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Ice Cover and Sea and Lake Ice Concentration with GOES-R ABI Presented by Yinghui Liu 1

Ice Cover and Sea and Lake Ice Concentration with GOES-R ABI Presented by Yinghui Liu 1 Team Members: Yinghui Liu 1 , Jeffrey R Key 2 , and Xuanji Wang 1 1 UW-Madison CIMSS 2 NOAA/NESDIS/STAR. GOES-R AWG Cryosphere Team. 1. 2011 GOES-R AWG Annual Meeting, June 13-16, Fort Collins, CO.

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Ice Cover and Sea and Lake Ice Concentration with GOES-R ABI Presented by Yinghui Liu 1

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  1. Ice Cover and Sea and Lake Ice Concentration with GOES-R ABI Presented by Yinghui Liu1 Team Members: Yinghui Liu1, Jeffrey R Key2, and Xuanji Wang1 1UW-Madison CIMSS 2NOAA/NESDIS/STAR GOES-R AWG Cryosphere Team 1 2011 GOES-R AWG Annual Meeting, June 13-16, Fort Collins, CO

  2. Outline • Executive Summary • Algorithm Description • ADEB and IV&V Response Summary • Requirements Specification Evolution • Validation Strategy • Validation Results • Summary 2

  3. Executive Summary • The GOES-R Ice Cover and Sea and Lake Ice Concentration are Option 2 products. • Software Version 5 was delivered in May 2011. ATBD (100%) is on track for a August delivery. • The algorithm has been developed and tested using MODIS, and SEVIRI data as proxy, and validated with the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) products. • Validation studies indicate spec compliance

  4. Algorithm Description Ice Cover: A binary yes/no detection of ice cover over ocean, inland lakes, and rivers. Ice Concentration: The fraction (in tenths) of the sea or lake surface covered by ice. MODIS true color image over Great Lakes on February 24 2008.

  5. Algorithm Description Ice Cover Ice cover Detection: Ice or snow covered ice show high NSDI value and high reflectance at visible and near-infrared bands. NDSI=(Rvis-Rswir) /(Rvis+Rswir) NDSI value: Water: ~ 0.5 New ice: ~ 1.0 Snow ice: ~ 1.0 Cloud: ~ 0.0 8% 5 Reflectances of ice, clouds, and water (Riggs et al. 1999).

  6. Algorithm Description Ice Cover Ice/snow surface temperature is retrieved by the following equation (Key et al. 1997). Ts = a + b T11 + cT12 + d [(T11-T12)(sec-1)] Ts = the estimated surface temperature (K) T11 = the brightness temperatures (K) at 11 um T12 = the brightness temperatures (K) at 12 um  = sensor scan angle a, b, c, d = coefficients, derived for the following temperature ranges: T11 < 240K, 240K < T11 < 260K, T11 > 260K. The 6 6

  7. Algorithm Description Ice Cover • In daytime, pixels with both NDSI and reflectance larger than set thresholds, with surface temperature lower than set thresholds are ice. • NDSI in this algorithm is defined as NDSI=(R1-R2)/(R1+R2) • R1 = reflectance at GOES-R ABI ch 3, 0.865 m • R2 = reflectance at GOES-R ABI ch 5, 1.61 m • Threshold : 0.6 • Reflectance at near infrared channel, 0.865 m • Threshold 0.08 • At nighttime, pixels with surface temperature lower than set thresholds are ice. 7

  8. Algorithm Description Ice Concentration Ice Concentration: Ice reflectance (temperature) change linearly with ice concentration Pure ice Reflectance Pure water Temperature

  9. Algorithm Description Ice Concentration Fractional ice concentration for each pixel (Fp) in a search window is then calculated as • Fp = (Bp - Bwater) / (Bice – Bwater) • Bwater = the reflectance/temperature (K) of a pure water pixel • Bice = the reflectance/temperature (K) of a pure ice pixel • Bp = the observed reflectance/temperature (K) of the pixel. • In this algorithm, reflectance at GOES-R ABI channel 2 (0.64 m) is used during the day, and surface temperature is used at night. • The spatial resolution is 0.5 km at 0.64 m channel, and 2.0 km for surface temperature at sub-satellite FOV • Bice is determined using tie-point algorithm; Bwater is parameterized. 9

