JP1.18
Quality assurance of temperature observations at the National Climatic Data Center
Matthew J. Menne, NOAA/NCDC, Asheville, NC; and C. E. Duchon
The National Climatic Data Center (NCDC) has used a variety of quality control/quality assurance techniques to detect errors in temperature and other variables as data are operationally ingested and processed prior to archival. As part of a recent initiative to monitor the "health" of NOAA's observational networks, new quality assurance methods recently have been developed and added to the existing suite of data processing algorithms in order to improve timely error detection in temperature data from the National Weather Service Cooperative Observer Network and the Automated Surface Observation System. These additions form part of a four-level, primarily statistical quality assurance processing system for temperature observations that is under development at the NCDC. Each of these levels is characterized by the time frame over which temperature observations are evaluated. Time frames range from operational, near-real time evaluation of daily observations to longer-term homogeneity assessments of monthly and annual means. We will describe each of these quality assurance levels as well as provide an outline of how they fit together to form a system.
Joint Poster Session 1, Joint Poster Viewing with Buffet (Joint between 15th Conference on Probability and Statistics in the Atmospheric Sciences and 12th Conference on Applied Climatology)
Wednesday, 10 May 2000, 5:30 PM-7:00 PM
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