observational_datasets.xml

<?xml version="1.0"?>
<observations
  headers="name, source, references"
  headernames="Observational Dataset, Source, References">

  <!-- OCEAN -->

  <observation>
    <name>
      SST merged Hadley Center-NOAA/OI data set
    </name>
    <component>
      ocean
    </component>
    <description>
      The merged Hadley-OI sea surface temperature (SST) and sea ice
      concentration (SIC) data sets were specifically developed as surface
      forcing data sets for AMIP style uncoupled simulations of the Community
      Atmosphere Model (CAM). The Hadley Centre's SST/SIC version 1.1
      (HADISST1), which is derived gridded, bias-adjusted in situ observations,
      were merged with the NOAA-Optimal Interpolation (version 2; OI.v2)
      analyses. The HADISST1 spanned 1870 onward but the OI.v2, which started
      in November 1981, better resolved features such as the Gulf Stream and
      Kuroshio Current which are important components of the climate system.
      Since the two data sets used different development methods, anomalies
      from a base period were used to create a more homogeneous record. Also,
      additional adjustments were made to the SIC data set.
    </description>
    <source>
      [NCAR Hadley-NOAA/OI SST website]
      (https://climatedataguide.ucar.edu/climate-data/merged-hadley-noaaoi-sea-surface-temperature-sea-ice-concentration-hurrell-et-al-2008)
    </source>
    <releasePolicy>
      Acknowledgment: Hurrell, J. W., J. J. Hack, D. Shea, J. M. Caron, and J. Rosinski,
      2008: A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community
      Atmosphere Model. Journal of Climate, 21, 5145-5153.
    </releasePolicy>
    <references>
      [Hurrell et al. (2008)](https://doi.org/10.1175/2008JCLI2292.1)
    </references>
    <bibtex>
      @article{Hurrell2008,
      author = {James W.  Hurrell  and  James J.  Hack  and  Dennis  Shea  and  Julie M.  Caron  and  James  Rosinski},
      title = {A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model},
      journal = {Journal of Climate},
      volume = {21},
      number = {19},
      pages = {5145-5153},
      year = {2008},
      doi = {10.1175/2008JCLI2292.1},
      URL = {https://doi.org/10.1175/2008JCLI2292.1}
      }
    </bibtex>
    <dataUrls>
      - ftp://ftp.cgd.ucar.edu/archive/SSTICE/MODEL.SST.HAD187001-198110.OI198111-201712.nc
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      - climatologyMapSST
    </tasks>
    <subdirectory>
      Ocean/SST
    </subdirectory>
    <nameInDocs>
      hadley_center_sst
    </nameInDocs>
  </observation>

  <observation>
    <name>
      SSS from NASA Aquarius satellite
    </name>
    <component>
      ocean
    </component>
    <description>
      Level 3 Aquarius sea surface salinity (SSS) data products have a temporal
      resolutions of daily, 8 day, monthly, 3 months, and annual.  Monthly and
      seasonal climatology products from Aquarius are also available. The Aquarius
      instrument provides global coverage every 7 days. L3 products are gridded
      at 1 degree spatial resolution.
    </description>
    <source>
      [NASA Aquarius Website]
      (https://podaac.jpl.nasa.gov/dataset/AQUARIUS_L4_OISSS_IPRC_7DAY_V4)
    </source>
    <releasePolicy>
      NASA data are not copyrighted; however, when you publish our data or
      results derived therefrom, we request that you include an acknowledgment
      within the text of the publication and reference list.
      [Data Citation and Acknowledgements]
      (https://podaac.jpl.nasa.gov/CitingPODAAC)
    </releasePolicy>
    <references>
      [Lagerloef et al. (2015)](ftp://podaac.jpl.nasa.gov/SalinityDensity/aquarius/docs/v4/AQ-014-PS-0016_AquariusSalinityDataValidationAnalysis_DatasetVersion4.0and3.0.pdf)
    </references>
    <bibtex>
    </bibtex>
    <dataUrls>
      ftp://podaac-ftp.jpl.nasa.gov/allData/aquarius/L4/IPRC/v4/7day/
    </dataUrls>
    <preprocessing>
      (missing)
    </preprocessing>
    <tasks>
      - climatologyMapSSS
    </tasks>
    <subdirectory>
      Ocean/SSS
    </subdirectory>
    <nameInDocs>
      aquarius_sss
    </nameInDocs>
  </observation>

  <observation>
    <name>
      WOA18 Temperature and Salinity Climatology
    </name>
    <component>
      ocean
    </component>
    <description>
      The World Ocean Atlas 2018 (WOA18) release July 2019 updates previous
      versions of the World Ocean Atlas to include approximately 3 million
      new oceanographic casts added to the World  Ocean  Database (WOD) since
      the previous release as well as renewed and updated quality control.
      Animal mounted pinniped temperature profiles have been added as a data
      source improving coverage in some high latitude areas. WOA18 includes
      analysis for temperature, salinity, dissolved oxygen, and dissolved
      inorganic nutrients (only temperature and salinity are used in MPAS-Analysis
      as of Aug 2019). The atlas includes annual, seasonal, and monthly
      climatologies and related statistical fields. Annual fields are available
      for the full depth (0-5500 m), while monthly and seasonal fields are
      available for the upper 1500 m only. Climatologies are available on a 1deg
      regular grid and on a 0.25deg grid.
    </description>
    <source>
      [NOAA National Oceanographic Data Center (NODC) website]
      (https://www.nodc.noaa.gov/OC5/woa18)
    </source>
    <releasePolicy>
      Acknowledgment: Locarnini and co-authors, 2019: World Ocean Atlas 2018,
      Volume 1: Temperature. A. Mishonov Technical Editor, NOAA Atlas NESDIS 81.
      Zweng and co-authors, 2019: World Ocean Atlas 2018, Volume 2: Salinity.
      A. Mishonov Technical Editor, NOAA Atlas NESDIS 82.
    </releasePolicy>
    <references>
      - [Locarnini et al. (2019)](https://data.nodc.noaa.gov/woa/WOA18/DOC/woa18_vol1.pdf)
      - [Zweng et al. (2019)](https://data.nodc.noaa.gov/woa/WOA18/DOC/woa18_vol2.pdf)
    </references>
    <bibtex>
      @manual{Locarninietal2019,
      author = {R. A. Locarnini and A. V. Mishonov and O. K. Baranova and T. P. Boyer and
      M. M. Zweng and H. E. Garcia and J. R. Reagan and D. Seidov and K. W. Weathers and
      C. R. Paver and I. V. Smolyar},
      title = {World Ocean Atlas 2018, Volume 1: Temperature},
      organization = {NOAA Atlas NESDIS 81},
      year = {2019},
      edition = {A. Mishonov Technical Editor}
      }
      @manual{Zwenetal2019,
      author = {M. M. Zweng and J. R. Reagan and D. Seidov and T. P. Boyer and R.A. Locarnini
      and H. E. Garcia and A. V. Mishonov and O. K. Baranova and K. W. Weathers and
      C. R. Paver and I. V. Smolyar},
      title = {World Ocean Atlas 2018, Volume 2: Salinity},
      organization = {NOAA Atlas NESDIS 82},
      year = {2019},
      edition = {A. Mishonov Technical Editor}
      }
    </bibtex>
    <dataUrls>
      - https://data.nodc.noaa.gov/woa/WOA18/DATA/
    </dataUrls>
    <preprocessing>
      - preprocess_observations/preprocess_WOA18Annual_data.bash
      - preprocess_observations/preprocess_WOA18Monthly_data.bash
    </preprocessing>
    <tasks>
      - climatologyMapWoa
    </tasks>
    <subdirectory>
      Ocean/WOA18
    </subdirectory>
    <nameInDocs>
      woa18_t_s
    </nameInDocs>
  </observation>

  <observation>
    <name>
      WOA23 Temperature and Salinity Climatology
    </name>
    <component>
      ocean
    </component>
    <description>
      The World Ocean Atlas 2023 (WOA23) was released on February 14, 2024 and
      includes temperature, salinity, oxygen (and parameters Apparent Oxygen
      Utilization and percent oxygen saturation) and inorganic nutrients
      (phosphate, silicate, and nitrate). WOA23 includes approximately 1.8
      million new oceanographic casts added to the WOD since WOA18’s release,
      as well as renewed and updated quality controls.
    </description>
    <source>
      [NOAA National Centers for Environmental Information (NCEI) website]
      (https://www.ncei.noaa.gov/products/world-ocean-atlas)
    </source>
    <releasePolicy>
      These data are openly available to the public. Please acknowledge the
      use of these data with the text given in the acknowledgment attribute.
    </releasePolicy>
    <references>
      - [Locarnini et al. (2024)](https://repository.library.noaa.gov/view/noaa/60599)
      - [Reagan et al. (2024)](https://repository.library.noaa.gov/view/noaa/60600)
    </references>
    <bibtex>
      @manual{locarnini_world_nodate,
      title = {World Ocean Atlas 2023, Volume 1: Temperature},
      url = {https://repository.library.noaa.gov/view/noaa/60599},
      shorttitle = {World Ocean Atlas 2023, Volume 1},
      year = {2024},
      author = {Locarnini, Ricardo A. and Mishonov, Alexey V. and Baranova,
      Olga K. and Reagan, James R. and Boyer, Timothy P. and Seidov, Dan and
      Wang, Zhankun and Garcia, Hernan E. and Bouchard, Courtney and Cross,
      Scott L. and Paver, Christopher R. and Dukhovskoy, Dmitry},
      }

      @manual{reagan_world_nodate,
      title = {World Ocean Atlas 2023, Volume 2: Salinity},
      url = {https://repository.library.noaa.gov/view/noaa/60600},
      shorttitle = {World Ocean Atlas 2023, Volume 2},
      author = {Reagan, James R. and Seidov, Dan and Wang, Zhankun and
      Dukhovskoy, Dmitry and Boyer, Timothy P. and Locarnini, Ricardo A. and
      Baranova, Olga K. and Mishonov, Alexey V. and Garcia, Hernan E. and
      Bouchard, Courtney and Cross, Scott L. and Paver, Christopher R.},
      year = {2024},
      }
    </bibtex>
    <dataUrls>
      - https://www.ncei.noaa.gov/access/world-ocean-atlas-2023/
    </dataUrls>
    <preprocessing>
      - preprocess_observations/preprocess_woa23.py
    </preprocessing>
    <tasks>
      - climatologyMapWoa
    </tasks>
    <subdirectory>
      Ocean/WOA23
    </subdirectory>
    <nameInDocs>
      woa23_t_s
    </nameInDocs>
  </observation>

