This data set contains information on historical marine debris survey and removal projects of the NOAA Marine Debris Program and its many funded partners. This data reports marine debris removal survey information and efforts by location, the amounts, and types of debris removed. The Marine Debris Clearinghouse data allows users in the marine debris community to discover these projects based on the project category, location, or debris type.

The National Climatic Data Center Tape Deck Documentation library is a collection of over 400 manuals describing NCDC's digital holdings (both historic and current). While many libraries are still available from NCDC, some datasets have been removed due to obsolesence--their respective manuals remain to serve as a permanent record of the dataset.

This dataset contains Level 1c inter-calibrated brightness temperatures from the Microwave Sounding Unit (MSU) sensors onboard nine polar orbiting satellites (TIROS-N, NOAA-6, -7, -8, -9, -10, -11, -12, and -14) spanning from 1978 to 2006. The dataset was produced by the NOAA Center for Satellite Applications and Research (STAR), and is a Fundamental Climate Data Record (FCDR) of microwave brightness temperatures in the NOAA CDR Program. MSU is a four-channel microwave radiometer measuring at 50.3, 53.74, 54.96, and 57.95 GHz, and has ground spatial resolution of about 250 km in diameter at nadir. The native MSU Level 1b data were inter-calibrated using the Integrated Microwave Inter-Calibration Approach (IMICA) method to obtain a long-term data product to be used in climate analyses. For comparison, data files also include the operational data used in NWP forecasting along with the IMICA calibrated radiances, which minimize or remove the biases found in the operational calibration. In addition, limb adjusted radiances for both the IMICA and operational calibrations are included for certain type of climate applications, such as atmospheric layer temperature development using the radiance datasets. The orbital swath data files include MSU channels 2 through 4 for the IMICA calibration, and channels 1 through 4 for the operational calibration. The inter-calibrated MSU data are not expected to change for the dataset time period.

This dataset contains Raleigh Durham International Airport weather data pulled from the NOAA web service described at Climate Data Online: Web Services Documentation. We have pulled this data and converted it to commonly used units. This dataset is an archive - it is not being updated.

Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version. The dataset contains three MSU channel-based, monthly gridded atmospheric layer temperature Climate Data Records generated by merging nine NOAA polar orbiting satellites, TRIOS-N and NOAA-6 through NOAA-14. These are temperatures of middle-troposphere (TMT), upper-troposphere (TUT, also known as temperature troposphere stratosphere), and lower-stratosphere (TLS), corresponding to measurements from MSU channels 2, 3, and 4, respectively. These products have global coverage with a 2.5 latitudes by 2.5 longitude grid resolution. Time period is from November 1978 through September 2006. Adjustments of observations included limb-adjustment, diurnal drift corrections, warm target temperature effect, and residual inter-satellite bias removal.

Contains 5 separate mean layer temperature datasets from NOAA NCEI: Mean Layer Temperature - NOAA CDR Configuration Item ID: 01B-25 The Mean Layer Temperature – NOAA Climate Data Record (CDR) provides long-term temperature measurements for a thick layer of the upper atmosphere. Input data comes from Mean Layer Temperature (MLT) level-1c swath radiances taken by the Microwave Sounding Unit (MSU), the Advanced Microwave Sounder Unit-A (AMSU-A) and the Advanced Technology Microwave Sounder (ATMS) aboard NOAA, NASA, and EUMETSAT satellites. The CDR was calibrated using the NOAA STAR Integrated Microwave Inter-Calibration Approach (IMICA) to remove calibration drifting errors. The final dataset incorporates inter-satellite bias corrections to ensure consistency, and adjustments that account for diurnal drift effect, differences between viewing angles, and channel frequency differences between sensors. The final record is a monthly global gridded dataset with 2.5°x2.5° Latitude/Lo

Datalogger files are raw USCRN data. However, instead of being collected via satellite, the raw data are collected from station dataloggers (also referred to as PDAs--Personal Digital Assistant) in the field during site maintenance visits by NOAA/ATDD engineers. These data are uploaded to a site at Oak Ridge National Lab from where they are pulled by NCEI. These raw data are received as CSV formatted files--detailed documentation are required to read the data and will be provided to ingest. These files may not be available until months after the included observations are made. These data are considered of higher quality than USCRN Raw/streamed data.

