1. Studying the radiative environment of individual biomass burning fire plumes using multi-platform observations: an example ARCTAS case study on June 30, 2008 Jens Redemann 1, M. Vaughan 2, Y. Shinozuka 1, P. Russell 3, J. Livingston 4, A. Clarke 5, L. Remer 6, C. Hostetler 2, R. Ferrare 2, J. Hair 2, P. Pilewskie 7, S. Schmidt 7, E. Bierwirth 7 1 BAER Institute, Sonoma, CA, 2 NASA Langley Research Center, Hampton, VA, 3 NASA Ames Research Center, Moffett Field, CA, 4 SRI International, Menlo Park, CA, 5 SOEST, Univ. of Hawaii, Honolulu, HI, 6 NASA Goddard Space Flight Center, Greenbelt, MD, 7 LASP, Univ. of Colorado, Boulder, CO Abstract The scientific goals of the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign included the study of biomass burning emissions through the synergistic use of observations using a wide variety of experimental techniques (e.g., in situ, radiometric, active remote sensing) from multiple platforms (ground, airborne, satellite). In this paper we report on the multi-platform fire plume study on June 30, 2008. A portion of the flight track of the NASA P-3 aircraft carrying a suite of in situ aerosol and radiometric instruments was coordinated to coincide in space and time with the flight track of the B-200 aircraft carrying a high spectral resolution lidar (HSRL) and with the A-Train suite of satellites. We used the P-3 radiometric instrumentation and applied different techniques to derive aerosol radiative forcing efficiency, absorption aerosol optical depth (AAOD) and single scattering albedo, and compare them to the P-3 in situ observations. We compare the suborbital observations of aerosol radiative properties to estimates from coincident MODIS, CALIPSO and OMI measurements and show how these satellites provide different estimates for some quantities based on sensor spatial resolution and scene heterogeneity alone. Finally, we describe a technique that combines AOD, AAOD and aerosol backscatter measurements to derive a set of aerosol radiative properties sufficient for aerosol direct radiative effect calculations. Comparing these calculations to spectral radiative flux measurements aboard the P-3 aircraft, we find good agreement for the broader wavelength range of 350-2150 nm, but less good agreement for the shorter wavelength range (350-700 nm). We will discuss reasons for the differences in agreement for the various spectral ranges, in particular those differences that may be traced to the newly developed retrieval methodology for aerosol radiative properties. Retrieval of aerosol radiative properties from A-Train observations (or suborbital measurements): METHODOLOGY Target:  F aerosol (z) +  F aerosol (z) Constraints/Input: - MODIS/AATS AOD (7/2 ) +  AOD - OMI/In situ AAOD (450 nm) +  AAOD - CALIPSO/HSRL ext (532, 1064 nm) +  ext - CALIPSO/HSRL back (532, 1064 nm) +  back Retrieval: ext (, z) +  ext ssa (, z) +  ssa g (, z) +  g Started with MODIS aerosol models: Now a total of 21 particle models define standard deviation and refractive indices of bi-modal log- normal size distribution → 441 combinations Free parameters: N mode1, N mode2 Rtx code Comparison: CERES/SSFR+AATS  F aerosol Methodology: 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 model#1/model#5) Methodology: 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) Methodology: Step 3 For all possible fine/coarse mode combinations, the observables are consistent with a set of fine/coarse mode particle concentration ranges Methodology: Step 4 A projection of the (best 10%) concentration ranges (wedges above) onto aerosol radiative property contours (not shown) yields a range of spectral aerosol radiative properties Test of Methodology: Use aerosol radiative properties in a radiative transfer model and calculate spectral radiative fluxes for comparison with airborne spectral flux observations MODIS AOD: (±0.03±5%) OMI AAOD: (±0.03±5%) No CALIOP  532 MODIS AOD: (±0.03±5%) OMI AAOD: (±0.03±5%) CALIOP:  532 (±20Mm -1 ±10%) MODIS AOD: (±0.03±5%) OMI AAOD: (±0.03±5%) CALIOP:  532 (±10Mm -1 ±10%) Constraints provided by CALIOP  532 Conclusions Retrieval of aerosol radiative properties from aerosol extinction, backscatter and absorption data: A.We have developed a methodology for the retrieval of spectral aerosol radiative properties from collocated AOD, AAOD and aerosol backscatter data as provided by the formation flying of the CALIPSO, MODIS and OMI instruments in the A-Train constellation of satellites. B.In a first application of our methodology to airborne testbed data, radiative fluxes modeled based on the multi-sensor aerosol retrievals compare well with radiative fluxes measured by an airborne spectral flux radiometer aboard the same aircraft. Satellite mapping of the main smoke plume : A.The MODIS standard 10-km product as well as the new 3km product (being developed for inclusion in Collection 6) do a reasonable job of mapping the smoke plume after the standard cloud screening is turned off. B.Different techniques for retrieving AOD yield different results due to different sampling geometries and volumes. Aerosol radiative forcing efficiencies: A.An initial application of the flux gradient technique for determining aerosol radiative forcing efficiencies yields larger forcing efficiencies with increasing distance from the fire source. NASA B-200: HSRL NASA P3-B: AATS, in situ, SSFR Test of method with suborbital and reduced input data: AATS AOD/ext @ 550/1240†nm, HSRL backscatter @ 532nm, in situ absorption @ 388nm‡ Satellite perspective - 30 June 2008: Aqua-MODIS, Aura-OMI Overflight of Smoke Plume  The MODIS 10-km and 3-km AOD retrievals map the smoke plume successfully.  MODIS 3-km AOD retrievals are noisier than the corresponding 10-km results.  The standard MODIS cloud screen rejects cloud- free pixels in the heart of the plume (olive and green cells) due to high variability of the radiance.  Horizontal plume structure causes differences between AATS and satellite AODs because AATS views a small subset of the satellite grid cell. MODIS 10-km resolution AOD retrieval: 550 nm AATS MODIS MODIS and AATS AOD spectra MODIS AOD MODIS % cloud OMAERUV (470 nm) OMAERO MODIS P3 flight track color coded by AATS 451-nm AOD MODIS 3-km retrieval with cloud screening MODIS 3-km retrieval without cloud screening MODIS 10-kmMODIS 3-km, no cloud screening MODIS 1  AOD uncertainty Aqua MODIS: 1950 UT Calipso P3 track B200 track Estimating aerosol radiative forcing efficiency using the gradient method A B C †: interpolated ‡: extrapolated Input Output The plots to the right and below show the retrieval output in extinction Angstrom exponent / single scattering albedo / lidar ratio space. Lines represent possible solutions through mixing of two particle modes. Red dots depict all possible solutions that reproduce the retrieval input to within 20%. Green stars show the suborbital testbed measurements. Detailed output for retrieval point #16 N mode1 (Model#1) N mode2 (Model#5) N mode1 (Model#1) N mode2 (Model#5)