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The combined use of MODIS, CALIPSO and OMI level 2 aerosol products for calculating direct aerosol radiative effects Jens Redemann, M. Vaughan, Y. Shinozuka,

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Presentation on theme: "The combined use of MODIS, CALIPSO and OMI level 2 aerosol products for calculating direct aerosol radiative effects Jens Redemann, M. Vaughan, Y. Shinozuka,"— Presentation transcript:

1 The combined use of MODIS, CALIPSO and OMI level 2 aerosol products for calculating direct aerosol radiative effects Jens Redemann, M. Vaughan, Y. Shinozuka, P. Russell, J. Livingston, A. Clarke, L. Remer, C. Hostetler, R. Ferrare, J. Hair, P. Pilewskie, S. Schmidt, E. Bierwirth BAERI – NASA Langley - NASA Ames – SRI – UHawaii - NASA Goddard - UColorado http://geo.arc.nasa.gov/AATS-website/ email: Jens.Redemann-1@nasa.govJens.Redemann-1@nasa.gov

2 Outline   Goal: To devise a new, methodology to derive direct aerosol radiative effects -  F aerosol (z) based on CALIOP, OMI and MODIS   Checking consistency of input data   Comparison of MODIS and CALIOP-derived AOD   Differences in CALIOP V2 and V3   Methodology for combining CALIOP, OMI and MODIS data   Sensitivity study using synthesized data   Horizontal variability considerations for comparing&combining satellite data sets and for extrapolating into data-sparse regions: see poster 190, Shinozuka   Aerosols above clouds: see poster 89, Kacenelenbogen   Proof of concept for actual data from October 2007   Conclusions

3 Observationally- based Model-based Motivation: Observation- and model-based estimates of direct aerosol radiatve forcing published in IPCC diverge # of Observationally- based  F< # of Model-based  F Mean of Observationally- based  F > Mean of Model-based  F Myhre, Science, July 10, 2009 Myhre: 1) 1)Observation-based methods too large 2) 2)Models show great divergence in regional and vertical distribution of DARF. 3) 3)“remaining uncertainty (in DARF) is probably related to the vertical profiles of the aerosols and their location in relation to clouds”.

4 Target:  F aerosol (z) +  F aerosol (z) Constraints/Input: - MODIS AOD (7/2 ) +  AOD - OMI AAOD (388 nm) +  AAOD - CALIPSO ext (532, 1064 nm) +  ext - CALIPSO back (532, 1064 nm) +  back Goal: To use A-Train aerosol obs to constrain aerosol radiative properties to calculate  F aerosol (z) Retrieval: ext (, z) +  ext ssa (, z) +  ssa g (, z) +  g MODIS aerosol models: 810 fine and 510 coarse mode distribution models define size and refractive indices of bi-modal log- normal size distribution → 20 80 100 combinations Free parameters: N fine, N coarse Issues to consider - Differences in data quality land/ocean - - Impact of model assumptions - - Spatial variability - - Aerosols above & near clouds Rtx code

5 Methodology: Bridging the clear sky – all sky gap Use suborbital observations to: 1) 1)Test retrievals of aerosol radiative properties 2) 2)Test calculated radiative fluxes 3) 3)Study spatial variability = uncertainty involved in going to data sparse regions (e.g., above clouds) See poster 89, Kacenelenbogen See poster 150, Shinozuka

6 MODIS Active fire detection CALIOP AOC occurrence (%) October 2007 Poster 89, Kacenelenbogen CALIOP AOC AOD 70 % of AOD in [0-0.1] 20 % of AOD in [0.1-0.2]

7 C.S. M c Naughton std rel = 19.4% std rel = 2.1% Horizontal variability of aerosol optical properties observed during the ARCTAS airborne experiment Shinozuka et al. Poster Asian outflow over AlaskaForest fire smoke over Canada

8 Target:  F aerosol (z) +  F aerosol (z) Constraints/Input: - MODIS AOD (7/2 ) +  AOD - OMI AAOD (388 nm) +  AAOD - CALIPSO ext (532, 1064 nm) +  ext - CALIPSO back (532, 1064 nm) +  back Part 2: Retrieval of aerosol radiative properties from A-Train observations - Methodology Retrieval: ext (, z) +  ext ssa (, z) +  ssa g (, z) +  g MODIS aerosol models: 810 fine and 510 coarse mode distribution models define size and refractive indices of bi-modal log-normal size distribution → 20 80 100 combinations Free parameters: N fine, N coarse Rtx code

