Level 2

SAR Composite Arctic Imagery (normalized radar cross section)

jebidiah.jeffery — Tue, 13 Sep 2022 18:10:08 +0000

SAR Composite Arctic Imagery (normalized radar cross section)

The daily composite of Synthetic Aperture Radar (SAR) Normalized Radar Cross Section (NRCS) imagery covering the Arctic and sub-Arctic maritime regions over a period of one day are available at 1-km resolution. These high-resolution, weather- and time-agnostic measurements of surface backscatter contain detailed information tailored for sea ice classification purposes.

jebidiah.jeffery Tue, 09/13/2022 - 14:10

A composite for typical day contains around 200-400 individual scenes gathered from several C-Band SAR systems, including Sentinel-1A/B, RADARSAT-2, and RADARSAT Constellation Mission, which are calibrated with values given by the SAR data provider and are then projected and resampled onto a 1km polar stereographic grid. The files are produced in SAROPS (SAR Operational Product System) by the Water Surface Conditions/Sea Surface Roughness group within the NOAA STAR Satellite Oceanography and Climatology Division.

For further details on the individual granules that make these composites and for links to the GeoTIFF versions of these files, please see the SAR NRCS page.

Data Courtesy of the Copernicus Program, RADARSAT Constellation Mission, and the Canadian Space Agency.

Short Names

NRCS Composites

Temporal Coverage

00:00Z-23:59Z (daily)

Product Families

Sea Surface Roughness

Synthetic Aperture Radar Marine Users Manual. Ed C.R Jackson and J.R. Apel: NOAA: Washington, DC, USA, 2004. ISBN 0-16-073214-X

Measurements

Normalized Radar Cross-Section

Processing Levels

Level 2

Level 4

Spatial Coverage

Arctic and Sub-Arctic Maritime

Latency Groups

24+ hours (Delayed)

Latency Details

Generated at 14Z the following day

Spatial Resolution Groups

100m < 2km

Spatial Resolution Details

1km

Platforms

Instruments

Data Providers

Copernicus

CSA

RCM

NOAA

STAR

Data Tool Links

CoastWatch Data Portal

Near Real-Time Search

Sample Filenames

Source filenames begin with satellite, data source, year, month, day, hour, minute, second, Julian seconds, center latitude, center longitude, polarization, delimited with an underscore NRCS: S1A_ESA_2016_12_07_18_18_57_0534449937_178.66E_51.85N_VV_C5_GFS05 CDF_nrcs_level2.[png,nc]

CoastWatch distributed composites: SAR_composite_2022070T0000_2022070T2359_NP06_1km_nrcs.[png,nc]

HTTPS

https://coastwatch.noaa.gov/data/pub0022/coastwatch/composite/nrcs/arctic/

THREDDS

https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_composite_sar_nrcs_arctic_daily.html

ERDDAP

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

Synthetic Aperture Radar Imagery (NRCS)

jebidiah.jeffery — Thu, 17 Mar 2022 15:30:36 +0000

Synthetic Aperture Radar Imagery (NRCS)

Spaceborne Synthetic Aperture Radar (SAR) imagery maps the surface microwave radar reflectivity at resolutions from a sub-meter to 100 m depending on the particular SAR satellite and mode. Since a radar provides its own illumination, imagery is independent of the time of day. At typical radar frequencies, SARs can image through clouds, so SARs are considered "all-weather" instruments. Several geophysical parameters can be derived from SAR including sea surface wind speed.

jebidiah.jeffery Thu, 03/17/2022 - 11:30

Spaceborne Synthetic Aperture Radar (SAR) imagery maps the surface microwave radar reflectivity at resolutions from a sub-meter to 100 m depending on the particular SAR satellite and mode. Since a radar provides its own illumination, imagery is independent of the time of day. At typical radar frequencies, SARs can image through clouds, so SARs are considered "all-weather" instruments. Several gephysical parameters can be derived from SAR including sea surface wind speed.

For side-scanning SARs, the normalized radar cross section (NRCS) of the surface is proportional to the surface roughness on the scale of the radar wave length (from 3 to 30 cm). Ocean surface roughness on this scale is dependent on the local wind speed and direction. The higher the wind speed the larger the NRCS of the surface. The highest NRCS occurs when the radar look direction and wind direction are aligned and smallest when the radar looks cross wind.

The relationship between wind speed and direction and radar cross section is called the "geophysical model function." These functions are generally empirically determined.

Although we can predict an expected NRCS value for a given wind speed and direction, the reverse is not true. A specific NRCS value can be associated with many pairs of wind speed and direction. If we know the wind direction a priori, we can infer the wind speed.

For the operational SAR-derived wind speed products, we use the model directions from NOAA’s Global Forecast System (GFS) model on a 0.5 degree, latitude-longitude grid to initiate the retrievals. The wind speed retrievals are provided at 500 m resolution. These retrievals agree with independent wind speed estimates to better than 2 m/s.

Current users of these data include the US National Ice Center, the Alaska Weather Service, and the Naval Oceanographic Office.

A good review of SAR operational wind speed retrieval can be found at: http://tos.org/oceanography/assets/docs/26-2_monaldo.pdf

Product Families

Sea Surface Roughness

Monaldo, F.M., C.R. Jackson, and W.G. Pichel. 2013. Seasat to RADARSAT-2: Research to operations. Oceanography 26(2):34–45, http://dx.doi.org/10.5670/oceanog.2013.29
SAR Marine User Manual (2004) Christopher Jackson and John Apel, Editors

Measurements

Normalized Radar Cross-Section

Sea Surface Wind Speed

Processing Levels

Level 1

Level 2

Level 3

Spatial Coverage

Selective Acquisitions

Latency Groups

0 Hours <= 24 Hours (NRT)

Spatial Resolution Groups

0 m <= 100 m

100m < 2km

Spatial Resolution Details

NRCS: Variable, 0-10 m
Winds: 500 m

Platforms

Instruments

Processing Algorithms

SAROPS

Data Providers

Copernicus

CSA

NOAA

NESDIS

OSPO

STAR

Data Tool Links

CoastWatch Tools

CoastWatch Data Portal (select Spatial Search)

Data files: https://coastwatch.noaa.gov/data/pub0022/coastwatch/

Northern & Southern Hemisphere Products

NRCS Search Tool

XPOL Search Tool

Other Search Tools

RadarSat-2 + RCM SAR Winds Search Tool (MECB)

Sentinel-1 SAR Winds Search Tool (MECB)

RadarSat-2 + Sentinel-1 SAR Winds Search Tool (OSPO) [Formally Operational]

Sample Filenames

Filenames begin with satellite, data source, year, month, day, hour, minute, second, Julian seconds, center latitude, center longitude, polarization, delimited with an underscore NRCS: S1A_ESA_2016_12_07_18_18_57_0534449937_178.66E_51.85N_VV_C5_GFS05 CDF_nrcs_level2.png
Wind: S1A_ESA_2016_12_07_18_18_57_0534449937_178.66E_51.85N_VV_C5_GFS05 CDF_wind_level3.png

Synthetic Aperture Radar (Surface Roughness) Winds

jebidiah.jeffery — Thu, 17 Mar 2022 15:27:13 +0000

Synthetic Aperture Radar (Surface Roughness) Winds

jebidiah.jeffery Thu, 03/17/2022 - 11:27

Spaceborne Synthetic Aperture Radar (SAR) imagery maps the surface microwave radar reflectivity at resolutions from a sub-meter to 100 m depending on the particular SAR satellite and mode. Since a radar provides its own illumination, imagery is independent of the time of day. At typical radar frequencies, SARs can image through clouds, so SARs are considered "all-weather" instruments. Several gephysical parameters can be derived from SAR including sea surface wind speed.

