Aqua

NOAA NCEI Blended Seawinds (NBS v2)

jebidiah.jeffery — Thu, 15 Sep 2022 16:54:41 +0000

NOAA NCEI Blended Seawinds (NBS v2)

jebidiah.jeffery Thu, 09/15/2022 - 12:54

The NOAA NCEI Blended Seawinds (NBS) version 2.0 dataset synthesizes observations from multiple satellites (up to seven satellites since June 2002) to create gridded wind speeds . This is an updated version of the existing NOAA NBS v1.0, which is a global gridded 0.25° and 6-hourly sea surface winds product that has wide applications in marine transportation, marine ecosystem and fisheries, offshore winds, weather and ocean forecasts, and other areas. Blending the data from multiple satellites fills in the temporal and spatial data gaps present in each source dataset, and reduces subsampling aliases and random errors. These satellites include scatterometers and microwave radiometers/imagers, which do not provide accurate observations of intensive high-speed hurricane winds because their signals saturate in very high winds or degrade in the presence of rain.
Recent advancements in satellite wind retrievals revealed that the L-band (1.42 GHz) instrument on the Soil Moisture Active Passive (SMAP) satellite and the AMSR2 All-Weather channel (~6.9 GHz) can provide accurate hurricane winds of up to 65 m/s (145 MPH) without being affected by rain; these data are incorporated in a new version of the Blended Sea Winds, NBS v2.0, using a multi-sensor data fusion technique based on random errors, enabling it to resolve very high winds, especially along the eyewalls of tropical cyclones and hurricanes. NBS v2.0 provides both a long-term record of >30 years retrospectively since July 1987 and a near-real-time (NRT) mode with 1-day latency. With the present seven satellites, there are very few data gaps over the global ocean in the 6-hourly interpolated fields, and those gaps are mostly in the higher latitudes (beyond 40°N or S). To produce a version of “gap-free” Level 4 wind data, the few remaining gaps are filled with the ERA-5 reanalysis winds in the delayed mode NBS (latency and cycle of a month) and with NOAA/NCEP/GFS forecast winds in the NRT version. The reanalysis or forecast data are also used to calculate the wind directions, which is essential to retrieve wind and wind stress components.

These products were developed in response to the increasing demand for higher resolution global datasets, and can be used to improve the accuracy of ocean and weather conditions forecasts. Please contact ncei.satellite.ocean.internal@noaa.gov for more information about these products.

Temporal Start Date

September 7, 1987

Temporal Coverage

Temporal: 6 hour, 1 day, 1 month; beginning July 1987

Product Families

Sea Surface Winds

Saha, K.; Huai-Min, Z. Hurricane and Typhoon Storm Wind Resolving NOAA NCEI Blended Sea Surface Wind (NBS) Product. Frontiers in Marine Sciences – Ocean Observation 2022, 9, 1–12. https://doi.org/10.3389/fmars.2022.935549.
Peng, G., H.-M. Zhang, H.P. Frank, J.-R. Bidlot, M. Higaki, S. Stevens, and W.R. Hankins, 2013: Evaluation of various surface wind products with OceanSITES buoy measurements. Weather and Forecasting, 28, 1281–1303, https://doi.org/10.1175/WAF-D-12-00086.1.
Zhang, H.-M., J. J. Bates, and R. W. Reynolds, 2006: Assessment of composite global sampling: Sea surface wind speed, Geophysical Research Letters, 33, L17714, https://doi.org/10.1029/2006GL027086.
Zhang, H.-M., R.W. Reynolds, and J.G. Bates, 2006: Blended and gridded high resolution global sea surface wind speed and climatology from multiple satellites: 1987–present. 14th Conference on Satellite Meteorology and Oceanography, Atlanta, GA, American Meteorological Society, Paper 100004. [https://ams.confex.com/ams/Annual2006/webprogram/Paper100004.html].

Measurements

Sea Surface Vector Winds

Processing Levels

Level 4

Spatial Coverage

Global

Saha, K.; Huai-Min, Z. Hurricane and Typhoon Storm Wind Resolving NOAA NCEI Blended Sea Surface Wind (NBS) Product. Frontiers in Marine Sciences – Ocean Observation 2022, 9, 1–12. https://doi.org/10.3389/fmars.2022.935549.

