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title. CALIPSO* and the A-Train: Spaceborne lidar for global aerosol/cloud/climate assessment. Qiang Fu Department of Atmospheric Sciences University of Washington. *Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations. title. Outline. 1. overview of capabilities

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  1. title CALIPSO* and the A-Train: Spaceborne lidar for global aerosol/cloud/climate assessment Qiang Fu Department of Atmospheric Sciences University of Washington *Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations

  2. title Outline 1. overview of capabilities 2. technical challenges 3. validation 4. science applications

  3. CALIPSO Adds the 3rd Dimension to MODIS Observations

  4. Major Saharan Dust Transport Event: Aug 17-28 (courtesy of Dave Winker, P.I.) Aug 17 Aug 18 Aug 19 Aug 20 Aug 21 Aug 25 Aug 22 5 km Aug 28 Aug 23

  5. Part 1 Capabilities

  6. The atrain thick clouds drizzle aerosol profiles, cloud tops polarization, multi-angle composition, chemistry, dynamics CERES: TOA fluxes MODIS: cloud re, t AMSR: LWP O2 A-band

  7. 705 km, sun-synchronous orbit Three co-aligned instruments: CALIOP: polarization lidar IIR: Imaging IR radiometer WFC: Wide-Field Camera CALIPSO: a NASA-CNES collaboration Launch: 28 April 2006

  8. Payload Specifications CALIOP Wide Field Camera Wide-Field Camera (WFC) Imaging Infrared Radiometer (IIR) Imaging Infrared Radiometer Lidar Transmitter

  9. Improve understanding aerosol/cloud forcings and feedbacks by providing: aerosol profiles over all surfaces, day and night cloud profiles of thin clouds and multi-layer cloud structures layer identification: cloud water phase cirrus particle size aerosol type test, refine, and complement other A-Train instruments CALIPSO Science Objectives

  10. CALIPSO Data Products Cloud-Aerosol Mask Cloud Phase Level 1: 532 nm total atten. backscatter Aerosol Subtypes (courtesy of Dave Winker, P.I.)

  11. Part 2 Technical Challenges

  12. CALIOP and GLAS Trends (courtesy of Dave Winker, NASA Langley)

  13. Analog detection 532 nm: PMT’s 1064 nm: APD 22-bit dynamic range Active boresight adjustment Lidar Calibration Calibration: - 532║ – normalization of molecular return night, clean upper stratosphere - 532┴ – relative to 532║ using on-board cal H/W - 1064 – relative to 532║ using cirrus backscatter

  14. Calibration Error: Cause and Effect (courtesy of Mark Vaughan, NASA Langley) Level 1 Attenuated Backscatter Coefficients 532 nm Calibration Coefficients 2 August 2006

  15. NIGHT DAY NIGHT Proposal: A Revised Calibration Procedure (courtesy of Mark Vaughan, NASA Langley) Polynomial approximation Interpolation between end-points of successive night segments

  16. CALIPSO obs. of strat. aerosols assessment Polynomial approximation Interpolation between end-points of successive night segments Thomason, Pitts, and Winker (2007)

  17. Altitude Error (courtesy of Bill Hunt, NASA Langley) Speed of light (in retrieval algorithm): • Old value: c = 3.00E8 m/sec • New value: c = 2.99792458E8 m/sec ?

  18. Part 3 Validation

  19. Ground-based lidar stations (courtesy of Anne Garnier, Laplace Institute)

  20. Ground-based lidar stations (courtesy of Anne Garnier, Laplace Institute)

  21. VIS CPL CRS MAS The CC-VEX Field Campaign (courtesy of Matt McGill, NASA GSFC) • Dedicated to CALIPSO-CloudSat validation. • July 26 - Aug 14, based in Warner-Robbins, GA. • Total of 13 underflights, with varying scenes. • Payload: Cloud Physics Lidar (CPL), • Cloud Radar System (CRS), • MODIS Airborne Simulator (MAS), • Visible camera (VIS). dateoffset 13Jul TBD 26Jul TBD 28Jul TBD 30Jul 611 m 31Jul 566 m 02Aug 1251 m 03Aug 1317 m 08Aug 61 m 10Aug 170 m 11Aug 498 m 12Aug 36 m 13Aug 1716 m 14Aug TBD

  22. CPL -vs- CALIPSO: the similarities and differences (courtesy of Matt McGill, NASA GSFC) Similarities: both are backscatter lidar --> use apples to validate apples both are above the atmosphere --> see the entire column both have dual wavelength and depolarization Differences: repetition rate: vertical resolution: platform speed: detection: footprint at surface: Resulting caveats: imperfect collocation --> instruments see different scenes advection of atmosphere --> true coincidence is instantaneous CPL 5 kHz 30 m ~200 m/s photon counting 2 m dia. CALIPSO 20.25 Hz 60 m ~7500 m/s analog 88 m dia.

  23. 15 15 10 10 Altitude (km) 5 5 0 0 km-1 sr-1 10-1 10-1 Altitude (km) 10-2 10-2 10-3 10-3 km-1 sr-1 36 36 39 39 37 37 38 38 latitude 11Aug06: 1064 nm Calibrated Attenuated Backscatter (courtesy of Matt McGill, NASA GSFC) Coincident at 08:00:00 UTC (37.2423, -87.8275)

  24. 532 nm 1064 nm 20 20 15 15 Altitude (km) Altitude (km) 10 10 5 5 0 0 10-5 10-5 10-4 10-4 10-3 10-3 10-2 10-2 10-1 10-1 attenuated backscatter (km-1 sr-1) attenuated backscatter (km-1 sr-1) 11Aug06: Calibrated Attenuated Backscatter Comparison (courtesy of Matt McGill, NASA GSFC) blue = CPL black = CALIPSO blue = CPL black = CALIPSO CPL is 25 second average (5 km). CALIPSO data is 5 km average.

