1. ARCTAS preliminary report to HQ ESD visitors at Ames Fri 12 Sep 2008 Phil Russell, NASA Ames with contributions from many, many leaders, experimenters, modelers, forecasters, aircraft crews, …

2. Third IPY (2007-2008) Why Study the Arctic Now?  ARCTIC IS UNDERGOING RAPID CHANGE- Rapid warming; receptor of mid-latitudes pollution; boreal forest fires increasing  POTENTIALLY LARGE RESPONSE & UNIQUE CHEMISTRY- Melting of polar ice sheets, decrease of snow albedo from soot, halogen chemistry  UNIQUE OPPORTUNITY- Large NASA satellite fleet; Interagency & international collaboration via POLARCAT & IPY ARCTAS: Arctic Research of the Composition of the Troposphere from Aircraft and Satellites

3. Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) A NASA contribution to IPY and the international POLARCAT initiative Conducted in spring and summer 2008 with the following foci: http://cloud1.arc.nasa.gov/arctas 1. Long-range transport of pollution to the Arctic (including arctic haze, tropospheric ozone, and persistent pollutants such as mercury) tropospheric ozone, and persistent pollutants such as mercury) 2. Boreal forest fires (implications for atmospheric composition and climate) 3. Aerosol radiative forcing (from arctic haze, boreal fires, surface-deposited black carbon, and other perturbations) black carbon, and other perturbations) 4. Chemical processes (with focus on ozone, aerosols, mercury, and halogens) Partners: NASA, NOAA, DOE, NSF, Canada, France, Germany April 2008: Fairbanks and Barrow, Alaska; Thule, Greenland July 2008: Cold Lake, Alberta; Yellowknife, NW Territories NASA DC-8 NASA P-3BNASA B-200 Slide courtesy Jim Crawford, HQ Mgr TCP

4. LaRCARCGSFCJPLMSFCGISSDFRCWFFUniv/OGOV MeasurementsXXXX Satellite TeamsXXXX Model ForecastingXXX Science Leadership and Decision Support XXXX Aircraft operationsXXXX Logistics and Data Archival XX The ARCTAS science team includes over 150 scientists and support personnel representing 8 NASA installations, 12 Universities, and 3 Government Labs Chemistry and Aerosols Radiation, Aerosols, Tracers Aerosol satellite validation 21 instruments HSRL – CALIPSO RSP – GLORY 9 Instruments Satellite Teams: CALIPSO, MODIS, TES, OMI, AIRS, MISR, MOPITT Model Forecasting: GEOS-5, GOCART, STEM, MOZART ARC-IONS: Ozonesonde network in cooperation with Environment Canada

5. AOD, 0Z,7/8 Multi-Center Participation on P-3 in ARCTAS DFRC: REVEAL MSFC: RTMM AATS COBALT SSFR Aero3X CAR CCNBBR HiGEAR ARCGSFCLaRC PDS

6. LaRC: 4 Science Instruments DFRC: REVEAL MSFC: RTMM Multi-Center Participation on DC-8 in ARCTAS

7. DC-8 P-3B B200 DC-8 (185 flight hours)P-3B (158 flight hours)B-200 (150 flight hours) Spring (1-20 April)9 sorties8 sorties27 sorties California (18-24 July)4 sorties1 sortie Summer (26 Jun-13 July)9 sorties12 Sorties21 Sorties

8. ARCTAS-California 2008 OMI NO 2 Oct. 22, ‘07 NASA CAPABILITIES: Airborne observations Satellite observations Global/regional models Integrated analysis NASA MAIN OBJECTIVES: Ozone/aerosol formation Aerosol & radiative forcing GHGs & precursors Long-range pollution transport Satellite validation

10. Ames Roles in ARCTAS Leadership

11. CALIPSO Satellites: CALIPSO, OMI, TES, MLS, MODIS, MISR, MOPITT, AIRS Aerosol optical depth, properties H 2 O, CO, ozone, NO 2, HCHO, SO 2, BrO B200 Aircraft: DC-8, P-3B, B200 Comprehensive in situ chemical and aerosol measurements measurements Passive remote sensing of atmospheric Passive remote sensing of atmospheric state and composition state and composition Active remote sensing of ozone, water vapor and aerosol optical properties and aerosol optical properties Models: CTMs, GCMs, ESMs Source-receptor relationships for pollution Inverse modeling for estimating emissions Aerosol radiative forcing Detailed chemical processing Model error evaluation Data assimilation Diagnostic studies Calibration and Validation Retrieval development Correlative information Small scale structure and processes ARCTAS Field Campaign Strategy: Maximize the value of satellite data for improving models of atmospheric composition and climate

12. NASA DC-8 NASA P-3B NOAA WP-3D NSF HIAPER DLR FALCON Measurement comparisons were conducted between the NASA DC-8 and partner aircraft as well as between the NASA P3-B and NOAA WP-3D

13. Example comparison of CO 2 measurements onboard the NASA DC-8 (S. Vay, NASA LaRC) and NOAA WP-3D (T. Ryerson, NOAA ESRL) -Blind comparison reveals no detectable difference -Establishing confidence in airborne CO 2 measurements is critical to future OCO validation and ASCENDS technology demonstrations.