  <observation>
    <name>
      AVISO Absolute Dynamic Topography
    </name>
    <component>
      ocean
    </component>
    <description>
      [NASA JPL AVISO website](https://podaac.jpl.nasa.gov/dataset/AVISO_L4_DYN_TOPO_1DEG_1MO)
      This dataset contains absolute dynamic topography (similar to sea level
      but with respect to the geoid) binned and averaged monthly on 1 degree
      grids. The coverage is from October 1992 to December 2010. These data
      were provided by AVISO (French space agency data provider) to support the
      CMIP5 (Coupled Model Intercomparison Project Phase 5) under the World
      Climate Research Program (WCRP) and was first made available via the JPL
      Earth System Grid. The dynamic topography are derived from sea surface
      height measured by several satellites including Envisat, TOPEX/Poseidon,
      Jason-1 and OSTM/Jason-2, and referenced to the geoid. Along with this
      dataset, two additional ancillary data files are included in the same
      directory which contain the number of observations and standard error
      co-located on the same 1 degree grids.
    </description>
    <source>
      [NASA JPL AVISO website](https://podaac.jpl.nasa.gov/dataset/AVISO_L4_DYN_TOPO_1DEG_1MO)
    </source>
    <releasePolicy>
      When using Ssalto/Duacs data (NRT or DT along-track Absolute Dynamic
      Topography (ADT), maps of SLA geostrophic currents (MSLA UV) or maps of
      ADT heights and currents (MADT H and UV), climatologies and averages of
      MSLA-H), please cite: "The altimeter products were produced by
      Ssalto/Duacs and distributed by Aviso, with support from Cnes
      (http://www.aviso.altimetry.fr/duacs/)"
    </releasePolicy>
    <references>
      [AVISO: Sea Surface Height above Geoid]
      (ftp://podaac.jpl.nasa.gov/allData/aviso/L4/dynamic_topo_1deg_1mo/docs/zosTechNote_AVISO_L4_199210-201012.pdf)
    </references>
    <bibtex>
    </bibtex>
    <dataUrls>
      - ftp://podaac-ftp.jpl.nasa.gov/allData/aviso/L4/dynamic_topo_1deg_1mo/zos_AVISO_L4_199210-201012.nc
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      - climatologyMapSSH
    </tasks>
    <subdirectory>
      Ocean/SSH
    </subdirectory>
    <nameInDocs>
      aviso_ssh
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Argo Mixed Layer Depth (MLD) climatology
    </name>
    <component>
      ocean
    </component>
    <description>
      A mixed layer climatology and database (described in Holte et al. 2017)
      using Argo profiles and a hybrid method (Holte and Talley 2009) for
      finding the mixed layer depth (MLD). The climatology incorporates over
      1,385,000 Argo profiles (through February 2017). The new hybrid algorithm
      models the general shape of each profile, searches for physical features
      in the profile, and calculates threshold and gradient MLDs to assemble a
      suite of possible MLD values. It then analyzes the patterns in the suite
      to select a final MLD estimate. Results are also presented for MLDs
      calculated using de Boyer Montegut et al.'s (2004) threshold values.
    </description>
    <source>
      [UCSD Mixed Layer Website](http://mixedlayer.ucsd.edu/)
    </source>
    <releasePolicy>
      [Acknowledgment:](http://mixedlayer.ucsd.edu/) If you use this data,
      please cite it as: Holte, J., L. D. Talley, J. Gilson, and D. Roemmich
      (2017), An Argo mixed layer climatology and database, Geophys. Res.
      Lett., 44, 5618-5626, doi:10.1002/2017GL073426.
    </releasePolicy>
    <references>
      - [Holte et al. (2017)](http://onlinelibrary.wiley.com/doi/10.1002/2017GL073426/full)
      - [Holte and Talley (2009)](http://journals.ametsoc.org/doi/abs/10.1175/2009JTECHO543.1)
      - [de Boyer Montegut et al. (2004)](https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2004JC002378)
    </references>
    <bibtex>
      @article{Holte2017,
      author = {James Holte and Lynne D. Talley and John Gilson and Dean Roemmich},
      title = {An Argo mixed layer climatology and database},
      journal = {Geophysical Research Letters},
      year = {2017},
      volume = {44},
      number = {11},
      pages = {5618-5626},
      keywords = {Argo, mixed layer, climatology, global},
      doi = {10.1002/2017GL073426},
      url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017GL073426}
      }
      @article{Holte2009,
      author = { James  Holte  and  Lynne  Talley },
      title = {A New Algorithm for Finding Mixed Layer Depths with Applications to Argo Data and Subantarctic Mode Water Formation},
      journal = {Journal of Atmospheric and Oceanic Technology},
      volume = {26},
      number = {9},
      pages = {1920-1939},
      year = {2009},
      doi = {10.1175/2009JTECHO543.1},
      URL = {https://doi.org/10.1175/2009JTECHO543.1}
      }
      @article{deBoyerMontegut2004,
      author = {Cl\'{e}ment {de Boyer Mont\'{e}gut} and Gurvan Madec and Albert S. Fischer and Alban Lazar and Daniele Iudicone},
      title = {Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology},
      journal = {Journal of Geophysical Research: Oceans},
      volume = {109},
      number = {C12},
      pages = {},
      year = {2004},
      keywords = {mixed layer, mixed layer depth criterion, density compensation},
      doi = {10.1029/2004JC002378},
      url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2004JC002378}
      }
    </bibtex>
    <dataUrls>
      - http://mixedlayer.ucsd.edu/data/Argo_mixedlayers_monthlyclim_03192017.nc
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      - climatologyMapMLD
    </tasks>
    <subdirectory>
      Ocean/MLD
    </subdirectory>
    <nameInDocs>
      argo_mld
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Meridional Heat Transport (MHT)
    </name>
    <component>
      ocean
    </component>
    <description>
      The Trenbert and Caron oceanic meridional heat transport is computed
      by computation of energy balance of the atmosphere, adjusted to fit
      physical constraints, and using two reanalysis products: the National
      Centers for Environmental Prediction-National Center for Atmospheric
      Research (NCEP-NCAR) reanalysis and the European Centre for Medium-Range
      Weather Forecasts (ECMWF) product. The analysis focuses on the period
      from February 1985 to April 1989 when there are reliable top-of-the-atmosphere
      radiation data from the Earth Radiation Budget Experiment.
    </description>
    <source>
      Data available upon request from Dr. Kevin Trenberth
    </source>
    <releasePolicy>
      Acknowledgment: please cite: Trenberth and Caron (2001). Estimates of
      Meridional Atmosphere and Ocean Heat Transports, J. of Climate, 14, 3433-3443.
    </releasePolicy>
    <references>
      [Trenberth and Caron (2001)](https://doi.org/10.1175/1520-0442%282001%29014&lt;3433%3AEOMAAO&gt;2.0.CO%3B2)
    </references>
    <bibtex>
      @article{Trenberth2001,
      author = { Kevin E.  Trenberth  and  Julie M.  Caron },
      title = {Estimates of Meridional Atmosphere and Ocean Heat Transports},
      journal = {Journal of Climate},
      volume = {14},
      pages = {3433-3443},
      year = {2001},
      doi = {10.1175/1520-0442%282001%29014&lt;3433%3AEOMAAO&gt;2.0.CO%3B2},
      URL = {https://doi.org/10.1175/1520-0442%282001%29014&lt;3433%3AEOMAAO&gt;2.0.CO%3B2}
      }
    </bibtex>
    <dataUrls>
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      - meridionalHeatTransport
    </tasks>
    <subdirectory>
      Ocean/MHT
    </subdirectory>
    <nameInDocs>
      trenberth_mht
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Roemmich-Gilson Argo Climatology
    </name>
    <component>
      ocean
    </component>
    <description>
      This new version of the Roemmich-Gilson Argo Climatology extends the
      analysis of Argo-only derived potential temperature and salinity fields
      through 2016. Several marginal seas and the Artic Oean have been added.
      The analysis method is similar to what was descibed in the Progress In
      Oceanography Roemmich and Gilson paper (2009). The only modification has
      been to scale the zonal equatorial correlation of the optimal estimation
      step, by 8 times, versus 4 times as in the 2009 paper. The additional
      Argo data utilized in the analysis results in a longer monthly record as
      well as better estimates of the mean and variability fields. Monthly
      updates are available in between major yearly re-analyses.
    </description>
    <source>
      [Scripps Roemmich-Gilson Argo Website](http://sio-argo.ucsd.edu/RG_Climatology.html)
    </source>
    <releasePolicy>
      [Acknowledgment:](http://sio-argo.ucsd.edu/RG_Climatology.html) Roemmich,
      D. and J. Gilson, 2009: The 2004-2008 mean and annual cycle of
      temperature, salinity, and steric height in the global ocean from the
      Argo Program. Progress in Oceanography, 82, 81-100.
    </releasePolicy>
    <references>
      [Roemmich and Gilson (2009)](http://www.sciencedirect.com/science/article/pii/S0079661109000160)
    </references>
    <bibtex>
      @article{Roemmich2009,
      title = "The 2004--2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo Program",
      journal = "Progress in Oceanography",
      volume = "82",
      number = "2",
      pages = "81 - 100",
      year = "2009",
      issn = "0079-6611",
      doi = "10.1016/j.pocean.2009.03.004",
      url = "http://www.sciencedirect.com/science/article/pii/S0079661109000160",
      author = "Dean Roemmich and John Gilson"
      }
    </bibtex>
    <dataUrls>
      - ftp://kakapo.ucsd.edu/pub/gilson/argo_climatology/RG_ArgoClim_Temperature_2017.nc.gz
      - ftp://kakapo.ucsd.edu/pub/gilson/argo_climatology/RG_ArgoClim_Salinity_2017.nc.gz
    </dataUrls>
    <preprocessing>
      preprocess_observations/Process_RG_Argo_climatology.ipynb
    </preprocessing>
    <tasks>
      - climatologyMapArgoTemperature
      - climatologyMapArgoSalinity
    </tasks>
    <subdirectory>
      Ocean/ARGO
    </subdirectory>
    <nameInDocs>
      roemmich_gilson_argo
    </nameInDocs>
  </observation>

