The 11th Conference on Applied Climatology

J7.2
SNOW CLIMATOLOGIES FOR NWS COOPERATIVE STATIONS--AN OVERVIEW

Richard R. Heim, NOAA/NESDIS/NCDC, Asheville, NC; and R. J. Leffler

The introduction, by the National Oceanic and Atmospheric Administration's (NOAA) National Weather Service (NWS) in the early 1990's, of the Automated Surface Observing System (ASOS) has improved meteorological observations by standardizing observational methodologies across the airport observing network and by creating the potential for increasing the number and geographical coverage of aviation stations. However, ASOS instrumentation does not measure snowfall and snow depth amounts. The nation will therefore now have to rely more heavily on the daily snowfall and snow depth observations of the voluntary Cooperative Network stations.

Comprehensive snow climatologies were generated for 5525 stations in the Cooperative Network (in the contiguous United States and Alaska) to support NWS operations in the ASOS era and to enable NOAA to better respond to user requests for snow information for use in economic and engineering decision-making. This paper summarizes the data base, quality assurance, and methodology used to create the climatologies. The statistics produced here represent the most comprehensive snow climatology ever computed for the United States. ---Daily snowfall and snow depth data from the National Climatic Data Center's (NCDC) TD-3200 data base were analyzed over the digital period of record through 1996. Three levels of quality control were applied. Several statistics were computed for several climatic elements using several snowfall and snow depth thresholds. The statistics include mean, median, first and third quartiles, extremes, and probabilities. The elements include number of days with snow (snowfall or snow depth) beyond various thresholds, monthly and seasonal total snowfall, number of consecutive days with snow, dates of the first and last occurrence of snowfall, daily and multiple-day extreme snowfall amounts, and daily snow depth amount.

Several indicators were computed, based on the data and metadata, to enable the user to assess the quality of the stations. These include frequencies of station moves and ob time changes, number of missing values and breaks in the record, number of values failing the QC checks, and percentages indicating how complete the data record is

The 11th Conference on Applied Climatology