Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA

Faybishenko, Boris; Versteeg, Roelof; Pastorello, Gilberto; Dwivedi, Dipankar; Varadharajan, Charuleka; Agarwal, Deb

doi:10.15485/1823516

Title: Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA

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Abstract

A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.

Authors:

; Versteeg, Roelof; Pastorello, Gilberto;

;

Lawrence Berkeley National Laboratory; Lawrence Berkeley National Laboratory
Subsurface Insights
Lawrence Berkeley National Laboratory

Publication Date:: Fri Jan 01 04:00:00 UTC 2021

Other Number(s):: paf_724_733

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; Air Temperature; Barometric Pressure; East River Watershed; Meteorology – weather stations; Precipitation; QA/QC; R packages; Relative Humidity; Solar Radiation; Wind Direction; Wind Speed; meteorological data

OSTI Identifier:: 1823516

DOI:: https://doi.org/10.15485/1823516

Citation Formats


                    Faybishenko, Boris, Versteeg, Roelof, Pastorello, Gilberto, Dwivedi, Dipankar, Varadharajan, Charuleka, and Agarwal, Deb. Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA.  United States: N. p., 2021. 
        Web.  doi:10.15485/1823516.

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                    Faybishenko, Boris, Versteeg, Roelof, Pastorello, Gilberto, Dwivedi, Dipankar, Varadharajan, Charuleka, & Agarwal, Deb. Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA.  United States.  doi:https://doi.org/10.15485/1823516

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                    Faybishenko, Boris, Versteeg, Roelof, Pastorello, Gilberto, Dwivedi, Dipankar, Varadharajan, Charuleka, and Agarwal, Deb. 2021.  
"Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA".  United States.  doi:https://doi.org/10.15485/1823516.  https://www.osti.gov/servlets/purl/1823516. Pub date:Fri Jan 01 04:00:00 UTC 2021

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@article{osti_1823516,

  title        = {Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA},

  author       = {Faybishenko, Boris and Versteeg, Roelof and Pastorello, Gilberto and Dwivedi, Dipankar and Varadharajan, Charuleka and Agarwal, Deb},

  abstractNote = {A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.},

  doi          = {10.15485/1823516},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Jan 01 04:00:00 UTC 2021},

  month        = {Fri Jan 01 04:00:00 UTC 2021}

}

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DOI: https://doi.org/10.15485/1823516

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