Role of Satellite and Remote Sensing in the Urban Environment

Transcription

1 Role of Satellite and Remote Sensing in the Urban Environment Jhoon Kim 1,2,5, Kelly Chance 2,5, Ben Veihelmann 3,5, Jay Al-Saadi 4,5 Pablo Saide 6 1 Yonsei University, Seoul, Korea 2 Harvard Smithonian Center for Astrophysics, Cambridge, MA, U.S.A. 3 ESA ESTEC, Noordwijk, Netherland 4 NASA LaRC, Hampton, VA, U.S.A. 5 CEOS AC-VC 6 UCAR, CO, U.S.A.

2 Measurements of O 3 & aerosol with precursors hν (λ<345 nm) hν (<420 nm) O O 3 HCHO CHOCHO NO O 3, RO 2 NO 2 AOD, type, Height Oxidation (OH, O 3, NO 3 ) t~an hour Aerosol SO 2 NO 2

3 Geostationary Air Quality Constellation TEMPO (hourly) Sentinel-4 (hourly) GEMS (hourly) Sentinel-5P (once per day) Courtesy Jhoon Kim, Andreas Richter High temporal and spatial resolution!

4 Tropospheric chemistry mission parameters (as of 9/2016) Europe Sentinel 4 USA TEMPO Korea GEMS Europe Sentinel 5 Precursor TROPOMI Orbit Geostationary Geostationary Geostationary Low-Earth Domain Europe and surrounding North America Asia-Pacific Global Revisit 1 hour 1 hour 1 hour 1 day Status Detailed Design, Phase C Instrument delivery 2017 Instrument delivery 2017 Instrument complete Launch Payload 2021 (Flight Acceptance Review first instrument) UV-Vis-NIR , nm Products O 3, trop. O 3, NO 2, SO 2, HCHO, AAI, AOD, heightresolved aerosol Spatial Sampling Nominal product resolution Notes pending host selection UV-Vis , nm O 3, trop. O 3, 0-2km O 3, NO 2, HCHO, SO 2, CHOCHO, AOD, AAI 8 km x 8 km at 45N 2.22 km N/S x 5.15 km 8.9 km N/S x 11.7 km Two instruments in sequence on MTG-S; use TIR sounder on MTG-S (expected sensitivity to O3 and CO). Synergy with imager on MTG-I w.r.t. aerosol and clouds km N/S x 5.15 km GEO-CAPE precursor or initial component of GEO-CAPE. Synergy with GOES-R/S ABI w.r.t. aerosol and clouds UV-Vis nm O 3, NO 2, SO 2, HCHO, AOD 3.5 km N/S x 8 km 7 km N/S x 8 km (gas), 3.5 km N/S x 8 km (aerosol) Synergy with AMI and GOCI-2 instruments w.r.t. aerosol and clouds. UV-Vis-NIR-SWIR , , nm O 3, trop. O 3, NO 2, SO 2, HCHO, AAI, AOD, heightresolved aerosol, CO, CH 4 7 km x 3.5 km nadir 7 km x 7 km nadir In formation with S-NPP for synergy w.r.t. clouds and O 3. (Courtesy, Jay Al-Saadi) 4 4

5 Coverage comparisons Spatial resolution: allows tracking pollution at sub-urban scale - GEO at 100 W: 2.1 km N/S 4.7 km E/W = 9.8 km 2 (native) at center of FOR (36.5 N, 100 W) - Full resolution for NO 2, HCHO, total O 3 products - Co-add 4 N/S pixels for O 3 profile product: 8.4 km N/S 4.7 km E/W ~ 1/300 of GOME-2 ~ 1/30 of OMI (Courtesy, Kelly Chance) 4/10/17 5

6 Development of Satellite RS Capability week MODIS TROPOMI OMI GOME-2 GOME Temporal Resolution day hr GOCI-2 GOCI H-8 TEMPO MI GEMS S-4 OMPS min Aerosol Trace Gases Spatial Resolution (km)

7 High spatial resolution retrieval (6 3, 1 km spatial resolution) DRAGON period GOCI 6 km MODIS 10 km 3 km 3 km 1 km 7

8 High spatial resolution retrieval (6 3, 1 km spatial resolution) Temporal collocation: min Spatial collocation: 25 km radius GOCI 6 km MODIS 10 km GOCI 3 km MODIS 3 km Temporal collocation: min Spatial collocation: 7.5 km radius 8

