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As components of the GOES-R ABI Air Quality products, a multi-channel algorithm similar to MODIS/VIIRS for NOAA’s next generation geostationary satellite.

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Presentation on theme: "As components of the GOES-R ABI Air Quality products, a multi-channel algorithm similar to MODIS/VIIRS for NOAA’s next generation geostationary satellite."— Presentation transcript:

1 As components of the GOES-R ABI Air Quality products, a multi-channel algorithm similar to MODIS/VIIRS for NOAA’s next generation geostationary satellite sensor, GOES-R ABI to retrieve Suspended Matters (SM) and Aerosol Optical Depth (AOD). ABI is a 16-channel Imager with wavelength coverage extending from visible to thermal IR. Its temporal (five minute coverage of the Contiguous United States) and spatial resolution (2 km at nadir) will provide unprecedented monitoring capabilities of short-lived and localized weather and air pollution events that can sometimes be missed by polar- orbiting satellite sensors. The algorithm development for SM/AOD has been completed and tested using three types of proxy data: (1) ABI radiances generated from a simulator using a radiative transfer model and MODIS derived land and atmospheric variables, (2) ABI radiances generated from a simulator using a radiative transfer model and WRF- CHEM model generated land and atmospheric variables, and (3) MODIS radiances. Analysis based on 10 years of ABI AOD retrievals using MODIS radiances shows that the product meets accuracy specifications (±0.06 over land and ±0.02 over water for AODs ranging between 0.04 and 0.8 and for AODs greater than 0.8, ±0.12 and ±0.1 over land and water respectively). Table 1. Channel numbers and wavelengths for the GOES-R ABI. Channels used in both the SM/AOD algorithm are given in the last column. 2. Introduction 3. ABI Aerosol Retrieval algorithm 4. Routine Validations of ABI AOD with MODIS Collection 5 Aerosol Product1. Abstract In this poster, we present the, (1) introduction on GOES-R ABI SM/AOD Algorithm; (2) routine validation with MODIS collection 5 aerosol product; (3) Validations with ground- based (AERONET) measurements; (4) introduction of simulator of ABI clear-sky radiance, and (5) summary 5. Validations SM/AOD product with ground-based (AERONET) measurements6. Comparisons with MODIS AOD over ocean 7. Summary 1.Extensive Validations of GOES-R ABI Suspended matter/AOD algorithm indicates that it meets the F&P required accuracy 2.Using MODIS gas-absorption corrected and clear sky radiance as proxy, ABI retrievals are evaluated with MODIS aerosol products and ground-based (AERONET) measurements 3.Validation system is operated routinely (two weeks delay for comparison with MODIS aerosol product and 4 month delay from ground-based validations. Results are archived and accessible through internal website 4.Performance of SM/AOD algorithm is monitored by the time-series of key statistical parameters from the comparison with MODIS AOD. Summary of GOESR-ABI SM/AOD algorithm:  Land algorithm: The land aerosol algorithm is designed to retrieve simultaneously surface reflectance at 2.25um and aerosol optical depth at 0.55um, and also select aerosol model from 4 predefined land aerosol type that produce the minimum residual between the calculated and observed TOA reflectance at channels used for land aerosol retrievals.  