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Oceanographic geographical features

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  • SpiArcBase is a software developed for the treatment of Sediment Profile images (SPIs). Sediment Profile Images (SPIs) are widely used for benthic ecological quality assessment under various environmental stressors. The processing of the information contained in SPIs is slow and its interpretation is largely operator dependent. SpiArcBase enhances the objectivity of the information extracted from SPIs, especially for the assessment of the apparent Redox Potential Discontinuity (aRPD). This software allows the user to create and manage a database containing original SPIs and corresponding derived pieces of information. Once you have downloaded it, you can ask for help and stablish a helpdesk.

  • Sediment Profile Images (SPIs) are commonly used to map physical, biological and chemical/nutrient gradients in benthic habitats. SpiArcBase is a software that has been developed for the analysis of Sediment Profile Images (SPIs). It has been conceived to improve the objectivity of extracted information (especially the apparent Redox Potential Discontinuity (aRPD). The software presents a graphical user interface designed to enhance the interpretation of features observed on SPIs in an objective manner and to facilitate image management and structures visualization via a data base.The software also allows for the storage of generated data and the automatic computation of a benthic habitat quality index. The facilities provided within JERICONext include access to the software through free downloading and assistance in its utilization.

  • The Joint Polar Satellite System (JPSS), starting with S-NPP launched on 28 October 2011, is the new generation of the US Polar Operational Environmental Satellites (POES). The Suomi National Polar-orbiting Partnership (S-NPP) is a collaboration between NASA and NOAA. NOAA is responsible for all JPSS products, including SST from the Visible Infrared Imaging Radiometer Suite (VIIRS). VIIRS is a whiskbroom scanning radiometer, which takes measurements in the cross-track direction within a field of view of 112.56-deg using 16 detectors and a double-sided mirror assembly. At a nominal altitude of 829 km, the swath width is 3,060 km, providing global daily coverage for both day and night passes. VIIRS has 22 spectral bands covering the spectrum from 0.4-12 um, including 16 moderate resolution bands (M-bands). The L2P SST product is derived at the native sensor resolution (~0.75 km at nadir, ~1.5 km at swath edge) using NOAA's Advanced Clear-Sky Processor for Ocean (ACSPO) system, and reported in 10-minute granules in netCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). There are 144 granules per 24hr interval, with a total data volume of 27GB/day. In addition to pixel-level earth locations, Sun-sensor geometry, and ancillary data from the NCEP global weather forecast, ACSPO outputs include four brightness temperatures (BTs) in M12 (3.7um), M14 (8.6um), M15 (11um), and M16 (12um) bands, and two reflectances in M5 (0.67um) and M7 (0.87um) bands. The reflectances are used for cloud identification. Beginning with ACSPO v2.60, all BTs and reflectances are destriped (Bouali and Ignatov, 2014) and resampled (Gladkova et al., 2016), to minimize the effect of bow-tie distortions and deletions. SSTs are retrieved from destriped BTs.SSTs are derived from BTs using the Multi-Channel SST (MCSST; night) and Non-Linear SST (NLSST; day) algorithms (Petrenko et al., 2014). An ACSPO clear-sky mask (ACSM) is provided in each pixel as part of variable l2p_flags, which also includes day/night, land, ice, twilight, and glint flags (Petrenko et al., 2010). Fill values are reported in all invalid pixels, including those with >5 km inland. For each valid water pixel (defined as ocean, sea, lake or river, and up to 5 km inland), four BTs in M12/14/15/16 (included for those users interested in direct "radiance assimilation", e.g., NOAA NCEP, NASA GMAO, ECMWF) and two refelctances in M5/7 are reported, along with derived SST. Other variables include NCEP wind speed and ACSPO SST minus reference SST (Canadian Met Centre 0.1deg L4 SST; available at https://podaac.jpl.nasa.gov/dataset/CMC0.1deg-CMC-L4-GLOB-v3.0). Only ACSM confidently clear pixels are recommended (equivalent to GDS2 quality level=5). Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (SSES bias and standard deviation) are reported in each pixel with QL=5. Note that users of ACSPO data have the flexibility to ignore the ACSM and derive their own clear-sky mask, and apply it to BTs and SSTs. They may also ignore ACSPO SSTs, and derive their own SSTs from the original BTs.The ACSPO VIIRS L2P product is monitored and validated against quality controlled in situ data provided by NOAA in situ SST Quality Monitor system (iQuam; Xu and Ignatov, 2014) using another NOAA system, SST Quality Monitor (SQUAM; Dash et al, 2010). Corresponding clear-sky BTs are validated against RTM simulations in the Monitoring IR Clear-sky Radiances over Ocean for SST system (MICROS; Liang and Ignatov, 2011). A reduced size (1GB/day), equal-angle gridded (0.02-deg resolution), ACSPO L3U product is also available at https://podaac.jpl.nasa.gov/dataset/VIIRS_NPP-OSPO-L3U-v2.61, where gridded L2P SSTs with QL=5 only are reported, and BT layers omitted.