  <observation>
    <name>
      2005-2010 climatology from SOSE the Southern Ocean State Estimate (SOSE)
    </name>
    <component>
      ocean
    </component>
    <description>
      Monthly potential temperature, salinity velocity components and neutral
      density output from the Southern Ocean State Estimate (SOSE) covering
      years 2005-2010
    </description>
    <source>
      [SOSE Website at UCSD]
      (http://sose.ucsd.edu/sose_stateestimation_data_05to10.html)
    </source>
    <releasePolicy>
      [Conditions of use]
      (http://sose.ucsd.edu/sose_stateestimation_disclaimer.html): The data on
      these webpages are made freely available for scientific, bona fide,
      not-for-profit research only. If your use of the data is different (e.g.
      commercial), you must contact the data providers and receive written
      permission for your use of the data prior to any such use. The user must
      acknowledge SOSE data in all products or publications that use them, e.g.
      by including the following written note: "Computational resources for the
      SOSE were provided by NSF XSEDE resource grant OCE130007." An appropriate
      citation should also be made.
    </releasePolicy>
    <references>
      [Mazloff et al. (2010)](http://doi.org/10.1175/2009JPO4236.1)
    </references>
    <bibtex>
      @article{Mazloff2010,
      author = {Matthew R.  Mazloff  and  Patrick  Heimbach  and  Carl  Wunsch},
      title = {An Eddy-Permitting Southern Ocean State Estimate},
      journal = {Journal of Physical Oceanography},
      volume = {40},
      number = {5},
      pages = {880-899},
      year = {2010},
      doi = {10.1175/2009JPO4236.1},
      URL = {https://doi.org/10.1175/2009JPO4236.1}
      }
    </bibtex>
    <dataUrls>
      - http://sose.ucsd.edu/DATA/SO6_V2/grid.mat
      - http://sose.ucsd.edu/DATA/SO6_V2/THETA_mnthlyBar.0000000100.data.gz
      - http://sose.ucsd.edu/DATA/SO6_V2/THETA_mnthlyBar.0000000100.meta
      - http://sose.ucsd.edu/DATA/SO6_V2/SALT_mnthlyBar.0000000100.data.gz
      - http://sose.ucsd.edu/DATA/SO6_V2/SALT_mnthlyBar.0000000100.meta
      - http://sose.ucsd.edu/DATA/SO6_V2/MLD_mnthlyBar.0000000100.data.gz
      - http://sose.ucsd.edu/DATA/SO6_V2/MLD_mnthlyBar.0000000100.meta
      - http://sose.ucsd.edu/DATA/SO6_V2/UVEL_mnthlyBar.0000000100.data.gz
      - http://sose.ucsd.edu/DATA/SO6_V2/UVEL_mnthlyBar.0000000100.meta
      - http://sose.ucsd.edu/DATA/SO6_V2/VVEL_mnthlyBar.0000000100.data.gz
      - http://sose.ucsd.edu/DATA/SO6_V2/VVEL_mnthlyBar.0000000100.meta
      - http://sose.ucsd.edu/DATA/SO6_V2/GAMMA_mnthlyBar.0000000100.data.gz
      - http://sose.ucsd.edu/DATA/SO6_V2/GAMMA_mnthlyBar.0000000100.meta
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_SOSE_data.py
    </preprocessing>
    <tasks>
      - climatologyMapSose
      - soseTransects
    </tasks>
    <subdirectory>
      Ocean/SOSE
    </subdirectory>
    <nameInDocs>
      sose
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Antarctic melt rates and fluxes
    </name>
    <component>
      ocean
    </component>
    <description>
      Melt rates and melt fluxes from Rignot et al. (2013)
    </description>
    <source>
      [Ice-Shelf Melting Around Antarctica](http://science.sciencemag.org/content/341/6143/266)
    </source>
    <releasePolicy>
      Data available upon request from co-author J. Mouginot.
    </releasePolicy>
    <references>
      [Rignot et al. (2013)](http://science.sciencemag.org/content/341/6143/266)
    </references>
    <bibtex>
      @article{Rignot2013,
	  title = {Ice-{Shelf} {Melting} {Around} {Antarctica}},
	  volume = {341},
	  url = {http://www.ncbi.nlm.nih.gov/pubmed/23765278},
	  doi = {10.1126/science.1235798},
	  number = {6143},
	  journal = {Science},
	  author = {Rignot, E. and Jacobs, S. and Mouginot, J. and Scheuchl, B.},
	  month = jul,
	  year = {2013},
	  pages = {266--270}
	  }
    </bibtex>
    <dataUrls>
      - http://science.sciencemag.org/highwire/filestream/594977/field_highwire_adjunct_files/0/1235798tableS1.xlsx
      - (data available upon request from J. Mouginot)
    </dataUrls>
    <preprocessing>
      preprocess_observations/remap_rignot.py
    </preprocessing>
    <tasks>
      - climatologyMapAntarcticMelt
      - timeSeriesAntarcticMelt
    </tasks>
    <subdirectory>
      Ocean/Melt
    </subdirectory>
    <nameInDocs>
      rignot_melt
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Antarctic melt rates and fluxes
    </name>
    <component>
      ocean
    </component>
    <description>
      Melt rates and melt fluxes from Adusumilli et al. (2020)
    </description>
    <source>
      [Data from: Interannual variations in meltwater input to the Southern Ocean from Antarctic ice shelves](https://doi.org/10.6075/J04Q7SHT)
    </source>
    <releasePolicy>
      Under copyright (US)

      Use: This work is available from the UC San Diego Library. This digital
      copy of the work is intended to support research, teaching, and private
      study.

      Constraint(s) on Use: This work is protected by the U.S. Copyright Law
      (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use"
      or any license applied to this work requires written permission of the
      copyright holder(s). Responsibility for obtaining permissions and any
      use and distribution of this work rests exclusively with the user and
      not the UC San Diego Library. Inquiries can be made to the UC San Diego
      Library program having custody of the work.
    </releasePolicy>
    <references>
      [Adusumilli et al. (2020)](https://doi.org/10.1038/s41561-020-0616-z)
    </references>
    <bibtex>
      @article{Adusumilli2020,
          title = {Interannual variations in meltwater input to the {Southern} {Ocean} from {Antarctic} ice shelves},
          copyright = {2020 The Author(s), under exclusive licence to Springer Nature Limited},
          issn = {1752-0908},
          url = {https://www.nature.com/articles/s41561-020-0616-z},
          doi = {10.1038/s41561-020-0616-z},
          journal = {Nature Geoscience},
          author = {Adusumilli, Susheel and Fricker, Helen Amanda and Medley,Brooke and Padman, Laurie and Siegfried, Matthew R.},
          month = aug,
          year = {2020},
          note = {Publisher: Nature Publishing Group},
          pages = {1--5}
      }
    </bibtex>
    <dataUrls>
      - http://library.ucsd.edu/dc/object/bb0448974g/_3_1.h5
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_adusumilli_melt.py
    </preprocessing>
    <tasks>
      - climatologyMapAntarcticMelt
      - timeSeriesAntarcticMelt
    </tasks>
    <subdirectory>
      Ocean/Melt/Adusumilli
    </subdirectory>
    <nameInDocs>
      adusumilli_melt
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Antarctic melt rates and fluxes
    </name>
    <component>
      ocean
    </component>
    <description>
      Melt rates and melt fluxes from Paolo et al. (2023)
    </description>
    <source>
      [Data from: ANT_G1920V01_IceShelfMelt.nc](https://doi.org/10.5067/SE3XH9RXQWAM)
    </source>
    <releasePolicy>
      Not stated.
    </releasePolicy>
    <references>
      [Paolo et al. (2023)](https://doi.org/10.5194/tc-17-3409-2023)
    </references>
    <bibtex>
      @article{Paolo2023,
          author = {Paolo, F. S. and Gardner, A. S. and Greene, C. A. and Nilsson, J. and Schodlok, M. P. and Schlegel, N.-J. and Fricker, H. A.},
          title = {Widespread slowdown in thinning rates of West Antarctic ice shelves},
          journal = {The Cryosphere},
          volume = {17},
          year = {2023},
          number = {8},
          pages = {3409--3433},
          url = {https://tc.copernicus.org/articles/17/3409/2023/},
          doi = {10.5194/tc-17-3409-2023}
      }
    </bibtex>
    <dataUrls>
      - https://its-live-data.s3.amazonaws.com/height_change/Antarctica/Floating/ANT_G1920V01_IceShelfMelt.nc
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_paolo_melt.py
    </preprocessing>
    <tasks>
      - climatologyMapAntarcticMelt
      - timeSeriesAntarcticMelt
    </tasks>
    <subdirectory>
      Ocean/Melt/Paolo
    </subdirectory>
    <nameInDocs>
      paolo_melt
    </nameInDocs>
  </observation>

  <observation>
    <name>
      HadISST Nino 3.4 Index
    </name>
    <component>
      ocean
    </component>
    <description>
      Nino 3.4 Index is computed from the Hadley-OI sea surface temperature
      (SST) and sea ice concentration (SIC) data set. This product was
      specifically developed as surface forcing data set for AMIP style
      uncoupled simulations of the Community Atmosphere Model (CAM). The
      Hadley Centre's SST/SIC version 1.1 (HADISST1), which is derived gridded,
      bias-adjusted in situ observations, were merged with the NOAA-Optimal
      Interpolation (version 2; OI.v2) analyses. The HADISST1 spanned 1870
      onward but the OI.v2, which started in November 1981, better resolved
      features such as the Gulf Stream and Kuroshio Current which are important
      components of the climate system. Since the two data sets used different
      development methods, anomalies from a base period were used to create
      a more homogeneous record. Also, additional adjustments were made to
      the SIC data set.
    </description>
    <source>
      [NCAR Hadley-NOAA/OI SST website]
      (https://climatedataguide.ucar.edu/climate-data/merged-hadley-noaaoi-sea-surface-temperature-sea-ice-concentration-hurrell-et-al-2008)
    </source>
    <releasePolicy>
      Acknowledgment: Hurrell, J. W., J. J. Hack, D. Shea, J. M. Caron, and J. Rosinski,
      2008: A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community
      Atmosphere Model. Journal of Climate, 21, 5145-5153.
    </releasePolicy>
    <references>
      [Hurrell et al. (2008)](https://doi.org/10.1175/2008JCLI2292.1)
    </references>
    <bibtex>
      @article{Hurrell2008,
      author = {James W.  Hurrell  and  James J.  Hack  and  Dennis  Shea  and  Julie M.  Caron  and  James  Rosinski},
      title = {A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model},
      journal = {Journal of Climate},
      volume = {21},
      number = {19},
      pages = {5145-5153},
      year = {2008},
      doi = {10.1175/2008JCLI2292.1},
      URL = {https://doi.org/10.1175/2008JCLI2292.1}
      }
    </bibtex>
    <dataUrls>
      - ftp://ftp.cgd.ucar.edu/archive/SSTICE/MODEL.SST.HAD187001-198110.OI198111-201712.nc
    </dataUrls>
    <preprocessing>
      (missing)
    </preprocessing>
    <tasks>
      - indexNino34
    </tasks>
    <subdirectory>
      Ocean/Nino/HadISST
    </subdirectory>
    <nameInDocs>
      hadisst_nino
    </nameInDocs>
  </observation>

