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First Workshop on EOS Snow and Ice Products 16-17 November 2004 MODIS Sea Ice Products and Validation George Riggs SSAI

First Workshop on EOS Snow and Ice Products 16-17 November 2004 MODIS Sea Ice Products and Validation George Riggs SSAI / GSFC / Code 971. Outline Sequence of products, swath to 8-day composite images and brief description Ice surface temperature validation status Collection 5 revisions

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First Workshop on EOS Snow and Ice Products 16-17 November 2004 MODIS Sea Ice Products and Validation George Riggs SSAI

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  1. First Workshop on EOS Snow and Ice Products 16-17 November 2004 MODIS Sea Ice Products and Validation George Riggs SSAI / GSFC / Code 971

  2. Outline • Sequence of products, swath to 8-day composite • images and brief description • Ice surface temperature validation status • Collection 5 revisions • Factors affecting usage of products

  3. Sequence of MODIS Sea Ice Products MOD29--swath, level-2 product in sensor sampling space MOD29P1--daily, level-3 spatially resampled (mapped) to EASE-Grid polar projection, tiled product. Intermediate L2G product generated but not archived. Day and night products. MOD29E1--daily, level-3 global EASE-Grid polar projection, Northern and Southern hemisphere maps included. MOD29E2--eight-day, level-3 global EASE-Grid polar projection, Northern and Southern hemisphere maps included. Experimental at this time.

  4. Sea Ice MOD29 2004 309 1100 UTC Ronne Ice Shelf Sea ice by reflectance features and NDSI MODIS bands, 2,4,6 1km resolution, swath ~ 2030x2340 km Cloud masking from MOD35_L2 MOD021KM bands 1,4,6 Sea_Ice_by_Reflectance

  5. Ronne Ice Shelf MOD29 2004 309 1100 UTC Ice surface temperature by split-window technique MODIS bands 31 and 32 1km resolution, swath ~ 2030x2340 km Cloud masking from MOD35_L2 MOD021KM bands 1,4,6 Ice_Surface_Temperature

  6. Quality Assessment Data • QA bit encoded • set by checks on input data within or out of nominal rage • set for cloud • type of checks done vary for reflectance and thermal data • QA varies with product level • has rarely been used Sea_Ice_by_Reflectance Sea_Ice_by_Reflectance_Pixel_QA Ice_Surface_Temperature Ice_Surface_Temperature_Pixel_QA

  7. Sea_Ice_by_Reflectance Ice_Surface_Temperature Ronne Ice Shelf Input data is L2G product in which all swaths (15 in this case) for the day have been mapped onto the projection. A scoring algorithm based on solar zenith, distance from nadir and observation coverage in a cell selects the most favorable observation for the day. MOD29P1D 1km resolution tiles are ~ 10° x 10°

  8. Sea Ice MOD29E1 2004 November 4 4km resolution Sampling technique The global 4km MOD29E1 grid is mapped over the MOD29P1 1km grid and the grid cell nearest the 4km cell center is chosen. Northern Hemisphere mapping 40° to 90° Southern Hemisphere mapping -50° to -90°

  9. MOD29E2 : 8-day composite IST EASE-Grid North Polar View South Polar View Daily global 4-km resolution ice surface temperature products - composites from May 15-19, 2000.

  10. MODIS Sea Ice Maps • Sea Ice Surface Temperature Product • Status: sea ice surface temperature product validated stage 2 • Daytime • Nighttime • North and South Polar Maps (0.05° resolution – EASE-Grid) 1 km resolution

  11. Sea ice surface temperature product (MOD29) Hall, et al., 2004 IEEE Trans. Geosci. Remote Sensing 42:1076-1087. AMSR-E AMSR image from Don Cavalieri & Al Ivanov

  12. MODIS IST Validation Study Conclusion Excellent measurement of actual temperature of sea ice during the Arctic cold period RMS error or accuracy, with bias removed, was 1.2 K for South Pole and 1.3 K for Arctic Ocean Limited to clear-sky conditions

  13. IST Potential Uses Ice conditions: details of ice floes, new and young ice, leads and recently refrozen leads, low ice concentration and ice edges can be observed in the IST imagery May be useful in energy-balance modeling Suggested possible relationship between MODIS IST and AMSR-E derived ice temperature

  14. Collection 5 Revisions MOD29 Deleted ‘Sea Ice by IST’ and ‘Combined Sea Ice’ data arrays. Spatial QA given as data values--change from bit encoding of V004. Set based on input data quality. New land water/water mask with accurate mapping of Antarctica coastlines

  15. Mosaic of MOD29P1N tiles on 20 July 2003 West Antarctica and Antarctic Peninsula shown Tiles h07v28, h08v28 h07v29, h08v29, h09v29 h07v30, h08v30, h09v30 Coastline of Antarctica is the feature of interest. The EOS land/water mask maps ice sheets as land with the coastline being the ice shelf edge. BU land/water mask maps grounding line of ice shelves as the coastline. And has a more accurate coastline elsewhere BU land/water mask EOS land/water mask

  16. Antarctic coastline map in the BU land/water mask is vastly superior to the EOS land/water mask. With the BU land/water mask; Ice shelves are correctly mapped as being on the ocean! (Mapped at grounding line not the ice edge) The BU integrated coastline map of Antarctica from the Antarctic Digital Database (www.nerc-bas.ac.uk/public/magic/add_home.html) is very accurate. (There is a newer version of that database available that adds details from -85 to -90 degrees.) The accurate Antarctic coastline map enhances comparative studies and validation work because it agrees with other data sources and maps of Antarctica and ice shelves. Snow products are improved because the ice shelves are removed from land. (Example of snow not shown because Antarctica in darkness during the July dates of the MODAPS test run.)

  17. Collection 5 Revisions MOD29P1 Deleted ‘Sea Ice by IST’ and ‘Combined Sea Ice’ data arrays. Spatial QA passed through from the MOD29 data as data values. HDF internal compression--transparent to the user.

  18. Collection 5 Revisions MOD29E1 Spatial QA given as data values--change from bit encoding of V004 HDF internal compression--transparent to the user MOD29E2 MOD29E2 New eight-day product is anticipated.

  19. Factors affecting usage of products Cloud detection (Cloud mask product related issue.) Effects differ for observation of sea ice and calculation of IST. Sea ice/cloud discrimination. Frequency of cloud cover. QA data--what is useful? Development of QA indices in the future? Data format, HDF-EOS has been troublesome for some users. Problematic detection of clouds and sea ice/cloud discrimination in the nighttime

  20. http://modis-snow-ice.gsfc.nasa.gov images news user guides literature links to other sites

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