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EG-CLIMET (ES0702) Blind Test: Liquid Water Cloud retrieval activity

EG-CLIMET (ES0702) Blind Test: Liquid Water Cloud retrieval activity. Background…. Generate uwave, lidar and radar signals based on `realistic’ model cases. Supply simulated signals to different groups. Apply retrieval algorithms Compare results to `truth’.

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EG-CLIMET (ES0702) Blind Test: Liquid Water Cloud retrieval activity

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  1. EG-CLIMET (ES0702)Blind Test: Liquid Water Cloud retrieval activity

  2. Background… • Generate uwave, lidar and radar signals based on `realistic’ model cases. • Supply simulated signals to different groups. • Apply retrieval algorithms • Compare results to `truth’ • Modified form of the EarthCARE simulator (ECSIM) was used to produce the signals. • Two simulated cases were used (all that time allowed) First a few words about ECSIM…..

  3. The EarthCARE Simulator D.Donovan1, G-J van Zadellhoff1, R. Voors1, P.Baptista2, H. Barker3, A. Bealune4, J-P Blanchet4, M. Quante5, N. Schutgens1, J.Testud6, W. Szyrmer4J-R Acareta9, J-J, R-Perez9, R. Moyano9R. Franco2 , D. Lajas2, M. Essigner2withinput from. J. Cole7, S. Kato8 1-KNMI the Netherlands 2-ESA/ESTEC the Netherlands 3-MSC, Canada 4-UQAM, Canada 5-GKSS, Germany 6-CETP/IPSL France. 7-Penn State, USA 8-NASA langely USA 9-DEIMOS Space, Madrid, Spain

  4. Forward model(s) Model Atmosphere Synthetic observations Compare Inversions

  5. Lidar MC code Radar simulator LW MC code SW MC code

  6. The simulator can ingest varied data steams in a consistent manner Modular unified approach

  7. CASE-I: LES simulation corresponding to FIRE conditions No microphysics in the simulation (LWC) only. No was fixed externally

  8. Brandau V1 (LWP used but NOT RETRIEVED)

  9. v1 v1 v2 v2 v2 v3 v3

  10. SYRSOC: Derives Lidar extinction for use in the retrievals. But I do not know how ? LWP is also used but NOT DERIVIED

  11. Clean Results

  12. Polluted Results

  13. IPT: LWP is retrieved True LWP=F(Bt) Lin Chilbolton LWP=F(Bt) Quad from Ulli

  14. CASE-II: Output from UQAM CCCM: Bin microphysics Cloud resolving model Conditions corresponding to ASTEX-1 Campaign

  15. Brandau V1 (LWP used but NOT RETRIEVED)

  16. V1 V1 V2 V2 V3 V3

  17. CLEAN

  18. Polluted

  19. Fire ASTEX Baedi et al 1999 CAMEX-3/CLARE98 Fox Illingworth 1997 Perhaps the IPT is using the “wrong” LWC-Ze relationship or underestimating the errors.

  20. No Radar

  21. Discussion…. • More questions than answers at this stage…. • Re. IPT • Clearly IPT (and NN ?) were better than statistical inversions for LWP. • LWC retrieved no too badly • Reff….not well retrieved • Adding Radar can make results worse….this may be consistent with CABAUW results Re. Brandau results. 1) If good LWP then reasonable results can be obtained…v1, v2 or v3 ? • Re: Syrsoc: • I do not understand the lidar ext retrieval. • Little difference between Clean and Polluted rets. (is this expected ?) • Needs good LWP measurement.

  22. Features 3-D Monte Carlo Radiative transfer codes used for Passive instrument simulations. 3-D Monte Carlo simulation of Lidar returns. Realistic Noise levels calculated via instrument parameters All instrument treated in a consistent fashion. Crude instrument specific parameterizations have been avoided. Both simple user defined scenes can be treated as well as complex scenes derived from cloud resolving model data.

  23. Current Scientific architecture Scene Scattering libraries Orbit Lidar RT Radar RT SW RT LW RT Lidar Radar MSI BBR Lidar L2a - Extinction profile - Targe mask Etc... Radar L2a - IWC profile - Target mask Etc... MSI L2a - Optical thickness - Effective radius Etc... Closure Lidar+Radar L2b - Reff profiles - Target mask Etc... Lidar+Radar+LW MSI L2b-3D Scene reconstruction algorithm Computed BB radiances + fluxes

  24. Extinction MSI 8.6 um cirrus stratus aerosol Lidar + Radar cirrus Ze stratus aerosol Mission Performance EarthCARE Simulator - Example atmospheric scene stratus cirrus Reff

