⇒ IQuOD:International Quality-controlled Ocean Database Project

 

The IQuOD (International Quality-controlled Ocean Database) effort is being organized by the oceanographic community, and includes experts in data quality and management, climate modellers and the broader climate-related community. The primary focus of IQuOD is to produce and freely distribute the highest quality and complete single ocean profile repository along with (intelligent) metadata and assigned uncertainties for use in ocean climate research applications. This goal will be achieved by developing and implementing an internationally-agreed framework.

http://www.iquod.org/

Collections in this community

Recent Submissions

  • A Framework to Quality Control Oceanographic Data. 

    Castelao, Guilherme P. (2020)
    The ocean is an intrinsically challenging environment to collect data, which makes spurious measurements inevitable. Thus, the quality of oceanographic datasets is highly dependent on the ability to identify and remove ...

  • Australian XBT Quality Control Cookbook Version 2.1. 

    Cowley, Rebecca; Krummel, Lisa (CSIRO, Hobart, Tasmania, Australia, 2023)
    Expendable Bathythermographs (XBTs) have been used for many years by oceanographers to measure the temperature of the upper ocean. These instruments are simple devices which are designed to be deployed from moving vessels, ...

  • Benchmarking of automatic quality control checks for ocean temperature profiles and recommendations for optimal sets. 

    Good, S.A.; Mills, Bill; Castelao, Guilherme; Cowley, Rebecca; Goni, Gustavo; Gouretski, Viktor; Domingues, Catia M.; Boyer, Tim; Bringas, Francis (2023)
    Millions of in situ ocean temperature profiles have been collected historically using various instrument types with varying sensor accuracy and then assembled into global databases. These are essential to our current ...

  • International Quality-Controlled Ocean Database (IQuOD) v0.1: The Temperature Uncertainty Specification. 

    Cowley, Rebecca; Killick, Rachel E.; Boyer, Tim; Reseghetti, Franco; Kizu, Shoichi; Palmer, Matthew D.; Cheng, Lijing; Storto, Andrea; Le Menn, Marc; Simoncelli, Simona; Macdonald, Alison M.; Domingues, Catia M. (2021)
    Ocean temperature observations are crucial for a host of climate research and forecasting activities, such as climate monitoring, ocean reanalysis and state estimation, seasonal-to-decadal forecasts, and ocean forecasting. ...

  • SalaciaML: A Deep Learning Approach for Supporting Ocean Data Quality Control. 

    Mieruch, Sebastian; Demirel, Serdar; Simoncelli, Simona; Schlitzer, Reiner; Seitz, Steffen (2021)
    We present a skillful deep learning algorithm for supporting quality control of ocean temperature measurements, which we name SalaciaML according to Salacia the roman goddess of sea waters. Classical attempts to ...

  • An Algorithm for Classifying Unknown Expendable Bathythermograph (XBT) Instruments Based on Existing Metadata. 

    Palmer, Matthew D.; Boyer, Tim; Cowley, Rebecca; Kizu, Shoichi; Reseghetti, Franco; Suzuki, Toru; Thresher, Ann (2018)
    Time-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key un- certainty in estimates of historical ocean heat content variability and change. One of the challenges in the development of ...