9 City Coverage of GEMS in East Asia Seoul Pyungyang Beijing Shanghai Hebei Tokyo Bangkok Singapore Taipei 9

10 City Coverage of TEMPO Los Angeles Mexico City Washington D.C. Bay Area TEMPO hourly footprints overlaid on the Baltimore-Washington metrop olitan area. The footprint size here is 2.4 km N/S 5.4 km E/W. Map cre ated using Google Earth/Landsat Imagery. (Courtesy, Kelly Chance) 10

11 Examples of retrieved products using OMI Troposp. O 3 O 3 profile HCHO NO 2 AOD SSA Aerosol Height CHOCHO GCA ECF 1 0 GCA CP Credit : Mijin Kim (Yonsei U) Aerosol Y.S. Choi (EWU) - Cloud Jae H. Kim (Busan NU) O 3 Hanlim Lee (Pukyung NU) - NO 2 Rokjin Park (SNU) HCHO, CHOCHO Y.J. Kim (GIST) SO 2 J.M. Yoo(EWU), M.J. Jeong(GWNU) Sfc p 11 M.H. Ahn (EWU) - calibration

12 KORUS-AQ combined assets from the Korean and U.S. atmospheric science communities and their supporting organizations (NIER, NASA, Universities, etc.) to implement an integrated observing system for improving our understanding of Air Quality NASA DC-8 (HSRL, 4 STAR..) LaRC King Air (GEOTASO, MOS) Hanseo King Air [Courtesy of James Crawford] KORUS-OC (1 May 14 June 2016) Model evaluation and improvement, chemical process understanding, Satellite Cal/Val and observing strategies GOCI, MI, Himawari-8, MODIS, OMI, MOPITT.. Broad spatial coverage for key atmospheric components (aerosols, ozone, precursors) Operational Air Quality Forecasts, Regional and Global models of atmospheric composition Air Quality Network, Research Sites, Research Vessels including in situ and remote sensing observations (Aeronet, Pandora, Lidar)

13 GEOTASO during KORUS-AQ ( ) Courtesy, Scott Janz (NASA GSFC), Laura Judd & Jay Al-Saadi (NASA LaRC) 13

14 KORUS-AQ Campaign : Case of 30 May 2016 HSRL Height 4STAR AOD (Zenith) GOCI AOD (1 hr) MI AOD (15 min) AHI AOD (10 min) 1~2 km, 4~6 km (Median of aerosol extinction profile) All campaign data avg. Mean of case date Range of 16/50/84 percentile HSRL Aerosol type Dusty Mix Details in Sam Leblanc et al. 14 Urban/Pollution and Smoke

15 Forecasts assimilating GOCI and MODIS AOD during KORUS-AQ (May 24 th flight, Chinese haze over Yellow sea) Day-3 Day-2 Day-1 Observed AOD (GOCI) WRF-Chem Day-1

16 Assimilation results for Korea Fractional bias per station Saide et al., GRL 2014 DUST Anthro 16 Anthro SMOKE Anthro

17 Summary (1) Aerosol optical properties are retrieved in 3 to 6 km resolution fro m geostationary satellite remote sensing, and showed reasonably good correlation with the ground-based AERONET. With the planned three GEO air quality constellation to be launch ed in time frame, column amounts of trace gases can be measured in nominal spatial resolution of 5(TEMPO) to 8(S-4 & GEMS) km. GEOTASO, an airborne TEMPO/GEMS instrument successfully dem onstrated the capability of remote sensing of these AQ compone nts during the DISCOVER-AQ and KORUS-AQ campaign. During the KORUS-AQ Campaign in 2016, integrated observation of satellite, airborne, and ground-based has been demonstrated s uccessfully near Seoul Metropolitan Area, together with chemical weather forecast through data assimilation.

18 Summary (2) Demonstrated - Satellite remote sensing of aerosol & trace gases from GEO in KM scal e - Standardized, near real time(nrt) satellite data service - Data Assimilation of AQ using GE O aerosol property retrieval Satellite RS Airborne RS Ground-based Barrier - Near real time(nrt) data transfe r to Data Assimilation(DA) system - Reliable, urban-scale, ground-ba sed observation network - Expand the coverage of GAW to include urban needs - Urban-scale, high resolution CT M Data Assimilation - Frequent updates in Emission D B DOAS Networ AQ Networ GAW k k SKYNET LIDAR Network High-resolution CTM Emission Met GURME NRT data communication Operational Services