20200408120000-STAR-L3S_GHRSST-SST_800.png

README (NRT)
README (RAN)
Data content description

*NRT - Near-Real Time data
*RAN - Reanalysis of L3S-LEO PM (Feb'2012-present) and L3S-LEO AM (Dec'2006-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.

20200408120000-STAR-L3S_GHRSST-SST_800.png

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 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) AVHRR FRACs (flown aboard METOP-A, B and C) and the PM product is produced from two VIIRSs (flown aboard NPP and N20). Adding MODIS-Terra to the AM line, and MODIS-Aqua to the PM line is being explored.

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.

Note that the ACSPO L3S-LEO-Daily product provided here is experimental while the PM and AM products are mature and validated. Both the L3S-LEO-Daily product, and its documentation, are currently in development and subject to change. Please contact the CoastWatch helpdesk with any questions.

KeyDescription
Platform/Sensor

Afternoon (PM): NPP, N20 / VIIRS
Mid-morning (AM): MetOp-A, -B and -C / AVHRR-3
Daily: NPP, N20, MetOp-A, B -and -C

Measurement/Products

Measurement Oceans > Sea Surface Temperature > subskin SST

DOI

n/a

Short Name

ACSPO-L3S-LEO-PM-v2.80
ACSPO-L3S-LEO-AM-v2.80
ACSPO-L3S-LEO-Daily-v2.80

Sample Filename

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_V2.80-v02.0-fv01.0.nc
20200330120000-STAR-L3S_GHRSST-SSTsubskin-LEO_PM_D-ACSPO_V2.80-v02.0-fv01.0.nc
20200330120000-STAR-L3S_GHRSST-SSTsubskin-LEO_Daily-ACSPO_V2.80-v02.0-fv01.0.nc

Dataset Type

Open

Processing Level

L3S

Spatial Coverage

Global
180W-180E
90N-90S

Temporal Coverage

The data does not have a specific expiration date after which it is removed, but keep in mind that this is not a long term archive.

Latency

24 hours

Resolution

0.02°

Projection

Equal-grid 0.02°

Swath Width

n/a

Sample Frequency

n/a

Temporal Repeat

Twice Daily (L3S-LEO-PM/AM), Daily (L3S-LEO-Daily)

Orbital Period

n/a

Orbit

Sun-synchronous

Data Provider

Creator: NOAA STAR
Release Place: College Park, MD, USA

Formats

NetCDF (GDS2)

Keywords

NOAA, NPP, N20, S-NPP, NOAA-20, METOP-A, METOP-B, METOP-C, JPSS, VIIRS, AVHRR, FRAC, ACSPO, sea surface temperature, SST, L3S, multisensor

Documentation: 

 

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 202212118, 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, 117521175202, 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.
Data Citation: 

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