Spatial Accuracy of Climate Networks: A Case Study in Nebraska

Authors

Andrea J. Coop, University of Nebraska-LincolnFollow
Kenneth Hubbard, University of Nebraska-LincolnFollow
Martha Shulski, University of Nebraska–LincolnFollow
Jinsheng You, University of Nebraska-LincolnFollow
David B. Marx, University of Nebraska-LincolnFollow

Document Type

Article

Date of this Version

2014

Citation

Journal Of Applied Meteorology And Climatology, Volume 53, pp. 1932

Comments

Copyright 2014 American Meteorological Society

Abstract

Climate data are increasingly scrutinized for accuracy because of the need for reliable input for climaterelated decision making and assessments of climate change. Over the last 30 years, vast improvements to U.S. instrumentation, data collection, and station siting have created more accurate data. This study explores the spatial accuracy of daily maximum and minimum air temperature data in Nebraska networks, including the U.S. Historical Climatology Network (HCN), the Automated Weather Data Network (AWDN), and the more recent U.S. Climate Reference Network (CRN). The spatial structure of temperature variations at the earth’s surface is compared for timeframes 2005–09 for CRN and AWDN and 1985–2005 for AWDN and HCN. Individual root-mean-square errors between candidate station and surrounding stations were calculated and used to determine the spatial accuracy of the networks. This study demonstrated that in the 5-yr analysis CRN and AWDN were of high spatial accuracy. For the 21-yr analysis the AWDN proved to have higher spatial accuracy (smaller errors) than the HCN for both maximum and minimum air temperature and for all months. In addition, accuracy was generally higher in summer months and the subhumid area had higher accuracy than did the semiarid area. The findings of this study can be used for Nebraska as an estimate of the uncertainty associated with using a weather station’s data at a decision point some distance from the station.