Cryosphere Products Validation Team

1. Cryosphere Products Validation Team Sean Helfrich, NOAA/NESDIS/OSPO, Snow and Ice Product Area Lead Kathleen Cole, NWS – Anchorage Field, Sea Ice Program Leader U. S. National Ice CenterNWS AnchorageUser Perspective for Cryospheric EDR Provisional Maturity 14 November 2013

2. VIIRS CRYO EDR Product Users • Applications • Navigation • Emergency Management • Operational Weather Prediction • Climate Research • Hydrology • U.S. Users • Operational: • NIC, National/Naval Ice Center • Alaska Ice Desk • NOHRSC • Naval Research Laboratory • River Forecast Offices • Science: • STAR, Center for Satellite Applications and Research • University of Washington, Polar Science Center • GSFC, NASA/Goddard Space Flight Center Hydrological Sciences Branch

3. U.S. National/Naval Ice Center • A multi-agency operational center operated by the United States Navy, National Oceanic and Atmospheric Administration, and United States Coast Guard. • Located in Suitland, Maryland and employs ~40 military and civilian personnel. • Over 140 National and International Customers, including SUBFOR, ONI, USCG, NOAA NESDIS, NWS Field offices, NWS NCEP, NSF, MSC, and NASA. • GLOBAL sea ice analysis and forecasting. Mission: Provide global Ice and Snow analysis and forecasting services for the maximum benefit of United States government interests.

4. Limitations of Analysis and Forecasting • Satellite remote sensing provides the best opportunity for year round monitoring of global sea ice and snow conditions. • Provides a method to collect critical parameters needed to assess climate change. • In-situ observation of critical parameters while essential for validation is limited by distance, harsh environment, darkness, no available resources, and lack of infra-structure and platforms of opportunity. • Remote sensing and observation communities collaboration with the modeling communities are essential for robust forecasting. All parameters require improved monitoring, prediction, and communication of sea ice conditions.

5. US NIC Sea Ice Characterization • Current Data sources include: Synthetic Aperture Radar (SAR), MODIS Imagery, ASCAT, OSCAT, VIIRS Imagery, In-Situ Reports, AVHRR imagery, SSMI/S, and Modeled Weather, Ocean, and Ice data. • The utility of VIIRS is currently limited to interpretation based on imagery. • Sea Ice Characterization was visually examined by NIC Science Dept for selected days RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. 5

6. US NIC Sea Ice Characterization • NIC found improvements of ice/no ice compared to MODIS Algorithm RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. Key, et al, 2013. 6

7. US NIC Sea Ice Characterization • Ice Extent appears close, but appears to have omission/comission issues. Key, et al, 2013. 7

8. US NIC Sea Ice Characterization • Ice Age estimates did not appear realistic and was prone to swath/cloud issues. • NIC Ice Analysis for this date suggest very little if any New/Young Ice in these areas. RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. Key, et al, 2013. 8

9. US NIC Sea Ice Characterization • Ice extent estimates still contain lots of cloud masking and identification issues, making it difficult to assess omission/comission issues. This makes it challenging to apply when the product is valid or not. • NIC plans to use the VIIRS SIC EDR to help in ice / no ice determination in IMS Version 3. Analysts will have the discretion to apply it when the results appear to match with other data sources. • No plans for use of the Ice Age values from the SIC EDR due to erroneous results. Recommended that the algorithm be improved. • Need Products in formats for ArcGIS display (netCDF, Geotiff, .Img, Shapefiles)

10. US NIC Sea Ice Characterization Ice Concentrations are much more valuable to NIC & NRL/NAVO than the ice age with only 3 categories. NIC requests the Ice Con IP be included in the SIC EDR. RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. NASA, 2013. 10

11. US NIC Snow Cover / Fraction • Current Data sources include: Visible, IR, Passive & Active Microwave, Surface station, Model Guidance, Foreign Snow Analysis, webcams, etc. • The utility of VIIRS is currently limited to interpretation based on imagery. • Planned to be a major component to IMS Version 3 Blended Snow Cover & Snow Depth • Snow Cover/Fraction was visually examined by NIC Science Dept for selected days RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. 11

12. US NIC VIIRS Snow Cover NPP-Suomi VIIRS snow cover map Better cloud masking than MODIS, so less cloud cover omissions. VIIRS has more omission errors due to off nadir detection in through dense forest Land/Water mask difference in the products MODIS Aqua snow cover map March 2, 2013 (day 2013061) 12 From VIIRS Cryospheric Validation team