Latency Groups

0 Hours <= 24 Hours (NRT)

24+ hours (Delayed)

Latency Details

24 hrs (for NRT)

Spatial Resolution Groups

2km+

Spatial Resolution Details

0.25°

Platforms

Instruments

Data Providers

NOAA

NESDIS

NCEI

STAR

Product DOI

https://doi.org/10.3389/fmars.2022.935549

Data Tool Links

Near Real-time: Coming Soon

Wind (6 hr [vector] + Daily [raster]): portal

Wind Stress (taux,tauy): portal -- coming soon

Science:

Wind (6 hr [vector] + Daily [raster]): portal

Wind Stress (taux,tauy): portal -- coming soon

Sample Filenames

Retrospective:

NBSv02_wind_6hourly_YYYYMMDD.nc

NBSv02_wind_stress_6hourly_YYYYMMDD.nc,

NBSv02_wind_daily_YYYYMMDD.nc,

NBSv02_wind_stress_daily_YYYYMMDD.nc,

NBSv02_wind_monthly_YYYYMM.nc,

NBSv02_wind_stress_monthly_YYYYMM.nc

NRT:

NBSv02_wind_6hourly_YYYYMMDD_nrt.nc

NBSv02_wind_stress_6hourly_YYYYMMDD_nrt.nc

NBSv02_wind_daily_YYYYMMDD_nrt.nc

NBSv02_wind_stress_daily_YYYYMMDD_nrt.nc

HTTPS

Near Real-time:

Wind (magnitude+uv components): https://coastwatch.noaa.gov/data/pub0015/coastwatch/blended/wind/nrt/uvcomp/

Wind Stress (taux,tauy): https://coastwatch.noaa.gov/data/pub0015/coastwatch/blended/wind/nrt/stress/

Science:

Wind (magnitude+uv components): https://coastwatch.noaa.gov/data/pub0015/coastwatch/blended/wind/science/uvcomp/

Wind Stress (taux,tauy): http://coastwatch.noaa.gov/data/pub0015/coastwatch/blended/wind/science/stress/

THREDDS

NRT and Science:

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

ERDDAP

NRT and Science:

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

ACSPO Global SST from MODIS

jebidiah.jeffery — Thu, 17 Mar 2022 15:23:08 +0000

ACSPO Global SST from MODIS

The ACSPO MODIS SST data are produced from Terra and Aqua satellites using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) enterprise system (Ignatov et al., 2016). Complete archive of ACSPO MODIS SST data is available for both the Terra (24 Feb 2000 - present) and Aqua (4 July 2002 - present) missions in 0.02° L3C (level 3 collated) format. New data is added in delayed mode (DM) with a 2-month latency. The last orbital maintenance maneuvers for Aqua and Terra were performed on 27 Feb 2020 (Terra) and 18 Mar 2021 (Aqua) and their orbit has been drifting ever since. We do not recommend usage of ACSPO MODIS SST dated a year or later after each satellites' last orbital maintenance maneuver. For more recent SST data from low earth orbit satellites, we recommend the ACSPO VIIRS and AVHRR FRAC datasets.

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

The MODIS SST data are produced from Terra and Aqua satellites using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) enterprise system (Ignatov et al., 2016). Complete archive of ACSPO MODIS SST data is available for the entire Terra (24 Feb 2000-present) and Aqua (4 July 2002-present) missions in L3C (level 3 collated; 0.02°) format. New data is added in delayed mode (DM) with a 2-month latency. The last orbital maintenance maneuvers for Aqua and Terra were performed on 27 Feb 2020 (Terra) and 18 Mar 2021 (Aqua) and their orbit has been drifting ever since. We do not recommend usage of ACSPO MODIS SST dated a year or later after each satellites' last orbital maintenance maneuver. For more recent SST data fromlow earth orbit satellites, we recommend the ACSPO VIIRS and AVHRR FRAC datasets.

The data are reported daily, separated into daytime and nighttime viewing conditions (two files per 24hr) in GHRSST Data Specifications v2 (GDS2) format, in 0.02° gridded L3C (C=collated), 2 files per day, with a total data volume of 0.4 GB/day.