Release of the hourly database containing 55 cruises spanning over 31 years, including the historical data from 12 cruises done in the 1990's (Fairall et al., 2003) and 9 cruises of the PACS/EPIC dataset. Data collected from these cruises are critical for supporting the study of physical oceanography, air-sea interaction, tropical meteorology, as well as global weather and climate variability and predictability. This includes improvement to our fundamental understanding of these processes in the ocean and their influence around the globe including the Continental United States. The data will also support improvement and validation of prediction models including parameterizations. Sensible heat flux was computed from vertical velocity - sonic temperature covariance. The humidity contribution to sonic temperature was removed using the bulk latent heat flux. acknowledgement=NOAA Global Ocean Monitoring and Observing (GOMO) program cdm_data_type=Trajectory cdm_trajectory_variables=cruise_name comment=Corrections and Data Quality Notes not contained in global or variable attributes: Unavailable data, bad data, and data within restricted Exclusive Economic Zones were assigned _FillValue = -9999. Please use the variables named flag_bad_ship and flag_bad_bulk to further mask out questionable or non-ideal data points depending on the application for state variables and bulk fluxes respectively. comment2=Sensible heat flux was computed from vertical velocity - sonic temperature covariance. The humidity contribution to sonic temperature was removed using the bulk latent heat flux. comment3=A correction to account for biases in gas concentration measurements has been applied on the covariance and ID latent heat fluxes. See Fratini et al. 2014 for more details. comment4=Data from the 2004 New England Air Quality Study (NEAQS-04) are included in this dataset but it has to be noted that during that project we found significant suppression of the transfer coefficients for momentum, sensible heat, and latent heat; mainly because our measurements at 18-m height did not realize the full surface flux in these shallower boundary layer conditions. (Fairall et al., 2006). Conventions=CF-1.6, ACCD-1.3, COARDS, ACDD-1.3 coverage_content_type=physicalMeasurement, qualityInformation, modelResult, coordinate date_metadata_modified=2023-04-18T13:10:40Z Easternmost_Easting=179.73351 featureType=Trajectory geospatial_lat_bounds=POLYGON [-179.833, 179.734, -53.754, 69.934] geospatial_lat_max=69.933717 geospatial_lat_min=-53.753807 geospatial_lat_units=degrees_north geospatial_lon_max=179.73351 geospatial_lon_min=-179.83283 geospatial_lon_units=degrees_east geospatial_vertical_max=0.014330280134111055 geospatial_vertical_min=1.7080496969024725E-4 geospatial_vertical_positive=down geospatial_vertical_units=m history=v0: original data, v1: first release id=doi = not yet assigned infoUrl=https://psl.noaa.gov/boundary-layer/ institution=(1) NOAA Physical Sciences Lab (PSL); (2) CIRES Cooperative Institute for Research in Environmental Sciences at the University of Colorado Boulder in partnership with NOAA PSL instrument_vocabulary=GCMD Version 12.3 keywords_library=GCMD Version 12.3 keywords_vocabulary=GCMD Science Keywords licence=Please acknowledge data according to global attribute info: acknowledgement, creator_name, creator_institution. These data may be redistributed and used without restriction. naming_authority=gov.noaa.ncei Northernmost_Northing=69.933717 platform=refer to platform_name variable that contains names of the different platforms from which the datasets were collected platform_vocabulary=GCMD Version 12.3 processing_level=processed and quality controlled program=Funding agencies: NOAA Global Ocean Monitoring and Observing (GOMO) program project=refer to cruise_name variable for project names of various datasets references=Fairall et al. 1996a JGR https://doi.org/10.1029/95JC03190 ...Fairall et al. 1996b JGR https://doi.org/10.1029/95JC03205 .... Fairall et al. 2003 JClim https://doi.org/10.1175/1520-0442(2003)016%3C0571:BPOASF%3E2.0.CO;2 ... Edson et al. 2013 JPO with corrigendum: the value should be m = 0.0017, and not m = 0.017 as originally appeared https://doi.org/10.1175/JPO-D-12-0173.1 ... Fratini et al. 2014https://doi.org/10.5194/bg-11-1037-2014 ... Fairall et al. 2006 https://doi.org/10.1029/2006JD007597 sea_name=Northwest, Equatorial and SouthEast Pacific Ocean; North Atlantic Ocean; Davis Strait; Labrador Sea; South Atlantic Ocean; Bay of Bengal; Indian Ocean; Tasman Sea source=observations from NOAA PSL sensors (no subscript, most accurate) and the ship permanent sensors (_ship subscript, less accurate), derivations from those observations using eddy covariance and inertial dissipation methods of estimating fluxes, model results from COARE 3.6 bulk air-sea flux algorithm. Wave parameters were not used as input to COARE since they were either unavailable or not consistently available on all projects. Also True water-relative wind speed was used as input to COARE when available. Otherwise when not available the true wind speed was used instead. sourceUrl=(local files) Southernmost_Northing=-53.753807 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=platform_call_sign, platform_name, cruise_name time_coverage_duration=31 years time_coverage_end=2021-08-31T23:00:00Z time_coverage_resolution=PT60.M time_coverage_start=1991-11-22T11:41:00Z Westernmost_Easting=-179.83283

