Comparison between cooperative observer data and co-located meteorological tower network in North Carolina

Technology has brought about radical changes in the way people use weather and agricultural data. Enhanced data collection provides agencies and individuals with the opportunity to improve among others weather forecasting, drought management, agricultural research, and climatology. Automation of weather and agricultural observation stations provides accurate, timely dissemination of valuable data important for various applications. The objective of this study is to ensure that the data collected is both accurate and comparable to the traditional method for climatological archival purposes. It is necessary to determine the relationship between the two methods and identify any bias in either system to maximize the efficiency and precision of data collection. Using ten automated AgNet and cooperative observer stations in North Carolina, the relationships between the observations from the two systems are analyzed using statistical analysis. Linear regression techniques examine the correlation between the two systems. Results indicate that both systems are consistent and are reliable sources of data collection. Analysis of the comparison results suggest that the automated stations are sensitive to radiational effects but have less standard error than the conventional cooperative observations. The automated stations underestimated during low and very high rainfall events. A knowledge of the difference in the two data collection methods can provide more accurate information and eliminate known biases.