ACSPO retrievals are made in full MODIS swath (~2,300 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 following layers are reported in L3C files: SSTs derived using the Non-Linear SST (NLSST) algorithm (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); MERRA2 wind speed; 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.

MODIS SST is 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

ACSPO_MODIS_RAN_L3C

Temporal Start Date

February 24, 2000

Temporal Coverage

24 Feb 2000-present (Terra)
4 July 2002-present (Aqua)

Product Families

Sea Surface Temperature

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 3

Spatial Coverage

Global

The ACSPO MODIS 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

24+ hours (Delayed)

Latency Details

2 months

Spatial Resolution Groups

2km+

Spatial Resolution Details

L3C: 0.02°

Platforms

Aqua

Terra

Instruments

MODIS

Processing Algorithms

ACSPO

Data Providers

NOAA

NESDIS

STAR

Sample Filenames

Terra L3C (night): 20120721120000-STAR-L3C_GHRSST-SSTsubskin-MODIS_T_N-ACSPO_V2.80-v02.0-fv01.0.nc
Terra L3C (day): 20120721120000-STAR-L3C_GHRSST-SSTsubskin-MODIS_T_D-ACSPO_V2.80-v02.0-fv01.0.nc

Aqua L3C (night): 20120721120000-STAR-L3C_GHRSST-SSTsubskin-MODIS_A_N-ACSPO_V2.80-v02.0-fv01.0nc
Aqua L3C (day): 20120721120000-STAR-L3C_GHRSST-SSTsubskin-MODIS_A_D-ACSPO_V2.80-v02.0-fv01.0.nc

HTTPS

Reanalysis / Reprocessed (RAN) [New data is added in delayed mode (DM) with a 2 month delay]

L3C:

https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/ran/modis/

THREDDS

Reanalysis / Reprocessed (RAN) [New data is added in delayed mode (DM) with a 2 month delay]

L3C:

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

Seascape Pelagic Habitat Classification

jebidiah.jeffery — Thu, 23 Dec 2021 17:21:24 +0000

Seascape Pelagic Habitat Classification

MBON Seascapes identifies spatially explicit water masses with particular biogeochemical features using a model and satellite-derived measurements. The seascape product is generated as monthly and 8-day composites at 5 km spatial resolution

jebidiah.jeffery Thu, 12/23/2021 - 12:21

The US and global Marine Biodiversity Observation Network (MBON) partnered with the US Integrated Ocean Observation System (IOOS), NOAA/OAR/AOML and NOAA/NESDIS/STAR to develop and routinely generate this Seascape Pelagic Habitat Classification product (MBON Seascapes) and make it available on CoastWatch. Derived from dynamic fields of satellite and modelled data, MBON Seascapes are classified and used as a biogeographical framework to describe dynamic, changing ocean habitats for MBON and other applications. MBON Seascapes provide information about the quality and extent of different oceanographic habitats or features and can be used to assess and predict the different planktonic and fisheries communities that reside within seascapes. Current MBON Seascapes products include monthly and 8-day time steps at 5 km resolution. High resolution (1 km) case studies are planned on a case by case basis through cooperation with US and global MBON partners.

Table of Seascape ID number definitions. SST, sea surface temperature; SSS sea surface salinity; ADT, absolute dynamic topography; ICE, Ice; CDOM, chromophoric dissolved organic material; CHLA, chlorophyll-a; NFLH, normalized fluorescent line height; NaN, not a number.