13. US NIC VIIRS Snow Cover Omission (snow miss) Commission (false snow) • When compared to IMS, VIIRS has more omission errors due to off nadir detection in through dense forest • VIIRS is likely to contain less comission errors on a daily basis than IMS under clear sky conditions. Daily VIIRS and IMS comparison statistics VIIRS binary snow cover with IMS overlaid (March 2, 2013) RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. VIIRS snow map errors: White: VIIRS & IMS snow Light Gray: VIIRS clouds Green: VIIRS & IMS snow-free land Dark gray: not processed, or no data 93-97% agreement From VIIRS Cryospheric Validation team 13

14. VIIRS Snow Fraction • NIC sees the MODIS Fraction product as superior due to its methodology of applying the NDSI. VIIRS Snow Fraction values of limited use. VIIRS snow fraction characterizes the patchiness of the snow cover MODIS snow fraction characterizes both patchiness and snow pack masking by the vegetation canopy. MODIS snow fraction is generally smaller than the VIIRS snow fraction. The difference between two snow fraction estimates is the largest over snow covered forested areas. VIIRS snow fraction MODIS snow fraction From VIIRS Cryospheric Validation team

15. US NIC VIIRS Snow Cover/Fraction Use • Snow Cover estimates has fewer cloud masking issues than MODIS, it has omission issues in forests. This makes it challenging to apply without forest fraction / scan angle adjustments. • NIC plans to use the VIIRS Snow Fraction EDR to help in snow / no snow determination in IMS Version 3. Analysts will have the discretion to apply it when the results appear to match with other data sources. This is expected to be add a significant improvement • No plans for use of the Snow Fraction values from the Snow Fraction EDR due to erroneous results. Recommended that the algorithm be improved. • Need Products in formats for ArcGIS display (netCDF, Geotiff, .Img, Shapefiles)

16. US NIC VIIRS Snow Cover/Fraction Use • Need to improve the Snow Fraction identification • Proper Snow Fraction identification will help in NWP, hydrological applications. and IMS Snow Depth assessment. • Better cloud masking combined with vegetation adjusted algorithm would help expand the utility of the snow cover and snow fraction. • Would be best uses as a part of a blended product. • Need project plans to add VIIRS to NOAA Automated Snow and Ice Cover.

17. NWS – Anchorage Sea Ice • Started in mid 1980s in NWS Fairbanks Forecast Office • Now located within the Anchorage Forecast Office • Sea ice analysis and forecast products • Sea surface temperature (SST) analysis product • Incident and weather driven 24/7/365 availability • http://pafc.arh.noaa.gov/ice.php Analysis Products Forecast Products RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image.

18. NWS – Anchorage Sea Ice

19. NWS – Anchorage Sea Ice • Current Data sources include: Synthetic Aperture Radar (SAR), MODIS Imagery, VIIRS Imagery, In-Situ Reports, AVHRR imagery, SSMI/S, and Modeled Weather, Ocean, and Ice data. • The utility of VIIRS is currently limited to interpretation based on imagery. • Sea Ice Characterization (or IST) products has not occurred yet. • Need Products in formats for ArcGIS and AWIPS 2 display (netCDF, Geotiff, .Img, Shapefiles) RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. 19

20. VIIRS I1+I2+I3 False Color RGB Image shows dense smoke (high absorption) in northwest, north central and central coastal portions of image. 20

21. VIIRS Day / Night Band

22. Conclusions • The VIIRS Snow Cover Product (which is part of the VIIRS Snow Cover EDR) will not be used by NIC, but only due to the resolution adding time for IMS to process .370km for the entire NH. • The VIIRS Fractional Snow Cover Product (which is part of the VIIRS Snow Cover EDR) will be used by only as a low resolution version of Ice Cover. Needs algorithm improvement to be apply Snow Fraction • The VIIRS Ice Age Product (which is part of the VIIRS Snow Characterization EDR) will be used by NIC on a limited basis to map ice extent, but has no utility for ice age identification. Needs algorithm improvement to be apply Ice Age product in operational ice charting or NWP assimilation. • The VIIRS Ice Concentration IP should be include in the VIIRS Snow Characterization EDR) .