Detecting and correcting sensor drifts in long-term weather data
Georg Von Arx, Matthias Dobbertin & Martine Rebetez
Résumé |
Quality control of long-term monitoring data of thousands and
millions of individual records as present in meteorological data is
cumbersome. In such data series, sensor drifts, stalled values, and
scale shifts may occur and potentially result in flawed conclusions
if not noticed and handled properly. However, there is no
established standard procedure to perform quality control of
high-frequency meteorological data. In this paper, we outline a
procedure to remove sensor drift in high-frequency data series
using the example of 15-year-long sets of hourly relative humidity
(RH) data from 28 stations subdivided into 202 individual sensor
operation periods. The procedure involves basic quality control,
relative homogeneity testing, and drift removal. Significant sensor
drifts were observed in 40.6 % of all sensor operation periods. The
drifts varied between data series and depended in a complex,
usually inconsistent way on absolute RH values; within single
series for instance, a drift could be negative in the lower RH
range and positive in the upper RH range. Detrending changed RH
values by, on average, 1.96 %. For one fifth of the detrended data,
adjustments were 2.75 % and more of the measured value, and in one
tenth 4.75 % and more. Overall, drifts were strongest for RH values
close to 100 %. The detrending procedure proved to effectively
remove sensor drifts. The principles of the procedure also apply to
other meteorological parameters and more generally to any time
series of data for which comparable reference data are
available. |
Citation | von Arx, G., Dobbertin, M., & Rebetez, M. (2013). Detecting and correcting sensor drifts in long-term weather data. Environmental Monitoring and Assessment, 185(6), 4483-4489. |
Type | Article de périodique (Anglais) |
Date de publication | 2013 |
Nom du périodique | Environmental Monitoring and Assessment |
Volume | 185 |
Numéro | 6 |
Pages | 4483-4489 |