The relationship between wind speed and direction and radar cross section is called the "geophysical model function." These functions are generally empirically determined.

Current users of these data are the US National Ice Center, the Alaska Weather Service, and the Naval Oceanographic Office.

A good review of SAR operational wind speed retrieval can be found at: http://tos.org/oceanography/assets/docs/26-2_monaldo.pdf

Product Families

Sea Surface Roughness

Sea Surface Winds

Monaldo, F.M., C.R. Jackson, and W.G. Pichel. 2013. Seasat to RADARSAT-2: Research to operations. Oceanography 26(2):34–45, http://dx.doi.org/10.5670/oceanog.2013.29
SAR Marine User Manual (2004) Christopher Jackson and John Apel, Editors

Measurements

Normalized Radar Cross-Section

Sea Surface Wind Speed

Processing Levels

Level 1

Level 2

Level 3

Spatial Coverage

Selective Acquisitions

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

Less than 24 hours

Spatial Resolution Groups

0 m <= 100 m

100m < 2km

Spatial Resolution Details

NRCS: Variable, 0-10 m
Winds: 500 m

Platforms

Instruments

Data Providers

NOAA

NESDIS

OSPO

Data Tool Links

CoastWatch Tools

CoastWatch Near Real-Time Search

Other Search Tools

Radarsat Constellation Mission / Radarsat-2 (MECB)

Sentinel-1 SAR Winds Search Tool (MECB)

Radarsat Constellation Mission + RadarSat-2 + Sentinel-1 SAR Winds Search Tool (OSPO) [Formally Operational]

Sample Filenames

Filenames begin with satellite, data source, year, month, day, hour, minute, second, Julian seconds, center latitude, center longitude, polarization, delimited with an underscore

NRCS: S1A_ESA_2016_12_07_18_18_57_0534449937_178.66E_51.85N_VV_C5_GFS05 CDF_nrcs_level2.png
Wind: S1A_ESA_2016_12_07_18_18_57_0534449937_178.66E_51.85N_VV_C5_GFS05 CDF_wind_level3.png

THREDDS

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

NCEI Archive

SAR Winds:

https://www.ncei.noaa.gov/products/sar-wind-data-quality-monitoring

AVHRR (MetOp-1/2) Level 2/3

jebidiah.jeffery — Thu, 17 Mar 2022 15:24:52 +0000

AVHRR (MetOp-1/2) Level 2/3

NOAA CoastWatch / OceanWatch / PolarWatch produces Level 2/3 sea surface temperature datasets using AVHRR sensors aboard the Metop 1/2 satellites.

jebidiah.jeffery Thu, 03/17/2022 - 11:24

Short Names

AVHRR_L2

AVHRR_L3

Temporal Coverage

Near real-time + 3 days

Product Families

Sea Surface Temperature

Measurements

Sea Surface Temperature - Polar-orbiting

Processing Levels

Level 2

Level 3

Spatial Coverage

CoastWatch US Regions

Latency Groups

0 Hours <= 24 Hours (NRT)

24+ hours (Delayed)

Latency Details

Less than 24 hours

Spatial Resolution Groups

2km+

Spatial Resolution Details

4km @Nadir; ~30km @swath edge

Platforms

MetOp

Instruments

AVHRR

Data Providers

ESA

EUMETSAT

Data Tool Links

CoastWatch Near Real-Time Search

Sample Filenames

2016_300_1446_n19_ax.hdf [YYYY_JJJ_HHMM_PPP_RR.[png, tif, hdf]

HTTPS

Swath + Mapped Regions:

https://www.star.nesdis.noaa.gov/data/socd3/coastwatch/products/legacy_sst/avhrr/

ACSPO Global SST from VIIRS

jebidiah.jeffery — Thu, 17 Mar 2022 15:23:21 +0000

ACSPO Global SST from VIIRS

These VIIRS SST data are produced using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) SST system, from the afternoon NPP, N20 and N21 satellites, in two formats: L2P and L3U (uncollated). The data are reported in 10 min granule files in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). For each satellite, there are 144 granules per 24 hr interval, with a total data volume of ~7.1 GB/day for L2P, and ~0.4 GB/day for L3U.

jebidiah.jeffery Thu, 03/17/2022 - 11:23

These VIIRS SST data are produced using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) SST system, from the afternoon NPP and N20 satellites, in two formats: L2P and L3U (uncollated). The data are reported in 10 min granule files in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). There are 144 granules per 24 hour interval, with a total data volume of ~7 GB/day for L2P, and ~0.5 GB/day for L3U (per-sensor) .

The L2P/L3U SST data is produced at NOAA STAR using the official enterprise ACSPO algorithms V2.80. A 2-week rotated buffer of the NRT data is provided here on Coast Watch, whereas the full data set is available from PO.DAAC and NOAA NCEI (see links under "Data Access"). Note that the NCEI archive has not been backfilled with ACSPO V2.80 and therefore contains SST data from earlier ACSPO versions, while PO.DAAC contains the full V2.80 archive. A complete archive of ACSPO V2.80 data is available on the Coast Watch archive for L3U data only due to large L2P data volume.

ACSPO retrievals are made in full VIIRS swath (~3,000 km). For data assimilation applications (such as production of L4 analyses, especially those that blend satellite and in situ data), correction for the Sensor-Specific Error Statistics (SSES; reported in ACSPO files; Petrenko et al., 2016) biases is strongly recommended. The NOAA SST team worked with the NOAA calibration team and used an up-to-date converter from RDR (L0) to SDR (L1b), to address quarterly spikes in day-time SST bias which coincide with quarterly warm-up-cool-down calibration exercises onboard NPP/N20. The algorithms used in VIIRS reanalysis version 3 (RAN3) are documented in Jonasson et al., 2022.

In each valid water pixel (defined as ocean, sea, lake or river, up to 5km inland; note that in "invalid" pixels, defined as those with >5km inland, fill values are reported), the following layers are reported in both L2P and L3U, among others: SSTs derived using multi-channel SST (MCSST; night) and Non-Linear SST (NLSST; day) algorithms (Petrenko et al., 2014); ACSPO clear-sky mask (ACSM; provided in each pixel as part of l2p_flags; Petrenko et al., 2010); SSES bias and standard deviation (Petrenko et al., 2016); GFS/MERRA wind speed; and ACSPO SST minus reference (Canadian Met Centre L4 SST).

Only ACSM "confidently clear" pixels (equivalent to GDS2 "quality level"=5; QLs are also reported for each pixel) should be used. The ACSM also provides day/night, land, ice, twilight, and glint flags. Note that users of ACSPO data have the flexibility to ignore the ACSM, derive their own clear-sky mask, and use SSTs in those pixels.

Both L2P and L3U SSTs are monitored and validated against in situ data (Xu and Ignatov, 2014) in SQUAM (Dash et al., 2010) and ARMS systems, and brightness temperatures are monitored in MICROS (Liang and Ignatov, 2011).