  <observation>
    <name>
      ERS SSTv4 Nino 3.4 Index
    </name>
    <component>
      ocean
    </component>
    <description>
      The Nino 3.4 Index is also computed using the Extended Reconstructed
      Sea Surface Temperature (ERSST) dataset, which is a global monthly
      sea surface temperature dataset derived from the International Comprehensive
      Ocean-Atmosphere Dataset (ICOADS). It is produced on a 2 degree by 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.
      The newest version of ERSST, version 4, is based on optimally tuned parameters
      using the latest datasets and improved analysis methods. ERSST is suitable
      for long-term global and basin-wide studies, and smoothed local and
      short-term variations are used in the dataset.
    </description>
    <source>
      [NOAA ERSST v4 website]
      (https://www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst-v4)
    </source>
    <releasePolicy>
      Cite this dataset when used as a source: Boyin Huang, Viva F. Banzon, Eric Freeman,
      Jay Lawrimore, Wei Liu, Thomas C. Peterson, Thomas M. Smith, Peter W. Thorne,
      Scott D. Woodruff, and Huai-Min Zhang, 2015: Extended Reconstructed Sea Surface
      Temperature (ERSST), Version 4. NOAA National Centers for Environmental Information.
      doi:10.7289/V5KD1VVF [access date: January 2017].
    </releasePolicy>
    <references>
      - [Huang et al. (2014)](https://journals.ametsoc.org/doi/10.1175/JCLI-D-14-00006.1)
      - [Liu et al. (2014)](https://journals.ametsoc.org/doi/10.1175/JCLI-D-14-00007.1)
      - [Huang et al. (2015)](https://journals.ametsoc.org/doi/10.1175/JCLI-D-15-0430.1)
    </references>
    <bibtex>
      @article{Huang2014,
      author = {Boyin Huang  and  Viva F. Banzon and Eric Freeman and Jay Lawrimore and Wei Liu
                and Thomas C. Peterson and Thomas M. Smith and Peter W. Thorne and Scott D. Woodruff
                and Huai-Min Zhang},
      title = {Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4).
               Part I: Upgrades and Intercomparisons},
      journal = {Journal of Climate},
      volume = {28},
      pages = {911-930},
      year = {2014},
      doi = {10.1175/JCLI-D-14-00006.1},
      URL = {https://doi.org/10.1175/JCLI-D-14-00006.1}
      }
      @article{Liu2014,
      author = {Wei Liu and Boyin Huang and Peter W. Thorne and Viva F. Banzon and
                Huai-Min Zhang and Eric Freeman and Jay Lawrimore and Thomas C. Peterson and
                Thomas M. Smith and Scott D. Woodruff},
      title = {Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4).
               Part II. Parametric and Structural Uncertainty Estimations},
      journal = {Journal of Climate},
      volume = {28},
      pages = {931-951},
      year = {2014},
      doi = {10.1175/JCLI-D-14-00007.1},
      URL = {https://doi.org/10.1175/JCLI-D-14-00007.1}
      }
      @article{Huang2015,
      author = {Boyin Huang and Peter W. Thorne and Thomas M. Smith and Wei Liu and
                Jay Lawrimore and Viva F. Banzon and Huai-Min Zhang and Thomas C. Peterson and Matthew Menne},
      title = {Further Exploring and Quantifying Uncertainties for Extended Reconstructed
               Sea Surface Temperature (ERSST) Version 4 (v4)},
      journal = {Journal of Climate},
      volume = {29},
      pages = {3119-3142},
      year = {2015},
      doi = {10.1175/JCLI-D-15-0430.1},
      URL = {https://doi.org/10.1175/JCLI-D-15-0430.1}
      }
    </bibtex>
    <dataUrls>
      - https://www1.ncdc.noaa.gov/pub/data/cmb/ersst/v4/netcdf
    </dataUrls>
    <preprocessing>
      (missing)
    </preprocessing>
    <tasks>
      - indexNino34
    </tasks>
    <subdirectory>
      Ocean/Nino/ERS_SSTv4
    </subdirectory>
    <nameInDocs>
      ers_sst_nino
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Antarctic Seafloor Temperature and Salinity
    </name>
    <component>
      ocean
    </component>
    <description>
      Temporal means in conservative temperature and absolute salinity
      of Antarctic Continental Shelf Bottom Water (ASBW) for depths shallower
      than 1500 m for the period 1975 to 2012.
    </description>
    <source>
      [ASCII data file](https://www.geomar.de/fileadmin/personal/fb1/po/sschmidtko/Antarctic_shelf_data.txt)
    </source>
    <releasePolicy>
     (missings)
    </releasePolicy>
    <references>
      [Schmidtko et al. (2014)](http://www.sciencemag.org/cgi/doi/10.1126/science.1256117)
    </references>
    <bibtex>
      @article {Schmidtko2014,
        author = {Schmidtko, Sunke and Heywood, Karen J. and Thompson, Andrew F. and Aoki, Shigeru},
        title = {Multidecadal warming of Antarctic waters},
        volume = {346},
        number = {6214},
        pages = {1227--1231},
        year = {2014},
        doi = {10.1126/science.1256117},
        publisher = {American Association for the Advancement of Science},
        issn = {0036-8075},
        url = {http://science.sciencemag.org/content/346/6214/1227},
        journal = {Science}
      }
    </bibtex>
    <dataUrls>
      - https://www.geomar.de/fileadmin/personal/fb1/po/sschmidtko/Antarctic_shelf_data.txt
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_Schmidtko_data.py
    </preprocessing>
    <tasks>
      - climatologyMapSchmidtko
    </tasks>
    <subdirectory>
      Ocean/Schmidtko
    </subdirectory>
    <nameInDocs>
      schmidtko
    </nameInDocs>
  </observation>

  <observation>
    <name>
      WOCE sections
    </name>
    <component>
      ocean
    </component>
    <description>
      WOCE
      ----
      The Hydrographic Programme of the international World Ocean Circulation
      Experiment (WOCE) was a comprehensive global hydrographic survey of
      physical and chemical properties, of unprecedented scope and quality, and
      represents the "state of the oceans" during the 1990s.

      The "Printed Atlas" is a copy of the published volume and contains full
      introductory text. The "Digital Atlas" presents the same graphical
      material, with additional properties and levels, ancillary data sets, and
      bibliographic material for each of the vertical sections.

      CCHDO
      -----
      The CCHDO's primary mission is to deliver the highest possible quality
      global CTD and hydrographic data to users. These data are a product of
      decades of observations related to the physical characteristics of ocean
      waters carried out during WOCE, CLIVAR and numerous other oceanographic
      research programs. Whenever possible we provide these data in three
      easy-to-use formats: WHP-Exchange (which we recommend for data
      submissions to the CCHDO), WOCE, and netCDF.
      global Argo and OceanSITES programs.
    </description>
    <source>
      - [WOCE Atlas Website](http://woceatlas.ucsd.edu/)
      - [CCHDO](https://cchdo.ucsd.edu/)
    </source>
    <releasePolicy>
      "Public" data may be placed on-line. They may be exchanged between
      investigators as desired. They may or may not be preliminary, and
      especially for preliminary public data users are strongly advised to
      contact the originating investigators regarding the status of updates or
      further data processing. [See Full Policy](https://cchdo.ucsd.edu/policy)
    </releasePolicy>
    <references>
      [Orsi and Whitworth (2005)](https://doi.org/10.21976/C6BC78)
    </references>
    <bibtex>
      @techreport{Orsi2015,
        author = {A. H. Orsi and T. Whitworth},
        title = {Hydrographic Atlas of the World Ocean Circulation Experiment (WOCE) Volume 1: Southern Ocean},
        year = 2005,
        url = {https://doi.org/10.21976/C6BC78},
        note = {Accessed May 2018}
      }
    </bibtex>
    <dataUrls>
    </dataUrls>
    <preprocessing>
      (missing)
    </preprocessing>
    <tasks>
      - woceTransects
    </tasks>
    <subdirectory>
      Ocean/WOCE
    </subdirectory>
    <nameInDocs>
      woce
    </nameInDocs>
  </observation>


   <observation>
    <name>
      AntShip sections
    </name>
    <component>
      ocean
    </component>
    <description>
      Southern Ocean (90°S-45°S) conservative temperature and absolute salinity
      profiles compilation (OCEAN ICE D1.1)

      This profile compilation contains conservative temperature and absolute
      salinity profiles computed from ship CTD, Argo floats and seal-borne
      profilers in the Southern Ocean (90°S-45°S) since 1972, using the GSW
      toolbox. It provides with an opportunity to investigate the broad scale
      climatology of the Southern Ocean hydrography on and off the continental
      shelf and facilitate localized timeseries analysis of the variability
      across various timescales.

    </description>
    <source>
      - [OCEAN ICE D1.1](https://www.seanoe.org/data/00886/99787/)
    </source>
    <releasePolicy>
      "Public" data may be placed on-line.
    </releasePolicy>
    <references>
      [Zhou et al. (2024)](https://doi.org/10.17882/99787)
    </references>
    <bibtex>
      @techreport{Zhou2024,
        author = {S. Zhou and P. Dutrieux and C. Giulivi},
        title = { Southern Ocean (90°S-45°S) conservative temperature and absolute salinity profiles compilation (OCEAN ICE D1.1)},
        year = 2024,
        url = {https://doi.org/10.17882/99787},
        note = {Accessed Nov 2024}
      }
    </bibtex>
    <dataUrls>
    </dataUrls>
    <preprocessing>
      (missing)
    </preprocessing>
    <tasks>
      - antshipTransects
    </tasks>
    <subdirectory>
      Ocean/AntShip
    </subdirectory>
    <nameInDocs>
      antship
    </nameInDocs>
  </observation>


