004: Mesoscale convective systems. Rev. Geophys., 42, 43 [CrossRef] [Google Scholar]
  12. Johnson R. H. T. M. Rickenbach. S. A. Rutledge, P. E. Ciesieski, and W. H. Schubert, 1999: Trimodal characteristics of Tropical convection. J. Clim, 12, 2397- 2418. [CrossRef] [Google Scholar]
  13. Klein S. and C. Jakob 1999 Validation and sensitivities of frontal clouds simulated by the ECMWF model. Monthly weather review, 127, 2514-2531 [CrossRef] [Google Scholar]
  14. Klein, S. A, Y. Zhang, M. D. Zelinka, R. Pincus, J. Boyle,and P. J. Gleckler (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. [CrossRef] [Google Scholar]
  15. Leary, C. A, and R. A. Houze (1979), Melting and evaporation of hydrometeors in precipitation from the anvil clouds of deep tropical convection, J. Atmos. Sci., 36(4), 669 – 679 [CrossRef] [Google Scholar]
  16. Liu, C. T, E. J. Zipser, D. J. Cecil, S. W. Nesbitt, and S. Sherwood, 2008: A cloud and precipitation feature database from nine years of TRMM observations. J. Appl. Meteor. Climatol.,47, 2712–2728. [CrossRef] [Google Scholar]
  17. Lindzen, R. S, M.-D. Chou, and A. Y. Hou (2002), Comments on “No evidence for iris”, Bull. Am. Meteorol. Soc., 83, 1345 – 1348. [CrossRef] [Google Scholar]
  18. Maddox RA. 1980. Mesoscale convective complexes. Bull. Am. Meteorol. Soc. 61: 1374–1387. [CrossRef] [Google Scholar]
  19. Machado, L. A. T., and W. B. Rossow, Structural characteristics and radiative properties of tropical cloud clusters, Mon. Weather Rev., 121, 3234–3260, 1993. [CrossRef] [Google Scholar]
  20. Mapes, B. E, and P. Zuidema, 1996: Radiative-dynamical consequences of dry tongues in the tropical troposphere. J. Atmos.Sci., 53,620–638. [CrossRef] [Google Scholar]
  21. Mace GG, Deng M, Soden B, Zipser E. 2006. Association of tropical cirrus in the 10–15-km layer with deep convective sources: An observational study combining millimeter radar data and satellite derived trajectories. J. Atmos. Sci. 63: 480–503. [CrossRef] [Google Scholar]
  22. Mullendore, G. L, A. J. Homann, K. Bevers, and C. Schumacher (2009), Radar reflectivity as a proxy for convective mass transport, J. Geophys. Res., 114, D16103, doi:10.1029/2008JD0114 [CrossRef] [Google Scholar]
  23. Nesbittt S. W. E. Zipser, 2002: the diurnal cycle of rainfall and connective intensity according to three years of TRMM measurement. , J. Clim, 16, 1456-1475 [CrossRef] [Google Scholar]
  24. Pfister, L., et al., Aircraft observations of thin cirrus clouds near the tropical tropopause, J. Geophys. Res., 106, 9765 – 9786, 2001. [CrossRef] [Google Scholar]
  25. Ramanathan, V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, Cloud-radiative forcing and climate: results from the earth radiation budget experiment, Science 243, 57-63, 1989 [CrossRef] [PubMed] [Google Scholar]
  26. Stephens, G. L. (2005), Cloud feedbacks in the climate system: A critical review, J. Clim., 18, 237 – 273 [CrossRef] [Google Scholar]
  27. Yuan J. and R. A. Houze Jr. 2010: Global variability of mesoscale convective system anvil structure from A-train satellite data , J. Clim, 23, 5864–5888 [CrossRef] [Google Scholar]
  28. Yuan J. and R. A. Houze Jr. 2011: vertical structure of anvil clouds of tropical mesoscale convective systems observed by CloudSat. J. Atmos. Sci. 68, 1653–1674. [CrossRef] [Google Scholar]
  29. Yuan J. and R. A. Houze Jr. 2013: Deep convective systems observed by A-Train in the tropical Indo-Pacific regions affected by the MJO. J. Atmos. Sci. 70, 465–486 [CrossRef] [Google Scholar]
  30. Zipser, E. J, 1969: The role of organized unsaturated downdrafts in the structure and rapid decay of an equatorial disturbance. J. Appl. Meteor., 8,799–814 [CrossRef] [Google Scholar]

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