Short Names

L2P: ACSPO_VIIRS_L2P

L3U: ACSPO_VIIRS_L3U

Temporal Start Date

February 1, 2012

Temporal Coverage

NRT NPP L2P/L3U: 1 Feb 2012 to present
NRT N20 L2P/L3U: 5 Jan 2018 to present
NRT N21 L2P/L3U: 19 March 2023 to present
RAN NPP L2P/L3U: 1 Feb 2012 to present
RAN N20 L2P/L3U: 5 Jan 2018 to present
RAN N21 L2P/L3U: 19 March 2023 to present

Product Families

Sea Surface Temperature

Jonasson, O.; Ignatov, A.; Pryamitsyn, V.; Petrenko, B.; Kihai, Y. JPSS VIIRS SST Reanalysis Version 3. Remote Sens. 2022, 14, 3476. doi:10.3390/rs14143476
Dash, P., A. Ignatov, Y. Kihai & J. Sapper, 2010: The SST Quality Monitor (SQUAM). JTech, 27, 1899-1917, doi:10.1175/2010JTECHO756.1, www.star.nesdis.noaa.gov/sod/sst/squam/
Ding, Y., A. Ignatov, I. Gladkova, M. Crosberg, and C. Chu, 2017: ACSPO Regional Monitor for SST (ARMS). BoM - NOAA SST Workshop, 18-21 April 2017, Melbourne, Australia (presentation), www.star.nesdis.noaa.gov/sod/sst/arms/
Liang, X. & A. Ignatov, 2011: Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS). JTech, 28, 1228-1242, doi:10.1175/JTECH-D-10-05023.1, www.star.nesdis.noaa.gov/sod/sst/micros/
Xu, F. & A. Ignatov, 2014: In situ SST Quality Monitor (iQuam). JTech, 31, 164-180, doi:10.1175/JTECH-D-13-00121.1, www.star.nesdis.noaa.gov/sod/sst/iquam/
Petrenko, B., A. Ignatov, Y. Kihai, P. Dash, 2016: Sensor-Specific Error Statistics for SST in the Advanced Clear-Sky Processor for Oceans. JTech, 33, 345-359, doi:10.1175/JTECH-D-15-0166.1
Petrenko, B., A. Ignatov, Y. Kihai, J. Stroup, P. Dash, 2014: Evaluation and Selection of SST Regression Algorithms for JPSS VIIRS. JGR, 119, 4580-4599, doi:10.1002/2013JD020637
Petrenko, B., A. Ignatov, Y. Kihai, and A. Heidinger, 2010: Clear-Sky Mask for ACSPO. JTech, 27, 1609-1623, doi:10.1175/2010JTECHA1413.1

Measurements

Sea Surface Temperature - Polar-orbiting

Processing Levels

Level 2

Level 3

Spatial Coverage

Global

The ACSPO NPP/N20/N21 VIIRS RAN3 data set is provided by NOAA STAR. We strongly recommend contacting NOAA SST team led by A. Ignatov before the data are used for any publication or presentation.

Latency Groups

0 Hours <= 24 Hours (NRT)

24+ hours (Delayed)

Latency Details

NRT: <6 hours
RAN: 8 weeks

Spatial Resolution Groups

100m < 2km

2km+

Spatial Resolution Details

L2P: 0.75km @ Nadir; ~1.5km @ swath edge
L3U: 0.02°

Platforms

NOAA

SNPP

Instruments

VIIRS

Processing Algorithms

ACSPO

Data Providers

NOAA

NESDIS

STAR

Data Tool Links

Near Real-Time (NRT) [14 Day Rotated Buffer]

NPP + N20 + N21 L2P:

CoastWatch Data Search

Sample Filenames

L2P: 20120301001000-STAR-L2P_GHRSST-SSTsubskin-VIIRS_NPP-ACSPO_V2.80-v02.0-fv01.0.nc
L3U: 20120301001000-STAR-L3U_GHRSST-SSTsubskin-VIIRS_NPP-ACSPO_V2.80-v02.0-fv01.0.nc

HTTPS

Near Real-Time (NRT) [14 Day Rotated Buffer]

NPP L2P:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/nrt/viirs/npp/l2p

N20 L2P:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/nrt/viirs/n20/l2p

N21 L2P:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/nrt/viirs/n21/l2p

NPP L3U:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/nrt/viirs/npp/l3u

N20 L3U:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/nrt/viirs/n20/l3u

N21 L3U:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/nrt/viirs/n21/l3u

Reanalysis Version 3 (RAN3) [Scientific Quality. New data Is added in Delayed Mode (DM)]

NPP L3U:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/ran/viirs/npp/l3u

N20 L3U:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/ran/viirs/n20/l3u

N20 L3U:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/ran/viirs/n21/l3u

*NRT - Near-Real Time data (1-3 hour latency).
*DM - Delayed mode "scientific quality" SST. Produced on a 8-week delay.
*RAN2 - Reanalysis-2 of VIIRS SST (NPP: Feb'2012-Apr'2019; N20: Jan'2018-Apr'2019). Produced using ACSPO V2.61.
*RAN3 - Reanalysis-3 of VIIRS SST (NPP: Feb'2012-Dec'2021; N20: Jan'2018-Dec'2021). Produced using ACSPO V2.80.
NPP - Suomi NPP satellite platform
N20 - NOAA-20 satellite platform
N21 - NOAA-21 satellite platform

THREDDS

Near Real-Time (NRT) [14 Day Rotated Buffer]

NPP L2P:

https://coastwatch.noaa.gov/thredds/catalog/swathNPPVIIRSNRTL2PWW00/catalog.html

N20 L2P:

https://coastwatch.noaa.gov/thredds/catalog/swathN20VIIRSNRTL2PWW00/catalog.html

N21 L2P:

https://coastwatch.noaa.gov/thredds/catalog/swathN21VIIRSNRTL2PWW00/catalog.html

NPP L3U:

https://coastwatch.noaa.gov/thredds/catalog/gridNPPVIIRSNRTL3UWW00/catalog.html

N20 L3U:

https://coastwatch.noaa.gov/thredds/catalog/gridN20VIIRSNRTL3UWW00/catalog.html

N21 L3U:

https://coastwatch.noaa.gov/thredds/catalog/gridN21VIIRSNRTL3UWW00/catalog.html

Reanalysis Version 3 (RAN3) [Scientific Quality. New data is added in Delayed Mode (DM)]

NPP L3U:

https://coastwatch.noaa.gov/thredds/catalog/gridNPPVIIRSSCIENCEL3UWW00/catalog.html

N20 L3U:

https://coastwatch.noaa.gov/thredds/catalog/gridN20VIIRSSCIENCEL3UWW00/catalog.html

N21 L3U:

https://coastwatch.noaa.gov/thredds/catalog/gridN21VIIRSSCIENCEL3UWW00/catalog.html

PO.DAAC Archive

Reanalysis / Reprocessed (RAN3)* [New data is added in NRT* and overwritten by DM* data with a 8 week delay]

NPP L2P: 10.5067/GHVRS-2PO28

N20 L2P: 10.5067/GHV20-2PO28

N21 L2P: 10.5067/GHN21-2P280

NPP L3U: 10.5067/GHVRS-3UO28

N20 L3U: 10.5067/GHV20-3UO28

N21 L3U: 10.5067/GHN21-3U280

NCEI Archive

Reanalysis / Reprocessed (RAN2)* [New data is added in NRT]

NPP L2P: 10.7289/v5pr7sx5

N20 L2P: 10.25921/sfs7-9688

N21 L2P: 10.25921/5mbf-ma56

NPP L3U: 10.7289/v5kk98s8

N20 L3U: 10.25921/7c1m-rw73

N21 L3U: 10.25921/xkhb-5e96

ACSPO Global SST from AVHRR GAC

jebidiah.jeffery — Thu, 17 Mar 2022 15:22:16 +0000

ACSPO Global SST from AVHRR GAC

AVHRR GAC Reanalysis 2 (RAN2) dataset is an improved and extended version of AVHRR GAC RAN1 (Ignatov et al., 2016). RAN2 is produced from 5 AVHRR/2s (onboard N07/09/11/12/14) and 5 AVHRR/3s (N15/16/17/18/19) using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) enterprise system v2.81. At the time of release, it covers from 1 Sep 1981 to 31 Dec 2021 and will be periodically extended as new L1b data from N15/18/19 arrive. Out of ten satellites, seven (N07/09/11/14/16/18/19) were initially launched into afternoon orbits (1:30pm/am), two (N12/15) into early-morning orbits (7:30pm/am), and one (N17) into mid-morning orbit (10am/pm). All NOAA orbits are not controlled and evolve in time. The RAN2 dataset is documented in (Petrenko et al. 2020 and 2021; Pryamitsyn et al. 2020)

jebidiah.jeffery Thu, 03/17/2022 - 11:22

AVHRR FRAC onboard three Metop-First Generation (FG) satellites have been processed separately. AVHRR FRAC RAN1 dataset is available at ACSPO Global SST from AVHRR FRAC.