The NOAA Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature dataset derived from the International Comprehensive Ocean-Atmosphere Dataset (ICOADS). It is produced on a 2 x 2 degree grid with spatial completeness enhanced using statistical methods. This monthly analysis begins in January 1854 continuing to the present and includes anomalies computed with respect to a 1971-2000 monthly climatology. Version 5 (v5) is the newest version of ERSST. Major revisions for v5 include: 1) using unadjusted first-guess instead of adjusted first-guess in QC, 2) using latest International Comprehensive Ocean Atmosphere Data Set (ICOADS) Release 3.0 (R3.0) over 1854-2015 instead of R2.5 over 1854-2007, 3) using Argo temperature above 5 meter depth that has not been used in previous version ERSST and other SST analysis, 4) using latest UK Met Office HadISST2 ice concentration over 1870-2015 instead of HadISST1 ice concentration over 1870-2010, 5) removing damping in high latitudes north of 60 degrees North and south of 50 degrees South in Empirical Orthogonal Teleconnection (EOT) Functions, 6) adding 10 more EOT modes in the Arctic, 7) reducing spatial filtering in training EOTs, and 8) revising ship SST bias correction relative to nighttime marine air temperature (NMAT) to the one relative to buoy SST observations. Other features remain same as in the previous ERSST version 4. The data are written to monthly netCDF files following CF Metadata Conventions.

This Version 7 NOAA Fundamental Climate Data Record (CDR) from Remote Sensing Systems (RSS) contains brightness temperatures that have been inter-calibrated and homogenized over the observation time period. The temperature data are from the Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) series of passive microwave radiometers carried onboard the Defense Meteorological Satellite Program (DMSP) satellites. These satellite sensors measure the natural microwave emission coming from the Earth’s surface in the spectral band from 19 to 85 GHz. This dataset encompasses data from a total of seven satellites including the SSM/I sensors on board DMSP satellites F08, F10, F11, F13, F14, and F15 as well as the SSMIS sensors on board DMSP satellite F17. The data record covers the time period from July 1987 through the present with a one month latency. The spatial and temporal resolutions of the CDR files correspond to the original resolution of the source SSMI(S) observations. There are roughly 15 orbits per day with a swath width of approximately 1400 km resulting in nearly global daily coverage. The spatial resolution of the data is a function of the sensor/channel and varies from approximately 50 km for the lowest frequency channels to approximately 15km for the high-frequency channels. The output parameters include the observed brightness temperatures for each of the seven SSM/I channels and 24 SSMIS channels at the original sensor channel resolution along with latitude and longitude information, time, quality flags, and view angle information. The file format is netCDF-4 with added metadata that follow the Climate and Forecast (CF) Conventions and Attribute Convention for Dataset Discovery (ACDD). There are three major changes in the Version 7 processing: (1) the water vapor continuum absorption model was re-derived, (2) the clear-sky bias in cloud water was removed and the data format for cloud water was changed, and (3) the beamfilling correction in the rain algorithm was modified. Relative to Version 6, Version 7 has: (1) increased vapor values in the range of 50-60 mm by 1%, (2) increased vapor values above 60 mm by 2-3%, (3) cloud data changed to the range of cloud water values: -0.05 to 2.45 mm (cloud data format has changed), and (4) increased the global mean rain rates by about 16% (mostly due to changes in the extratropical values).