  25. Extinction MSI 0.6 um cirrus stratus aerosol Lidar + Radar cirrus Ze stratus aerosol Mission Performance EarthCARE Simulator - Exampleatmospheric scene cirrus stratus Reff

  26. Example using ECSIM scene derived from LES model data with an added uniform BL aerosol field

  27. Mie signal Rayleigh signal Aircraft at 10 km Ecare at 450 km

  28. What is needed to build a scene ? • 3-D Field of T,P,Rho • 3-D Field of size-dist parameters. • 3-D Extinction or Mass field • Appropriate Scattering Libraries. Note: 3-D can be faked….2D + same in cross-track direction: This is what will likely be done for Campaign tracks

  29. 1,4,4,5 num_modes, nx, ny, nz -------- 0.0,2.0,4.0,6.0 x(1),x(2)....x(nx) -------- 0.0,2.0,4.0,6.0 y(1),y(2)....y(ny) -------- 4.0,5.0,6.0,7.0,8.0 z(1),z(2)....z(nz) -------- 0.0,1000.0 Min Size, Max. Size -----ix=1,iy=1--- 0.0,0.0,0.0 Mass-density (g/m3) OR Extinction 1/m, g1, Reff for x(1),y(1),z(1) 0.0,0.0,0.0 etc.. 0.0,0.0,0.0 0.0,0.0,0.0 0.0,0.0,0.0 -----ix=1,iy=2--- 0.0,0.0,0.0 0.0,0.0,0.0 0.0,0.0,0.0 0.0,0.0,0.0 0.0,0.0,0.0 . . . 0.0,0.0,0.0 0.0,0.0,0.0 0.0,0.0,0.0 0.0,0.0,0.0 0.0,0.0,0.0 -----ix=2,iy=2--- 0.0,0.0,0.0 0.0,0.0,0.0 0.001,3.0,100.0 0.001,3.0,100.0 0.0,0.0,0.0 . . . Example size dist file Similar format for T,P,Rho data ! NetCDF equivalents also exist for 3-D data As well as for Bin-Resolved Size dist data !

  30. <list> <name>DRY_Soot</name> <type>1</type> <n_files>166</n_files> <n_temps>1</n_temps> <n_rel_hum>1</n_rel_hum> <n_wavel>166</n_wavel> <!-- Radar file(s) --> <name_rad>NULL</name_rad> <n_rad_temp> 1 </n_rad_temp> <n_rad_wavel> 1 </n_rad_wavel> <!-- Number of size bins to extrpolate (intepolate) to --> <n_size_bins>30</n_size_bins> <!-- wavelen[mic],t[K],rh[%],file --> <data_info> <var> <wavel>00.200</wavel> <temp>-99.0</temp> <rh>-99.0</rh> <file>./data_files/gen_aerosol/Soot_00p200.dat</file> </var> <var> <wavel>00.250</wavel> <temp>-99.0</temp> <rh>-99.0</rh> <file>./data_files/gen_aerosol/Soot_00p250.dat</file> </var> …… …… </data_info> <!-- Radar info --> <!-- wavlength [mm], t[k] Filename --> <radar_info> <var> <wavel>3.19</wavel> <temp>-99.0</temp> <file>./data_files/null</file> </var> </radar_info> <!-- size grid to interpolate things to For both RT and DDA calculations (data are bin-mid-points) --> <size_grid> <var> 0.01000</var> <var> 0.01269</var> <var> 0.01610</var> …… </size_grid> </list> Example scattering master file in XML format

  31. Example Scattering data file 1.55000 (Wavelength [micron]) 1.29100 0.000485000 (Refr. Index: Real and Imaginary part) 7 (number of radii [in case of non-spherical particles: half the maximum size]) 237 (number of scattering angles) -------------- (Radius, Volume, X-section, Total Extinction, Absorption um^2) 30.0000 5261.10 494.784 984.000 33.7800 -------------- (Scattering angle [degrees], P11,P22/P11, P33/P11, P44/P11, P12/P11, P34/P11) 0.0000 2.57500000e+03 0.9992 0.9993 0.9985 0.0005 0.0002 0.0050 2.51500000e+03 0.9992 0.9992 0.9984 0.0006 0.0002 0.0100 2.45600000e+03 0.9992 0.9992 0.9984 0.0006 0.0002 0.0150 2.39900000e+03 0.9992 0.9992 0.9984 0.0007 0.0002 0.0200 2.34300000e+03 0.9991 0.9992 0.9983 0.0007 0.0002 0.0250 2.28800000e+03 0.9991 0.9991 0.9983 0.0008 0.0002 ……. ……. …….

  32. Space-Craft and Aircraft Simulated observations using ECSIM Contains entire 3-D atmospheric state info Scene Rad transfer `Orbit’ data Instrument model L1 Data

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