  <observation>
    <name>
      World Ocean Atlas v2
    </name>
    <component>
      ocean
    </component>
    <description>
      The World Ocean Atlas (WOA) is a data product of the Ocean Climate
      Laboratory of the National Oceanographic Data Center. It consists of
      objectively analyzed climatological mean fields at 1 degree spatial
      resolution. The climatology is based on all data that are available from
      the early 1900s to present.
    </description>
    <source>
      - [World Ocean Atlas v2 Website](https://www.nodc.noaa.gov/OC5/woa13/)
    </source>
    <releasePolicy>
      Cite the World Ocean Atlas 2013 for the data sets used (see references).
      The World Ocean Atlas 2013 (and all previous versions) are available free
      of charge.
    </releasePolicy>
    <references>
      - [Oxygen: Garcia et al. 2014a](https://data.nodc.noaa.gov/woa/WOA13/DOC/woa13_vol3.pdf)
      - [Nutrients: Garcia et al. 2014b](https://data.nodc.noaa.gov/woa/WOA13/DOC/woa13_vol4.pdf)
    </references>
    <bibtex>
      @article{garcia64volume,
      title={Volume 3: dissolved oxygen, apparent oxygen utilization, and oxygen saturation, edited by: Levitus},
      author={Garcia, HE and Locarnini, RA and Boyer, TP and Antonov, JI},
      journal={S., NOAA Atlas NESDIS},
      volume={64}
      }
      @article{garciaNutrients,
      title={Volume 4: dissolved inorganic nutrients (phosphate, nitrate, silicate), edited by: Levitus},
      author={Garcia, HE and Locarnini, RA and Boyer, TP, and Atonov, JI},
      journal={S., NOAA Atlas NESDIS},
      volume={64}
      }
    </bibtex>
    <dataUrls>
      - https://data.nodc.noaa.gov/woa/WOA13/DATA/nitrate/netcdf/all/1.00/
      - https://data.nodc.noaa.gov/woa/WOA13/DATA/phosphate/netcdf/all/1.00/
      - https://data.nodc.noaa.gov/woa/WOA13/DATA/silicate/netcdf/all/1.00/
      - https://data.nodc.noaa.gov/woa/WOA13/DATA/oxygen/netcdf/all/1.00/
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_BGC_data.py
    </preprocessing>
    <tasks>
      - climatologyMapBGC
    </tasks>
    <subdirectory>
      Ocean/BGC
    </subdirectory>
    <nameInDocs>
      woa
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Landschuetzerv2016 SOM-FFN
    </name>
    <component>
      ocean
    </component>
    <description>
      The observation-based pCO2 fields were created using a 2-step neural
      network method extensively described and validated in Landschuetzer et
      al. 2013, 2014, 2016. The method first clusters the global ocean into
      biogeochemical provinces and in a second step reconstructs the non-liner
      relationship between CO2 driver variables and observations from the 4th
      release of the Surface Ocean CO2 Atlas (SOCATv4, Bakker et al. 2016).
      This file contains the resulting monthly pCO2 fields at 1 x 1 deg resolution
      covering the global ocean with the exception of the Arctic Ocean and few
      marginal seas. The air-sea CO2 fluxes are computed from the air-sea CO2
      partial pressure difference and a bulk gas transfer formulation
      following Landschuetzer et al. 2013, 2014, 2016. Furthermore, the monthly
      climatology is created from the monthly average of the period 1985-2015.
    </description>
    <source>
      [SOM-FFN Website](https://www.nodc.noaa.gov/ocads/oceans/SPCO2_1982_2015_ETH_SOM_FFN.html)
    </source>
    <releasePolicy>
      This product is free to be used. Please cite the data set as:
      Landschuetzer, P., N. Gruber and D.C.E. Bakker (2017). An updated observation-based global monthly gridded sea surface pCO2 and air-sea CO2 flux product from 1982 through 2015 and its monthly climatology (NCEI Accession 0160558). Version 2.2. NOAA National Centers for Environmental Information. Dataset. [2017-07-11]
    </releasePolicy>
    <references>
      - [Landschuetzer et al. 2013](http://doi.org/10.5194/bg-10-7793-2013)
      - [Landschuetzer et al. 2014](http://doi.org/10.1002/2014GB004853)
      - [Landschuetzer et al. 2016](http://doi.org/10.1002/2015GB005359)
      - [Bakker et al. 2016](http://doi.org/10.5194/essd-8-383-2016)
    </references>
    <bibtex>
      @article{landschutzer2013neural,
      title={A neural network-based estimate of the seasonal to inter-annual variability of the Atlantic Ocean carbon sink},
      author={Landsch{\"u}tzer, P and Gruber, N and Bakker, DCE and Schuster, U and Nakaoka, S and Payne, MR and Sasse, TP and Zeng, J},
      journal={Biogeosciences},
      volume={10},
      number={11},
      pages={7793},
      year={2013},
      publisher={Copernicus GmbH}
      }
      @article{landschutzer2014recent,
      title={Recent variability of the global ocean carbon sink},
      author={Landsch{\"u}tzer, P and Gruber, N and Bakker, DCE and Schuster, U},
      journal={Global Biogeochemical Cycles},
      volume={28},
      number={9},
      pages={927--949},
      year={2014},
      publisher={Wiley Online Library}
      }
      @article{landschuetzer2016decadal,
      title={Decadal variations and trends of the global ocean carbon sink},
      author={Landschuetzer, Peter and Gruber, Nicolas and Bakker, Dorothee CE},
      journal={Global Biogeochemical Cycles},
      volume={30},
      number={10},
      pages={1396--1417},
      year={2016},
      publisher={Wiley Online Library}
      }
      @article{bakker2016multi,
      title={A multi-decade record of high-quality fCO 2 data in version 3 of the Surface Ocean CO 2 Atlas (SOCAT)},
      author={Bakker, Dorothee CE and Pfeil, Benjamin and Landa, Camilla S and Metzl, Nicolas and O'brien, Kevin M and Olsen, Are and Smith, Karl and Cosca, Cathy and Harasawa, Sumiko and Jones, Stephen D and others},
      journal={Earth System Science Data},
      volume={8},
      number={2},
      pages={383},
      year={2016},
      publisher={Copernicus GmbH}
      }
    </bibtex>
    <dataUrls>
      - https://www.nodc.noaa.gov/archive/arc0105/0160558/3.3/data/0-data/
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_BGC_data.py
    </preprocessing>
    <tasks>
      - climatologyMapBGC
    </tasks>
    <subdirectory>
      Ocean/BGC
    </subdirectory>
    <nameInDocs>
      landschuetzer-som-ffn
    </nameInDocs>
  </observation>

  <observation>G
    <name>
      SeaWiFS
    </name>
    <component>
      ocean
    </component>
    <description>
      SeaWiFS (Sea-Viewing Wide Field-of-View Senson) was a project dedicated
      to monitoring ocean water quality and ecological characteristics covering
      multiple optical bands with a resolution of roughly 1.1km. Chlorophyll
      concentrations are derived from images of ocean color.
    </description>
    <source>
      [Ocean Color Website](https://oceancolor.gsfc.nasa.gov/)
    </source>
    <releasePolicy>
      Please provide acknowledgement of the use of Ocean Biology Processing
      Group (OBPG) data products, images, and services, e.g.:

      NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean
      Biology Processing Group; (2014): Sea-viewing Wide Field-of-view Sensor
      (SeaWiFS) Ocean Color Data, NASA OB.DAAC. http://doi.org/10.5067/ORBVIEW
      -2/SEAWIFS_OC.2014.0. Accessed on 2016/02/29.
    </releasePolicy>
    <references>
      - [O'Reilly et al. 1998](https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/98JC02160)
    </references>
    <bibtex>
      @article{o1998ocean,
      title={Ocean color chlorophyll algorithms for SeaWiFS},
      author={O'Reilly, John E and Maritorena, Stephane and Mitchell, B Greg and Siegel, David A and Carder, Kendall L and Garver, Sara A and Kahru, Mati and McClain, Charles},
      journal={Journal of Geophysical Research: Oceans},
      volume={103},
      number={C11},
      pages={24937--24953},
      year={1998},
      publisher={Wiley Online Library}
      }
    </bibtex>
    <dataUrls>
      - https://oceandata.sci.gsfc.nasa.gov/SeaWiFS/Mapped/Monthly_Climatology/9km/chlor_a/
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_BGC_data.py
    </preprocessing>
    <tasks>
      - climatologyMapBGC
    </tasks>
    <subdirectory>
      Ocean/BGC
    </subdirectory>
    <nameInDocs>
      seawifs
    </nameInDocs>
  </observation>

  <observation>
    <name>
      GLODAPv2
    </name>
    <component>
      ocean
    </component>
    <description>
      GLODAPv2 (Global Ocean Data Analysis Project version 2) is an international
      data synthesis project for interior ocean inorganic carbon data and
      related variables for the global ocean. It includes data from all ocean
      areas of the globe and synthesizes 724 unique cruises.
    </description>
    <source>
      [GLODAPv2 Website](https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2/)
    </source>
    <releasePolicy>
      The GLODAPv2 database is freely available.
    </releasePolicy>
    <references>
      - [Olsen et al. 2016](http://cdiac.ess-dive.lbl.gov/ftp/oceans/GLODAPv2/Data_Products/essd-8-297-2016.pdf)
      - [Lauvset et al. 2016](http://cdiac.ess-dive.lbl.gov/ftp/oceans/GLODAPv2/Data_Products/essd-8-325-2016.pdf)
      - [Olsen et al. 2017](https://www.nodc.noaa.gov/ocads/data/0162565.xml)
    </references>
    <bibtex>
      @article{olsen2016global,
      title={The Global Ocean Data Analysis Project version 2 (GLODAPv2)--an internally consistent data product for the world ocean},
      author={Olsen, Are and Key, Robert M and van Heuven, Steven and Lauvset, Siv K and Velo, Anton and Lin, Xiaohua and Schirnick, Carsten and Kozyr, Alex and Tanhua, Toste and Hoppema, Mario and others},
      journal={Earth System Science Data},
      volume={8},
      number={2},
      pages={297},
      year={2016},
      publisher={Copernicus GmbH}
      }
      @article{lauvset2016new,
      title={A new global interior ocean mapped climatology: the 1$^\circ$ $\times$ 1$^\circ$ GLODAP version 2},
      author={Lauvset, Siv K and Key, Robert M and Olsen, Are and van Heuven, Steven and Velo, Anton and Lin, Xiaohua and Schirnick, Carsten and Kozyr, Alex and Tanhua, Toste and Hoppema, Mario and others},
      journal={Earth System Science Data},
      volume={8},
      number={2},
      pages={325},
      year={2016},
      publisher={Copernicus GmbH}
      }
    </bibtex>
    <dataUrls>
      - https://www.nodc.noaa.gov/archive/arc0107/0162565/2.2/data/0-data/mapped/
    </dataUrls>
    <preprocessing>
      preprocess_observations/preprocess_BGC_data.py
    </preprocessing>
    <tasks>
      - climatologyMapBGC
    </tasks>
    <subdirectory>
      Ocean/BGC
    </subdirectory>
    <nameInDocs>
      glodapv2
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Surface Current Variance from Drifter Data
    </name>
    <component>
      ocean
    </component>
    <description>
      Contains information about current variance (eddy kinetic energy) derived from
      residuals with respect to the time-mean, seasonal, spatial gradient, and
      SOI-related currents. The file contains the following variables:

        * Lon (1x720): longitude (degrees), negative=West.
        * Lat (1x317): latitude (degrees), 73S to 85N.
        * Up2bar (317x720): Zonal Velocity Variance, mean(u' ^2) (m^2/s^2).
        * Vp2bar (317x720): Meridional Velocity Variance, mean(v' ^2) (m^2/s^2).
        * rA (317x720): Variance ellipse semimajor axis (m^2/s^2).
        * rB (317x720): Variance ellipse semiminor axis (m^2/s^2).
        * angle (317x720): Orientation angle of variance ellipse (degrees, 0=east/west).
        * N (317x720): Number of drifter-days per square degree.

      Note that Up2bar+Vp2bar=rA+rB, which is twice the eddy kinetic energy.

      For more information, see: http://www.aoml.noaa.gov/phod/gdp/mean_velocity.php

      The global near-surface current climatology described here is publicly available
      through the [Gulf of Mexico Research Initiative Information &amp; Data Cooperative (GRIIDC)](http://dx.doi.org/10.7266/N7SJ1HN5), and through
      [NOAA/AOML](http://www.aoml.noaa.gov/phod/dac/dac_meanvel.php) at
      http://www.aoml.noaa.gov/phod/dac/drifter_variance.nc.

      This climatology was developed by Rick Lumpkin (NOAA/AOML) and Lucas Laurindo
      (Univ. Miami), in collaboration with Arthur Mariano (Univ. Miami), Mayra Pazos
      (NOAA/AOML), and Erik Valdes (CIMAS/AOML). Previous versions were developed with
      Gregory Johnson (NOAA/PMEL), Silvia Garzoli (NOAA/AOML), Jessica Redman (CIMAS),
      and Zulema Garraffo(Univ. Miami).
    </description>
    <source>
      [NOAA/AOML](http://www.aoml.noaa.gov/phod/dac/dac_meanvel.php)
    </source>
    <releasePolicy>
      Please cite as reference:
      Laurindo, L., A. Mariano, and R. Lumpkin, 2017: An improved near-surface
      velocity climatology for the global ocean from drifter observations Deep-Sea
      Res. I, 124, pp.73-92, doi:10.1016/j.dsr.2017.04.009.
    </releasePolicy>
    <references>
      [Laurindo et al. (2017)](https://doi.org/10.1016/j.dsr.2017.04.009)
    </references>
    <bibtex>
      @article{LAURINDO201773,
      title = {An improved near-surface velocity climatology for the global ocean from drifter observations},
      journal = {Deep Sea Research Part I: Oceanographic Research Papers},
      volume = {124},
      pages = {73-92},
      year = {2017},
      issn = {0967-0637},
      doi = {10.1016/j.dsr.2017.04.009},
      url = {http://www.sciencedirect.com/science/article/pii/S0967063716302850},
      author = {Lucas C. Laurindo and Arthur J. Mariano and Rick Lumpkin},
      keywords = {Near-surface velocity climatology, Ocean drifters, Gauss-Markov estimation, Drifter slip bias, Error analysis}
      }
    </bibtex>
    <dataUrls>
      http://www.aoml.noaa.gov/phod/dac/drifter_variance.nc
    </dataUrls>
    <preprocessing>
      (missing)
    </preprocessing>
    <tasks>
      - climatologyMapEKE
    </tasks>
    <subdirectory>
      Ocean/EKE
    </subdirectory>
    <nameInDocs>
      drifter_eke
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Wave Reanalysis: ERA5
    </name>
    <component>
      ocean
    </component>
    <description>
      ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 4 to 7 decades.
      Currently data is available from 1950, with Climate Data Store entries for 1950-1978 (preliminary back extension)
      and from 1959 onwards (final release plus timely updates, this page). ERA5 replaces the ERA-Interim reanalysis.