What is NOAA?

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2Fef430b23fd655fb2135bda88d89fa129%2F_430ed758-dc6f-4d24-8238-ae99d4c42870_small.jpeg?generation=1718958727077209&alt=media" alt="">

The National Oceanic and Atmospheric Administration (abbreviated as NOAA /ˈnoʊ.ə/ NOH-ə) is a US scientific and regulatory agency charged with forecasting weather, monitoring oceanic and atmospheric conditions, charting the seas, conducting deep-sea exploration, and managing fishing and protection of marine mammals and endangered species in the US exclusive economic zone. The agency is part of the United States Department of Commerce and is headquartered in Silver Spring, Maryland.

From Wikipedia

What is AIS data?

The automatic identification system, or AIS, transmits a ship’s position so that other ships are aware of its position. The International Maritime Organization and other management bodies require large ships, including many commercial fishing vessels, to broadcast their position with AIS in order to avoid collisions. Each year, more than 400,000 AIS devices broadcast vessel location, identity, course and speed information. Ground stations and satellites pick up this information, making vessels trackable even in the most remote areas of the ocean.

https://globalfishingwatch.org/faqs/what-is-ais/

NOAA AIS Data

Vessel traffic data, or Automatic Identification System (AIS) data, are collected by the U.S. Coast Guard through an onboard navigation safety device that transmits the location and characteristics of large vessels for tracking in real time. The MarineCadastre.gov project team has worked with the Coast Guard and NOAA’s Office of Coast Survey to repurpose and make available some of the most important data for use in ocean planning applications.

From https://coast.noaa.gov/digitalcoast/training/ais.html

Data Dictionary

(Ignore the year label, but the data fields are the same)

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2F0f0fa208b61293a2628687c983d28bd2%2F2018DataDictionary.png?generation=1718932879871904&alt=media" alt="">

Other Data Dictionaries

• MMSI Country code prefixes
• Navigational Status Codes
• Ship Types
• Vessel Types

Source

https://coast.noaa.gov/htdata/CMSP/AISDataHandler/2022/index.html

Notes

• Original data consists of daily data and was 100GB+. What I did was I separated the ship from the AIS data, plus broke it down per month of a year for a smaller footprint. I also converted it to parquet file format.
• Some erroneous lines are being encountered when importing. I removed them but this is so very, very, very, small nuber of records that it's insignificant

Citations

I did not create the dataset

I made the data more accessible and easier to utilize from an end user's perspective. All credits to NOAA and the AIS methodology.

For citation of NOAA, go here

More info here

Image

Image Generated with Bing

See the whole series

• 2014 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2015 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2016 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2017 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2018 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2019 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2020 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2021 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2022 🇺🇸 US Coast Guard + NOAA AIS Dataset
• 2023 🇺🇸 US Coast Guard + NOAA AIS Dataset

