CoastWatch Global Sectors

VIIRS - Sea Ice Concentration, Ice Thickness, Ice Surface Temperature

jebidiah.jeffery — Thu, 17 Mar 2022 14:32:41 +0000

VIIRS - Sea Ice Concentration, Ice Thickness, Ice Surface Temperature

VIIRS Sea Ice Concentration, Sea Ice Thickness and Ice Surface Temperature NOAA CoastWatch/OceanWatch/PolarWatch Level 3, Daily and daily 4-day rolling merged, mapped composites in both polar stereographic projections and CW sector mapped for Northern and Southern hemispheres.

jebidiah.jeffery Thu, 03/17/2022 - 10:32

VIIRS Sea Ice Concentration, Sea Ice Thickness and Ice Surface Temperature, NOAA CoastWatch/OceanWatch/PolarWatch Level 3, Daily and daily 4-day rolling merge, mapped composites are nominally at native spatial resolution (~750 m), clear sky only.

North Polar (NP06) and South Polar (SP06) are Polar Stereographic projected daily composites
Six Northern hemisphere and six Southern hemisphere high latitude CoastWatch VIIRS sectors (see sector map below)
- North Sectors: UZ, VZ, WZ, XZ, YZ, ZZ
- South Sectors: UW, VW, WU, XW, YW, ZW

Map of CoastWatch regional sectors

Data Provider: JPSS Center for Satellite Applications and Research Cryosphere Team

STAR Cryosphere Environmental Data Record Team Lead: Jeff Key

Sea ice age is defined as the time that has passed since the formation of the surface layer of an ice covered region of the ocean.

Sea ice concentration is the fraction of a horizontal cell covered by ice.

NDE Enterprise Ice Age/Thickness Algorithm

One-dimensional Thermodynamic Ice Model (OTIM):

Based on the surface energy budget at thermo-equilibrium state
Independent of historical records for ice thickness and age estimation
Capable of retrieving daytime and nighttime sea and lake ice thickness under both clear and cloudy sky conditions

IDPS Sea Ice Concentration is an intermediate product (IP)

Algorithm computes ice fractions based on ice and water tie points determined from VIIRS I1 (0.64 µm) and I2 (0.865 µm) reflectance and surface temperature from the VIIRS Surface Temperature IP

Enterprise Sea Ice Concentration Algorithm

Use threshold tests to detect possible ice cover: Daytime and Nighttime
Use a tie-point algorithm to derive reflectance (temperature) for pure ice pixel, and then calculate ice concentration

https://stratus.ssec.wisc.edu/cgi-bin/amsr2snow_prod?seaice

Temporal Coverage

Daily and
Daily 4-day rolling merge

Product Families

Polar Sea Ice

Wang, Xuanji and Key, Jeffrey R., NOAA/NESDIS Center for Satellite Applications and Research, Algorithm Theoretical Basis Document: ABI and VIIRS Ice Thickness and Age, Version 1.0, 17 December 2015.

Ice Age ATBD (NDE), (PDF, 2.6 MB)

Liu, Yinghui and Key, Jeffrey R.,, NOAA/NESDIS Center for Satellite Applications and Research, Algorithm Theoretical Basis Document: Ice Surface Temperature, Ice Concentration, and Ice Cover, Version 1.0, 17 December 2015.

Ice Cover ATBD (NDE), (PDF, 1.69 MB)

EDR Long Term-Monitoring

Data Viewer at STAR: VIIRS Sea Ice; AMSR-2/ GCOM-W1 Sea Ice
University of Wisconsin Cryo Team CIMSS website

Measurements

Sea Ice Concentration

Sea Ice Temperature

Sea Ice Thickness

Visible And Near IR Radiometry

Processing Levels

Level 3

Spatial Coverage

CoastWatch Global Sectors

Polar (Artic/Antarctic)

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

about 12 to 24 h

Spatial Resolution Groups

100m < 2km

Spatial Resolution Details

Nominal 750 m

Platforms

NOAA

SNPP

Instruments

VIIRS

Data Providers

NOAA

NESDIS

OSPO

STAR

CoastWatch

Cryosphere Team

Data Tool Links

CoastWatch Near Real-Time Search Tool

S-NPP & NOAA-20:

Sample Filenames

VXSCCW_B2019203_C244_011341-233757_NP06_edgemask_IceConc.nc
VXSCCW_B2019203_C103_011341-232508_UZ00_edgemask_IceConc.nc
VXSACW_B2019203_C246_002354-224644_SP06_edgemask_IceThickness.nc
VXSCCW_B2019203_C102_003351-224644_VW00_edgemask_IceSrfTemp.nc
VXSCCW is
B2019201 is Year and day of year as BYYYYdoy
C### is number of granules in composite
Series of 6-digit numbers are the range of granule start times included in composite
UZ00, for example, is sector indicator (see Description tab for sector map) for equatorial projection
NP06 or SP06 is indicator for polar stereographic projection from the 6 sectors regions (North or South)
edgemask
Product DescriptionIceConc = Ice Concentration
IceThickness = Ice Thickness
IceSrfTemp = Ice Surface Temperature

North Polar (NP06) and South Polar (SP06) are Polar Stereographic projected daily composites from the 6 CoastWatch VIIRS sectors

UZ, VZ, WZ, XZ, YZ, ZZ Northern high latitude CoastWatch VIIRS sectors (see sector map below)

UW, VW, WU, XW, YW, ZW Southern high latitude CoastWatch VIIRS sectors (see sector map below)

THREDDS

Aggregated and Per-File View

Ice Thickness:

S-NPP:
- Daily merge: https://www.star.nesdis.noaa.gov/thredds/socd/coastwatch/catalog_viirs_npp_ice_thick_daily.html
- Daily 4-day rolling merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_npp_ice_thick_4day.html
NOAA-20:
- Daily merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_n20_ice_thick_daily.html
- Daily 4-day rolling merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_n20_ice_thick_4day.html

Ice Surface Temperature:

S-NPP:
- Daily merge: https://www.star.nesdis.noaa.gov/thredds/socd/coastwatch/catalog_viirs_npp_ice_temp_daily.html
- Daily 4-day rolling merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_npp_ice_temp_4day.html
NOAA-20:
- Daily merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_n20_ice_temp_daily.html
- Daily 4-day rolling merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_n20_ice_temp_4day.html

Ice Concentration:

S-NPP:
- Daily merge: https://www.star.nesdis.noaa.gov/thredds/socd/coastwatch/catalog_viirs_npp_ice_conc_daily.html
- Daily 4-day rolling merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_npp_ice_conc_4day.html
NOAA-20:
- Daily merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_n20_ice_conc_daily.html
- Daily 4-day rolling merge: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_viirs_n20_ice_conc_4day.html

Top Level Sea Ice Catalog

https://www.star.nesdis.noaa.gov/thredds/socd/coastwatch/catalog_coastwatch_ice.html

ERDDAP

S-NPP:

https://coastwatch.noaa.gov/erddap/search/index.html?page=1&itemsPerPage=1000&searchFor=nppice

NOAA-20:

** Not yet available **

NOAA MSL12 Ocean Color - Science Quality - VIIRS SNPP

jebidiah.jeffery — Thu, 17 Mar 2022 14:30:02 +0000

NOAA MSL12 Ocean Color - Science Quality - VIIRS SNPP

VIIRS Science Quality Ocean Color Level 2 (EDR) is produced by NOAA/STAR Ocean Color Team through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) using an improved calibration for the satellite data record (OC-SDR, which is Level 1b). CoastWatch Level-3 composites, binned and mapped data products also available.

jebidiah.jeffery Thu, 03/17/2022 - 10:30

The current VIIRS SNPP science quality collection, released in CoastWatch as of 07 August 2017, is produced from MSL12 v1.2* using OC-SDR v04. VIIRS NOAA-20 Science Quality is currently in development. NOAA-20 Near real-time is already available.

Ocean Color satellite sensors measure visible light at specific wavelengths which leaves the surface of the ocean and arrives at the top of the atmosphere where the sensor is located. nL_w, can be calculated. nL_ws are used to derive other ocean properties such as the concentration of chlorophyll-a (chlor-a, chlora, or sometimes chl , which is the green pigment responsible for photosynthesis and therefore and indicator of the amount of phytoplankton biomass in the ocean water) and the coefficients for attenuation of downwelling irradiance (K_d(PAR) and K_d(490) which are related to water clarity).

The ocean color datasets described here are from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi-NPP satellite (SNPP) which was launched in November 2011 and aboard the NOAA-20 which was launched in November 2017. The ocean color science quality collection differ in several ways from the near real-time products (Table 1).

*Note that the metadata in the NetCDF files show v1.20 from the beginning of the collection (2 Jan. 2012) up tthrough 24 April 2017 and v1.21 from 25 April 2017 forward. This version change did not affect retrieval values for the standard products served by CoastWatch.