Table of Seascape ID number definitions

Short Names

seascapes

Temporal Coverage

Monthly and 8-Day

Product Families

Seascape Classification

Montes Enrique, Djurhuus Anni, Muller-Karger Frank E., Otis Daniel, Kelble Christopher R., Kavanaugh Maria T., 2020. Dynamic Satellite Seascapes as a Biogeographic Framework for Understanding Phytoplankton Assemblages in the Florida Keys National Marine Sanctuary, United States. Frontiers in Marine Science, 7, https://doi.org/10.3389/fmars.2020.00575
Kavanaugh, M.T., Church, M.J., Davis, C.O., Karl, D.M., Letelier, R.M. and Doney, S.C., 2018. ALOHA from the Edge: Reconciling three decades of in situ Eulerian observations and geographic variability in the North Pacific Subtropical Gyre. Frontiers in Marine Science, 5, p.130.
Muller-Karger, F., Digna Rueda-Roa, Francisco Chavez, Maria Kavanaugh, and Mitchell A. Roffer. 2017. Megaregions Among the Large Marine Ecosystems of the Americas. Environmental Development. http://dx.doi.org/10.1016/j.envdev.2017.01.005.
Kavanaugh, M.T., Oliver, M J., Chavez, F. P., Letelier, R.M., Muller-Karger, F.E., Doney, S.C. 2016. Seascapes as a new vernacular for ocean monitoring, management and conservation. ICES Journal of Marine Science. doi:10.1093/icesjms/fsw086.
Kavanaugh, M.T., Hales, B., Saraceno, M., Spitz, Y.H., White, A.E. and Letelier, R.M., 2014. Hierarchical and dynamic seascapes: A quantitative framework for scaling pelagic biogeochemistry and ecology. Progress in Oceanography, 120, pp.291-304.
Muller-Karger, F.E., M.T. Kavanaugh, E. Montes, W.M. Balch, M. Breitbart, F.P. Chavez, S.C. Doney, E.M. Johns, R.M. Letelier, M.W. Lomas, H.M. Sosik, and A.E. White. 2014. A framework for a marine biodiversity observing network within changing continental shelf seascapes. Oceanography 27(2):18–23, http://dx.doi.org/10.5670/oceanog.2014.56.

Measurements

Pelagic Seascape Classification

Processing Levels

Level 4

Spatial Coverage

Global

Latency Groups

24+ hours (Delayed)

Spatial Resolution Groups

2km+

Spatial Resolution Details

5 km

Platforms

Instruments

Data Providers

NOAA

NESDIS

STAR

CoastWatch

Data Tool Links

Coastwatch Data Portal

THREDDS

8-Day Composite

https://cwcgom.aoml.noaa.gov/thredds/SEASCAPE_8DAY.html?dataset=SEASCAPE_8DAY

Monthly Composite

https://cwcgom.aoml.noaa.gov/thredds/SEASCAPE_MONTH.html?dataset=SEASCAPE_MONTH

ACSPO Global 0.02º Gridded Super-collated SST and Thermal Fronts from Low-Earth-Orbiting Platforms (L3S-LEO)

jebidiah.jeffery — Thu, 21 Oct 2021 15:47:25 +0000

ACSPO Global 0.02º Gridded Super-collated SST and Thermal Fronts from Low-Earth-Orbiting Platforms (L3S-LEO)

NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) L3S-LEO SST is a family of multisensor gridded ("L3") 0.02º resolution super-collated ("S") products. The L3S-LEO family is organized into three lines: PM, AM and Daily. The AM and PM lines correspond to 9:30am/pm and 1:30am/pm equator crossing times, respectively. The Daily line combines PM and AM (day and night) SSTs into a single daily L3S SST that is normalized to 1:30am viewing conditions.

jebidiah.jeffery Thu, 10/21/2021 - 11:47

The NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) L3S-LEO is a family of multisensor super-collated (L3S) gridded 0.02º resolution SST products from low earth orbit (LEO) satellites. The L3S-LEO family is organized into three lines: PM, AM and Daily. The AM (mid-morning orbit) and PM (afternoon orbit) lines contain SST data from satellites with 9:30am/pm and 1:30am/pm equator crossing times, respectively. Both AM and PM lines are split into day-time (solar zenith angle < 90º) and night-time (solar zenith angle >= 90º) files, resulting in 4 files per day in total, which approximately cover the 24 hours diurnal cycle in 4 points. The Daily (DY) line combines PM and AM (day and night) SSTs into a single daily L3S SST that is normalized to 1:30am viewing conditions using a statistical model informed by surface wind speed and shortwave radiation.

The AM product is produced from three (currently two active) AVHRR FRACs (flown aboard METOP-A, B and C). The PM product is produced from three VIIRSs (flown aboard NPP, N20, N21) and MODIS (onboard Aqua; included until Dec 31 2022). The DY product is produced by combining all four L3S-LEO-AM/PM day/night SSTs. SST from Terra MODIS is also included in DY in until 31 Dec 2021.