9 Refractive Index of MODIS modes as a function of wavelength

10 Step 1: Each observable (here AOD 550nm) is consistent with a range of fine/coarse mode particle concentrations for a given fine/coarse mode combination (here fine#1/coarse#5)

11 Step 2: The totality of all observables is consistent with a smaller range of fine/coarse mode particle concentrations for a given fine/coarse mode combination (here fine#1/coarse#5)

12 Step 3: For a different fine/coarse mode combination (here fine#3/coarse#6), the observables are consistent with a different range of fine/coarse mode particle concentrations

13 Step 4: For all possible fine/coarse mode combinations, the observables are consistent with a different range of fine/coarse mode particle concentrations

14 Step 5: The best 10% of possible fine/coarse mode combinations & concentrations, define a range of aerosol radiative properties.

15 : retrieved parameters : observables Current choices in retrieval method: 1) 1)Metric / error / cost function 2) 2)Observables x i = AOD 550nm, AOD 1240 nm (±0.03±5%) - MODIS AAOD 388 nm (±0.03±5%) - OMI  532 (±10Mm -1 ±10%) - CALIOP 3) 3)Use 10% best solutions in context of metric above

16 AOD/ssa0.80.90.98 0.05Case 1Case 2Case 3 0.2Case 4Case 5Case 6 0.7Case 7Case 8Case 9 Sensitivity study Consider 9 cases: Metric: allow 50% deviation in  Case Number

17 Sensitivity study Consider 9 cases: Metric: allow 10% deviation in  AOD/ssa0.80.90.98 0.05Case 1Case 2Case 3 0.2Case 4Case 5Case 6 0.7Case 7Case 8Case 9 Case Number

18 Solution space: expansion from over-ocean MODIS models

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22 Aerosol Optical Depth comparisons (CALIOP V2/V3)   Eight months of data: January, April, July and October 2007 and 2009   Use CALIOP 5/40km-avg. (V3/V2) aerosol extinction profiles, and 5km aerosol and cloud layer products   Find all instantaneously collocated, MODIS MYD04_L2 (10x10km) aerosol retrievals traversed by 40km CALIPSO track   For V2, apply three CALIPSO profile quality criteria: 1. 1.Alt_top_aerosol > Alt_top_cloud 2. 2.EQC532_flag = 0 or 1 3. 3.Integrated attenuated backscatter @ 532 <=0.011   Stratify by MODIS cloud fraction and FMF   Break down geographically → zonal mean AOD comparisons and repre- sentativeness of MODIS obs. along CALIPSO track for ALL MODIS obs.   Compare zonal means

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24 1) Alt_top_aerosol > Alt_top_cloud 2) EQC532_flag = 0 or 1 3) Integrated attenuated backscatter @ 532 <=0.011

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29 CALIPSO AOD > MODIS AOD + 0.2 MODIS AOD > CALIPSO AOD + 0.2 FOC<0.01

30 Zonal mean differences in AOD (550nm) from MODIS and CALIPSO over land and ocean during 4 months in 2007

31 Zonal mean differences in AOD (550nm) from MODIS and CALIPSO over land and ocean during 4 months in 2009

32 Proof of concept: Data sources

33 CALIOP ext.

34 Proof of concept: Data sources CALIOP ext., MODIS AOD

35 Proof of concept: Data sources CALIOP ext., MODIS AOD, OMI AAOD

36 Proof of concept: Data sources CALIOP ext., MODIS AOD, OMI AAOD, ALL

37 Example of successful retrieval from actual collocated OMI, MODIS, CALIOP (V3) data: Oct. 23, 2007

38 Proof of concept: Instantaneous aerosol radiative forcing calculated from combined CALIOP, MODIS, OMI observations for October 23, 2007

39 Validating/Testing the retrievals and calculated aerosol radiative effects: 1) Input/output consistency checks 2) Field observations of aerosol radiative properties: Using HSRL, AATS, and in situ data as test bed