Table 1. Comparison of primary processing differences for VIIRS SNPP near real time versus science quality ocean color data.

Parameter	Near real-time	Science Quality
Latency	~12 hours (best effort)	Delayed 15 days
Sensor Data Record (SDR)	IDPS Operational SDR	SDR produced by the NOAA/STAR ocean color team
Ancillary Data	Predicted	Assimilated
Spatial Coverage	May have gaps	As complete as possible

Standard VIIRS SNPP ocean color data Level 2 products from MSL12 v1.2(both near real-time and science quality) include:

Normalized water-leaving (nL_w) radiance at 6 visible bands (nominal center wavelengths)
- M1 (410nm)
- M2 (443nm)
- M3 (486nm)
- M4 (551nm)
- M5 (671nm)
- I1 (638 nm)
Chlorophyll-a concentration
Diffuse attenuation coefficient at 490 nm (K_d(490)), and
Diffuse attenuation coefficient of photosynthetically active radiation (K_d(PAR))
QA Score (a quantitative assessment of VIIRS ocean color performance with respect to an empirical catalog of in situ spectra, Wei et al., 2016; see reference tab)

See Table 2 for quick reference matrix of additional science quality VIIRS ocean color products. The Ocean Color Granule Selector is a tool to interactively preview, choose and download L2 granule files. Data files are in NetCDF4/CF but differ from past NOAA CoastWatch products in their use of hierarchical groups to store attributes, variables, and dimensions. CoastWatch Utilities Software has been updated to work with these files. Additional metadata can be obtained using THREDDS services such as ISO or OPeNDAP.

Table 2. Quick reference matrix of science quality VIIRS ocean color products available from CoastWatch.


Product Description	Processing Level	Nominal Spatial Resolution	Chl-a	nLws	K_d(PAR)	K_d(490)	QA Score
Daily granule @750 m	L2	750 m	X	X	X	X	X
Daily merged global sectorized *	L3	750 m	X	X	X	X	not currently available
7-day merged global sectorized *	L3	750 m	X	X	X	X	not currently available
True monthly merged global sectorized *	L3	750 m	X	X	X	X	not currently available
Daily merged global single file	L3	4 km	X	X	X	X	X
7-day merged global single file	L3	4 km	X	X	X	X	X
Monthly merged global single file	L3	4 km	X	X	X	X	X

*See Figure 1 for description and identification of sectors.

Level-2 science quality ocean color products are organized by Year and Day-of-the-Year. Filenames will appear as follows: V2017187003435_NPP_SCINIR_L2.nc where:

V:	Sensor VIIRS
2017:	Year of observation (YYYY)
187:	Day of year for the observation (DDD)
003435:	Hour, minutes, and seconds of the start of observation (hhmmss) in UTC
NPP:	Spacecraft S-NPP
SCINIR:	Sensor data record source and environmental data record algorithm. Indicates the standard Science Quality output for distribution
L2:	Processing level. L2 includes calibrated and geolocated geophysical products

Figure 1. Twenty-four sectors identified for file naming convention. Sectors enable downloads of select subset regions from global high resolution VIIRS ocean color science quality data.

Temporal Start Date

January 2, 2011

Temporal Coverage

SNPP: 02 January 2011 through 15 days before present (15 day delay on Science Quality)
NOAA-20: TBD - coming soon

