Sand and Dust Monitoring in RA II

Transcription

1 Sand and Dust Monitoring in RA II Xiang Fang National Satellite Meteorological Center,CMA

2 Outline Dust products in RA II Validation of multi-satellite products Action Proposed

3 Dust products in RA II Operational Dust Monitoring and Forecasting in RAII PM10, AOD (Skyradiometer, Lidar), Visibility, et al. from Weather Chart (Obs. In situ.) AOD, et al.(mtsat Himawari-8; COMS; FY-2 FY-4; FY-3 ;EOS/MODIS) (Obs. With Satellite) Assimilation (Model) Validation Operational Forecast Model Dust Information Sharing Forecast Application Issuance for Public

4 PM10,et al. PM Mass Concentration Data-KMA Cheorwon So Baengnyeongdo Gwangdeoksan Munsan Chuncheon kc Seoul Daegwallyeong ho Ullengdo Ganghwa Gwanaksan Yeongwol Suwon Uljin Gyeokgryeolbi-do Cheonan Cheongwon Anmyeondo Andong Chupungnyeong Gunsan Jeonju Daegu Ulsan Jinju Gudeoksan Heuksando Gwangju Jindo Dust observation in situ PM Mass Concentration Data-JMA Gosan AOD Ryori Yonagunijima Minamitorishima

5 Visibility Routine SDS Observational and visibility Data -Asia

6 Lidar

7 Current operational dust forecast systems Country Model Area China CUACE/Dust Asia Japan MASINGAR-mk2 Global Korea UM-ADAM2 Asia Mongolia MGL-ADAM E. Asia Now, Only CUACE/Dust model has assimilated satellite product (IDDI). So, it is essential for improving satellite data assimilation.

8 Dust products from satellite data Orbit Satellite Instrument Product Waveband TOU AI(Absorption Aerosol Index ) UV FY-3B/C MERSI AOD, Angstrom exponent VIS,NIR Polar Orbit VIRR Dust Score VIS,NIR,IR Dust Optical Thickness IR FY-3C VIRR Dust Particle Effective Radii IR Dust Column Density IR FY-2D/E/F/G S-VISSR IDDI IR GEO Orbit MTSAT-2 JAMI AOD VIS Himawari-8 AHI AOD, Angstrom VIS,NIR KOMPSAT GOCI AOD, AI VIS

9 Satellite Products from JMA MTSAT AOD for Asian dust monitoring Aerosol optical depth (AOD) product is used for monitoring dust events. MTSAT-2 AOD Surface weather observation in Japan n.b. AOD cannot be estimated over cloudy area. Dust Event: 29 Apr 2 May 2011 Blue circles are weather stations where dust was visually observed by human eyes.

10 MTSAT AOD for Asian dust monitoring Aerosol optical depth (AOD) over the ocean estimated from MTSAT data. Method: Generate a lookup table which relates MTSAT visible band s reflectivity to aerosol property using radiative transfer simulation. Estimate aerosol property from MTSAT data using the lookup table. MTSAT band: VIS ( μm) Ångström exponent (proxy for particle size) is fixed Aerosol type is assumed to be Asian dust. Not optimized for other types of aerosol (e.g. haze) User: JMA routinely uses MTSAT aerosol product for monitoring Asian dust events ( Kosa in Japanese).

11 Himawari-8 AOD for Asian dust monitoring Aerosol optical depth (AOD) and Ångström exponent (proxy for particle size) to be estimated from Himawari-8/AHI data. Ångström exponent only over the ocean. Method: Generate a lookup table which relates Himawari-8/AHI visible and near-infrared bands reflectivities to aerosol property using radiative transfer simulation. Estimate aerosol property from Himawari-8/AHI data using the lookup table. AHI bands: 0.64, 0.86 μm (ocean), 0.64, 2.25 μm (land) Aerosol type is assumed to be Asian dust. Not optimized for other types of aerosol (e.g. haze) Validation plan: Comparison with surface observation of AOD User: JMA will routinely use Himawari-8 aerosol product for monitoring Asian dust events ( Kosa in Japanese).

12 Satellite Products from KMA Instrument Product Area MI Aerosol Index (AI) Aerosol Optical Depth (AOD) COMS GOCI AOD Fine-Mode Fraction(FMF) Single scattering Albedo (SSA) Aerosol Type KMA has developed the new sand and dust detection algorithm using 4 channels of COMS/MI: 3 IR channels with VIS channel, to improve the previous algorithm which uses 2 IR channels. KMA is testing and validating the performance of this algorithm with surface observation data. Asian dust Index May

13 Yellow Dust Retrieval results from GOCI : Dust case ( ) Low FMF (~0.3): coarse particle GOCI RGB GOCI AOD (1hr interval) GOCI FMF GOCI SSA MI AOD 2.0 (15min interval) MODIS AOD (2 times per day) MODIS FMF GOCI Aerosol Type (AOD > 0.3) HA, fine MA, fine NA, fine Mixture Dust NA/coarse FMF 0.6 ~ ~ ~ ~ ~ ~0.4 SSA 0.85~ ~ ~ ~ ~ ~

14 Validation results of AODs from GOCI and MI AERONET level 2.0 AOD data ( ) - Spatial co-location : within 25km at each AERONET site - Time co-location : ±30min AERONET at each satellite center measurement time AERONET lev2.0 Data [110 0 E E, 20 0 N-45 0 N] ~

15 Satellite products from Mongolia Dust storm by MODIS NOAA and MODIS data are used for detection of SDS in the Environmental Information Center, National Agency for Meteorology and Hydrology (NAMEM), Mongolia

16 China Satellite Geo orbit products IDDI: Infrared Difference Dust Index with infrared window channel could be ratio to dust density.