  10. Ice cover and concentration algorithm begin ABI channel radiance, satellite viewing angles, cloud mask, land/water mask Group-criteria detection Ice Tie point algorithm Ice concentration Ice cover and concentration algorithm end Ice cover Algorithm Description High Level Flowchart of the ice concentration and extent algorithm step1 step2 step3 10 10

  11. Algorithm Changes from 80% to 100% • A new test, using the ice surface temperature in the daytime for ice detection is added in the version 5 code. • Pure water surface reflectance is parameterized as a function of water salinity and solar zenith angle. In the 80% version, it is a constant value. • Metadata output added • Quality flag added 11

  12. ADEB and IV&V Response Summary • All comments on ATBD clarification have been addressed. • Suggestions on algorithm improvement have been considered and implemented. • Suggestions on validation work are taken and more extensive validation work is undergoing. • Feedback:I would recommend to explain this clearly in the beginning and possibly modify the title of ATBD to reflect “the ice over water” application, i.e. no land ice applications are included. • Response:In the beginning of the ATBD, we point out that the ice concentration is only retrieved in ABI pixels over water surfaces covered with ice.

  13. ADEB and IV&V Response Summary • Feedback:Explain why temperature thresholds are not used during daytime ice detection. This would make algorithm more consistent between daytime and night time scenes. • Response:We added a new test, using the temperature in the daytime ice detection, in the version 5 code and updated this in the ATBD. • Feedback:While ATBD contains interesting comparisons between retrievals from MODIS, SEVIRI and AMSR-E, it requires more systematic analysis and quantitative evaluation of its performance. For 80% ATBD level, the material is likely adequate. • Response:More systematic analysis and quantitative validation of the products are undergoing using AMSR-E, ice charts, and Landsat data.

  14. Requirements Specification Evolution FD – FullDisk • February 2009 • Ice Cover / Landlocked: Change the accuracy from Binary yes/no detection to 85% correct detection. • Change the name to 'Ice Cover'. • Sea & Lake Ice: Extent: Delete product.

  15. Requirements Specification Evolution No changes in specification in ice concentration

  16. Validation Strategy Ice Cover and Sea and Lake Ice Concentration retrieved from MODIS data as proxy were validated with ice cover and concentration from the AMSR-E product as truth. • AMSR-E Level 3 product provides ice concentration over the Great Lakes and the Arctic Ocean. Ice cover is assigned when ice concentration is larger than 15%. • Ice cover and sea and lake ice concentration retrievals uses the GOES-R ABI algorithm, and MODIS data as proxy. • Two datasets are matched daily by averaging the retrieved product in the footprint of AMSR-E product. • Validation statistics are computed based on 1,576,298 matched pairs covering different seasons.

  17. Validation Strategy • Validate of ice cover and concentration retrievals using MODIS data as proxy with ice cover and concentration results from Landsat , which has much higher spatial resolution, and ice charts, which have better spatial resolution than AMSR-E, are undergoing. Meanwhile, validation with AMSR-E are continuing. 17

  18. Validation Strategy Ice concentration over Great Lakes Lake ice concentration (%) with MODIS Aqua data (left), MODIS true color image (middle), and from AMSR-E (right) over Great Lakes on February 24 2008. 18

  19. Validation Results Ice cover • Performance of Ice Cover product • The product measurement accuracy is higher than required 85% correct detection.

  20. Validation Results Ice concentration • Performance of Ice Concentration product • The product measurement accuracy and precision meet the requirement.

  21. Validation Results Ice concentration Performance of ice concentration product Frequency distribution of ice concentration differences between the AMSR-E product and retrievals using the ABI algorithm based on selected 41 clear day MODIS data in four seasons in 2007 over the Arctic Ocean.

  22. Summary • ABI allows us to monitor ice conditions at high temporal and spatial resolution. • The ice cover product is generated using group threshold tests. Comparison of ice cover products using MODIS as proxy with AMSR-E shows that products exceed the required detection accuracy of 85%. • The ice concentration product is produced using a tie-point algorithm. Validation of this product with the AMSR-E product shows that products meet the required measurement accuracy and precision. • Further tuning of the algorithm, including test thresholds in the group threshold test, and parameters in tie-point algorithm are needed. More quantitative validation of the products with AMSRE and other available products, including ice chart, and data from LANDSAT are undergoing.

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