CALIPSO Version 3 Data Products: Additions and Improvements
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1 CALIPSO Version 3 Data Products: Additions and Improvements Dave Winker and the CALIPSO team CALIPSO/CloudSat Science Team Meeting July, Madison, WI 1
2 Version 3 Status Version 3 algorithms now used for Level 1 forward processing Starting from turn-on of CALIOP backup laser Reprocessing with Version 3 Level 1 to begin soon All mission data to be reprocessed, from 7 June 2006 Version 3 algorithms for Level 2 processing in final testing Profile products restructured Numerous algorithm improvements Significant bugs fixed All mission data to be reprocessed, probably from 13 June
3 Version 3 Data Products: Level 1 Level 1 data processed using Version 3 algorithms since March 2009 Calibration improvements Goal for calibration uncertainty, radiometric stability: 5% Improved 532 nm daytime calibration > 30 km Rayleigh calibration can only be done at night > Daytime uncertainties improved from 10% to 5% > Stratospheric aerosol biases not yet corrected 1064 nm calibration: significant biases remain > Initial approach using cirrus targets determined to be unreliable > Investigating new approaches (sea surface, etc.) 3
4 Improved daytime 532 calibration Version 3 daytime calibration Version 2 daytime calibration Version 1 daytime calibration (using previous nighttime mean calibration) 8-12 km, clear-air attenuated scattering ratios: 4
5 1064: calibration biases remain from cirrus backscatter: X 1064 /X 532 from ocean surface backscatter: X 532 /X Latitude Magnitude and details of biases are seasonally dependent 5
6 Version 3 Data Products: Level 2 New parameters added Aerosol and cloud profile products restructured and improved Aerosol now reported at 5 km Many added parameters Data quality flags now included Algorithm Improvements: Revised strategy for extinction retrievals boundary layer aerosol, constrained cirrus retrievals 1064 nm lidar ratio for dust changed from 30 to 50 New cloud ice/water phase algorithm Several significant bug fixes 6
7 Added Level 2 Parameters Column optical depth in aerosol and cloud layer and profile products Shape parameter (ice clouds) Classification of ice habit: plate-like, column-like, irregular, and oriented Based on algorithm of Noel (2002, 2004, 2006) Cloud-fraction parameter added to 5-km layer and profile products Orbit and path numbers Cloud base, mid, top pressure Cloud base and top temperature Uncertainties now provided for most parameters 7
8 Added Parameters: χ p χ p vs IAB χ vs IAB 8
9 Added Parameters: δ p δ p vs IAB δ p vs δ V 9
10 Added parameters: IWP, IWC Cloud profile product: Ice Water Content Cloud layer product: Ice Water Path g/m 3 10
11 Restructured Profile Products Version 2: Profiles of aerosol and cloud 532 and 1064 extinction and backscatter only Cloud profiles reported at 5 km Aerosol profiles averaged to 40 km Both aerosol and cloud profiles now reported at 5-km horizontal resolution Still retrieved at km Added profiles: 532 nm perpendicular backscatter and particle depolarization Atmospheric Volume Description (cloud/aerosol/clear etc.) Cloud fraction within the 5-km horizontal grid Backscatter and extinction uncertainties Added column parameters: Column optical depth: cloud, aerosol, stratosphere Column integrated attenuated backscatter (IAB) Added data quality information CAD score Ext_QC flag Feature type QA flags 11
12 Algorithm Improvements Revisions to constrained extinction retrieval strategy Version 2: constrained retrievals not applied to any cloud or aerosol layer detected on more than one pass through the detection loop This requirement relaxed in Version 3: more constrained retrievals, primarily for nighttime cirrus Revised retrievals of boundary layer aerosol Version 2: extinction only retrieved within detected layers Version 3: extinction retrieved from top of lowest aerosol layer to the surface 1064 nm lidar ratio for dust changed from 30 sr to 50 sr With the revised boundary layer retrieval strategy, will increase column AOD in dust regions New ice-water phase algorithm 12
13 Revised boundary layer aerosol retrieval 532 nm Attenuated Backscatter HSRL V3-alpha V nm Attenuated Backscatter Vertical Feature Mask 13
14 New Ice-Water Phase Algorithm Oriented crystals HOI water water ROI random ice IAB δ (Yong Hu, et al., Optics Express, 2007) (Yong Hu, et al., JTech, 2009) 14
15 Reduced artifacts in cloud ice-water phase Oriented ice now properly classified (HOI water in V2) Version 2.01 Version 3 Number of ice clouds with tops below 3.25 km 15
16 Zonal fractions: ice cloud water cloud V3 (Aug) V2 (Jan) 16 16
17 Bug Fixes Surface detection more reliable, especially in 1/3 km product Bugs in surface detection algorithms caused low marine clouds to be sometimes classified as ocean surface Other times, surface detections were underreported Handling of multiple scattering corrected Version 2: multiple scattering corrections applied incorrectly to constrained retrievals (4% of cirrus in Version 2) Multiple scattering corrections not propagated to lower layers Clearing of boundary layer cloud Fix has biggest impacts in marine trade cumulus regions 17
18 Bug in boundary layer cloud clearing In Version 2, clouds below 4 km not cleared properly Cloud-contaminated aerosol classified as cloud Cloud-clearing scheme fixed in Version 3 18
19 CALIPSO layer detection scheme Remove Clouds from boundary layerat single shot resolution Use Profile Scanning Engine to locate features at 1-km and 1/3-km High Resolution Cl ou d Cl ea r i n g Average Data in troposphere to 1-km horizontal resolution NO Boundary layer cleared? YES layer detection algorithm applies a special cloudclearing scheme below 4 km to retrieve boundary layer aerosol Average Data to horizontal resolution K Use Profile Scanning Engine to locate features at resolution K K = 1? Set K = K+1 M ulti-resolution Layer Detection NO YES Remove Layers Apply Attenuation Correction NO K = N? YES Write Level II Data Products 19
20 Trade cumulus scene V2.01 cloud aerosol V3 (correct) 20 20
21 Improved low-cloud statistics Version 2.01 Global mean cover of singlelayer low cloud reduced from 26.1% to 21.8% Regional reductions as much as a factor of 5. Version 3-alpha test 21
22 ISCCP vs. CALIPSO ISCCP (25.1%) CALIPSO (24.0%) Low clouds (Single-layer low clouds, except high clouds with OD < 3 ignored) June-August
23 Next steps Further improvements to calibration Use multiple consistency checks to improve 1064 nm calibration Improve aerosol AOD/extinction retrievals using ocean surface returns accurate AOD/cloud screening on single shots no microphysical assumptions Standard CALIPSO AOD vs. MODIS AOD from ocean sfc returns (D. Josset) 23
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