The data are reported in GHRSST Data Specifications v2 (GDS2) format, in three projections: swath (L2P), 0.02° gridded L3U (U=uncollated) and 0.02° gridded L3C (C=collated). L2P and L3U products are aggregated into 10min granules, 144 per day, with a total daily data volumes of 0.27GB/L2P and 0.32GB/L3U. L3C product contains two collated files per day, daily volume of 0.3GB/day, : one file for the daytime SST and one for the nighttime SST. ACSPO retrievals are made in full AVHRR swath (~2,800 km). For data assimilation applications (such as production of L4 analyses, especially those blending satellite and in situ data), subtraction of the Sensor-Specific Error Statistics (SSES; Petrenko et al., 2016) biases reported in ACSPO files, is recommended.

In each valid water pixel (defined as ocean, sea, lake or river, up to 5km inland), the following layers are reported in both L2P and L3U: SSTs derived using Non-Linear SST (NLSST) algorithms (Petrenko et al., 2020); ACSPO clear-sky mask (ACSM; provided in each pixel as part of l2p_flags; Petrenko et al., 2010); SSES bias and standard deviation (Petrenko et al., 2016); MERRA-2 wind speed; and ACSPO SST minus reference SST (ESA CCI L4 SST from 1 Sep 1981 - 31 Aug 1991; switched to CMC L4 SST from 1 Sep 1991 to present time). In "invalid" pixels (defined as those with >5km inland), fill values are reported.

All L2P, L3U and L3C SSTs are monitored and validated against in situ data iQuam (Xu and Ignatov, 2014) in SQUAM (Dash et al., 2010), and BTs are monitored in MICROS (Liang and Ignatov, 2011). The AVHRR sensors calibration and characterization, and orbital stability of NOAA satellites, are monitored in the NOAA 3S system (He et al., 2016)

Short Names

L2P: ACSPO AVHRR GAC RAN2 L2P

L3U: ACSPO AVHRR GAC RAN2 L3U

Temporal Start Date

September 1, 1981

Product Families

Sea Surface Temperature

Algorithms and Evaluation

Petrenko, B., A. Ignatov, Y. Kihai, and A. Heidinger, 2010: Clear-Sky Mask for ACSPO. JTech, 27, 1609-1623, doi:10.1175/2010JTECHA1413.1

Petrenko, B., A. Ignatov, Y. Kihai, J. Stroup, P. Dash, 2014: Evaluation and Selection of SST Regression Algorithms for JPSS VIIRS. JGR, 119, 4580-4599, doi:10.1002/2013JD020637

Petrenko, B., A. Ignatov, Y. Kihai, P. Dash, 2016: Sensor-Specific Error Statistics for SST in the Advanced Clear-Sky Processor for Oceans. JTech, 33, 345-359, doi:10.1175/JTECH-D-15-0166.1

Ignatov, A., X. Zhou, B. Petrenko, X. Liang, Y. Kihai, P. Dash, J. Stroup, J. Sapper, & P. DiGiacomo, 2016: AVHRR GAC SST Reanalysis Version 1 (RAN1). Remote Sens., 8(4), 315,doi: 10.3390/rs6040315

Petrenko B., V. Pryamitsyn, , A. Ignatov, & Y. Kihai, 2020: SST and cloud mask algorithms in reprocessing 1981-2002 NOAA AVHRR data for SST with the Advanced Clear-Sky Processor for Oceans (ACSPO). SPIE Defense + Commercial Sensing, 11420, SI, www.spiedigitallibrary.org,

Pryamitsyn, V., A. Ignatov, B. Petrenko, O. Jonasson & Y. Kihai, 2020: Evaluation of the initial NOAA AVHRR GAC SST reanalysis version 2 (RAN2 B01). SPIE Defense + Commercial Sensing, 11420I, https://doi.org/10.1117/12.2558660,

Petrenko, B.; Pryamitsyn, V.; Ignatov, A. 2021;Filtering cold outliers in SSTs retrieved from early AVHRRs for the second AVHRR GAC reanalysis. SPIE Defense + Commercial Sensing , 11752, https://doi.org/10.1117/12.2585908

Petrenko B, Pryamitsyn V, Ignatov A, Jonasson O, Kihai Y. 2022; AVHRR GAC Sea Surface Temperature Reanalysis Version 2, Remote Sens. 14(13):3165. https://doi.org/10.3390/rs14133165

Monitoring

Dash, P., A. Ignatov, Y. Kihai & J. Sapper, 2010: The SST Quality Monitor (SQUAM). JTech, 27, 1899-1917, doi:10.1175/2010JTECHO756.1, www.star.nesdis.noaa.gov/sod/sst/squam/

Ding, Y., A. Ignatov, I. Gladkova, M. Crosberg, and C. Chu, 2017: ACSPO Regional Monitor for SST (ARMS). BoM - NOAA SST Workshop, 18-21 April 2017, Melbourne, Australia (presentation), www.star.nesdis.noaa.gov/sod/sst/arms/

Liang, X. & A. Ignatov, 2011: Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS). JTech, 28, 1228-1242, doi:10.1175/JTECH-D-10-05023.1, www.star.nesdis.noaa.gov/sod/sst/micros/

Xu, F. & A. Ignatov, 2014: In situ SST Quality Monitor (iQuam). JTech, 31, 164-180, doi:10.1175/JTECH-D-13-00121.1, www.star.nesdis.noaa.gov/sod/sst/iquam/ He, K.; Ignatov, A.; Kihai, Y.; Cao, C.Y.; Stroup, J. 2016; Analyzing Avhrr Thermal Calibration Using Sensor Stability for Sst (3s) System. 2016 Ieee International Geoscience and Remote Sensing Symposium (Igarss) , 1950-1953, https://doi.org/10.1109/Igarss.2016.7729502

Measurements

Sea Surface Temperature - Polar-orbiting

Processing Levels

Level 2

Level 3

Spatial Coverage

Global

Petrenko B, Pryamitsyn V, Ignatov A, Jonasson O, Kihai Y. 2022; AVHRR GAC Sea Surface Temperature Reanalysis Version 2, Remote Sens. 14(13):3165. https://doi.org/10.3390/rs14133165 (link is external)

The ACSPO AVHRR GAC RAN data are provided by NOAA STAR. We strongly recommend contacting NOAA SST team led by A. Ignatov before the data are used for any publication or presentation.