      Reanalysis combines model data with observations from across the world into a globally complete and
      consistent dataset using the laws of physics. This principle, called data assimilation, is based on
      the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF)
      a previous forecast is combined with newly available observations in an optimal way to produce a new
      best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued.
      Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset
      spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts,
      so there is more time to collect observations, and when going further back in time, to allow for the
      ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product.

      ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities.
      An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals.
      Ensemble mean and spread have been pre-computed for convenience.
      Such uncertainty estimates are closely related to the information content of the available
      observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas.
      To facilitate many climate applications, monthly-mean averages have been pre-calculated too,
      though monthly means are not available for the ensemble mean and spread.

      ERA5 is updated daily with a latency of about 5 days (monthly means are available around the 6th of each month).
      In case that serious flaws are detected in this early release (called ERA5T), this data could be different
      from the final release 2 to 3 months later. In case that this occurs users are notified.

      The data set presented here is a regridded subset of the full ERA5 data set on native resolution.
      It is online on spinning disk, which should ensure fast and easy access.
      It should satisfy the requirements for most common applications.

      An overview of all ERA5 datasets can be found in this [article](https://confluence.ecmwf.int/display/CKB/The+family+of+ERA5+datasets).
      Information on access to ERA5 data on native resolution is provided in these [guidelines](https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5).

      Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and
      0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves).
      There are four main sub sets: hourly and monthly products, both on pressure levels
      (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities).

      The present entry is "ERA5 monthly mean data on single levels from 1959 to present".
    </description>
    <source>
      [Copernicus Climate Data Store](https://doi.org/10.24381/cds.f17050d7)
    </source>
    <releasePolicy>
      Access to Copernicus Products is given for any purpose in so far as it is lawful, whereas use
      may include, but is not limited to: reproduction; distribution; communication to the public;
      adaptation, modification and combination with other data and information; or any
      combination of the foregoing. [Licence Agreement](https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf)
    </releasePolicy>
    <references>
      - [Hersback et al. 2020](https://rmets.onlinelibrary.wiley.com/doi/10.1002/qj.3803)
    </references>
    <bibtex>
      @article{Hersbach2020,
        doi = {10.1002/qj.3803},
        url = {https://doi.org/10.1002/qj.3803},
        year = {2020},
        month = jun,
        publisher = {Wiley},
        volume = {146},
        number = {730},
        pages = {1999--2049},
        author = {Hans Hersbach and Bill Bell and Paul Berrisford and Shoji Hirahara and Andr{\'{a}}s Hor{\'{a}}nyi and Joaqu{\'{\i}}n Mu{\~{n}}oz-Sabater and Julien Nicolas and Carole Peubey and Raluca Radu and Dinand Schepers and Adrian Simmons and Cornel Soci and Saleh Abdalla and Xavier Abellan and Gianpaolo Balsamo and Peter Bechtold and Gionata Biavati and Jean Bidlot and Massimo Bonavita and Giovanna Chiara and Per Dahlgren and Dick Dee and Michail Diamantakis and Rossana Dragani and Johannes Flemming and Richard Forbes and Manuel Fuentes and Alan Geer and Leo Haimberger and Sean Healy and Robin J. Hogan and El{\'{\i}}as H{\'{o}}lm and Marta Janiskov{\'{a}} and Sarah Keeley and Patrick Laloyaux and Philippe Lopez and Cristina Lupu and Gabor Radnoti and Patricia Rosnay and Iryna Rozum and Freja Vamborg and Sebastien Villaume and Jean-Noël Th{\'{e}}paut},
        title = {The {ERA}5 global reanalysis},
        journal = {Quarterly Journal of the Royal Meteorological Society}
      }
    </bibtex>
    <dataUrls>
      - https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=form
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      - climatologyMapWaves
    </tasks>
    <subdirectory>
      Ocean/ERA5
    </subdirectory>
    <nameInDocs>
      era5_waves
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Wave Satelite Altimeter Observations: ESA Sea State Climate Change Initiative
    </name>
    <component>
      ocean
    </component>
    <description>
      The ESA Sea State Climate Change Initiative (CCI) project has produced global merged multi-sensor
      time-series of monthly gridded satellite altimeter significant wave height (referred to as Level 4 (L4) data)
      with a particular focus for use in climate studies.

      This dataset contains the Version 1.1 Remote Sensing Sea Surface Height product, gridded over a global
      regular cylindrical projection (1°x1° resolution), averaging valid and good measurements from all
      available altimeters on a monthly basis (using the L2P products also available).
      These L4 products are meant for statistics and visualization.

      This first version of the Sea State CCI products is inherited from the GlobWave project,
      building on experience and existing outputs. It extends and improves the GlobWave products,
      which were a post-processing over existing L2 altimeter agency products with additional filtering,
      corrections and variables. A major improvement consists in a new denoised sea surface height
      variable using Empirical Mode Decomposition, which was used as input to these monthly statistical fields.

      The altimeter data used in the Sea State CCI dataset v1.1 come from multiple satellite missions
      spanning from 1991 to 2018 (ERS-1, ERS-2, Topex, Envisat, GFO, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL).
      Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used,
      for consistency reasons, being available on each altimeter but SARAL (Ka band).
    </description>
    <source>
      - [CEDA Archive](http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478)
    </source>
    <releasePolicy>
      Public data: access to these data is available to both registered and non-registered users.
      Use of these data is covered by the following [licence](https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sea_state_terms_and_conditions.pdf).
      When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
    </releasePolicy>
    <references>
      - [Dodet et al. 2020](https://essd.copernicus.org/articles/12/1929/2020/)
    </references>
    <bibtex>
      @article{Dodet2020,
        doi = {10.5194/essd-12-1929-2020},
        url = {https://doi.org/10.5194/essd-12-1929-2020},
        year = {2020},
        month = sep,
        publisher = {Copernicus {GmbH}},
        volume = {12},
        number = {3},
        pages = {1929--1951},
        author = {Guillaume Dodet and Jean-Fran{\c{c}}ois Piolle and Yves Quilfen and Saleh Abdalla and Mickaël Accensi and Fabrice Ardhuin and Ellis Ash and Jean-Raymond Bidlot and Christine Gommenginger and Gwendal Marechal and Marcello Passaro and Graham Quartly and Justin Stopa and Ben Timmermans and Ian Young and Paolo Cipollini and Craig Donlon},
        title = {The Sea State {CCI} dataset v1: towards a sea state climate data record based on satellite observations},
        journal = {Earth System Science Data}
      }
    </bibtex>
    <dataUrls>
      - https://data.ceda.ac.uk/neodc/esacci/sea_state/data/v1.1_release/l4/v1.1
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      - climatologyMapWaves
    </tasks>
    <subdirectory>
      Ocean/SSCCI
    </subdirectory>
    <nameInDocs>
      sscci_waves
    </nameInDocs>
  </observation>

  <observation>
    <name>
      OSNAP Temperature Salinity and Velocity Climatology
    </name>
    <component>
      ocean
    </component>
    <description>
      OSNAP is designed to provide a continuous record of the full-water
      column, trans-basin fluxes of heat, mass and freshwater in the subpolar
      North Atlantic. It consists of two legs: one extending from southern
      Labrador to the southwestern tip of Greenland across the mouth of the
      Labrador Sea (OSNAP West), and the second from the southeastern tip of
      Greenland to Scotland (OSNAP East). The observing system also includes
      subsurface floats (OSNAP Floats) in order to trace the pathways of
      overflow waters in the basin and to assess the connectivity of currents
      crossing the OSNAP line. The location of the OSNAP East and West legs
      purposefully melds with a number of long-term observational efforts in
      the North Atlantic: the Canadian repeat AR7W program in the Labrador
      Sea; the German Labrador Sea western boundary array at 53°N; the
      global Ocean Observatories Initiative node to be placed in the
      southwestern Irminger Sea; the repeat A1E/AR7E hydrographic sections
      across the Irminger and Iceland basins; and the Ellett line in the
      Rockall region. Importantly, this observing system, in conjunction with
      the RAPID/MOCHA array at 26ºN and the EU THOR/NACLIM program, will
      provide a comprehensive measure of the Atlantic Meridional Overturning
      Circulation (AMOC) and provide a means to evaluate intergyre
      connectivity in the North Atlantic. OSNAP is a collaborative effort,
      which includes several countries including US, Canada, China, France,
      Germany, Netherlands and the UK.
    </description>
    <source>
      [Overturning in the Subpolar North Atlantic Program (OSNAP) website]
      (https://www.o-snap.org/data-access/)
    </source>
    <releasePolicy>
      Acknowledgment: OSNAP data were collected and made freely available by the OSNAP (Overturning in the Subpolar North Atlantic Program) project and all the national programs that contribute to it (www.o-snap.org).
    </releasePolicy>
    <references>
    </references>
    <bibtex>
    </bibtex>
    <dataUrls>
      - https://duke.app.box.com/s/4qbi9ocpvmxdv44wnx2g5rgoyy85jmz6
    </dataUrls>
    <preprocessing>
      - preprocess_observations/preprocessingOSNAP30day.ipynb
    </preprocessing>
    <tasks>
      - osnapTransects
    </tasks>
    <subdirectory>
      Ocean/OSNAP
    </subdirectory>
    <nameInDocs>
      osnap_t_s
    </nameInDocs>
  </observation>


<!--
  <observation>
    <name>
    </name>
    <component>
      ocean
    </component>
    <description>
    </description>
    <source>
      []()
    </source>
    <releasePolicy>
    </releasePolicy>
    <references>
      -
    </references>
    <bibtex>
    </bibtex>
    <dataUrls>
      -
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      -
    </tasks>
    <subdirectory>
      Ocean/
    </subdirectory>
    <nameInDocs>
    </nameInDocs>
  </observation>
-->

