NESDIS Global Automated Satellite Snow Product: Current Status and Planned Upgrades Peter Romanov
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1 NESDIS Global Automated Satellite Snow Product: Current Status and Planned Upgrades Peter Romanov NOAA-CREST, City University of New York (CUNY) Center for Satellite Applications and Research (STAR), NOAA/NESDIS
2 Outline Overview of the system/product Performance in VIIRS snow Planned Improvements
3 Global Multisensor Automated Snow/Ice (GMASI-Autosnow) Mapping System: Overview Objective: Generate daily spatially-continuous global snow/ice cover product for use in NWP models and other operational applications Approach: Synergy of satellite observations in the visible/infrared and in the microwave - Currently Metop-B AVHRR and SSMI/SSMIS on DMSP F-15 to F19 Recurrent gap-filling if no valid retrieval is made on the current day
4 Daily Snow/Ice Map Current day snow/ice map becomes available at ~10AM UTC the next day Projection: Plate Carree, x (or about 4 km grid cell size) On the Web:
5 Autosnow: Current Status No changes to the operational system since 2014 Operational system maintained by NESDIS Routine validation and quality evaluation are ongoing Product application: - IMS - S-NPP IDPS (VIIRS and OMPS retrievals) Further development/improvement of the system is not funded
6 Season Snow and ice fraction is obtained by aggregating 4 km retrievals within 10x10 grid cell boxes
7 Snow Extent Monitor, NH Northern Hemisphere Snow area extent over N. Hemisphere and all continents is updated daily North America Eurasia Online at
8 Snow Extent Monitor, SH South America Estimated yearly min snow extent: 33,000-39,000 km 2 Compare to 25,500 km 2 glacier total area extent (USGS) Australia & New Zealand Southern Africa Online at
9 Autosnow vs insitu data Performed daily, mostly CONUS area Agreement on snow/no-snow - Mostly above 80% in winter - Over 90% yearly average Percent of correct snow and correct no-snow identifications Station data are not quality controlled! Errors in the in situ dataset may reduce the agreement by 1-2%
10 Autosnow vs IMS Percent of daily snow and no-snow identifications consilient with IMS Products compared daily More snow mapped by IMS in late spring Agreement between products in NH - Over 90% in winter - Yearly mean: 96.2% ( ), 96.0% ( )
11 Snow Extent Anomalies Snow area extent daily anomalies, AutoSnow and IMS Correlation of daily snow extent anomalies, Autosnow vs IMS: in North America in Eurasia in N. Hemisphere
12 VIIRS Snow Products - Binary and Fractional Snow Cover Maps m nominal spatial resolution - Universal cloud mask applied to all products - Snow Fraction: simplistic algorithm, will be replaced Feb 19, 2015 S-NPP VIIRS Binary Snow Snow Land Cloud No data
13 VIIRS Snow vs MODIS and AVHRR Mean agreement to IMS and cloud-clear fraction of daily automated snow products in 2013 Northern Hemisphere * Cloud-clear fraction is estimated in N latitude band VIIRS: Marginally better accuracy but smaller effective clear-sky coverage : VIIRS cloud-clear fraction increased to 40.7% while the rate of agreement to IMS dropped to 97.8%
14 VIIRS: Too conservative cloud mask Cloud cover is frequently overestimated Snow/no-snow transition zones are typically mapped as cloudy snow land cloud No data
15 Further Plans Potential improvements - Improve resolution to 2 km globally (2 km SH map is operational) - Add topographic correction (available in SH) - Add AMSR2/GCOM-W1 - Add VIIRS - This may introduce inhomogeneity/inconsistency to the time series Reprocess historical data, fill in existing data gaps - Request from the GPM group for time series back to 1998 All plans are dependent on the future funding of the project
16 Links NESDIS STAR Automated snow remote sensing page: NESDIS OSDPD Operational Automated Snow Maps: Peter Romanov
17 THANK YOU
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