87th AMS Annual Meeting

Thursday, 18 January 2007: 11:15 AM
Observer Bias in Daily Precipitation Measurements at United States Cooperative Network Stations
206A (Henry B. Gonzalez Convention Center)
Christopher Daly, Oregon State Univ., Corvallis, OR; and W. Gibson, G. H. Taylor, M. Doggett, and J. Smith
Poster PDF (1.5 MB)
The Cooperative Observer Program (COOP), established over one hundred years ago, has become the backbone of temperature and precipitation data that characterize means, trends, and extremes in US climate. However, significant and widespread biases in the way COOP observers measure daily precipitation have been discovered. These include: (1) Under-reporting of daily precipitation amounts of less than 0.05 inches (1.27 mm), and (2) over-reporting of daily precipitation amounts divisible by five and/or ten hundredths of an inch, i.e., 0.1, 0.25, 0.30 inches, etc. (2.54, 6.35, 7.62 mm, etc). Observer biases were found to be highly variable in space and time, which has serious implications for the spatial and temporal trends and variations of commonly-used precipitation statistics. In addition, it was found that few COOP stations had sufficiently complete data to allow the calculation of stable precipitation statistics for a daily weather simulation model. Out of more than 12,000 COOP stations nationally, only 784 passed data completeness and observer bias screening tests for the climatological period 1971-2000. Of the 1221 COOP stations selected for the US Historical Climate Network (USHCN), which provides much of the country's official data on climate trends and variability over the past century, only 218 stations passed these tests. Even the most effective training materials are not likely to eliminate observer bias. The ultimate solution to observer bias is to automate the COOP precipitation measurement system. In the meantime, further analyses are needed to better quantify and characterize observer bias, and to develop methods for dealing with its effects.

Supplementary URL: http://mistral.oce.orst.edu/bias/