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Radiometric Comparison between Suomi NPP VIIRS and AQUA MODIS using Extended Simultaneous Nadir Overpass in the Low Latitudes Sirish Uprety a Changyong.

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Presentation on theme: "Radiometric Comparison between Suomi NPP VIIRS and AQUA MODIS using Extended Simultaneous Nadir Overpass in the Low Latitudes Sirish Uprety a Changyong."— Presentation transcript:

1 Radiometric Comparison between Suomi NPP VIIRS and AQUA MODIS using Extended Simultaneous Nadir Overpass in the Low Latitudes Sirish Uprety a Changyong Cao b Slawomir Blonski c Xi Shao d a CIRA, Colorado State University, College Park, MD, b NOAA/NESDIS/STAR, College Park, MD, c, d CICS, University of Maryland, College Park, MD Extended Simultaneous Nadir Overpass (SNO-x) in low latitudes is a recently introduced approach (inherited from traditional SNO approach) that extends SNO orbits to low latitudes for inter-comparing sensors in tropical region over a wide dynamic range such as over ocean surface, desert targets, green vegetation etc. In addition to SNO events at high latitude polar region, there exists SNO events between Suomi NPP VIIRS and AQUA MODIS at low latitudes, every 2-3 days apart but with larger time differences of more than 8 minutes. The two sensors are compared at overlapping regions of extended SNO orbits at North African deserts whereas the inter-comparison is done at both the exact orbital intersection and extended overlapping orbits over ocean. VIIRS moderate resolution channels (M-1 through M-8) are compared to MODIS equivalent channels to assess radiometric bias. The observed bias is target dependent due to a) spectral differences of targets and b) differences in spectral response functions of matching VIIRS and MODIS channels c) BRDF due to time difference between MODIS and VIIRS observation, atmospheric variability etc. Expected bias due to spectral differences is quantified using instruments such as Hyperion and AVIRIS and using radiative transfer models such as MODTRAN Stable earth targets such as Antarctica Dome C site is also used to evaluate the temporal radiometric calibration stability of VIIRS and verify the radiometric bias of VIIRS bands. VIIRS radiometric bias trends for VNIR channels are consistent at both targets, desert and ocean, for most of the bands suggesting decreasing trend in the beginning and getting more stable after May, 2012. VIIRS band M5 indicates the largest bias relative to MODIS of more than 8% at desert primarily due to spectral differences between MODIS and VIIRS RSR. The major uncertainties are due to 1) cloud movement, residual cloud contamination and cloud shadow, 2) sun glint over ocean surface 3) BRDF 4) spectral differences 5) co-location errors 6) atmospheric absorption variability etc. More than 8 minutes of time difference between MODIS and VIIRS observations for SNO-x comparison introduces larger uncertainties. After accounting for the expected bias due to spectral differences and uncertainties in bias trends, VIIRS measurements for VNIR bands agree with MODIS within 2% with uncertainty less than 1%. VIIRS SWIR band M-8 indicate larger than 2% bias over desert. Bias results at Dome C are consistent with the bias estimated at desert suggesting less 2% bias for VIIRS VNIR channels. VIIRS bands M-8 indicate larger than 3% bias with uncertainty greater than 2%. The larger bias in M-8 needs to be investigated further. Comparison of VIIRS observations over different target types with consistent results helps to understand and quantify the on-orbit radiometric performance of VIIRS in more detail. SNO-x approach has been successfully implemented for inter-sensor comparison between S-NPP VIIRS and AQUA MDOIS. The study suggests that SNO-x is a potential approach for continuously monitoring VIIRS radiometric accuracy and stability to keep the radiometric calibration well within the specification. References: [1] Cao, C, Weinreb, M, Xu, H: Predicting simultaneous nadir overpasses among polar-orbiting meteorological satellites for the intersatellite calibration of radiometers. Journal