Differences in wind speeds according to measured and homogenized series in the Czech Republic, 1961–2015

Abstract

Non-meteorological factors may bias wind speed measurements in a number of ways, among them the types of instruments used, their calibration and standards of maintenance, station relocations, and changes in the physical surroundings of a given station. Moreover, homogenisation of series of such measurements is more complicated than that of other climatic variables. This contribution uses figures from the Czech Republic as an example to demonstrate that measured (raw) data may produce different results in mean daily wind speeds from those acquired in homogenous series. A basic set of measurements taken in 1961-2015 at 178 meteorological stations was quality-checked and then homogenized using the Standard Normal Homogeneity test (SNHT) and the Maronna-Yohai test. Subsequent analyses were based on homogenized series from 119 stations. Station relocations and automation of wind speed measurements were identified as the most important sources of break-points in series of mean daily wind speeds. Generally lower mean wind speeds (as well as wind speed variability) were obtained from homogenous series in comparison with measured data, with reflections also found in their spatial distribution around the territory of the Czech Republic. Statistically significant decreasing linear trends calculated from measured and homogenized daily wind speed series from 119 stations confirm the existence of wind stilling as a typical feature of land mid-latitudes in recent decades. However, trends from measured data are highly overestimated compared with those from homogenized series.

Assess hydrological responses to a warming climate at the Lysina Critical Zone Observatory in Central Europe

“…In contrast, in the summer it will stay similar or will be higher. A statistically significant decrease is observed in the wind speed over the past years in the Czech Republic (Zahradníček et al, 2019). In the future climate no trend of wind speed is predicted by RCM models (Brázdil et al, 2019).…”

The Influence of the Atlantic Multidecadal Oscillation on the Choco Low-Level Jet and Precipitation in Colombia

“…Following previous suggestion that a combination of statistical methods is more effective in assessing inhomogeneities [64,65], we used three homogeneity tests: (1) the nonparametric Pettitt test [66] to seek change points along the time series, estimating the p-values using Monte Carlo resampling, (2) the Buishand range test [67], and (3) the Standard Normal Homogeneity Test (SNHT) [68,69]. These tests were extensively used to detect homogeneity in historical series of hydrometeorological variables [70][71][72][73][74], and have some common features, but also some differences. Buishand range and Pettit tests detect interruptions in the middle of a time series, while SNHT, near the beginning and end of a series [75].…”

Circulation and Climate Variability in the Czech Republic between 1961 and 2020: A Comparison of Changes for Two “Normal” Periods

“…The homogenisation procedure of analysed climatic variables uses ProClimDB and An-Clim software [19], based on broad practical experience with homogenisation (e.g., [20][21][22]). Because detailed descriptions of the whole procedure are already covered in several papers with applications to temperature [11,12], precipitation [10], and wind speed [9,23], only some basic steps of the homogenisation procedure are addressed below:…”