14. DC-8 P-3B B200 California and Boreal (Cold Lake) CH 4, N 2 O, CO2 & CO measurements: Highly correlated time series can characterize emissions from varied sources (incl. rice paddies, feed lots, other agriculture, wooded lands, wildfires)

15. AOD, 0Z,7/8 GEOS5 Model prediction of Aerosol Optical Thickness (AOT) ARCTAS P-3 & B-200 Tracks, 26 Jun-12 Jul 2008 Flight Plan A Planned P3 Flight Track

17. AOD, 0Z,7/8 GEOS5 Model prediction of Aerosol Optical Thickness (AOT) ARCTAS P-3 Data Flight #17, 30 Jun 2008 To measure composition & radiative effects of wildfire smokes in CALIPSO & B200 lidar tracks Flight Plan A Planned P3 Flight Track

18. AOD, 0Z,7/8 View from cockpit approaching Lake Athabasca fires ARCTAS P-3 Data Flight #15, 28 Jun 2008 - Canadian researchers (Mike Flannigan, Merritt Turetsky, Brian Stocks) now working on ground to assess impact of fires ARCTAS sampled

19. AOD, 0Z,7/8 A closer view from cockpit ARCTAS P-3 Data Flight #15, 28 Jun 2008

20. AOD, 0Z,7/8 A closer view from cockpit

21. Turnaround Point NRL COAMPS PREDICTED SMOKE FROM ATHABASKA FIRES (courtesy Jeff Reid) GEOS5 - Weak Siberia biomass burning plume between 1-6 km in central Canada, Courtesy Mian Chin - Similar features in some other models. 18 Z 9 Jul 2008 P-3B B200 CALIPSO Track

22. 9 July 2008: B200 and P-3B underfly the CALIPSO track sampling smoke plume from boreal fires in northern Saskatchewan. Turnaround Point P-3B B200 CALIPSO Track

23. P-3 in ARCTAS: Payload Ames Airborne Tracking Sunphotometer (AATS-14) Solar Spectral Flux Radiometer (SSFR) Broad-Band Radiometers (BBR) LW SW HiGEAR Aerosols & O 3  OPC & DMA dry size dist, volatility  Tandem Volatility DMA  Neph scat + PSAP abs  Humidified Neph f(RH)  Ultrafine & CN  Time of Flight Mass Spec size resolved chemistry  SP2 black carbon mass AERO3XCloud Absorption Radiometer (CAR) P-3 Data System (PDS): Nav, Flight, Met (P, T, RH, …) REVEAL & RTMM  AOD  Ext  H 2 O vapor  Cavity Ringdown ext (2 )  Reciprocal Neph sca (2, RH )  Radiance, BRDF  Flux ↑, ↓ ( ), albedo( )  Flux ↑, ↓, albedo  Nenes CCN  PVM cloud drop r eff, vol  TECO O 3 COBALT: CO

24. Extinction Smoke layer Optical Thickness HSRL/AATS-14 Aerosol Optical Thickness (AOT) Comparison Comparison of AOT derived from HSRL (B200) and derived from AATS-14 Airborne Sun Photometer (P-3B) while P-3B spiraled up below B200 (AATS14 data courtesy of Jens Redemann) Large variability in AOT associated with smoke plume Preliminary

25. HSRL/In situ Aerosol Extinction Comparison Extinction Smoke layer Comparison of aerosol extinction derived from HSRL (B200) and in situ dry scattering (neph) + absorption (PSAP) measurements while P-3 spiraled up below B200 (in situ data courtesy of Tony Clarke) Preliminary

26. Good agreement in and above the smoke! CALIPSO slightly lower Low level feature due to temporal offset Vertical Feature Mask misidentification Preliminary

27. MODIS OMI

28. light cloud P-3 DC-8 Typical maneuvers flown by P-3 in ARCTAS To measure aerosols, CO, O3, & radiative effects

29. Comparison of AATS, OMI, and MODIS AOD spectra Preliminary J. Redemann, J. Livingston

30. Comparison of AATS and MODIS AOD spectra Preliminary J. Redemann, J. Livingston

31. AOD, 0Z,7/8 ARCTAS Summary & Future 1.NASA’s contribution to IPY & International POLARCAT 2.Strong intercenter, university, interagency, & international collaboration. 3.Strong coordination among aircraft, satellites, & models (showed just 1 case of many, many [3 satellites, 2 A/C, several models]). 4.Ames lead roles in project science, project management, & platform science. Also A/C instruments. 5.Most analyses just getting started (preliminary data archival due 1 Oct 2008). Potential strong link to ecosystems. - Highly correlated A/C time series of CH 4, N 2 O, CO 2 & CO can characterize emissions from varied sources (e.g., rice paddies, feed lots, other ag, woods, wildfires) - Canadian researchers (Mike Flannigan, Merritt Turetsky, Brian Stocks) assessing impact of fires ARCTAS sampled 6.ARCTAS Special Sessions: AGU Fall 2009

32. AOD, 0Z,7/8 END OF PRESENTATION REMAINING SLIDES ARE BACKUP

33. 1) California agriculture and wetlands: N 2 O in the PBL over some valley areas of California reached levels rarely seen by the N 2 O/CH 4 /CO team. CH4 also reached high levels, sometimes in concert with N 2 O, sometimes not. Agriculture/land surface, not pollution: no CO correlation. 2) Boreal observations showed variations of N 2 O and CH 4 within expectations. However extremely high concentrations were noted at and near the airport on takeoff from Cold Lake in one instance. Cold Lake is near the dividing line between cattle pasturage and forest. Unfortunately, no ethane (C 2 H 6 ) or other hydrocarbon measurements were made which might have distinguished the source. "Glenn S. Diskin" Glen Sachse Chatfield will communicate Christopher Potter’s characterization of sources to the Langley team. Possibility: day-by-day estimation of emissions by Potter (responding to irrigation, fertilization, and cropping) may focus on particular source regions and processes. Notable N 2 O and CH 4 observations Suggesting Strong Sources Glenn Diskin and Glen Sachse (communications with Bob Chatfield)