Abstract
High value of instrumental databases is attained and maintained through a rigorous quality assurance/quality control program involving care of the instrument and sensors to assure the quality of the data stream, careful instrument calibration, and continuous data quality control to ensure that data is flowing and to detect spikes and data gaps or instrument drift. In the case of remote sensing or numerical model databases, vicarious calibration or field validation is required. Instrument data and metadata are stored digitally using prescribed character codes and database formats that facilitate retrieval and visualization of selected data packets from large databases. Value of the data to the user is affirmed when knowledge is extracted from the data packet through visualization of data products that may include tables or time series data but most usually consist of a combination of graphics and text.
The original version of this chapter was revised. A correction to this chapter can be found at https://doi.org/10.1007/978-3-319-78352-9_9
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anselmi-Molina CM, Canals M, Morell J, Gonzalez J, Capella J, Mercado A. Development of an operational nearshore wave forecast system for Puerto Rico and the U.S. Virgin Islands. J Coast Res. 2012;28(5):1049–56.
Brown SW, Flora SJ, Feinholz ME, Yarbrough MA, Houlihan T, Peters D, Kim YS, Mueller J, Johnson BC, Clark DK. The Marine Optical BuoY (MOBY) radiometric calibration and uncertainty budget for ocean color satellite sensor vicarious calibration Proceedings of the SPIE optics and photonics; sensors, systems, and next-generation satellites XI. 2007;6744:67441M.
Chen C, Huang H, Beardsley RC, Liu H, Xu Q, Cowles G. A finite volume numerical approach for coastal ocean circulation studies: Comparisons with finite difference models. J Geophys Res. 2007;112(C3):C03018.
Corredor JE, Amador A, Canals M, Rivera S, Capella JE, Morell JM, Glenn S, Handel E, Rivera E, Roarty H. Optimizing and validating high frequency radar surface current measurements in the Mona passage. Mar Technol Soc J. 2011;45(3):49–58.
Haldivogel DB, et al. Ocean forecasting in terrain-following coordinates: formulation and skill assessment of the Regional Ocean Modeling System. J Comput Phys. 2008;227(7):3595–624.
U.S. Integrated Ocean Observing System. Manual for real-time quality control of in-situ temperature and salinity data version 2.0: a guide to quality control and quality assurance of in-situ temperature and salinity observations. Silver Spring: NOAA US National Atmospheric and Oceanic Administration; 2015a. p. 56.
U.S. Integrated Ocean Observing System. Manual for real-time quality control of ocean optics data: a guide to quality control and quality assurance of coastal and oceanic optics observations. Sivler Spring: NOAA, US National Atmospheric and Oceanic Administration; 2015b. p. 46.
U.S. Integrated Ocean Observing System. Manual for real-time quality control of high frequency radar surface currents data: a guide to quality control and quality assurance of high frequency radar surface currents data observations. Silver Spring: NOAA; 2016. p. 58.
Willmott CJ, Robeson SM, Matsuura K. Climate and other models may be more accurate than reported. EOS. 2017;98(9):13–4.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Corredor, J.E. (2018). Coastal Ocean Observing Data Quality Assurance and Quality Control, Data Validation, Databases, and Data Presentation. In: Coastal Ocean Observing. Springer, Cham. https://doi.org/10.1007/978-3-319-78352-9_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-78352-9_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-78351-2
Online ISBN: 978-3-319-78352-9
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)