1 An initial CALIPSO cloud climatology ISCCP Anniversary, 23-25 July 2008, New York Dave Winker NASA LaRC.

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Presentation transcript:

1 An initial CALIPSO cloud climatology ISCCP Anniversary, July 2008, New York Dave Winker NASA LaRC

2 Merged CALIPSO-CloudSat product now available CloudSat Merged CALIOP

3 CALIPSO vs. GEWEX CA Cloud cover, height - CALIOP Cloud temperature –Mid-cloud temperature (from CALIOP height and GMAO) –Brightness temperature (from CALIOP + IIR) Optical depth, extinction profile –‘Thin’ cirrus only,  < 3 to 5 –From CALIOP transmittance (good, 4%) –From CALIOP retrieval (not as good, 96%) Emissivity – CALIOP + IIR Ice/Water phase – CALIOP depolarization LWC/IWC – parameterized from CALIOP extinction Particle size –Cirrus only – CALIOP + IIR –CloudSat + CALIOP (overlap regions only) Available now Available, but Beta (near) future Not available

4 clouds aerosol Sampling resolution:  z = 30 m footprint = 70 m dia. footprint separation = 335 m Altitude location error << 30 m  ~ 0.02 Cloud detection is weakly dependent on calibration surface

5 Arctic Stratus, full resolution (30 m, single shots) 600 m

6 Temporal Averaging (high clouds) one month one season

7 Cloud Fraction Analysis Merge clouds in 1/3-km and 5-km products –1/3-km clouds are cleared from 5-km profiles during processing Use only layers with CAD score –Layers with CAD = < 70 (especially 0-20) tend to be “spurious” >Affects cloud fraction at the 1% level –101 = thin polar cirrus originally classified as aerosol, reclassified based on depolarization –102 = cloud dominated by horizontally oriented ice crystals Reclassify “aerosol” over Antarctic plateau as cloud –Increases Antarctic cloud fraction by ~ 5% Reject PSCs mistakenly classified as tropospheric cloud –Ambiguous GMAO tropopause results in misclassifications

8 Total Cloud Cover JJA 78.8% DJF 76.5% JJA 63.5% DJF 65.6% CALIPSO ISCCP

9 Profile of Cloud Frequency Black -> All Layers Detected, Red -> Highest layer only Tropics 30N - 60N

10 High Clouds - SON ISCCP (2005)CALIOP (2006)

11 High Opaque Clouds - SON CALIPSO ISCCP (IR clouds) ISCCP CALIOP

12 High clouds, diurnal difference – Jan 2007 night day

13 Cloud layer-average backscatter (V2.01) Night Day 5-km avg 80-km avg Histograms of layer- average cloud backscatter for 5-km and 80-km layers July 1-7, E-4/km/sr 3E-3/km/sr 2E-3/km/sr 6E-4/km/sr  min ~  min ~  min ~  min ~  min estimated from distribution of layer IAB

14 Middle Clouds - SON CALIPSO ISCCP (IR clouds) ISCCP (2005) CALIOP (2006)

15 Low Clouds - JJA ISCCP: 25.2% CALIPSO: 49.4% CALIPSO, single-layer low cloud: 27.5%

16 Sensitivity to layers underneath thin clouds (night) weaker layers disappear as overlying layer becomes optically thicker Stratus detectable underneath clouds of optical depth ~ 5 Aerosols detectable underneath clouds of optical depth 1-2

17 8 July, 1200Z 532 nm 1064 nm

18 Cloud layer-average backscatter distributions (V2.01) Night Day Histograms of layer-average cloud backscatter for single-shot clouds, July 1-7, E-2/km/sr 1E-2/km/sr  min ~ 0.17  min ~ 0.1

19 Antarctica All cloud Opaque cloud winter (JJA) summer (DJF)

20 15 June 2006 Antarctic winter

21 Annual cycle of polar cloud, 60S – 82S land only all cloud high cloud

22 Profile of Cloud Frequency: Antarctica Black -> All Layers, Red -> Highest layer only Summer Winter

23 CALIPSO Is Providing A Wealth of Information on Polar Stratospheric Clouds Extensive measurement coverage over polar regions into polar night

24 Annual cycle: global total cloud CALIPSO ISCCP* TOVS-B* HIRS* Global annual mean (%) RMS difference (%) *

25 Zonal fraction of ice and water Ice/water determination is based on depolarization signature

26 Fraction of Ice and Water Cloud Cloud Fraction = Cloud (all, ice, or water) / # of Samples Cloud Fraction = Cloud (ice or water) / Cloud (all) Cloud, Ice Cloud, Water Cloud Tropics NH mid- latitudes misclassifications likely

27 CALIPSO-CERES collaboration Surface and atmospheric fluxes estimated from: Cloud profiles: CALIPSO, CloudSat Cloud/aerosol properties: CALIPSO, CloudSat, MODIS TOA radiances: CERES

28 Flux Profiles: first example

29 Next Steps Complete evaluation of cloud statistics for GEWEX assessement Development and distribution of Level 3 cloud product Improve cirrus optical depth, ice/water classification –Cloud fraction as a function of cloud optical depth –Cloud fraction by cloud type Characterize uncertainties due to sparse spatial sampling Climatologies of other cloud properties ( , etc) Coordinate with CALIPSO simulator group at LMD