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Investigation of Earth radiation budget variability by cloud object analysis

Investigation of Earth radiation budget variability by cloud object analysis. Seiji Kato 1 , Kuan-Man Xu 1 , Takmeng Wong 1 , Patrick C. Taylor 1 , Tristan S. L’Ecuyer 2 , Shengtao Dong 3 , Jenny Chen 3 , Sunny Sun-Mack 3 , Fred Rose 3 , Walter Miller 3 , and Yan Chen 3

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Investigation of Earth radiation budget variability by cloud object analysis

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  1. Investigation of Earth radiation budget variability by cloud objectanalysis Seiji Kato1, Kuan-Man Xu1, Takmeng Wong1, Patrick C. Taylor1, Tristan S. L’Ecuyer2, Shengtao Dong3, Jenny Chen3, Sunny Sun-Mack3, Fred Rose3, Walter Miller3, and Yan Chen3 1NASA Langley Research Center 2University of Wisconsin 3Science System & Applications Inc.

  2. CCCM product • Contains: • Merged CALIPSO, CloudSat derived clouds, CERES TOA radiative flux (SW, LW, and WN), MODIS (CERES_ST) derived cloud properties both along CALIPSO-CloudSat ground-track and over the whole CERES footprint, • MODIS derived cloud properties by an enhanced cloud algorithm, • CALIPSO and MODIS derived aerosol properties • Vertical radiative flux profiles computed with CALIPSO, CloudSat, and MODIS derived cloud properties. • 57 months of data (July 2006 through April 2011) are available from http://eosweb.larc.nasa.gov/PRODOCS/ceres-news/table_ceres-news.html

  3. Objectives and Scientific questions • Understand radiation budget variability caused by clouds • Reduces the uncertainty of cloud object analysis by CALIPSO and CloudSat observations • How is the frequency of occurrence of cloud objects perturbation related to the variability of TOA radiation budget? • How do cloud properties within cloud objects change with dynamical state or sea surface temperature?

  4. Cloud objects • A cloud object is a contiguous patch of cloudy regions with a single dominant cloud-system type, shifting from Eulerian to Lagrangian views of cloud systems • The shape and size of a cloud object is determined by the satellite footprintdata and by the footprint selection criteria for a given cloud-system type

  5. Extended cloud object type

  6. Cloud Objects Numbers (CCCM Matched) 1: cloud fraction 0.1 to 0.4(Trade/shallow cumulus) 2: cloud fraction 0.4 to 0.99 (Transition stratocumulus) 3: cloud fraction great than 0.99 (Solid stratus) a: size of 100 km to 150 km b: 150 to 300 km c: great than 300 km.

  7. TOA net radiative flux variability Kato 2009 J. Climate

  8. Cloud macroscopic property difference due to Positive MEI versus negative MEI • Separate cloud properties derived from MODIS or CALIPSO/CloudSat by MEI index • Cloud type: SC3c • Positive MEI: 200608 (0.759), 200609 (0.793), 200610 (0.892), 200611 (1.292) • Negative MEI: 200808 (-0.266), 200809 ( -0.643), 200810 (-0.78) 200811 (-0.621)

  9. Cloud fraction derived from CALIPSO and CloudSat Positive MEI Negative MEI

  10. Cloud top height derived from CALIPSO and CloudSat Positive MEI Negative MEI km km

  11. Cloud base height derived from CALIPSO and CloudSat Positive MEI Negative MEI km km

  12. Cloud top comparison CALIPSO/CloudSat Proportional to counts Red: Positive MEI Blue: Negative MEI

  13. Precipitationdifference of the fraction of precipitating clouds Positive - Negative

  14. Initial task timeframe (tentative) • January-May 2013: Cloud object subletting from SSF and CCCM • April-July/2013: Initial analysis of cloud objects, comparison with previous results (Xu et al. 2007, 2006, 2007, 2008) • Aug. – Dec./2013: Initial analysis of active sensor derived cloud properties • Jan-Sep/2014: Understanding relationship between cloud objects and radiation variability.

  15. Cloud profile difference Height (km) Uppermost cloud top height (km) Positive – Negative MEI

  16. T and RH difference (positive – negative MEI) Height (km) Uppermost cloud top height (km)

  17. Reflected Solar Radiation -100 Incoming Solar Radiation 340 Outgoing LW Radiation -240 TOA Imbalance 0.5 Reflected from Cloudy Regions -79 Reflected from Clear Regions -21 -136 Emitted from Cloudy Regions 221 Absorbed by Atmosphere 77 Atmosphere LW cooling -186 Emitted from Clear Regions -104 Emitted from Clear Regions 123 Reflected by Atmosphere Latent Heat -88 Sensible Heat -21 Absorbed at Surface 163 Surface Emission -398 Absorbed at Surface 344 Reflected at Surface -24 Surface Imbalance 0.5 Radiative Effect of Clouds SW LW NET TOA -47 26 -21 ATM 4 -4 0 SFC -51 30 -21 Earth’s Energy Budget

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