Photo credit: D.K. Hall / NASA Visible and Near-Infrared Systems and Publicly-Available Products for Studies of Seasonal Snow Cover Dorothy K. Hall Cryospheric Sciences Laboratory NASA / GSFC, Greenbelt, Md. NASA Snow Remote Sensing Workshop CIRES - University of Colorado Boulder, Colorado 14 August 2013

snowcrystals.com What advances have led to the current state of snow mapping using visible and near-IR sensors?

Image from TIROS-1, the First Successful Weather Satellite TIROS=Television and Infrared Observation Satellite TIROS provided data for the first accurate weather forecasts based on data gathered from space. TIROS began continuous coverage of the Earth's weather in From NASA:

Snow Mapping from Space in 1962

Issues in the 1960s Spatial resolution Snow / cloud discrimination Snow depth

From: Barnes & Bowley, 1966, WRR, 4(2): Snow Extent and Snow Depth Mapping from Space Accuracy of snow mapping from TIROS or ESSA data was estimated to be ±32 km in 1966 Apt is automatic picture transmission

NOAA visible climate data record Nov 1966 Oct 1972 May s May 1999 Feb 1997 Feb 2004 ESSA, NOAA, GOES Series Weekly 190 km digitized METEOSAT & GMS added Reanalysis of IMS 24 kmIMS 4 km 7 Slide courtesy of Dave Robinson/Rutgers Univ. The NESDIS product had not been envisioned at first as a CDR; more standardized mapping was instituted in the 1970s.

Launch of ERTS-1 (Landsat-1) in 1972 allowed snow- cover mapping at ~80-m spatial resolution once every 18 days, cloud-cover permitting; Progress in the 1970s

From Colvocoresses, 1976 ERTS-1 (Landsat-1) Image of Rocky Mts., 11 January 1973 Rocky Mts. Snow mapping was largely accomplished using hard- copy images and manual techniques in the 1970 and early 1980s.

First NOAA Advanced Very High Resolution Radiometer (AVHRR) was launched in 1978 on TIROS-N; NOAA NESDIS snow maps were being produced weekly for the Northern Hemisphere and in an increasingly- consistent manner. Progress in the 1970s, cont’d.

NOAA Northern Hemisphere Snow Chart NOAA / NESDIS NESDIS provided weekly snow maps such as this one from 1972 – 1997 at ~190 km spatial resolution

Early Landsat (MSS): Could not separate snow and most clouds; Low dynamic range of MSS instrument over snow; 18-day repeat was not frequent enough; Cloud cover obscured the surface too often. Need more-frequent coverage at good spatial resolution with snow/cloud discrimination; TM band 5 (1.6 µm)* under development for objectively separating snow from clouds with an expected launch in 1982 (Barnes and Bowley, 1977). Issues in the 1970s *Decline in SWIR reflectance of snow was useful in separating snow and clouds.

Use of remotely-sensed data from satellites related to water- resources management is still lacking in several respects (V. Salomonson, in 1979): Spatial and spectral resolution; Processing of high volumes of data & high data rate*; Need 48-hour turnaround time for water-resource managers; High data rate conflicts with rapid turnaround of data and ease of processing. *We must “learn to drink from a firehose” (Salomonson & Hall 1979) referring to high data volumes to be produced by Landsat-4 TM that would be in the 10 7 to 10 8 bits/sec order of magnitude. Data rate today for Landsat-8 is ~4.5 times what it was for Landsat-4. Issues in the 1970s

“…it seems possible to simulate discharge in ungaged sites by using Landsat images of the snow cover together with temperature and precipitation data.” (Martinec and Rango, 1979). Progress in the 1970s, cont’d.

From Rango (1980), IAHS Pub. #129 Landsat-1 image of snow cover in Wyoming, 28 June 1976, showing boundaries of the Dinwoody Creek and Bull Lake Creek Basins Using a zoom transfer scope, a satellite image was superimposed on a map and the snowline was drawn onto the map. SCA was determined by planimetering.