  <!-- SEA ICE -->

  <observation>
    <name>
      Ice concentration: SSM/I, NASATeam algorithm
    </name>
    <component>
      seaice
    </component>
    <description>
      This data set is generated from brightness temperature data and is
      designed to provide a consistent time series of sea ice concentrations
      spanning the coverage of several passive microwave instruments. The data
      are provided in the polar stereographic projection at a grid cell size of
      25 x 25 km.
    </description>
    <source>
      [NSIDC NASATeam Website](http://nsidc.org/data/NSIDC-0051)
    </source>
    <releasePolicy>
      NASA data are not copyrighted; however, when you publish our data or
      results derived therefrom, we request that you include an acknowledgment
      within the text of the publication and reference list.
      [Data Citation and Acknowledgements]
      (https://podaac.jpl.nasa.gov/CitingPODAAC)
    </releasePolicy>
    <references>
      [Cavalieri et al. (1996)](https://doi.org/10.5067/8GQ8LZQVL0VL)
    </references>
    <bibtex>
      @misc{Cavalieri1996,
      author = {D. J. Cavalieri,  and C. L. Parkinson and P. Gloersen and H. J. Zwally},
      title = {Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1},
      year = {1996},
      doi = {10.5067/8GQ8LZQVL0VL},
      notes = {updated yearly},
      url = {https://doi.org/10.5067/8GQ8LZQVL0VL}
      }
    </bibtex>
    <dataUrls>
      (missing, requires registration with NSIDC)
    </dataUrls>
    <preprocessing>
      preprocess_observations/NASATeam_Antarctic_compute_climo.m
      preprocess_observations/NASATeam_Arctic_compute_climo.m
      (missing remapping from stereographic to lat/lon)
    </preprocessing>
    <tasks>
      - climatologyMapSeaIceConcNH
      - climatologyMapSeaIceConcSH
    </tasks>
    <subdirectory>
      SeaIce/SSMI/NASATeam_NSIDC0051
    </subdirectory>
    <nameInDocs>
      nasateam_conc
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Ice concentration: SSM/I, Bootstrap algorithm
    </name>
    <component>
      seaice
    </component>
    <description>
      This sea ice concentration data set was derived using measurements from
      the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7
      satellite and from the Special Sensor Microwave/Imager (SSM/I) sensors on
      the Defense Meteorological Satellite Program's (DMSP) -F8, -F11, and -F13
      satellites. Measurements from the Special Sensor Microwave Imager/Sounder
      (SSMIS) aboard DMSP-F17 are also included. The data set has been
      generated using the Advanced Microwave Scanning Radiometer - Earth
      Observing System (AMSR-E) Bootstrap Algorithm with daily varying
      tie-points. Daily (every other day prior to July 1987) and monthly data
      are available for both the north and south polar regions. Data are
      gridded on the SSM/I polar stereographic grid (25 x 25 km) and provided
      in two-byte integer format. Data are available via FTP.
    </description>
    <source>
      [NSIDC Bootstrap Website](http://nsidc.org/data/NSIDC-0079)
    </source>
    <releasePolicy>
      NASA data are not copyrighted; however, when you publish our data or
      results derived therefrom, we request that you include an acknowledgment
      within the text of the publication and reference list.
      [Data Citation and Acknowledgements]
      (https://podaac.jpl.nasa.gov/CitingPODAAC)
    </releasePolicy>
    <references>
      [Comiso (2017)](https://doi.org/10.5067/7Q8HCCWS4I0R)
    </references>
    <bibtex>
      @misc{Comiso1996,
      author = {J. C. Comiso},
      title = {Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS, Version 3},
      year = {2017},
      doi = {10.5067/7Q8HCCWS4I0R},
      notes = {updated yearly},
      url = {https://doi.org/10.5067/7Q8HCCWS4I0R}
      }
    </bibtex>
    <dataUrls>
      (missing, requires registration with NSIDC)
    </dataUrls>
    <preprocessing>
      preprocess_observations/Bootstrap_Antarctic_compute_climo.m
      preprocess_observations/Bootstrap_Arctic_compute_climo.m
      (missing remapping from stereographic to lat/lon)
    </preprocessing>
    <tasks>
      - climatologyMapSeaIceConcNH
      - climatologyMapSeaIceConcSH
    </tasks>
    <subdirectory>
      SeaIce/SSMI/Bootstrap_NSIDC0079
    </subdirectory>
    <nameInDocs>
      bootstrap_conc
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Ice area and extent time series: SSM/I derived
    </name>
    <component>
      seaice
    </component>
    <description>
      The sea ice data presented here were derived from satellite
      passive-microwave radiometers, specifically, the Scanning Multichannel
      Microwave Radiometer (SMMR) on NASA's Nimbus 7 satellite, for November
      1978-August 1987, a sequence of Special Sensor Microwave Imagers (SSMIs)
      on the F8, F11, and F13 satellites of the Defense Meteorological
      Satellite Program (DMSP), for August 1987-December 2007, and the Special
      Sensor Microwave Imager Sounder (SSMIS) on the DMSP F17 satellite for
      January 2008-December 2012. The baseline data used were daily maps of
      sea ice concentration. The maps are polar stereographic projections with
      individual grid elements of approximately 25 km x 25 km; and the ice
      concentration data are also archived at the National Snow and Ice Data
      Center (NSIDC) at http://nsidc.org. The concentrations are calculated for
      each ocean grid element and are used to derive 'sea ice extent', which is
      calculated as the sum of all ocean elements having a sea ice
      concentration of at least 15%, and 'sea ice area', which is calculated as
      the sum over all ocean grid elements of the product of ice concentration
      and grid element area. The data sets provided here include the
      hemispheric totals and additionally the values for nine regions in the
      Arctic and five regions in the Antarctic. These regions are identified in
      Figures 1 and 2 respectively. Figures 3 and 4 provide plots of the trends
      in the Arctic and Antarctic sea ice extents, along with monthly
      deviations and 12-month running means. The monthly deviations are
      calculated by taking the individual month's ice extent/area and
      subtracting from it the average over the course of the data set of the
      extents/areas for that month.
    </description>
    <source>
      [NASA Ice area and extent website](https://neptune.gsfc.nasa.gov/csb/index.php?section=59)
    </source>
    <releasePolicy>
      NASA data are not copyrighted; however, when you publish our data or
      results derived therefrom, we request that you include an acknowledgment
      within the text of the publication and reference list.
      [Data Citation and Acknowledgements]
      (https://podaac.jpl.nasa.gov/CitingPODAAC)
    </releasePolicy>
    <references>
      - [Cavalieri et al. (1999)](https://doi.org/10.1029/1999JC900081)
      - [Cavalieri et al. (2012)](https://doi.org/10.1109/LGRS.2011.2166754)
      - [Cavalieri and Parkinson (2012)](https://doi.org/10.5194/tc-6-881-2012)
      - [Parkinson et al. (1999)](https://doi.org/10.1029/1999JC900082)
      - [Parkinson and Cavalieri (2012)](https://doi.org/10.5194/tc-6-871-2012)
      - [Zwally et al. (2002)](https://doi.org/10.1029/2000JC000733)
    </references>
    <bibtex>
      @article{Cavalieri1999,
      author = {D. J. Cavalieri and C. L. Parkinson and P. Gloersen and J. C. Comiso and H. J. Zwally},
      title = {Deriving long-term time series of sea ice cover from satellite passive-microwave multisensor data sets},
      journal = {Journal of Geophysical Research: Oceans},
      volume = {104},
      number = {C7},
      year = {1999},
      pages = {15803-15814},
      doi = {10.1029/1999JC900081},
      url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/1999JC900081}
      }
      @article{Cavalieri2012a,
      author={D. J. Cavalieri and C. L. Parkinson and N. DiGirolamo and A. Ivanoff},
      journal={IEEE Geoscience and Remote Sensing Letters},
      title={Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records},
      year={2012},
      volume={9},
      number={2},
      pages={233-236},
      doi={10.1109/LGRS.2011.2166754},
      ISSN={1545-598X},
      month={March}
      }
      @Article{Cavalieri2012b,
      AUTHOR = {Cavalieri, D. J. and Parkinson, C. L.},
      TITLE = {Arctic sea ice variability and trends, 1979--2010},
      JOURNAL = {The Cryosphere},
      VOLUME = {6},
      YEAR = {2012},
      NUMBER = {4},
      PAGES = {881--889},
      URL = {https://www.the-cryosphere.net/6/881/2012/},
      DOI = {10.5194/tc-6-881-2012}
      }
      @article{Parkinson1999,
      author = {Claire L. Parkinson and Donald J. Cavalieri and Per Gloersen and H. Jay Zwally and Josefino C. Comiso},
      title = {Arctic sea ice extents, areas, and trends, 1978--1996},
      journal = {Journal of Geophysical Research: Oceans},
      volume = {104},
      number = {C9},
      year = {1999},
      pages = {20837-20856},
      doi = {10.1029/1999JC900082},
      url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/1999JC900082}
      }
      @Article{Parkinson2012,
      AUTHOR = {Parkinson, C. L. and Cavalieri, D. J.},
      TITLE = {Antarctic sea ice variability and trends, 1979--2010},
      JOURNAL = {The Cryosphere},
      VOLUME = {6},
      YEAR = {2012},
      NUMBER = {4},
      PAGES = {871--880},
      URL = {https://www.the-cryosphere.net/6/871/2012/},
      DOI = {10.5194/tc-6-871-2012}
      }
      @article{Zwally2002,
      author = {H. Jay Zwally and Josefino C. Comiso and Claire L. Parkinson and Donald J. Cavalieri and Per Gloersen},
      title = {Variability of Antarctic sea ice 1979--1998},
      journal = {Journal of Geophysical Research: Oceans},
      volume = {107},
      number = {C5},
      pages = {9-1-9-19},
      keywords = {sea ice, Antarctic, climate, passive microwave, Southern Ocean},
      doi = {10.1029/2000JC000733},
      url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2000JC000733},
      year = {2002}
      }
    </bibtex>
    <dataUrls>
      - https://neptune.gsfc.nasa.gov/uploads/files/NH_IceArea_Monthly_1978-2012.txt
      - https://neptune.gsfc.nasa.gov/uploads/files/NH_IceExt_Monthly_1978-2012.txt
      - https://neptune.gsfc.nasa.gov/uploads/files/SH_IceArea_Monthly_1978-2012.txt
      - https://neptune.gsfc.nasa.gov/uploads/files/SH_IceExt_Monthly_1978-2012.txt
    </dataUrls>
    <preprocessing>
      preprocess_observations/IceaArea_txt2netcdf.m
    </preprocessing>
    <tasks>
      - timeSeriesSeaIceAreaVol
    </tasks>
    <subdirectory>
      SeaIce/IceArea_timeseries
    </subdirectory>
    <nameInDocs>
      ssmi_ice_area
    </nameInDocs>
  </observation>

  <observation>
    <name>
      IceSat Ice Thickness
    </name>
    <component>
      seaice
    </component>
    <description>
      This data set provides measurements of sea ice freeboard and sea ice
      thickness for the Arctic region. The data were derived from measurements
      made by from the Ice, Cloud, and land Elevation Satellite (ICESat)
      Geoscience Laser Altimeter System (GLAS) instrument, the Special Sensor
      Microwave/Imager (SSM/I), and climatologies of snow and drift of ice.
    </description>
    <source>
      [NASA: Arctic Sea Ice Freeboard and Thickness](http://nsidc.org/data/NSIDC-0393)
    </source>
    <releasePolicy>
      NASA data are not copyrighted; however, when you publish our data or
      results derived therefrom, we request that you include an acknowledgment
      within the text of the publication and reference list.
      [Data Citation and Acknowledgements]
      (https://podaac.jpl.nasa.gov/CitingPODAAC)
    </releasePolicy>
    <references>
      [Yi and Zwally (2009)](https://doi.org/10.5067/SXJVJ3A2XIZT)
    </references>
    <bibtex>
      @misc{Yi2009,
      author = {D. Yi and H. J. Zwally},
      title = {Arctic Sea Ice Freeboard and Thickness, Version 1},
      year = {2009},
      doi = {10.5067/7Q8HCCWS4I0R},
      url = {https://doi.org/10.5067/SXJVJ3A2XIZT}
      }
    </bibtex>
    <dataUrls>
      (missing, requires registration with NSIDC)
    </dataUrls>
    <preprocessing>
      ICESat_Arctic_compute_climo.m
      (missing Antarctic climo)
      (missing remapping from stereographic to lat/lon)
    </preprocessing>
    <tasks>
      - timeSeriesSeaIceAreaVol
    </tasks>
    <subdirectory>
      SeaIce/ICESat
    </subdirectory>
    <nameInDocs>
      icesat_thickness
    </nameInDocs>
  </observation>