Product Families

Ocean Color

Algorithm Theoretical Basis Document (ATBD): Wang, M., X. Liu, L. Jiang and S. Son, "The VIIRS Ocean Color Products", Algorithm Theoretical Basis Document Version 1.0, 68 pp., June 2017.
Sun, J., X. Xiong, E. Waluschka, and M. Wang, 2016, "Suomi National Polar- Orbiting Partnership Visible Infrared Imaging Radiometer Suite polarization sensitivity analysis", Appl. Opt., 55, 7645-7658 (2016). doi:10.1364/AO.55.007645
Wang, M. and S. Son, 2016, "VIIRS -derived chlorophyll-a using the ocean color index method", Remote Sens. Environ ., 182, 141-149 (2016). doi:10.1016/j.rse.2016.05.001
Sun, J. and M. Wang, 2016, "VIIRS reflective solar bands calibration progress and its impact on ocean color products", Remote Sens., 8, 194 (2016). doi:10.3390/rs8030194
Sun, J., M. Chu, and M. Wang, 2016, "Degradation nonuniformity in the solar diffuser bidiretional reflectance distribution function", Appl. Opt ., 55, 6001-6016 (2016). doi:10.1364/AO.55.006001
Wang, M., 2016, "Rayleigh radiance computations for satellite remote sensing: accounting for the effect of sensor spectral response function", Opt. Express, 24, 12414-12429 (2016). doi:10.1364/OE.24.012414
Wang, M., P. Naik, and S. Son, 2016, "Out-of-band effects of satellite ocean color sensors", Appl. Opt ., 55, 2312-2323 (2016). doi:10.1364/AO.55.002312
Wang, M., W. Shi, L. Jiang, and K. Voss, 2016, "NIR- and SWIR-based on-orbit vicarious calibrations for satellite ocean color sensors", Opt. Express, 24, 20437-20453 (2016). doi:10.1364/OE.24.020437
Sun, J. and M. Wang, 2015, "On-orbit calibration of Visible Infrared Imaging Radiometer Suite reflective solar bands and its challenges using a solar diffuser", Appl. Opt ., 54, 7210-7223 (2015). doi:10.1364/AO.54.007210
Sun, J. and M. Wang, 2015, "On-orbit characterization of the VIIRS solar diffuser and solar diffuser screen", Appl. Opt ., 54, 236-252 (2015). doi:10.1364/AO.54.000236
Sun, J. and M. Wang, 2015, "Radiometric calibration of the Visible Infrared Imaging Radiometer Suite reflective solar bands with robust characterizations and hybrid calibration coefficients", Appl. Opt ., 54, 9331-9342 (2015). doi:10.1364/AO.54.009331
Son, S. and M. Wang, 2015, "Diffuse attenuation coefficient of the photosynthetically available radiation K_d(PAR) for global open ocean and coastal waters", Remote Sens. Environ., 159, 250-258 (2015). doi:10.1016/j.rse.2014.12.011
Wang, M., W. Shi, L. Jiang, X. Liu, S. Son, and K. Voss, 2015, "Technique for monitoring performance of VIIRS reflective solar bands for ocean color data processing", Opt. Express, 23, 14446-14460 (2015). doi:10.1364/OE.23.014446
Xiong, X., J. Sun, J. Fulbright, Z. Wang, and J. Butler, 2015, "Lunar calibration and performance for S-NPP VIIRS reflective solar bands", IEEE Trans. Geosci . Remote Sens., 54, 1052-1061 (2015). doi:10.1109/TGRS.2015.2473665
Sun, J. and M. Wang, 2014, "Visible Infrared Imaging Radiometer Suite solar diffuser calibration and its challenges using solar diffuser stability monitor", Appl. Opt ., 53, 8571-8584 (2014). doi:10.1364/AO.53.008571
Mikelsons, K., M. Wang, L. Jiang, and M. Bouali, 2014, "Destriping algorithm for improved satellite-derived ocean color product imagery", Opt . Express, 22, 28058-28070 (2014). doi:10.1364/OE.22.028058
Sun, J., M. Wang, L. Tan, and L. Jiang, 2014, "An efficient approach for VIIRS RDR to SDR data processing", IEEE Geosci . Remote Sens. Lett ., 11, 2037-2041 (2014). doi:10.1109/LGRS.2014.2317553
Jiang, L. and M. Wang, 2014, "Improved near-infrared ocean reflectance correction algorithm for satellite ocean color data processing", Opt. Express, 22, 21657-21678 (2014). doi:10.1364/OE.22.021657
Jiang, L. and M. Wang, 2013, "Identification of pixels with stray light and cloud shadow contaminations in the satellite ocean color data processing", Appl. Opt., 52, 6757-6770 (2013). doi:10.1364/AO.52.006757
Wang, M., X. Liu, L. Tan, L. Jiang, S. Son, W. Shi, K. Rausch, and K. Voss, 2013, "Impacts of VIIRS SDR performance on ocean color products", J. Geophys . Res. Atmos., 118, 10347-10360 (2013). doi:10.1002/jgrd.50793

Measurements

Chlorophyll-a Concentration

Diffuse Attenuation Coefficients

Normalized Water-Leaving Radiances

Ocean Color Quality Score

Processing Levels

Level 2

Level 3

Spatial Coverage

Global

CoastWatch Global Sectors

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

~12-24 h

Spatial Resolution Groups

100m < 2km

2km+

Spatial Resolution Details

750 m @ Nadir; ~1.7 km at swath edge full resolution in L2 granules
L3 mapped to 24 sector files (see description tab).
And 4 km L3 reduced resolution global mapped in one file.