All L3S-LEO products contain information about thermal fronts, which is included in ACSPO files in two new variables ‘sst_front_position’ and ‘sst_gradient_magnitude’. The first variable is a binary indicator of SST front position. It is set to ‘1’ where a front is present, and to ‘0’ elsewhere. The second variable is the SST gradient magnitude (in units of K/km).

L3S-LEO data are provided in GHRSST Data Specification v2 (GDS2) NetCDF format, as L3S (gridded, super-collated, 0.02º). We plan to create an L3S-GEO line, and eventually consolidate the L3S-LEO and L3S-GEO into one sensor-agnostic L3S SST product.

All ACSPO L3S-LEO products provided here are mature and validated. Please contact the CoastWatch helpdesk with any questions.

Short Names

ACSPO-L3S-LEO-PM-v2.81

ACSPO-L3S-LEO-AM-v2.80

ACSPO-L3S-LEO-Daily-v2.81

Temporal Start Date

February 24, 2000

Product Families

Sea Surface Temperature

Algorithms

Jonasson, O.; Gladkova, I.; Ignatov, A. Towards global daily gridded super-collated SST product from low earth orbiting satellites (L3S-LEO-Daily) at NOAA. Proc. SPIE 2022, 12118, 1211805, doi:10.1117/12.2620103, [pdf paper (link)], [mp4 presentation (link)], [ppt presentation (link)].
Jonasson, O.; Gladkova, I.; Ignatov, A.; Kihai, Y. Algorithmic Improvements and Consistency Checks of the NOAA Global Gridded Super-Collated SSTs from Low Earth Orbiting Satellites (L3S-LEO). Proc. SPIE 2021, 11752, 1175202, doi:10.1117/12.2585819, [pdf paper (link)], [mp4 presentation (link)], [ppt presentation (link)].
Jonasson, O.; Gladkova, I.; Ignatov, A.; Kihai, Y. Progress with Development of Global Gridded Super-Collated SST Products from Low Earth Orbiting Satellites (L3S-LEO) at NOAA. Proc. SPIE 2020, 11420, 1142002. doi:10.1117/12.2551819. [pdf paper (link)], [mp4 presentation (link)], [ppt presentation (link)].
Gladkova, I.; Ignatov, A.; Pennybacker, M.; Kihai, Y. Towards High-Resolution Multi-Sensor Gridded ACSPO SST Product: Reducing Residual Cloud Contamination. Proc. SPIE 2019, 11014, 110140L. doi:10.1117/12.2518462, [pdf paper (link)], [ppt presentation (link)].
Gladkova, I., A. Ignatov, M. Pennybacker, Y. Kihai, 2019: Towards High-Resolution Multi-Sensor Gridded ACSPO L3S SST Product. GHRSTT XX: Science Team Meeting, June 2019, Frascati, Italy [ppt presentation (link)].

Monitoring

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: Xu, F., A. Ignatov, 2014: In situ SST Quality Monitor (iQuam). JTech, 31, 164-180, doi:10.1175/JTECH-D-13-00121.1.
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 [ppt presentation 21.5Mb (link)].
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 - Polar-orbiting

Processing Levels

Level 3

Spatial Coverage

Global

The ACSPO L3S-LEO SST data are provided by NOAA STAR. We strongly recommend contacting Olafur.Jonasson@noaa.gov or Alex.Ignatov@noaa.gov, before the data are used for any publication or presentation.

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

24 hours

Spatial Resolution Groups

2km+

Spatial Resolution Details

0.02°

Platforms

Instruments

Processing Algorithms

ACSPO

Data Providers

NOAA

NESDIS

STAR

Data Tool Links

Routine Research Production (source: STAR)
(Best effort, most recent ACSPO release, last 90 days)

PM L3S: Day Night

AM L3S: Day Night

Daily L3S: Day+Night Fronts

Reanalysis (RAN) Research Production (source: STAR)
(delayed 2 months, science quality)

PM L3S: Day Night

AM L3S: Day Night

Daily L3S: Day+Night Fronts

Sample Filenames

Near Real-Time (NRT) Operational Production (source: OSPO)