Ocean algorithm: Ocean bidirectional surface reflectance is explicitly calculated according to the state of ocean (wind speed and wind direction etc.) with Cox and Mon model. A pair of aerosol, i.e, one from 5 predefined fine mode models and one from 4 coarse mode model is chosen to give best fit to the observed TOA reflectance at channels used for ocean aerosol retrievals. Disclaimer: The views, opinions, and findings contained in this work are those of the authors and should not be interpreted as an official NOAA or US Government position, policy, or decision. Status of GOES-R Advanced Baseline Imager (ABI) Suspended Matter/Aerosol Optical Depth (SM/AOD) Algorithm and Product Validation The Aerosol Team (NOAA/NESDIS/STAR) Global Aerosol optical depth for 07/ 01/2009, Terra ABI MODIS ABI-MODIS GlobalGOES-WESTCONUS Figure 8. scatter plots of ABI AOD v.s. AERONET AOD in spring, summer, Autumn, and Winter for GOES-EAST coverage Table 2. Statistics of ABI AOD v.s. AERONET AOD for different geographical coverage and season. L – Land; W – Water GLOBALGOES-EASTGOES-WESTCONUS springsummerautumnwinterallspringsummerautumnwinterallspringsummerautumnwinterall sprin g summerautumnwinterall Accura cy (slope) L 0.045 (0.89) 0.051 (0.93) 0.015 (0.88) -0.018 (0.80) 0.032 (0.87) 0.048 (0.81) 0.056 (0.93) 0.022 (0.94) -0.015 (0.74) 0.038 (0.86) 0.050 (0.78) 0.062 (0.90) 0.025 (0.89) -0.016 (0.74) 0.041 (0.82) 0.055 (0.75) 0.053 (0.86) 0.025 (0.81) 0.039 (0.77) w 0.014 (0.88) 0.007 (0.88) 0.007 (0.84) 0.005 (0.85) 0.011 (0.88) 0.017 (0.92) 0.006 (0.86) 0.008 (0.83) 0.005 (0.84) 0.011 (0.88) 0.019 (0.97) 0.013 (0.93) 0.006 (0.84) 0.005 (0.84) 0.012 0.014 (0.97) 0.001 (0.93) 0.003 (0.81) 0.007 (0.91) Precisi on L 0.1490.1420.1110.0800.1340.1470.1450.1070.0730.1350.154 0.1050.0720.1400.1620.1470.1110.143 W 0.0980.0830.0680.0400.0860.0760.0830.0630.0400.0700.0800.0830.0610.0400.0710.0780.0720.0640.066 spring summer autumnwinter LAND Figure 2.Global distribution of ABI AOD, MODIS AOD and the difference between them on a daily base. Figure 3. Dynamic monitoring of algorithm performance by monitoring the time series of ensemble statistic parameters, such as global mean AOD, bias between ABI AOD and MODIS AOD and it’s standard deviation Figure 1. Flowchart of GOES-R ABI SM/AOD retrieval algorithm OCEAN a. Aerosol Optical Depth (AOD) Figure 7. scatter plot of ABI AOD v.s. AERONET AOD for different geographic coverage, such as global, GOES-EAST, GOES-WEST and CONUS global GOES-E GOES-W conus LAND OCEAN As figure 3 shows, the difference between ABI AOD and MODIS AOD has not only large magnitude but also has clear seasonal pattern. The difference between ABI ocean algorithm and MODIS collection-5 ocean algorithm are: 1.MODIS used fixed wind speed (6m/s) and wind direction (westerly wind). ABI algorithm used wind speed and direction from NCEP reanalysis data 2.ABI used actual NCEP surface pressure to correct for rayleigh scattering 3.MODIS used all 7 bands, but ABI used only 4 bands, the missing bands are 0.47, 0.55 and 1.24 um) AOD (MODIS-C5) AOD (ABI-NCEP) wind speed (m/s) AOD (ABI-fixed wind speed And direction) RGB image for MODIS (Aqua) on 03/01/2005, 17:45 UTC Figure 9. daily global mean of difference of ABI aod with MODIS aod for year of 2002. OCEAN LAND 5. Accuracy and precision of ABI AOD product AOD measurement range is -1.0 ~ 5.0 (from year 2000 for Terra (2002 for Aqua) to year 2009) Algorithm allows linear extrapolation at the lower end of look-up table for negative AOD retrieval. MODIS 10 by 10 gas absorption corrected clear-sky radiance was used as proxy AccuracyPrecisionRMSECorrelationMinErrMaxErr ABI0.02790.13700.139883.29%-2.17941.9816 MODIS0.02660.12430.127187.21%-1.88923.3308 AccuracyPrecisionRMSECorrelationMinErrMaxErr ABI0.00780.09060.090986.96%-1.01382.5461 MODIS0.01720.10020.101784.83%-0.97562.6681 7. Fast GOESR-ABI clear-sky radiance simulator and application Comparison of input to simulation with those retrieved from the simulated radiance with the ABI algorithm. a and b are for an granule over ocean, respectively for AOD and fine-mode weight (FW) in percentage. C and d are for two granules over land Range LandOcean AODAccuracyPrecisionAODAccuracyPrecision Low<0.04 0.060.13 <0.40.020.15 Medium0.04 - 0.8 0.040.25 High> 0.8 0.120.35>0.40.100.23 GOESR-ABI AOD SPEC:


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