Platforms

SNPP

Instruments

VIIRS

Processing Algorithms

MSL12

Data Providers

NOAA

NESDIS

STAR

Data Tool Links

Daily Level-2, granule/swath data:

Granule Overlays via CoastWatch Data Portal

CoastWatch Data Portal Spatial Search Tool (Temporal/Spatial Search)

Global 4km:

Daily

Sample Filenames

V2011355013534_NPP_SCINIR_L2.nc

HTTPS

Daily, global, Level 2 granule/swath (nominal 750 m)

https://coastwatch.noaa.gov/pub/socd1/mecb/coastwatch/viirs/science/L2/

Global, Level 3 merged single file, ~4 km

Chlorophyll-a: Daily Weekly Monthly
Diffuse Attenuation Coefficient (K_d(490) and K_d(PAR): Daily Weekly Monthly
Normalized Water Leaving Radiances (nLw’s, all bands): Daily Weekly Monthly

THREDDS

Top Level of Science Quality, Life of Mission THREDDS catalog

Daily, global, Level 2 granule/swath (nominal 750 m)THREDDS Catalog

Global, Level 3 merged single file, ~4 km

Chlorophyll-a: Daily Weekly Monthly
Diffuse Attenuation Coefficient (K_d(490) and K_d(PAR)): Daily Weekly Monthly
Normalized Water Leaving Radiances (nLw’s, all bands): Daily Weekly Monthly

Global, Level 3 merged sectorized files, ~750 m (see sector map under description tab)*

Chlorophyll-a: Daily Weekly Monthly
Diffuse Attenuation Coefficient (K_d(490) and K_d(PAR)): Daily Weekly Monthly
Normalized Water Leaving Radiances (nLw’s, all bands): Daily Weekly Monthly

*Note, CW sector 750 m merge files are currently available through ~early January 2019 and are filling in as processing is completed.

NOAA CoastWatch co-gridded VIIRS SST from ACSPO

jebidiah.jeffery — Thu, 21 Oct 2021 15:58:41 +0000

NOAA CoastWatch co-gridded VIIRS SST from ACSPO

NOAA CoastWatch co-gridded VIIRS SST products are Level 3 daily composites in compatible format and projection with other CoastWatch Level 3 sector and global products (such as CoastWatch sector VIIRS ocean color). Twenty four CoastWatch sector files mapped to equatorial projection that cover the globe (see Description tab for sector definitions) two polar stereographic sectors in 750 m nominal, native resolution and a global, 4 km resolution, single file mapped product is also available. These CoastWatch Level 3 products are generated from ACSPO L2P SST as input.

jebidiah.jeffery Thu, 10/21/2021 - 11:58

NOAA CoastWatch creates these co-gridded AVHRR SST Level 3 daily composites to be compatible in format and projection with the VIIRS Ocean Color Level 3 daily composites (Note VIIRS sector full resolution is 750m). The input for these CoastWatch Sector SST files is daily, near real time ACSPO SST for AVHRR.

These SST products are intended for users who seek AVHRR ACSPO SST data co-registered with CoastWatch ocean color data from AVHRR and are not the NOAA operational L3U ACSPO products. The CoastWatch co-gridded products are available in regional Sectors at full 1.2 kilometer AVHRR resolution and as global products at 4 km resolution. The regional products consist of 24 sectors (see Sector map below) mapped to the VIIRS ocean color sectors, and polar stereographic regions NP06 and SP06 mapped identically to the CoastWatch VIIRS ice products. The 4 km global product is also mapped identically to the corresponding CoastWatch VIIRS ocean color product.

CoastWatch Regional Sectors

These products start with the operational ACSPO L2P product (in the canonical ten-minute granule form), ingest that for CoastWatch processing, and then georegister and mask those granule-level products. The mask applied is 0xC002.That rejects pixels flagged 0x40, 0x80, and 0xC0 (anything but confident clear) and pixels flagged 0x02 (land). The L3 masked granule products are aggregated to a daily product on the same grid on the basis of the last pixel seen. The 4 km global product is created by averaging the non-null values for the pixels of the daily sector maps in a 5x5 grid.

Note: CoastWatch also distributes a gap-filled polar plus geosynchronous blended daily SST analysis product suite at 5 km resolution.

Short Names

CW Sector SST

Temporal Coverage

Daily

Product Families

Sea Surface Temperature

Measurements

Sea Surface Temperature - Polar-orbiting

Processing Levels

Level 3

Spatial Coverage