20240930120000-OSPO-L3S_GHRSST-SSTsubskin-LEO_AM_D-ACSPO_V2.80-v02.0-fv01.0.nc
20240930120000-OSPO-L3S_GHRSST-SSTsubskin-LEO_AM_N-ACSPO_V2.80-v02.0-fv01.0.nc
20240930120000-OSPO-L3S_GHRSST-SSTsubskin-LEO_PM_D-ACSPO_V2.80-v02.0-fv01.0.nc
20240930120000-OSPO-L3S_GHRSST-SSTsubskin-LEO_PM_N-ACSPO_V2.80-v02.0-fv01.0.nc

Research Production (source: STAR)

20200330120000-STAR-L3S_GHRSST-SSTsubskin-LEO_AM_N-ACSPO_V2.80-v02.0-fv01.0.nc
20200330120000-STAR-L3S_GHRSST-SSTsubskin-LEO_AM_D-ACSPO_V2.80-v02.0-fv01.0.nc
20200330120000-STAR-L3S_GHRSST-SSTsubskin-LEO_PM_N-ACSPO_V2.81-v02.0-fv01.0.nc
20200330120000-STAR-L3S_GHRSST-SSTsubskin-LEO_PM_D-ACSPO_V2.81-v02.0-fv01.0.nc
20200330120000-STAR-L3S_GHRSST-SSTsubskin-LEO_Daily-ACSPO_V2.81-v02.0-fv01.0.nc

HTTPS

Near Real-Time (NRT) Operational Production (source: OSPO)

AM,PM L3S (last 15 days):

https://coastwatch.noaa.gov/data/pub0053/coastwatch/sst/nrt/l3s/

Routine Research Production (source: STAR)
(Best effort, most recent ACSPO release, last 90 days)

PM L3S:

https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/nrt/l3s/leo/pm

AM L3S:

https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/nrt/l3s/leo/am

Daily L3S:

https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/nrt/l3s/leo/daily

Reanalysis (RAN) Research Production (source: STAR)
(delayed 2 months, science quality)

PM L3S:

https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/ran/l3s/leo/pm

AM L3S:

https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/ran/l3s/leo/am

Daily L3S:

https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/ran/l3s/leo/daily

Production sources

STAR - Center for Satellite Applications and Research

OSPO - Office of Satellite and Product Operations

Data content description

*NRT - Near-Real Time data
*RAN - Reanalysis of L3S-LEO-PM (Jul'2002-present), L3S-LEO-AM (Dec'2006-present), and L3S-LEO-DY (Feb'2000-present). Note that reanalysis data is produced on a 8-week delay.

Please acknowledge "NOAA CoastWatch/OceanWatch" when you use data from our site and cite the particular dataset DOI as appropriate.

THREDDS

Routine Research Production (source: STAR)
(Best effort, most recent ACSPO release, last 90 days)

https://coastwatch.noaa.gov/thredds/socd/coastwatch/acspo/catalog_sst_acspo_l3s_nrt.html

Reanalysis (RAN) Research Production (source: STAR)
(delayed 2 months, science quality)

https://coastwatch.noaa.gov/thredds/socd/coastwatch/acspo/catalog_sst_acspo_l3s_ran.html

ERDDAP

Near Real-Time (NRT) Research Production (source: STAR)
(Best effort, most recent ACSPO release, last 90 days)

Daily L3S:

https://coastwatch.noaa.gov/erddap/griddap/noaacwLEOACSPOSSTL3SnrtKDaily.html (Kelvin)

https://coastwatch.noaa.gov/erddap/griddap/noaacwLEOACSPOSSTL3SnrtCDaily.html (degrees Celsius)

Reanalysis (RAN) Research Production (source: STAR)
(delayed 2 months, science quality)

Daily L3S:

https://coastwatch.noaa.gov/erddap/griddap/noaacwLEOACSPOSSTL3SKDaily.html (Kelvin)

https://coastwatch.noaa.gov/erddap/griddap/noaacwLEOACSPOSSTL3SCDaily.html (degrees Celsius)

PO.DAAC Archive

NRT data is overwritten with RAN 'scientific quality' SST data with a 2-month delay

L3S-AM: 10.5067/GHLAM-3SS28

L3S-PM: 10.5067/GHLPM-3S281

L3S-Daily: 10.5067/GHLDY-3S281

NCEI Archive

NRT data is overwritten with RAN 'scientific quality' SST data with a 2-month delay

L3S-AM: 10.25921/0twk-7h57

L3S-PM: 10.25921/fddx-gq76