The Mean Layer Temperature - NOAA CDR V5.0 is a monthly global dataset with 2.5°×2.5° grid resolution covering the period from November 1978 to present. The dataset measures mean layer atmospheric temperatures from the lower-troposphere to the lower-stratosphere. The dataset was inter-calibrated and merged from three generations of microwave sounders, MSU, AMSU-A, and ATMS, with 16 polar-orbiting satellites including TIROS-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-10, NOAA-11, NOAA-12, NOAA-14, NOAA-15, NOAA-18, NOAA-19, MetOp-A, Aqua, SNPP, and NOAA-20. The dataset includes temperature mid-troposphere (TMT, MSU channel 2 merged with AMSU-A channel 5 and ATMS channel 6), temperature upper-troposphere (TUT, MSU channel 3 merged with AMSU-A channel 7 and ATMS channel 8), temperature lower-stratosphere (TLS, MSU channel 4 merged with AMSU-A channel 9 and ATMS channel 10), and temperature lower-troposphere (TLT, derived from combinations of TMT, TUT, and TLS). TLT, TMT, TUT, and TLS measure layer temperatures peaking roughly at 3km, 5km, 10km, and 17km, respectively, above the Earth's surface. Features in the dataset development include a use of backward merging approach, development of an observation- and semi-physically-based algorithm for diurnal drift adjustment, and removal of spurious calibration drifting errors in NOAA-15, NOAA-14, NOAA-12, and NOAA-11 through recalibration. Satellite microwave sounding observations in stable sun-synchronous orbits (Aqua, MetOp-A, SNPP, NOAA-20) were used as a reference in the backward merging process. Bias corrections and satellite recalibration have resulted in inter-consistent CDR records for reliable climate change investigation.

This dataset contains the bias-corrected CPC MORPHing technique (CMORPH) global precipitation analyses, version 1, and is obtained from the NOAA Climate Data Record [https://www.ncei.noaa.gov/products/climate-data-records/precipitation-cmorph]. The following description is from the NOAA Climate Data Record CMORPH dataset page: This data set is for the bias-corrected, reprocessed CPC Morphing technique (CMORPH) high-resolution global satellite precipitation estimates. The CMORPH satellite precipitation estimates are created in two steps. First, the purely satellite-based global fields of precipitation are constructed through integrating Level 2 retrievals of instantaneous precipitation rates from all available passive microwave measurements aboard low earth orbiting platforms. Bias in these integrated satellite precipitation estimates is then removed through comparison against CPC daily gauge analysis over land and adjustment against the Global Precipitation Climatology Project (GPCP) merged analysis of pentad precipitation over ocean. The bias corrected CMORPH satellite precipitation estimates are created on an 8 km by 8 km grid over the global domain from 60 degrees S to 60 degrees N and in a 30-minute interval from January 1, 1998. Due to the delay of some input data sets, this formal version (Version 1) bias corrected CMORPH is produced manually once a month at a latency of 3-4 months. For the CDR production, the bias corrected CMORPH generated at its native resolution of 8 km by 8 km / 30-minute is upscaled to form THREE sets of data files of different time/space resolution for improved user experience: a) the full-resolution CMORPH data; Output variable: precipitation rate in mm/hour; spatial resolution: 8 km by 8km (at equator); spatial coverage: global (60S-60N); temporal resolution: 30min; data period: January 1, 1998 to the present b) Hourly CMORPH; Output variable: precipitation rate in mm/hour; spatial resolution: 0.25 degrees latitude/longitude;...

The NOAA Radiosonde Observations Data Set contains data that were extracted from the NOAA operational analysis system and transmitted to the FIS. Data are available from July 1985 to October 1988, there are 1123 days of data during this period with data at twelve hour intervals. These data were collected using sondes released in Dodge City and Topeka, Kansas, 337 km and 68 km, respectively, from the FIFE site. Radiosonde observations were made to determine the pressure, temperature, and humidity from the surface to the point where the sounding was terminated.

The FIFE Staff Science effort included the acquisition, processing and archiving of meteorological parameters of the atmosphere above the FIFE study area, which would furnish surface meteorological parameters from hourly reporting network for the FIFE area, and provide input data and/or verification data for numerical simulation models. Though the measurements presented in this data set were not taken precisely at the FIFE site, it is hypothesized that they present a representative horizontal cross-section of meteorological variables and sky conditions in and around the site. It is also realized that many of the variables presented in this data set are somewhat subjective and dependent on the skill (and biases) of the observer, such as estimates of cloud amount and height. The NOAA regional surface reports were extracted from the NOAA operational analysis system and transmitted to the FIS. This contained hourly surface meteorological data from selected stations as received from NESDIS for FIFE.