of Atmospheric Technology 21(4), 537-542 (2004) [2] Heidinger, A. K., C. Cao, and J. T. Sullivan: Using Moderate Resolution Imaging Spectrometer (MODIS) to calibrate advanced very high resolution radiometer reflectance channels, Journal of Geophysical Research, vol. 107, no. 0, XXXX, doi:10.1029/2001JD002035. (2002) [3] Cao, C., F. Deluccia, X. Xiong, R. Wolfe, and F. Weng: Early on orbit performance of VIIRS, submitted to TGRS, (2013). [4] Uprety. S. and C. Cao: Radiometric and spectral characterization and comparison of the Antarctic Dome C and Sonoran Desert sites for the calibration and validation of visible and near-infrared radiometers, J. Appl. Remote Sens., (2012) Acknowledgment : This study is partially funded by the Joint Polar Satellite System (JPSS) program. Introduction Summary Methodology Figure 2. a) MODIS and b) VIIRS image mapped to MODIS latitude/longitude Figure 4. Reflectance spectra at desert, ocean and Dome C along with VIIRS and MODIS matching RSRs Results Figure 3. VIIRS radiometric bias time series over Left: Desert; and Right: Ocean surface; for matching bands, Bias=(V-M)×100%/M Table 3. VIIRS radiometric bias at Antarctica Dome C 1. Sensors and data sets used: a) SNPP VIIRS Moderate channels (M1 to M8 with spatial resolution ~750 m) b) AQUA MODIS (1 km L1B data) c) EO-1 Hyperion (30 m) and NASA AVIRIS (~10 m) 2. Data Processing: Figure 1. Flowchart: Computing observed bias using SNO-x and expected bias Identify low latitude SNO events and collect VIIRS and MODIS data for extended exact and extended SNO orbits Start ROI selection  spatial uniformity < 2% (Desert), < 1% (Ocean)  sensor zenith: <10 ⁰ (Desert), <6 ⁰ (Ocean)  apply strict cloud mask criteria for ocean  size: VIIRS and MODIS: 9km × 9km Hyperion and AVIRIS: 3km × 3km Map VIIRS into MODIS grid using fast geospatial matching (GSM) algorithm 1 1  Extract TOA reflectance mean for each ROI and compute bias between VIIRS and MODIS matching pairs, Bias=(VIIRS – MODIS)*100%/MODIS  Calculate the mean and stdev of all ROI mean values of an SNO event.  Construct the time series using all existing SNO events and analyze the observed bias Stop Convolve Hyperion/AVIRIS/MODTRAN reflectance with RSR of VIIRS and MODIS Calculate Spectrally induced bias Stop Figure 2. b) Orbits showing Low latitude SNO events i) Extended SNOs to desert ii) SNOs over ocean Desert Ocean MODIS a) Mapped VIIRS b) Start VIIRS Desert Bias (V-M)×100%/MOcean Bias (V-M)×100%/M HyperionMODTRANAVIRISMODTRAN M-1--0.26%-1.10%-1.40% M-2-0.94% ± 0.03%0.01%0.52%0.70% M-3-0.47% ± 0.07%0.00%-0.45%0.36% M-4-1.63% ± 0.17%-1.04%0.79%-1.17% M-57.8% ± 0.06%9.72%0.92%0.45% M-6-1.41%0.40% M-71.56% ± 0.16%1.22%2.76%0.87% M-80.18% ± 0.18%-0.39%-- VIIRSMODISObserved Bias (May 2012 to Dec. 2012) BandWavelength (µm)BandWavelength (µm)Ocean (V-M)×100%/MDesert (Mean ± Stdev) M10.402 - 0.42280.405 - 0.420-1.91% ± 1.2%-1.51% ± 1.5% M20.436 - 0.45490.438 - 0.448-3.38% ± 0.86%-2.49% ± 0.73% M30.478 - 0.498100.483 - 0.493-0.88% ± 0.69%-1.23% ± 0.39% M40.545 - 0.565 4 --1.51% ± 0.27% 120.546 - 0.556-1.04% ± 0.96%- M50.662 - 0.682 10.620 - 0.670-9.66% ± 0.69% 130.662 - 0.6720.91% ± 1.22%- M60.739 - 0.754150.743 - 0.7531.01% ± 1.03%Saturated M70.846 - 0.885 20.841 - 0.876-3.35% ± 0.65% 160.862 - 0.8852.03% ± 1.22%- M81.230 - 1.2505 -2.43% ± 0.71% VIIRSMODIS Observed Bias Day 350 (V-M)×100%/M Expected Bias (V-M)×100%/M Residual Bias (observed – Expected) M1 (0.402 - 0.422 µm)B8 (0.405 - 0.420 µm)-0.16%-0.76%0.6% ± 0.63% M4 (0.545 - 0.565 µm)B4 (0.545 - 0.565 µm)1.69%0.11% ± 0.05%1.58% ± 1.57% M5 (0.662 - 0.682 µm)B1(0.620 - 0.670 µm)4.40%3.06% ± 0.35%1.34% ± 1.25% M7 (0.846 - 0.885 µm)B2(0.841 - 0.876 µm)2.32%0.1% ± 0.05%2.22% ± 1.01% M8 (1.230 - 1.250 µm)B5 (1.230 -1.250 µm)4.47%0.98% ± 0.09%3.49% ± 2.28% Figure 6. VIIRS and MODIS TOA reflectance time series at Antarctica Dome C Figure 5. Residual Bias trends (linear trends from Table 2 and 3 after subtracting expected bias) left: Desert and right: Ocean Table 2. VIIRS expected bias at ocean and desert Table 1. VIIRS observed radiometric bias at ocean and desert


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