2014
DOI: 10.1002/joc.4059
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Climate of the Carpathian Region in the period 1961-2010: climatologies and trends of 10 variables

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Cited by 189 publications
(166 citation statements)
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“…Moreover, depending on the site, significant shifts in P between months agree in terms of direction, but vary in size ( Table 3), indicating that local factors play a role in the resulting change [22]. Hence, it seems not surprising that significant linear trends in annual and seasonal area precipitation for the Carpathian region are (currently) absent, as shown in [6].…”
Section: Discussionmentioning
confidence: 94%
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“…Moreover, depending on the site, significant shifts in P between months agree in terms of direction, but vary in size ( Table 3), indicating that local factors play a role in the resulting change [22]. Hence, it seems not surprising that significant linear trends in annual and seasonal area precipitation for the Carpathian region are (currently) absent, as shown in [6].…”
Section: Discussionmentioning
confidence: 94%
“…However, on the basis of regional climate simulations at a spatial resolution of 25 km, projected 21st century changes (2070-2099 versus 1970-1999) in Alpine precipitation include a decrease in the frequency of wet days in the summer accompanied by an increase in mean precipitation in the winter [5]. Concerning the Carpathian region, with its highest range (Tatra Mountains), the identified significant trend in annual mean surface temperature representing the entire area was found to be increasing, with a rate of change of 0.27 • C per decade ; and for the period since 1981, a higher warming rate of 0.51 per decade has been identified [6]. Wind speed was found to decrease in every season, while relative sunshine duration increased.…”
Section: Introductionmentioning
confidence: 86%
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“…In this way, statistical correction models can be equipped with more spatial information compared to those using merely local meteorological factors. While weather classification has been widely used in many fields, such as climate analysis [24][25][26], wind reconstruction [27] and weather prediction [28,29], it has not been conventionally applied or considered in the wind energy field for the forecast bias correction.…”
Section: Introductionmentioning
confidence: 99%