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

~2 to 6 hours latency

Spatial Resolution Groups

2km+

Spatial Resolution Details

L2P: 4km @Nadir; ~25km @swath edge
L3U: 0.02°

Platforms

NOAA

Instruments

AVHRR

Processing Algorithms

ACSPO

Data Providers

NOAA

NESDIS

STAR

Sample Filenames

19810901000000-STAR-L2P_GHRSST-SSTsubskin-AVHRRG_N07-ACSPO_V2.81-v02.0-fv01.0.nc
19810904000000-STAR-L3U_GHRSST-SSTsubskin-AVHRRG_N07-ACSPO_V2.81-v02.0-fv01.0.nc

HTTPS

L2P + L3U + L3C:

https://coastwatch.noaa.gov/data/pub0014/coastwatch/sst/ran/avhrr_gac/

THREDDS

L2P + L3U + L3C:

https://coastwatch.noaa.gov/thredds/socd/coastwatch/acspo/catalog_sst_acspo_gac_ran.html

ACSPO Global SST from AVHRR FRAC

jebidiah.jeffery — Thu, 17 Mar 2022 15:21:57 +0000

ACSPO Global SST from AVHRR FRAC

The AVHRR FRAC SST data are produced from AVHRR/3s onboard Metop-A, -B and -C satellites using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v2.80 enterprise system, described in (Ignatov et al., 2016). Currently, near-real time (NRT) L2P and 0.02° L3U (gridded uncollated) data for Metop-A, -B and -C is produced at STAR (with ~2 to 6hrs latency). The data are being archived at PO.DAAC, and also available at this CoastWatch page as a 2 weeks rotated buffer. Metop-A mission officially ended at 2021-11-15 and the production of the ACSPO SST for the Metop-A ended at 2021-11-14 due to data degradation on 2021-11-15.

jebidiah.jeffery Thu, 03/17/2022 - 11:21

he AVHRR FRAC SST data are produced from AVHRR/3s onboard Metop-A, -B and -C satellites using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v2.80 enterprise system, described in (Ignatov et al., 2016). Currently, near-real time (NRT) L2P and 0.02° L3U (gridded uncollated) data for Metop-A, -B and -C is produced at STAR (with ~2 to 6hrs latency). The data are being archived at PO.DAAC, and also available at this Coast watch page as a 2 weeks rotated buffer. Metop-A mission officially ended at 2021-11-15 and the production of the ACSPO SST for the Metop-A ended at 2021-11-14 due to data degradation on 2021-11-15.

The full-mission global AVHRR FRAC SST is produced from all three Metop First Generation satellites: A (2006-12-01 to 2021-11-14), B (2012-present) and C (2018-present), using the ACSPO enterprise system. Historical reprocessing (Reanalysis-1, RAN1) starts at the beginning of each mission and continues into near-real time (NRT). The L2P+L3U version of FRAC RAN1 is being archived in PO.DAAC.

The data are reported in 10min granule files in GHRSST Data Specifications v2 (GDS2) format, in swath projection (L2P) and 0.02° gridded L3U (U=uncollated), 144 granules per day, with a total data volume of 8GB/day for L2P and 0.4GB/day for L3U, respectively.

ACSPO retrievals are made in full AVHRR swath (~2,800 km). For data assimilation applications (such as production of L4 analyses, especially those that blend satellite and in situ data), correction for the Sensor-Specific Error Statistics (SSES; reported in ACSPO files; Petrenko et al., 2016) biases is strongly recommended.

In each valid water pixel (defined as ocean, sea, lake or river, up to 5km inland; note that in "invalid" pixels, defined as those with >5km inland, fill values are reported), the following layers are reported in both L2P and L3U: SSTs derived using multi-channel SST (MCSST; night) and Non-Linear SST (NLSST; day) algorithms (Petrenko et al., 2014); ACSPO clear-sky mask (ACSM; provided in each pixel as part of l2p_flags; Petrenko et al., 2010); SSES bias and standard deviation (Petrenko et al., 2016); NCEP wind speed for the NRT data and from MERRA-2 for RAN; and ACSPO SST minus reference (Canadian Met Centre L4 SST).

Only ACSM "confidently clear" pixels (equivalent to GDS2 "quality level"=5; also reported for each pixel) should be used. The ACSM also provides day/night, land, ice, twilight, and glint flags.

Both L2P and L3U SSTs are monitored and validated against in situ data iQuam (Xu and Ignatov, 2014) in SQUAM (Dash et al., 2010) and ARMS (Ding et al., 2017) systems, and BTs are monitored in MICROS (Liang and Ignatov, 2011).

Short Names

AVHRRF_MA-STAR-L2P-v2.80

AVHRRF_MA-STAR-L3U-v2.80

AVHRRF_MB-STAR-L2P-v2.80

AVHRRF_MB-STAR-L3U-v2.80

AVHRRF_MC-STAR-L2P-v2.80

AVHRRF_MC-STAR-L3U-v2.80

Temporal Start Date

December 1, 2006

Temporal Coverage

2-week rotated

Product Families

Sea Surface Temperature

Algorithms

Petrenko, B., A. Ignatov, Y. Kihai, P. Dash, 2016: Sensor-Specific Error Statistics for SST in the Advanced Clear-Sky Processor for Oceans. JTech, 33, 345-359, doi:10.1175/JTECH-D-15-0166.1

Petrenko, B., A. Ignatov, Y. Kihai, J. Stroup, P. Dash, 2014: Evaluation and Selection of SST Regression Algorithms for JPSS VIIRS. JGR, 119, 4580-4599, doi:10.1002/2013JD020637

Petrenko, B., A. Ignatov, Y. Kihai, and A. Heidinger, 2010: Clear-Sky Mask for ACSPO. JTech, 27, 1609-1623, doi:10.1175/2010JTECHA1413.1

Monitoring

Dash, P., A. Ignatov, Y. Kihai & J. Sapper, 2010: The SST Quality Monitor (SQUAM). JTech, 27, 1899-1917, doi:10.1175/2010JTECHO756.1, www.star.nesdis.noaa.gov/sod/sst/squam/

Liang, X. & A. Ignatov, 2011: Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS). JTech, 28, 1228-1242, doi:10.1175/JTECH-D-10-05023.1, www.star.nesdis.noaa.gov/sod/sst/micros/

Xu, F. & A. Ignatov, 2014: In situ SST Quality Monitor (iQuam). JTech, 31, 164-180, doi:10.1175/JTECH-D-13-00121.1, www.star.nesdis.noaa.gov/sod/sst/iquam/

Measurements

Sea Surface Temperature - Polar-orbiting

Processing Levels

Level 2

Level 3

Spatial Coverage

Global

The ACSPO AVHRR FRAC data are provided by NOAA STAR. We strongly recommend contacting NOAA SST team led by A. Ignatov before the data are used for any publication or presentation.

