Seventh Conference on Artificial Intelligence and its Applications to the Environmental Sciences
23rd Conference on Hydrology

J6.3

Comparison of manual and automated quality control of operational hourly precipitation data of the national weather service

Dongsoo Kim, NOAA/NESDIS/NCDC, Asheville, NC; and E. I. Tollerud, S. V. Vasiloff, and J. Caldwell

The NWS Office of Hydrologic Development (OHD) operates the collection and dissemination of real-time Hydrometeorological Automated Data System (HADS) and other precipitation gauge data to the end-users at River Forecast Centers (RFCs) and Weather Forecast Offices (WFOs). As most of the data are delivered to the users with minimal quality control (QC) in order to shorten data latency, forecasters at RFCs apply significant effort toward QC to insure proper hydrologic forecasting. Thus there is a great need for automated gauge QC. Locally archived datasets of HADS data that have undergone manual QC at the Lower Mississippi RFC (LMRFC) provide an opportunity to evaluate automated QC methods using algorithms developed at the Earth System Research Laboratory (ESRL) and National Climatic Data Center (NCDC). Both methods rely heavily on comparisons between gauges but apply these neighbor checks in different ways. We present results from both systems and compare them to station lists produced at the LMRFC by manual QC. One notable difference that emerges from this comparison is a large discrepancy in the way that manual and automated procedures handle potentially faulty gauges reporting small precipitation amounts. Based on our comparisons, we discuss gauge quality issues with potential impact on operational forecasters, including the value of including radar estimates in the QC process.

extended abstract  Extended Abstract (276K)

wrf recording  Recorded presentation

Joint Session 6, Hydrology and AI: Status and Applications–I
Tuesday, 13 January 2009, 11:00 AM-12:00 PM, Room 125A

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