DMSP

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

Winds from Special Sensor Microwave Imager (SSM/I)

jebidiah.jeffery — Thu, 17 Mar 2022 15:29:52 +0000

Winds from Special Sensor Microwave Imager (SSM/I)

Defense Meteorological Satellite Program (DMSP) / Special Sensor Microwave Imager (SSM/I) Wind Speed

jebidiah.jeffery Thu, 03/17/2022 - 11:29

Temporal Coverage

Near real-time + 3 days

Product Families

Sea Surface Winds

Measurements

Sea Surface Wind Speed

Processing Levels

Level 3

Spatial Coverage

Global

Latency Groups

0 Hours <= 24 Hours (NRT)

Latency Details

Less than 24 hours

Spatial Resolution Groups

2km+

Spatial Resolution Details

0.33° (37 km)

Platforms

DMSP

Instruments

SSMIS

Data Providers

NOAA

NESDIS

OSPO

Data Tool Links

CoastWatch Near Real-Term Search

Sample Filenames

SSMI1630004as_WW.hdf

HTTPS

https://coastwatch.noaa.gov/pub/socd1/coastwatch/products/ssmi/

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.