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

L2P: 3 hours
L3U: 3 hours

Spatial Resolution Groups

100m < 2km

2km+

Spatial Resolution Details

L2P: 1km @Nadir; ~6 km @swath edge
L3U: 0.02°

Platforms

MetOp

Instruments

AVHRR

Processing Algorithms

ACSPO

Data Providers

NOAA

NESDIS

STAR

Product DOI

https://doi.org/10.5067/GHMTA-2PS28

https://doi.org/10.5067/GHMTA-3US28

https://doi.org/10.5067/GHMTB-2PS28

https://doi.org/10.5067/GHMTB-3US28

https://doi.org/10.5067/GHMTC-2PS28

https://doi.org/10.5067/GHMTC-3US28

Data Tool Links

[14 Day Rotated Buffer]

L3U:

CoastWatch Data Portal

Sample Filenames

L2P: 20190809200000-OSPO-L2P_GHRSST-SSTsubskin-AVHRRF_MA-ACSPO_V2.70-v02.0-fv01.0.nc
L3U: 20190809200000-OSPO-L3U_GHRSST-SSTsubskin-AVHRRF_MA-ACSPO_V2.70-v02.0-fv01.0.nc

HTTPS

[14 Day Rotated Buffer]

L2P + L3U:

https://coastwatch.noaa.gov/data/pub0012/coastwatch/sst/nrt/avhrr_frac/

THREDDS

[14 Day Rotated Buffer]

L2P + L3U:

coastwatch.noaa.gov/thredds/socd/coastwatch/acspo/catalog_sst_acspo_frac_nrt.html

PO.DAAC Archive

AVHRRF_MA-STAR-L2P-v2.80: 10.5067/GHMTA-2PS28

AVHRRF_MA-STAR-L3U-v2.80: 10.5067/GHMTA-3US28

AVHRRF_MB-STAR-L2P-v2.80: 10.5067/GHMTB-2PS28

AVHRRF_MB-STAR-L3U-v2.80: 10.5067/GHMTB-3US28

AVHRRF_MC-STAR-L2P-v2.80: 10.5067/GHMTC-2PS28

AVHRRF_MC-STAR-L3U-v2.80: 10.5067/GHMTC-3US28

NCEI Archive

GHRSST-AVHRRF_MA-STAR-L2P: https://doi.org/10.25921/am4h-a956 (incomplete version of PO.DAAC 10.5067/GHMTA-2PS28)

GHRSST-AVHRRF_MA-STAR-L3U : https://doi.org/10.25921/rnn8-jh57 (incomplete version of PO.DAAC 10.5067/GHMTA-3US28)

GHRSST-AVHRRF_MB-OSPO-L2P: https://doi.org/10.25921/pakj-ez21 (incomplete version of PO.DAAC 10.5067/GHMTB-2PS28)

GHRSST-AVHRRF_MB-OSPO-L3U: https://doi.org/10.25921/ba3d-yz14 (incomplete version of PO.DAAC 10.5067/GHMTB-3US28)

GHRSST-AVHRRF_MC-OSPO-L2P: https://doi.org/10.25921/xcj3-sd43 (incomplete version of PO.DAAC 10.5067/GHMTC-2PS28)

GHRSST-AVHRRF_MC-OSPO-L3U: https://doi.org/10.25921/ktez-s353 (incomplete version of PO.DAAC 10.5067/GHMTC-3US28)

ACSPO Global SST from AHI

SST.Team — Thu, 17 Mar 2022 15:20:21 +0000

ACSPO Global SST from AHI

The AHI SST data are produced from Himawari-9 (Himawari-8 before 2022-Dec-13) geostationary satellite using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v2.90 enterprise system,(ACSPO v2.70 was used for Himawari-8). Currently, only near-real time (NRT) data are produced at STAR, with a 2-6 hour latency (typically closer to 2 hours). The data are available in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). The data for Himawari-8 was archived with PO.DAAC with start date 2019-Oct-16 and end date 2022-Dec-13. The full mission of the Himawari-9 has been archiving in PO.DAAC. The data for Himawari-9 is also available at this Coast Watch page as a 2week rotated buffer. The reanalysis of the full mission of the Himawari-8 is available at this Coast Watch page. There is a plan to reprocess the AHI data, for the full Himawari-9 missions.

SST.Team Thu, 03/17/2022 - 11:20

The AHI SST data are produced from Himawari-9 (Himawari-8 before 2022-Dec-13 ) geostationary satellite using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v2.90 enterprise system (ACSPO v2.70 was used for Himawari-8). Currently, only near-real time (NRT) data are produced at STAR, with a 2-6 hour latency (typically closer to 2 hours). The data are available in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). The data for Himawari-8 was archived with PO.DAAC with start date 2019-Oct-16 and end date 2022-Dec-13. The full mission of the Himawari-9 has been archiving in PO.DAAC. The data is also available at this Coast Watch page as a 2week rotated buffer. The reanalysis of the full mission of the Himawari-8 with ACSPO v2.90 is available at this Coast Watch page. There is a plan to reprocess the AHI data, for the full Himawari-9 missions.

The data are reported hourly, in AHI Full Disk (FD), for view zenith angle not exceeding 68°, both in swath projection (L2P) and as a 0.02° gridded L3C. There are 24 FDs per day, with a total data volume of 6.3GB/day for L2P and 0.6GB/day for L3C, respectively.

In each valid water pixel (defined as ocean, sea, lake or river, up to 5km inland; note that in "invalid" pixels, defined as those with >5km inland, fill values are reported), the following layers are reported in both L2P and L3C: SSTs derived using multi-channel SST (MCSST; night) and Non-Linear SST (NLSST; day) algorithms (Petrenko et al., 2014); ACSPO clear-sky mask (ACSM; provided in each pixel as part of l2p_flags; Petrenko et al., 2010); SSES bias and standard deviation (Petrenko et al., 2016); NCEP wind speed; and ACSPO SST minus reference (Canadian Met Centre L4 SST). For L2P, brightness temperatures (BTs) in 3.9, 8.6, 10, 11, and 12 µm bands are also reported, for those users interested in direct radiance assimilation (e.g., NOAA NCEP, NASA GMAO).

Only ACSM "confidently clear" pixels (equivalent to GDS2 "quality level"=5; also reported for each pixel) should be used. The ACSM also provides day/night, land, ice, twilight, and glint flags. Note that users of ACSPO data have the flexibility to ignore the ACSM, derive their own clear-sky mask, and use BTs and SSTs in those pixels. They may also ignore ACSPO SST, and derive their own SSTs from the original BTs.

Both L2P and L3C SSTs are monitored and validated against in situ data (Xu and Ignatov, 2014) in SQUAM (Dash et al., 2010) and ARMS (Ding et al., 2017) systems, and BTs are monitored in MICROS (Liang and Ignatov, 2011).

Short Names

AHI_H08-STAR-L2P-v2.70

AHI_H08-STAR-L3C-v2.70

H09-AHI-L2P-ACSPO-v2.90

H09-AHI-L3C-ACSPO-v2.90

Temporal Start Date

October 16, 2019

Product Families

Sea Surface Temperature

Algorithms:

Petrenko, B., A. Ignatov, Y. Kihai, M. Pennybacker, 2019: Optimization of sensitivity of GOES-16 ABI sea surface temperature by matching satellite observations with L4 analysis. Remote Sens, 11, 206, doi: 10.3390/rs11020206, https://www.mdpi.com/2072-4292/11/2/206/htm
Petrenko, B., A. Ignatov, M. Kramar, Y. Kihai, 2016: Exploring new bands in multichannel regression SST algorithms for the next generation infrared sensors at NOAA. Proc. SPIE 9827, Ocean Sensing and Monitoring VIII, 98270N (30 May 2016); doi:10.1117/12.2229578, ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/aignatov/SPIE/2016/Papers/PetrenkoEtAl_Improved_ACSPO_Algorithms_98270N.pdf
Kramar, M., A. Ignatov, B. Petrenko, Y. Kihai, P. Dash, 2016: Near Real Time SST retrievals from Himawari-8 at NOAA using ACSPO system. Proc. SPIE 9827, Ocean Sensing and Monitoring VIII, 98270L (30 May 2016); doi:10.1117/12.2229771, ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/aignatov/SPIE/2016/Papers/KramarEtAl_ACSPO_AHI_98270L.pdf
Ignatov, A., I. Gladkova, Y. Ding, F. Shahriar, Y. Kihai, X. Zhou, JPSS VIIRS level 3 uncollated SST Product at NOAA”. J. Appl. Remote Sens., 11(3), 032405, doi:10.1117/1.JRS.11.032405 (2017), ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/aignatov/Irina/L3U/JARS_11_3_032405.pdf

