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A method to infer time of observation at US Cooperative Observer Network stations using model analyses
Author(s) -
Belcher Brian N.,
DeGaetano Arthur T.
Publication year - 2005
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.1183
Subject(s) - morning , midnight , observer (physics) , context (archaeology) , statistics , climatology , environmental science , meteorology , time of day , estimation , scale (ratio) , computer science , mathematics , geography , cartography , medicine , zoology , physics , management , archaeology , quantum mechanics , astronomy , geology , economics , biology
A method to estimate the time of observation employed at US Cooperative Observer Network stations has been developed using rapid update cycle model analyses. This method uses the day‐to‐day variability in model temperature biases to estimate observation schedules on a time scale of weeks, making it ideal for use in ‘real‐time’ applications. Observation time estimates from a two‐category system (morning and ‘non‐morning’) and three‐category system (morning, afternoon and midnight) were both evaluated. The performance of the two‐category system was compared with existing techniques that employ this system on monthly time scales. The results were comparable, showing dependence on season and climatological characteristics, but reveal an ability to reach high levels of accuracy (>90% of stations have observation schedules correctly estimated) over similar time periods (10–50 days). To our knowledge, the evaluation of three‐category estimation performance for the time scales investigated has not been documented. Accuracy remained high for morning and midnight stations (>90%), and decreased for stations with afternoon observation schedules (85–65%). Additionally, the three‐category estimation technique was extended to four categories in order to identify observers who shift temperature records temporally. The accuracy of detecting shifted records within the context of the four‐category estimation technique was comparable to the performance of the three‐category system, with shifted observations correctly identified more than 75% of the time in most cases. Copyright © 2005 Royal Meteorological Society