  <observation>
    <name>
      PIOMAS Arctic Sea Ice Volume Reanalysis
    </name>
    <component>
      seaice
    </component>
    <description>
      Sea Ice Volume is calculated using the Pan-Arctic Ice Ocean Modeling and
      Assimilation System (PIOMAS, Zhang and Rothrock, 2003) developed at
      APL/PSC.  Anomalies for each day are calculated relative to the average
      over the 1979-2016 period for that day of the year to remove the annual
      cycle. The model mean annual cycle of sea ice volume over this period
      ranges from 28,000 km3 in April to 11,500 km3 in September.
    </description>
    <source>
      [PIOMAS website](http://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/)
    </source>
    <releasePolicy>
      Data is public, but they optionally ask for basic information about the
      person downloading the data (name, e-mail, and affiliation).
    </releasePolicy>
    <references>
      - [Schweiger et al. (2011)](https://doi.org/10.1029/2011JC007084)
      - [Zhang and Rothrock (2003)](https://doi.org/10.1175/1520-0493%282003%29131&lt;0845:MGSIWA&gt;2.0.CO;2)
    </references>
    <bibtex>
      @article{Schweiger2011,
      author = {Axel Schweiger and Ron Lindsay and Jinlun Zhang and Mike Steele and Harry Stern and Ron Kwok},
      title = {Uncertainty in modeled Arctic sea ice volume},
      journal = {Journal of Geophysical Research: Oceans},
      volume = {116},
      number = {C8},
      pages = {},
      keywords = {Arctic, climate change, ice volume, modelling, sea ice},
      doi = {10.1029/2011JC007084},
      url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2011JC007084},
      year = {2011}
      }
      @article{Zhang2003,
      author = { Jinlun  Zhang  and  D. A.  Rothrock },
      title = {Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates},
      journal = {Monthly Weather Review},
      volume = {131},
      number = {5},
      pages = {845-861},
      year = {2003},
      doi = {10.1175/1520-0493(2003)131&lt;0845:MGSIWA&gt;2.0.CO;2},
      URL = {https://doi.org/10.1175/1520-0493(2003)131&lt;0845:MGSIWA&gt;2.0.CO;2}
      }
    </bibtex>
    <dataUrls>
      - http://psc.apl.uw.edu/wordpress/wp-content/uploads/schweiger/ice_volume/PIOMAS.2sst.monthly.Current.v2.1.txt
    </dataUrls>
    <preprocessing>
      preprocess_observations/PIOMAS_txt2netcdf.m
    </preprocessing>
    <tasks>
      - timeSeriesSeaIceAreaVol
    </tasks>
    <subdirectory>
      SeaIce/PIOMAS
    </subdirectory>
    <nameInDocs>
      piomass_ice_volume
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Sea ice production and transport: Haumann et al 2016
    </name>
    <component>
      seaice
    </component>
    <description>
      This data set provides estimates of annual freshwater fluxes related to sea-ice formation from ocean freezing
      and snow-ice formation, sea-ice melting, lateral transport of sea ice in the Southern Ocean over the period
      1982 to 2008. It is derived from a mass balance calculation of local sea-ice volume change and divergence
      from satellite data and sea-ice reconstructions. The mass balance is calculated on a daily basis and fluxes are
      then integrated over the entire year, where a year is defined from March to February of the next year (i.e.
      from March 1982 to February 2009). This approach combines multiple products of sea-ice concentration
      (Cavalieri &amp; Parkinson, 2008; Comiso, 1986; Meier et al., 2013), sea-ice thickness (Kurtz &amp; Markus, 2012;
      Massonnet et al., 2013; Worby et al., 2008), and sea-ice drift (Fowler et al., 2013; Kwok 2005; Schwegmann
      et al., 2011). For a detailed description of the method see Haumann et al. (2016). The data set is derived to
      estimate large-scale (regional to basin-scale) fluxes on an annual basis. Our confidence is reduced on a grid
      cell basis, such as for single coastal polynyas, where the method and underlying data induce large, unknown
      uncertainties.
    </description>
    <source>
      [EnviDat](https://www.envidat.ch/dataset/10-16904-8)
    </source>
    <releasePolicy>
      This data set is free to use for any non-commercial purpose at the risk of the user'
      and the authors do not take any liability on the use of the data set. The authors
      assembled the data set carefully and assessed accuracy, errors, and uncertainties.
      Please contact the authors if you find any issues.
    </releasePolicy>
    <references>
      [Haumann et al (2016), data](https://doi.org/10.16904/8)
      [Haumann et al (2016), paper](https://doi.org/10.1038/nature19101)
    </references>
    <bibtex>
      @article{haumann2016antarctic,
      title={Antarctic sea-ice freshwater fluxes associated with freezing, transport, and melting},
      author={Haumann, Alexander and Gruber, Nicolas and M{\"u}nnich, Matthias and Frenger, Ivy and Kern, Stefan},
      year={2016},
      doi={10.16904/8},
      publisher={ETH Z{\"u}rich}
      }
      @article{haumann2016sea,
      title={Sea-ice transport driving Southern Ocean salinity and its recent trends},
      author={Haumann, F Alexander and Gruber, Nicolas and M{\"u}nnich, Matthias and Frenger, Ivy and Kern, Stefan},
      journal={Nature},
      volume={537},
      number={7618},
      pages={89--92},
      year={2016},
      doi={10.1038/nature19101}
      publisher={Nature Publishing Group}
      }
    </bibtex>
    <dataUrls>
      -https://data.up.ethz.ch/shared/AnIceFlux/AnIceFlux_v01.pdf
    </dataUrls>
    <preprocessing>
      none
    </preprocessing>
    <tasks>
      - climatologyMapSeaIceProductionSH
      - climatologyMapSeaIceMeltingSH
    </tasks>
    <subdirectory>
      SeaIce/Haumann
    </subdirectory>
    <nameInDocs>
      aniceflux
    </nameInDocs>
  </observation>

  <observation>
    <name>
      Risk Index Values
    </name>
    <component>
      seaice
    </component>
    <description>
      This data set contains the Risk Index Values in Table 1.3 of the
      International Maritime Organization rules within the Polar Operational 
      Limit Assessment Risk Indexing System (POLARIS). The basis of POLARIS is 
      an evaluation of the risks posed to the ship by ice conditions in relation 
      to the ship's assigned ice class.
    </description>
    <source>
      [International Maritime Organization (IMO) Rules Website](https://www.imorules.com/GUID-2C1D86CB-5D58-490F-B4D4-46C057E1D102.html)
    </source>
    <releasePolicy>
      Unknown, openly available on website.
    </releasePolicy>
    <references>
      [International Maritime Organization (2016)](https://www.imorules.com/GUID-2C1D86CB-5D58-490F-B4D4-46C057E1D102.html)
    </references>
    <bibtex>
      @misc{IMO2016,
      author = {International Maritime Organization},
      title = {{Guidance on Methodologies for Assessing Operational Capabilities and Limitations in Ice}},
      year = {2016},
      howpublished = {{IMO Publications and Documents - Circulars - Maritime Safety Committee - MSC.1/Circular.1519 - Guidance on Methodologies for Assessing Operational Capabilities and Limitations in Ice - (6 June 2016) - Appendix - Methodology for Assessing Operational Capabilities and Limitations in Ice: Polar Operational Limit Assessment Risk Indexing System (POLARIS)}}
      url = {https://www.imorules.com/GUID-2C1D86CB-5D58-490F-B4D4-46C057E1D102.html}
      }
    </bibtex>
    <dataUrls>
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      - climatologyMapRiskIndexOutcomeNH
      - climatologyMapRiskIndexOutcomeSH
    </tasks>
    <subdirectory>
      SeaIce/RIV
    </subdirectory>
    <nameInDocs>
      imo_riv
    </nameInDocs>
  </observation>

  <!-- ICEBERGS -->

  <observation>
    <name>
      Iceberg Concentration: Altiberg
    </name>
    <component>
      seaice
    </component>
    <description>
      Iceberg probabilities from the Altiberg dataset for small icebergs (less than 3km in length) detected by altimeters using the high resolution waveforms. The database is also available for other several altimeter mission (ERS-1, ERS-2, Jason-1, Jason-2, CryoSat-2, Topex, Envisat, AltiKa). A merged product combining all the available altimeters is also provided, which is used in MPAS-Analysis.
    </description>
    <source>
      [Altiberg website](http://cersat.ifremer.fr/user-community/news/item/473-altiberg-a-database-for-small-icebergs)
    </source>
    <releasePolicy>
      Unknown, openly available on website.
    </releasePolicy>
    <references>
      - [Tournade et al (2017)](ftp://ftp.ifremer.fr/ifremer/cersat/projects/altiberg/v2/documentation/ALTIBERG-rep_v2_1.pdf)
    </references>
    <bibtex>
      @article{tournadre2013altiberg,
      title={The Altiberg iceberg database version 2},
      author={Tournadre, J and Accensi, M and Girard-Ardhuin, F},
      journal={Doc. Tech. LOS},
      volume={2},
      year={2017}
      }
    </bibtex>
    <dataUrls>
      - ftp://ftp.ifremer.fr/ifremer/cersat/projects/altiberg/
    </dataUrls>
    <preprocessing>
      preprocess_observations/Altiberg_mergefiles.sh
    </preprocessing>
    <tasks>
      - climatologyMapIcebergConcSH
    </tasks>
    <subdirectory>
      Icebergs/
    </subdirectory>
    <nameInDocs>
      altiberg
    </nameInDocs>
  </observation>

<!--
  <observation>
    <name>
    </name>
    <component>
      seaice
    </component>
    <description>
    </description>
    <source>
      []()
    </source>
    <releasePolicy>
    </releasePolicy>
    <references>
      -
    </references>
    <bibtex>
    </bibtex>
    <dataUrls>
      -
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      -
    </tasks>
    <subdirectory>
      SeaIce/
    </subdirectory>
    <nameInDocs>
    </nameInDocs>
  </observation>
-->

  <!-- LAND ICE -->

<!--
  <observation>
    <name>
    </name>
    <component>
      landice
    </component>
    <description>
    </description>
    <source>
      []()
    </source>
    <releasePolicy>
    </releasePolicy>
    <references>
      -
    </references>
    <bibtex>
    </bibtex>
    <dataUrls>
      -
    </dataUrls>
    <preprocessing>
    </preprocessing>
    <tasks>
      -
    </tasks>
    <subdirectory>
      LandIce/
    </subdirectory>
    <nameInDocs>
    </nameInDocs>
  </observation>
-->

</observations>