The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a blended product from two independent analysis products: the Extended Reconstructed Sea Surface Temperature (ERSST) analysis and the land surface temperature (LST) analysis using the Global Historical Climatology Network (GHCN) temperature database. The data is merged into a monthly global surface temperature dataset dating back from 1850 to the present. The monthly product output is in gridded (5 degree x 5 degree) and time series formats. The product is used in climate monitoring assessments of near-surface temperatures on a global scale. Changes to the data in version 5.1 included: removing the EOT filtering; filling in data gaps over the polar regions; and extending the beginning data coverage from 1880 to 1850.

Analysis of ‘Local Weather Archive’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/121f9438-c65b-4ec1-a356-758d438e11eb on 05 November 2021.

--- Dataset description provided by original source is as follows ---

Pull weather data as collected at Raleigh-Durham International Airport by NOAA.

This dataset contains Raleigh Durham International Airport weather data pulled from the NOAA web service described at:

http://www.ncdc.noaa.gov/cdo-web/webservices/v2

We have pulled this data and converted the data to commonly used units.

--- Original source retains full ownership of the source dataset ---

The Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) consists of radar reflectivity data run through the Multi-Radar, Multi-Sensor (MRMS) framework to create a three-dimensional radar volume on a quasi-Cartesian latitude-longitude grid across the entire contiguous United States. The radar reflectivity grid is also combined with hourly forecast model analyses to produce derived products such as echo top heights and hail size estimates. Radar Doppler velocity data was also processed into two azimuthal shear layer products. The source radar data was from the NEXRAD Level-II archive and the model analyses came from NOAA's Rapid Update Cycle model. Radar reflectivity was quality controlled to remove non-weather echoes and the data set was manually quality contolled to remove errors as revealed through inspection of daily accumulations of the hail size product and the azimuthal shear products. MYRORSS contains data from April 1998 through December 2011. The horizontal resolution is 0.01° by 0.01° and the vertical spacing is stretched where at the lowest levels the spacing is 250-m and at the top of the domain 1000-m. The radar data was merged at imperfect timesteps, though in general the temporal spacing is around 5-min.

This dataset corresponds to Figure 5-1 in DRAFT TECHNICAL SUPPORT DOCUMENT TO THE PRELIMINARY ASSESSMENT FOR THE FWS - HAWAIIAN ISLANDS NATIONAL WILDLIFE REFUGE: TERN ISLAND, prepared for the US EPA by Weston Solutions on June 9, 2014

Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version. The Special Sensor Microwave Imagers (SSM/I) are a series of six satellite radiometers that have been in operation since 1987 under the Defense Meteorological Satellite Program (DMSP). The six SSM/Is (aboard F08, F10, F11, F13, F14, and F15) have a seven channel linearly polarized passive microwave radiometer that operate at frequencies of 19.36 (vertical and horizontal polarized), 22.235 (vertical polarized), 37.0 (vertical and horizontal polarized), and 85.5 GHz (vertical and horizontal polarized). The Remote Sensing Systems (RSS) Version-6 SSM/I Fundamental Climate Data Record (FCDR) dataset has incorporated all past geolocation corrections, sensor calibration (including cross-scan biases), and quality control procedures in a consistent way for the entire 24-year SSM/I brightness temperature period of record. Version-5 was relatively short lived due to subtle calibration problems that caused small spurious trends in the climate retrievals (the SSM/I record had become long enough at this point to detect such errors). The problem was due to subtle correlations in the derivation of the target factors for the F10 and F14 SSM/I. Like the Microwave Sounding Unit (MSU), some of the SSM/I exhibit errors that are correlated with the hot-load target temperatures, and we removed these errors using the target multiplier approach. Application of the solutions described herein provided the current V6 SSM/I TA and TB dataset. RSS Version-6 SSM/I FCDR data are stored as netCDF-4 files that have been internally compressed at the maximum GZIP utility level. A typical file will have a size of 6.4 megabytes.