Landsat-1-Derived Snow Cover Estimates vs. Measured Runoff in the Wind River Range, Wyo., 1973 – 1974 From Rango and Salomonson (1975)

Image saturation in snow was improved with the larger dynamic range of the TM instruments (vs. MSS) allowed great strides to be made in mapping snow cover and albedo using Landsat data in the 1980s (e.g., Dozier, 1984 & Dozier & Marks, 1987); Rosenthal and Dozier (1996) present a decision-tree classification model using Landsat TM data to map fractional snow cover in the Sierra Nevada Mts; Landsat-7 ETM+ and the MODerate-resolution Imaging Spectroradiometer (MODIS) were launched in Progress in the 1980s and 1990s

NOAA visible climate data record Nov 1966 Oct 1972 May s May 1999 Feb 1997 Feb 2004 ESSA, NOAA, GOES Series Weekly 190 km digitized METEOSAT & GMS added Reanalysis of IMS 24 kmIMS 4 km 18 Slide courtesy of Dave Robinson/Rutgers Univ.

NOAA Interactive Multisensor Snow and Ice Mapping System (IMS) NESDIS and the National Ice Center (NIC) have provided daily snow maps such as this one from 1997 – present at 25 km and 4 km (since 2004) spatial resolution

NOAA Interactive Multisensor Snow and Ice Mapping System (IMS) 1 January 2013

Daily Snow Map from Rutgers University Global Snow Lab Climate Data Record of Snow-Cover Extent 1 January 2013 NESDIS & NIC maps were elevated to the status of a snow- cover extent Climate Data Record by RUCL

D. Robinson / Rutgers Univ. Northern Hemisphere monthly average snow extents since 1966* *compared the long term average Source: Rutgers University Global Snow Lab

Publicly-Available Satellite Snow-Cover Products National Ice Center (NIC) snow- cover map Northeastern U.S. MODIS swath fractional snow-cover map, MOD10_L2 MODIS monthly snow-cover map, MOD10CM Feb Dec IMS 12 Feb Daily, weekly and monthly snow cover and SWE maps from GlobSnow NOHRSC modeled SWE map 1 Jan 2013 MODIS 500- Cloud- Gap-Filled Snow Map

Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS)* Snow-Cover Products Higher spatial resolution than MODIS (375 m); Wider swath (3000 km vs km), no orbit gaps compared to MODIS; Primarily for operational user community; Need NRT turnaround for weather forecasting. Expected continuity with MODIS to make a Climate-Data Record (CDR) of snow-cover extent. *Launched in October 2011

VIIRS Binary Snow-Cover Map* 12 February 2012 *VIIRS binary snow-cover algorithm is based on the MODIS snow-cover algorithm. cloud snow

From R. Solberg et al. GlobSnow

MEaSUREs Snow Product: blended MODIS, IMS and passive microwave Slide courtesy of Dave Robinson/Rutgers Univ. Other results from blended snow maps include those of Romanov, 2000; Hall et al., 2007; Gao et al., 2010; Foster et al., 2011;

First successful weather satellite VIIRS “Blue Marble” April 1, 1960

Conclusion Major advances in mapping snow-cover extent and snow albedo have been enabled by technological and computational advances; Many early (1960s & 1970s) issues with mapping snow were addressed by the launch of new instruments (e.g., Landsat-1 MSS in 1972 and AVHRR in 1978); Increasingly-sophisticated instruments launched in the 1980s permitted refinement of snow-mapping capabilities (e.g., Landsat-4 and -5 TM in 1982 & 1984, and an improved AVHRR in 1981); MODIS and VIIRS, first launched in 1999 and 2011, respectively, allow daily snow mapping for research and operational purposes; Blended products, such as GlobSnow, map snow cover and SWE through clouds; Snow maps from vis/near-IR sensors have improved dramatically in the last ~40 years leading to great advances; far fewer advances in mapping of snow through clouds and SWE have been possible using passive-MW sensors.