  25. Airborne High Spectral Resolution Lidar (HSRL) (courtesy of Chris Hostetler, NASA Langley)

  26. Airborne High Spectral Resolution Lidar (HSRL) (courtesy of Chris Hostetler, NASA Langley)

  27. Airborne High Spectral Resolution Lidar (HSRL) (courtesy of Chris Hostetler, NASA Langley)

  28. Part 4 Science Applications

  29. Combining CALIPSO and Cloudsat (courtesy of Dave Winker, P.I.) Clouds link the radiation budget and the hydrologic cycle CALIPSO (532 nm) Japan CloudSat

  30. Combining CALIPSO and CloudSat (courtesy of Dave Winker, P.I.) CALIPSO and CloudSat together provide the first reliable view of the full vertical structure of clouds over the globe (especially at night) Zonally averaged distribution of cloudiness CloudSat (July-Aug) CALIPSO (July)

  31. Aerosol Type Discrimination 532 nm Dust Smoke 1064 nm Depolarization ratio

  32. Using Water Clouds as a Lidar Target (courtesy of Y. Hu, NASA Langley) Similar to molecules, water clouds are well-understood objects 1. Lidar ratio, Sc, and single scattering property can be accurately computed from Mie theory Gustav Mie 2. Lidar multiple scattering can be well characterized through depolarization measurements (1. Hu et al, 2006, Optics Letters; 2. Hu et al, 2006, 23rd ILRC; ) d: depolarization ratio

  33. Using Water Clouds as a Lidar Target (courtesy of Y. Hu, NASA Langley)

  34. Using Water Clouds as a Lidar Target (courtesy of Y. Hu, NASA Langley) Verifying the simple relation between multiple scattering and depolarization

  35. Using Water Clouds as a Lidar Target (courtesy of Y. Hu, NASA Langley) Optical Depth of Aerosol above cloud Aerosol Layer Cloud

  36. In-situ Measurement Opportunity:Above-cloud single scatter albedo (SSA) Chemical Transport Model estimates (AEROCOM): - cloudy-sky DCF (direct climate forcing) virtually eliminates clear-sky DCF clear-sky: -0.7 W/m2 all-sky: -0.2 W/m2 - effect is entirely due to absorbing aerosol above low clouds - effect varies wildly among the different models (see figure) - there is essentially no empirical constraint! Prospects for empirical constraint: - satellite lidar (GLAS and now CALIPSO) will yield AOD above cloud - this information will be close to meaningless without knowing SSA - only in-situ methods can supply data on SSA

  37. Aerosol forcing in cloudy skies (AEROCOM) (courtesy of Michael Schulz) ISCCP low level cloud cover Schulz et al. 2006, Atmos Chem Phys Disc

  38. My Research Interests with CALIPSO CALIPSO’s capability to detect tropical thin cirrus and its vertical profile - identify the top of the TTL (Fu et al. 2007) - quantify cloud radiative forcing in the TTL - understand processes controlling TTL vertical transport and dehydration - Constrain cloud microphysics parameterizations used in both GCMs and CRMs CALIPSO’s capability to detect aerosol vertical profiles in both clear & cloudy sky: - aerosol direct radiative forcing in cloudy sky Dust aerosol (with JP Huang at LZU) Biomass burning aerosols (with Brian Magi at GFDL/Princeton) black carbon aerosols (with Terry Nakajima at CCSR?) Validations - thin cirrus (ARM TWP sites) - aerosol (LZU site with JP Huang)

  39. Tropical Tropopause Layer (TTL) • TTL is a transition region whose properties are intermediate between the troposphere and stratosphere, rather than a material surface (Highwood and Hoskins, 1998; Folkins et al, 1999). The base of TTL (~15 km): The level of zero net radiative heating rate It is more difficult to define the top of the TTL. A useful conceptual definition is that it is the height at which the upward convective mass flux becomes small in comparison to the B-D mass flux. Unfortunately, it is intrinsically difficult to diagnose the high altitude tail of the convective detrainment profile from observations(Folkins, 2006). Fueglistaler et al. (2007)

  40. Method

  41. SHADOZ data (temperature, O3, H2O) http://croc.gsfc.nasa.gov/shadoz 12 stations within -20S—20N from 1998 to 2005): 2244 profiles Thompson et al. (2003)

  42. Temperature & O3 profiles: Raw data

  43. Temperature & O3 & H2O profiles above ~10 mb T O3 ~3km ~3km Ptop radiosonde Ptop radiosonde Pbase Pbase UKMO HALOE Weight function: W=1- (lnPbase-lnP)/(lnPbase-lnPtop) Vartransition(P) =(1-W)*climate(P)+W*Varradiosonde(P) Climate: UKMO/HALOE

  44. Radiative heating rate profile (total mean) ρ T T ρ ~17km Qrad Qrad θ θ

  45. Identify the top of TTL Mean mass flux Top of TTL We define the top of the TTL as the level at which the vertical mass flux is less than 110% of the mean mass flux between 19 and 24 km.

  46. Validation with CALIPSO Lidar Cloud Obs. Fu et al. (2007)

  47. Validation with CALIPSO Lidar Cloud Obs. Fu et al. (2007)

  48. Validation with CALIPSO Lidar Cloud Obs. Fu et al. (2007)

  49. Dust Storm from CALIPSO over China

  50. Dust Storm from CALIPSO over China

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