Rebetez, Martine

2015-1-3, Rebetez, Martine, Renaud, Valentine, von Arx, Georg, Dobbertin, Matthias

2013, von Arx, Georg, Dobbertin, Matthias, Rebetez, Martine

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.

2012, von Arx, Georg, Dobbertin, Matthias, Rebetez, Martine

Forest canopy generally moderates below-canopy air temperature and relative humidity and thus creates a specific microclimate for tree seedling growth. Climate change will alter the moderating capacity, which may render the below-canopy conditions unsuitable for recruitment of the hitherto dominant tree species. We assigned long-term meteorological data (1997-2010) recorded inside and outside of 14 different forest ecosystems in Switzerland to three forest types (broadleaved, non-pine conifer, pine), two altitudinal levels (low, high), the four seasons and general weather situations (normal, hot/dry, cold/wet) to compare moderating capacity of each of these classifiers. Our results confirmed a general moderating effect of canopy on below-canopy microclimate with a decrease of daily maximum air temperature of up to 5.1 degrees C (overall average: 1.8 degrees C) and an increase of daily minimum relative humidity of up to 12.4% (overall average: 5.1%) in the long-term average, respectively. Broadleaved and non-pine conifer forests moderated daytime microclimate about twice as much as pine forests, while at nighttime considerably less cooling down and even negative effects on levels of relative humidity compared to the open area were recorded at the pine forest sites. Moderating capacity was stronger at low altitude than at high altitude. It was strongest during the growing season, particularly in summer, and depended in a complex way on the general weather situation. Deviations from the general seasonal and weather condition patterns most likely occurred when soil moisture pools were depleted. Despite the moderating capacity, below-canopy microclimate did not lag behind open area microclimate. Based on our results we conclude that natural recruitment in pine forests and high-altitude forests may respond most sensitively to climate change. (c) 2012 Elsevier B.V. All rights reserved.