Monitoring:

SQUAM (https://www.star.nesdis.noaa.gov/sod/sst/squam/): Dash, P., A. Ignatov, Y. Kihai & J. Sapper, 2010: The SST Quality Monitor (SQUAM). JTech, 27, 1899-1917,doi:10.1175/2010JTECHO756.1
iQUAM (https://www.star.nesdis.noaa.gov/sod/sst/iquam/): Xu, F. & A. Ignatov, 2014: In situ SST Quality Monitor (iQuam). JTech, 31, 164-180, doi:10.1175/JTECH-D-13-00121.1
ARMS (https://www.star.nesdis.noaa.gov/sod/sst/arms/): Ding, Y., A. Ignatov, K. He, I. Gladkova, 2018: ACSPO Regional Monitor for SST (ARMS). GHRSTT XIX: Science Team Meeting, June 2018, Darmstadt, Germany, ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/aignatov/GHRSST/G19/Presentations/G19_Oral_ARMS_Ignatov_v02.pptx
MICROS (https://www.star.nesdis.noaa.gov/sod/sst/micros/):Liang, X. & A. Ignatov, 2011: Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS). JTech, 28, 1228-1242, doi:10.1175/JTECH-D-10-05023.1

Measurements

Sea Surface Temperature - Geostationary

Processing Levels

Level 2

Level 3

Spatial Coverage

East Asia & Western Pacific

The ACSPO AHI SST data are provided by NOAA STAR. We strongly recommend contacting NOAA SST team led by A. Ignatov before the data are used for any publication or presentation.

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

2-6 hours (typically closer to 2 hours)

Spatial Resolution Groups

2km+

Spatial Resolution Details

L2P: From 2km@Nadir(link sends e-mail) to ~12km @VZA=68°
L3C: 0.02°

Platforms

Himawari

Instruments

AHI

Processing Algorithms

ACSPO

Data Providers

JMA

NOAA

NESDIS

STAR

Product DOI

https://doi.org/10.5067/GHH08-2PO27

https://doi.org/10.5067/GHH08-3CO27

https://doi.org/10.5067/GHH09-2P290

https://doi.org/10.5067/GHH09-3C290

Data Tool Links

Near Real-Time (NRT) [14 Day Rotated Buffer]

H09 L3C:

CoastWatch Data Portal

Sample Filenames

L2P: 20191016000000-STAR-L2P_GHRSST-SSTsubskin-AHI_H08-ACSPO_V2.70-v02.0-fv01.0.nc
L3C: 20191016000000-STAR-L3C_GHRSST-SSTsubskin-AHI_H08-ACSPO_V2.70-v02.0-fv01.0.nc

HTTPS

Near Real-Time (NRT) [14 Day Rotated Buffer]

H09 L2C + L3C:

https://coastwatch.noaa.gov/data/pub0014/coastwatch/sst/nrt/ahi/h09/

Reanalysis (RAN)

H08 L2C + L3C:

https://coastwatch.noaa.gov/data/pub0014/coastwatch/sst/ran/ahi/h08/

THREDDS

Near Real-Time (NRT) [14 Day Rotated Buffer]

H09 L2C:

https://coastwatch.noaa.gov/thredds/catalog/swathH09AHINRTL2CWW00/catalog.html

H09 L3C:

https://coastwatch.noaa.gov/thredds/catalog/gridH09AHINRTL3CWW00/catalog.html

Reanalysis (RAN)

H08 L2C + L3C:

https://coastwatch.noaa.gov/thredds/catalog/socd/coastwatch/acspo/ahi/catalog_h08_ran.html

PO.DAAC Archive

Near Real-Time (NRT)

H08 L2C:

H08 L3C:

H09 L2C:

H09 L3C:

NCEI Archive

GHRSST-AHI_H08-STAR-L2P
10.25921/mzv0-km10

GHRSST-AHI_H08-STAR-L3C
10.25921/p1y5-yv98

GHRSST-AHI_H09-STAR-L2P
10.25921/73xy-1v10

GHRSST-AHI_H09-STAR-L3C
10.25921/3rew-g964

ACSPO Global SST from ABI

SST.Team — Thu, 17 Mar 2022 15:19:53 +0000

ACSPO Global SST from ABI

The ABI SST data are produced from GOES-East (at present GOES-19, before 2025/04/06 GOES-16) and GOES-West (at present GOES-18, before 2023/01/10 GOES-17) satellite using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v.3.0 and v290 enterprise system. Currently, near-real time (NRT) data are produced at STAR, with a ~2-6 hour latency. A Reanalysis (RAN) dataset for GOES-16 is also available. The data are available in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). Currently, the data are archived on PO.DAAC and available at this Coast Watch page as a 2week rotated buffer.

SST.Team Thu, 03/17/2022 - 11:19

The ABI SST data are produced from GOES-EAST, now GOES-19 (GOES-16 with ACSPO v2.70 before 2025/04/06) satellite using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v3.00 and GOES-WEST, nowGOES-18 satellite using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v2.90 enterprise system, GOES-17 (GOES-WEST) used ACSPO v2.71. Currently, for GOES-19 and GOES-18 near-real time (NRT) data are produced at STAR, with a latency of 2 to 6 hours (typically closer to 2 hours). For GOES-16 a reanalysis and reanalysis ver. 2 (ACSPO v2.90) starting 2017-Dec-15 exist. The data are available in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). The data is archived with PODAAC with start date 2019-Feb-01 and end date 2023-Jan-10 (G17W) , 2022-Jun-7 (G18W) and 2017-Dec-15 (G16E) respectively. The NRT data is also available at this Coast Watch page as a 2-week rotated buffer. There is a plan to reprocess the GOES-17 and -18 ABI data and to repeat the reprocessing of the GOES-16 data.

The data are reported hourly, in ABI Full Disk (FD), for view zenith angle not exceeding 68° in GHRSST Data Specifications v2 (GDS2) format, in swath projection (L2P) and 0.02° gridded L3C, 24 FDs per day, with a total data volume of 6.3GB/day for L2P and 0.5GB/day for L3C, respectively.

It should be noted that, due to an issue with its Loop Heat pipe, the L1b data for G17 was compromised for certain hours of the day and cannot be used to generate sensible SSTs. Therefore, SSTs from G17 was not reported for the times between 09:00 UTC and 19:00 UTC. Since this is a hardware issue it is unlikely to be resolved in the near future. (see Pennybacker et al., 2019). The new GOES-West (G18) is free from such problems.

In each valid water pixel (defined as ocean, sea, lake or river, up to 5km inland; note that in "invalid" pixels, defined as those with >5km inland, fill values are reported), the following layers are reported in both L2P and L3C: SSTs derived using multi-channel SST (MCSST; night) and Non-Linear SST (NLSST; day) algorithms (Petrenko et al., 2014); ACSPO clear-sky mask (ACSM; provided in each pixel as part of l2p_flags; Petrenko et al., 2010); SSES bias and standard deviation (Petrenko et al., 2016); NCEP wind speed; and ACSPO SST minus reference (Canadian Met Centre L4 SST). For L2P, brightness temperatures (BTs) in 3.9, 8.6, 10, 11, and 12 µm bands are also reported, for those users interested in direct "radiance assimilation" (e.g., NOAA NCEP, NASA GMAO).