  • The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to the Special Sensor Microwave Imager (SSM/I), that contains lower frequency channels required for sea surface temperature (SST) retrievals. The TRMM is part of the NASA's mission to planet Earth, and is a joint venture between NASA and the Japan Aerospace Exploration Agency (JAXA) to measure precipitation, water vapor, sea surface temperature (SST) and surface wind in the global tropical regions and was launched in 27 November 1997 from the Tanegashima Space Center in Tanegashima, Japan. The TRMM satellite travels west to east in a 402 km altitude semi-equatorial processing orbit that results in day-to-day changes in the observation time of any given earth location between 38S and 38N. Remote Sensing Systems (REMSS) has produced a Version-7.1a TMI SST dataset for the Group for High Resolution Sea Surface Temperature (GHRSST) by applying an algorithm to the 10.7 GHz channel through a removal of surface roughness effects. In contrast to infrared SST observations, microwave retrievals can be measured through clouds, which are nearly transparent at 10.7 GHz. Microwave retrievals are also insensitive to water vapor and aerosols. The algorithm for retrieving SSTs from radiometer data is described in "AMSR Ocean Algorithm."

  • A Group for High Resolution Sea Surface Temperature (GHRSST) global Level 4 sea surface temperature analysis produced daily on a 0.25 degree grid at the NOAA National Climatic Data Center. This product uses optimal interpolation (OI) using data from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Version 5 time series (when available, otherwise operational NOAA AVHRR data are used), the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), and in situ ship and buoy observations. A second similar product is available back to 1981 that includes only in situ and AVHRR Pathfinder data in its analysis. The OI analysis is a daily average SST that is bias adjusted using a spatially smoothed 7-day in situ SST average and is thus tuned to about 0.3 meter. Both day and night satellite fields are independently bias adjusted. More information is available at http://www.ncdc.noaa.gov/oa/climate/research/sst/oi-daily.php

  • A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis by the Danish Meteorological Institute (DMI) using an optimal interpolation (OI) approach on a global 0.05 degree grid. The analysis is based upon nighttime GHRSST L2P skin and subskin SST observations from several satellites. The sensors include the Advanced Very High Resolution Radiometer (AVHRR), the Spinning Enhanced Visible and Infrared Imager (SEVIRI), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Visible Infrared Imager Radiometer Suite (VIIRS), and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua. An ice field from the EUMETSAT OSI-SAF is used to mask out areas with ice. This dataset adheres to the version 2 GHRSST Data Processing Specification (GDS).

  • A Group for High Resolution Sea Surface Temperature (GHRSST) global Level 4 sea surface temperature analysis produced daily on a 0.25 degree grid at the NOAA National Climatic Data Center. This product uses optimal interpolation (OI) using data from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Version 5 time series (when available, otherwise operational NOAA AVHRR data are used), the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), and in situ ship and buoy observations. A second similar product is available back to 1981 that includes only in situ and AVHRR Pathfinder data in its analysis. The OI analysis is a daily average SST that is bias adjusted using a spatially smoothed 7-day in situ SST average and is thus tuned to about 0.3 meter. Both day and night satellite fields are independently bias adjusted. More information is available at http://www.ncdc.noaa.gov/oa/climate/research/sst/oi-daily.php

  • A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced as a retrospective dataset at the JPL Physical Oceanography DAAC using wavelets as basis functions in an optimal interpolation approach on a global 0.25 degree grid. The version 4 Multiscale Ultrahigh Resolution (MUR) L4 analysis is based upon nighttime GHRSST L2P skin and subskin SST observations from several instruments including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. The ice concentration data are from the archives at the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) High Latitude Processing Center and are also used for an improved SST parameterization for the high-latitudes. The dataset also contains an additional SST anomaly variable derived from a MUR climatology (average between 2003 and 2014). This dataset was originally funded by the NASA MEaSUREs program (http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects ) and the NASA CEOS COVERAGE project and created by a team led by Dr. Toshio M. Chin from JPL. It adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications.

  • A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis, produced daily on an operational basis at the Australian Bureau of Meteorology (BoM) using optimal interpolation (OI) on a global 0.25 degree grid. This Global Australian Multi-Sensor SST Analysis (GAMSSA) v1.0 system blends satellite SST observations from passive infrared and passive microwave radiometers with in situ data from ships, drifting buoys and moorings from the Global Telecommunications System (GTS). SST observations that have experienced recent surface wind speeds less than 6 m/s during the day or less than 2 m/s during night are rejected from the analysis. The processing results in daily foundation SST estimates that are largely free of nocturnal cooling and diurnal warming effects. Sea ice concentrations are supplied by the NOAA/NCEP 12.7 km sea ice analysis. In the absence of observations, the analysis relaxes to the Reynolds and Smith (1994) Monthly 1 degree SST climatology for 1961 - 1990.

  • A Group for High Resolution Sea Surface Temperature (GHRSST) global Level 4 sea surface temperature analysis produced daily on a 0.25-degree grid at Remote Sensing Systems. This product uses optimal interpolation (OI) from microwave (MW) sensors including the Global Precipitation Measurement (GPM) Microwave Imager (GMI), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), the NASA Advanced Microwave Scanning Radiometer-EOS (AMSRE), the Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the GCOM-W1 satellite, and WindSat operates on the Coriolis satellite. The through-cloud capabilities of microwave radiometers provide a valuable picture of global sea surface temperature (SST). This analysis does not use any in situ SST data such as drifting buoy SST. Comparing with previous version 4.0 dataset, the version 5.0 has made the updates in several areas, including the diurnal warming model, the sensor-specific error statistics (SSES) for each microwave sensor, the sensor correlation model, and the quality mask.