40 Conclusions A.Instantaneous MODIS-CALIOP AOD comparisons show decent agreement after severe cloud clearing, and regional and zonal averaging. Zonal mean MODIS over ocean AOD is greater than CALIOP AOD by 0.05 - 0.1. Increased data density in V3 comes without accuracy loss by comparison to V2. B.A methodology for the retrieval of aerosol radiative properties from MODIS AOD, OMI AAOD and CALIPSO  532 &  1064 has been devised. C.A sensitivity study of current method shows good retrievals for almost all AOD/ssa combinations with AOD greater or equal to 0.2. Solution space issues remain to be resolved. D.Proof of concept study complete for one day of data in October 2007. E.Next steps: 1)Continue test of retrieval assumptions (metric, solution space, etc.) and output against suborbital data 2)Constrain OMI AOD retrievals with CALIOP height input 3)Test CALIOP aerosol above cloud measurements 4)Extrapolation of radiative properties to data-sparse regions 5)Testing additional constraints afforded by APS 6)Comparisons to CERES results

41 Validating/Testing the retrievals and calculated aerosol radiative effects: 1) Input/output consistency checks 2) Field observations of aerosol radiative properties 3) AERONET retrievals

42 CALIPSO AOD > MODIS AOD + 0.2 MODIS AOD > CALIPSO AOD + 0.2

43 Validating/Testing the retrievals and calculated aerosol radiative effects: 1) Input/output consistency checks 2) Field observations of aerosol radiative properties 3) AERONET retrievals

44 Proof of concept: Available data CALIOP ext., MODIS AOD, OMI AAOD, ALL

45 Retrieving aerosol radiative properties above clouds Importance (IPCC uncertainty) Is the thickness of the aerosol layers overlying clouds significant enough to even consider retrieving aerosol radiative properties? Where and when are there aerosols over clouds on the globe? Devise a method of retrieving aerosol radiative properties above clouds using CALIOP and OMI (no MODIS data) Preliminary results using CALIPSO level 2-5km layer product data in 2007…

46 Constraints afforded by lidar backscatter retrieval - 1 MODIS AOD (±0.03±5%) OMI AAOD (±0.03±5%) No CALIOP  532

47 Constraints afforded by lidar backscatter retrieval - 3 MODIS AOD (±0.03±5%) OMI AAOD (±0.03±5%) CALIOP  532 (±10Mm -1 ±10%)

48 EXTINCTION AOD\SSA0.80.90.98 0.05 58.84 +/- 14.88 (30.88/97.62) input 50.13 49.40 +/- 13.03 (23.98/96.49) input 49.93 47.53 +/- 13.73 (25.75/93.67) input 50.01 0.2 201.71 +/- 6.87 (187.96/219.39) input 199.29 206.81 +/- 20.30 (159.51/256.14) input 200.54 199.62 +/- 10.33 (172.22/234.64) input 200.11 0.7 696.87 +/- 6.23 (689.88/717.68) input 699.13 708.94 +/- 22.61 (665.50/759.05) input 699.23 702.61 +/- 23.40 (664.51/762.79) input 699.91 SSA AOD\SSA0.80.90.98 0.05 0.83 +/- 0.05 (0.75/0.94) input 0.80 0.87 +/- 0.05 (0.75/0.98) input 0.90 0.97 +/- 0.01 (0.94/0.99) input 0.98 0.2 0.80 +/- 0.01 (0.77/0.83) input 0.80 0.90 +/- 0.02 (0.85/0.93) input 0.90 0.98 +/- 0.00 (0.97/0.98) input 0.98 0.7 0.80 +/- 0.00 (0.80/0.81) input 0.80 0.90 +/- 0.00 (0.89/0.91) input 0.90 0.98 +/- 0.00 (0.98/0.98) input 0.98 ASYMMETRY AOD\SSA0.80.90.98 0.05 0.80 +/- 0.04 (0.62/0.85) input 0.83 0.76 +/- 0.05 (0.56/0.85) input 0.69 0.77 +/- 0.03 (0.61/0.80) input 0.75 0.2 0.82 +/- 0.01 (0.79/0.84) input 0.83 0.74 +/- 0.04 (0.62/0.78) input 0.69 0.78 +/- 0.01 (0.72/0.79) input 0.75 0.7 0.83 +/- 0.00 (0.82/0.83) input 0.82 0.71 +/- 0.02 (0.68/0.73) input 0.69 0.77 +/- 0.01 (0.73/0.79) input 0.75 OLD Sensitivity: MODIS AOD (±0.03+5%), OMI AAOD (±0.03+5%), CALIOP  532 (±10Mm -1 ±10%)

49 C.S. M c Naughton r = 0.37 r = 0.95 Asian outflow over AlaskaForest fire smoke over Canada Horizontal variability of aerosol optical properties observed during the ARCTAS airborne experiment Shinozuka et al. Poster

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