Short Names

ABI_G16-STAR-L2P-v2.70

ABI_G16-STAR-L3C-v2.70

ABI_G17-STAR-L2P-v2.71

ABI_G17-STAR-L3C-v2.71

G18-ABI-L2P-ACSPO-v2.90

G18-ABI-L3C-ACSPO-v2.90

Temporal Start Date

December 15, 2017

Temporal Coverage

G16/EAST RAN+NRT: 2017-Dec-15 to 2019-May-07 (RAN) to present (NRT) (PODAAC)

G17/WEST NRT: 2019-Oct-16 to present (PODAAC)

G18/WEST RAN+NRT: 2022-Jun-7 to present(RAN 2 months delayed) (NRT) (PODAAC)

Product Families

Sea Surface Temperature

Algorithms:

Petrenko, B., A. Ignatov, Y. Kihai, M. Pennybacker, 2019: Optimization of sensitivity of GOES-16 ABI sea surface temperature by matching satellite observations with L4 analysis. Remote Sens, 11, 206, doi: 10.3390/rs11020206, https://www.mdpi.com/2072-4292/11/2/206/htm
Pennybacker, M., A. Ignatov, O. Jonasson, I. Gladkova, B. Petrenko, Y. Kihai, 2019, Mitigation of the GOES-17 ABI performance issues in the NOAA ACSPO SST products, Proc. SPIE 11014, Ocean Sensing and Monitoring XI, 110140Q (30 May 2019); doi:10.1117/12.2521051, ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/aignatov/SPIE/2019/Papers/PennybackerEtAl_Mitigation_G17_SST_110140Q.pdf
Ignatov, A., I. Gladkova, Y. Ding, F. Shahriar, Y. Kihai, X. Zhou, JPSS VIIRS level 3 uncollated SST Product at NOAA”. J. Appl. Remote Sens., 11(3), 032405, doi:10.1117/1.JRS.11.032405 (2017), ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/aignatov/Irina/L3U/JARS_11_3_032405.pdf

Monitoring:

SQUAM (https://www.star.nesdis.noaa.gov/sod/sst/squam/): Dash, P., A. Ignatov, Y. Kihai & J. Sapper, 2010: The SST Quality Monitor (SQUAM). JTech, 27, 1899-1917,doi:10.1175/2010JTECHO756.1
iQUAM (https://www.star.nesdis.noaa.gov/sod/sst/iquam/): Xu, F. & A. Ignatov, 2014: In situ SST Quality Monitor (iQuam). JTech, 31, 164-180, doi:10.1175/JTECH-D-13-00121.1
ARMS (https://www.star.nesdis.noaa.gov/sod/sst/arms/): Ding, Y., A. Ignatov, K. He, I. Gladkova, 2018: ACSPO Regional Monitor for SST (ARMS). GHRSTT XIX: Science Team Meeting, June 2018, Darmstadt, Germany, ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/aignatov/GHRSST/G19/Presentations/G19_Oral_ARMS_Ignatov_v02.pptx
MICROS (https://www.star.nesdis.noaa.gov/sod/sst/micros/):Liang, X. & A. Ignatov, 2011: Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS). JTech, 28, 1228-1242, doi:10.1175/JTECH-D-10-05023.1

Measurements

Sea Surface Temperature - Geostationary

Processing Levels

Level 2

Level 3

Spatial Coverage

Western Hemisphere

The ACSPO ABI SST data are provided by NOAA STAR. We strongly recommend contacting NOAA SST team led by A. Ignatov before the data are used for any publication or presentation.

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

NRT: 2-6 hours (in most cases closer to 2 hours)

Spatial Resolution Groups

2km+

Spatial Resolution Details

L2P: 2km at Nadir to ~12km at VZA=68°
L3C: 0.02°

Platforms

GOES-East

GOES-West

Instruments

ABI

Processing Algorithms

ACSPO

Data Providers

NOAA

NESDIS

STAR

Product DOI

https://doi.org/10.5067/GHG16-2PO27

https://doi.org/10.5067/GHG16-3UO27

https://doi.org/10.5067/GHG17-2PO71

https://doi.org/10.5067/GHG17-3UO71

https://doi.org/10.5067/GHG18-2PO29

https://doi.org/10.5067/GHG18-3CO29

Data Tool Links

Near Real-Time (NRT) [14 Day Rotated Buffer]

G18 + G19 L3C:

CoastWatch Data Portal

Sample Filenames

L2P: 20191016000000-STAR-L2P_GHRSST-SSTsubskin-ABI_G16-ACSPO_V2.70-v02.0-fv01.0.nc
L3C: 20191016000000-STAR-L3C_GHRSST-SSTsubskin-ABI_G16-ACSPO_V2.70-v02.0-fv01.0.nc

HTTPS

Near Real-Time (NRT) [14 Day Rotated Buffer]

G18 L2P/L3C:

https://coastwatch.noaa.gov/data/pub0014/coastwatch/sst/nrt/abi/g18/

G19 L2P/L3C:

https://coastwatch.noaa.gov/data/pub0014/coastwatch/sst/nrt/abi/g19/

Reanalysis ver. 2 (RAN2) [2 months delayed]

G16 L2P/L3C:

https://coastwatch.noaa.gov/data/pub0014/coastwatch/sst/ran/abi/g16/

THREDDS

Near Real-Time (NRT) [14 Day Rotated Buffer]

G18 L2P:

https://coastwatch.noaa.gov/thredds/catalog/swathG18ABINRTL2CWW00/catalog.html

G18 L3C:

https://coastwatch.noaa.gov/thredds/catalog/gridG18ABINRTL3CWW00/catalog.html

G19 L2P:

https://coastwatch.noaa.gov/thredds/catalog/swathG19ABINRTL2CWW00/catalog.html

G19 L3C:

https://coastwatch.noaa.gov/thredds/catalog/gridG19ABINRTL3CWW00/catalog.html

Reanalysis ver. 2 (RAN2)

G16 L2P/L3C:

https://coastwatch.noaa.gov/thredds/catalog/socd/coastwatch/acspo/abi/catalog_g16_ran.html

PO.DAAC Archive

G16 L2P:

G16 L3C:

G17 L2P:

G17 L3C:

G18 L2P:

G18 L3C:

NCEI Archive

NCEI archive contains an incomplete copy of PO.DAAC archive

GHRSST-ABI_G16-STAR-L2P

10.25921/ayf6-c438

GHRSST-ABI_G16-STAR-L3C

10.25921/rtf0-q898

GHRSST-ABI_G17-STAR-L2P
10.25921/6yga-qb89

GHRSST-ABI_G17-STAR-L3C
10.25921/4cs0-ym62

GHRSST-ABI_G18-STAR-L2P
10.25921/sr4z-pj22

GHRSST-ABI_G18-STAR-L3C
10.25921/jaxf-9b11

Along-track significant wave height, wind speed and sea level anomaly from multiple altimeters

jebidiah.jeffery — Thu, 17 Mar 2022 15:09:40 +0000

Along-track significant wave height, wind speed and sea level anomaly from multiple altimeters

The NOAA Laboratory for Satellite Altimetry's (LSA) sea surface height team produces 0.25-degree longitude/latitude Level-3 significant wave height, wind speed, and sea level anomaly (SLA) daily datasets by applying optimal interpolation to along-track satellite observations over the global ocean from a constellation of radar altimeter missions. Theses grids are produced with near-real time (3-5 hour latency) data.

jebidiah.jeffery Thu, 03/17/2022 - 11:09

Temporal Start Date

September 1, 2016

Temporal Coverage

Along-track data products available 09-2016 to present for Jason-3; Sentinel-3A; CryoSat-2; SARAL.

Jason-2 ended 1 Oct 2019.

Product Families

Sea Surface Height

Sea Surface Winds

Measurements

Along-track Significant Wave Height

Sea Surface Height Anomalies