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18 Forecasting application in CMA DUST-IDDI Developed DUST-IDDI numerical assimilation system with FY-2 IDDI product, DUST-IDDI is coupled with dust numerical forecasting system named as GRAPES- CUACE/Dust, could provide 72 hours forecasting results in Asian region as real-time services. 29 Apr. 2011, FY-2D IDDI product Forecasting result of GRAPRS-CUACE/Dust without DUST-IDDI Forecasting result of GRAPRS-CUACE/Dust with DUST-IDDI

19 AOD product over land from FY-4 (proxy data AQUA/MODIS) 21 Mar Mar RGB figure 26 Mar Mar RGB figure

20 China Satellite Polar orbit products RGB figure monitoring The dust weather event occurred in southeast Mongolia, the middle of Inner Mongolia, the Bohai Sea and the Korean Peninsula caused by Mongolia cyclone during February 21-23, 2015.

21 AOD product from VIS and NIR spectral band based on look-up table method, sensitive to weak dust storm under clear pixels

22 Absorption Aerosol Index (AAI) using 331nm and 360nm, FY3 TOU present the semi-quantity information of absorption aerosols. 24 Apr.2010 FY2D IDDI 23 Apr ,May

23 Dust identification product - dust score based on multithreshold method using 12 dust identification indexes for monitoring.

24 Global dust monitoring with FY-3A/VIRR. Result shows in binary image.

25 Quantitative retrieval from TIR using infrared split-window channel, sensitive to strong dust storm and less affected by surface type, could be used in dust source region. 25

26 Test result: ,FY-3A/VIRR RGB AOD overlay RGB

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28 Validation of multi-satellite products Related to the SCOPE-Nowcasting Pilot Project 4, JMA had shared the data in situ and MTSAT AOD products with CMA. CMA had finished the validation of the products of MTSAT, FY-3, FY-4 using same validate method and shown the result in AMSUC-5. Satellite L2 Data MTSAT : AOD from MTSAT-1R or MTSAT-2 supplied by MSC/JMAM Spatial resolution: 0.25 *0.2 (lon*lat) Case area range: N, E. Case time period: Mar. 2009, Mar. 2010, Apr. 2010, 29 Apr - 02 May FY-3/MERSI Spatial resolution: 1km. Case area range: N, E. (Product: global) Case time period: Mar. 2009, Mar. 2010, Apr. 2010, May 2011 (FY-3A) FY-4 ( using AQUA/MODIS as proxy data) Spatial resolution: 1km. Case area range: N, E. Case time period: Mar. 2010, Apr Ground-based Data AERONET The level 2 data which are cloud screened and quality assured are used in the validation. AOD match up: Spatial window : 0.25 *0.2 (lon*lat) for MTSAT ; 0.25 *0.25 for FY-3/4 Temporal window : ±20min

29 Land Scatter plot of AOD from FY-3/MERSI and FY-4 (proxy) against AERONET AOD from FY-4 using MODIS as proxy data is overestimated over Land. There is no systematic bias for AOD from FY-3 when AOD smaller than 1.5.

30 Ocean Scatter plot of AOD from FY-3/MERSI and MTSAT against AERONET When compared with AERONET, AOD from MTSAT is underestimated over ocean. AOD from FY-3 tends to be overestimated at low value while underestimated at high value. RMSE of AOD from these 3 satellite products during the process of dust storm is nearly 0.2.

31 Conclusions about Validation The AOD product over ocean from MTSAT has better distribution pattern and good quality for monitoring floating dust in the dust storm process. The AOD algorithm for FY-4 (using MODIS as proxy data) is credible, which is proved by the validation result. FY-4 is expected to provide valid AOD product for dust storm monitoring. Limited by the observation frequency, the AOD product from FY-3 can only provide partial information of the dust storm transmission. The large area affected by sun glint over ocean is against the continuity of AOD distribution. From the RMSE, it shows that the AOD data quality of FY-3 is a little poorer than MTSAT over ocean and FY-4 using MODIS as proxy data over land. FY-3 AOD product is suitable for the aerosol climate background estimation. This validation is preliminary work for the limited samples.

32 Action Proposed The first session is invited to comment on the comparison between dust products of different satellites. It is further invited to consider the following suggestions: Enhancing the comparison between dust products of different satellites. The validation and comparison of Himawari-8 and FY-4 AOD should be done in the future. Establishing a website for Asian dust monitoring which should include dust products from all countries, and provide access to users. Assimilating the satellite products into operational dust forecast models is improved.

33 Thanks for your attention!