Local climatic drivers of changes in phenology at a boreal-temperate ecotone in eastern North America

Ecosystems in biogeographical transition zones, or ecotones, tend to be highly sensitive to climate and can provide early indications of future change. To evaluate recent climatic changes and their impacts in a boreal-temperate ecotone in eastern North America, we analyzed ice phenology records (1975?C2007) for five lakes in the Adirondack Mountains of northern New York State. We observed rapidly decreasing trends of up to 21?days less ice cover, mostly due to later freeze-up and partially due to earlier break-up. To evaluate the local drivers of these lake ice changes, we modeled ice phenology based on local climate data, derived climatic predictors from the models, and evaluated trends in those predictors to determine which were responsible for observed changes in lake ice. November and December temperature and snow depth consistently predicted ice-in, and recent trends of warming and decreasing snow during these months were consistent with later ice formation. March and April temperature and snow depth consistently predicted ice-out, but the absence of trends in snow depth during these months, despite concurrent warming, resulted in much weaker trends for ice-out. Recent rates of warming in the Adirondacks are among the highest regionally, although with a different seasonality of changes (early winter > late winter) that is consistent with other lake ice records in the surrounding area. Projected future declines in snow cover could create positive feedbacks and accelerate current rates of ice loss due to warming. Climate sensitivity was greatest for the larger lakes in our study, including Wolf Lake, considered one of the most ecologically intact ??wilderness lakes?? in eastern North America. Our study provides further evidence of climate sensitivity of the boreal-temperate ecotone of eastern North America and points to emergent conservation challenges posed by climate change in legally protected yet vulnerable landscapes like the Adirondack Park.     

Changes in ice-season characteristics of a European Arctic lake from 1964 to 2008

The long-term ice record (from 1964 to 2008) of an Arctic lake in northern Europe (Lake Kilpisj?rvi) reveals the response of lake ice to climate change at local and regional scales. Average freeze-up and ice breakup occurred on 9 November and 19 June, respectively. The freeze-up has been significantly delayed at a rate of 2.3 d per decade from 1964 onward (P?<?0.05). No significant change has taken place in ice breakup. Annual average ice thickness has become smaller since the mid-1980s (P?<?0.05). Air temperature during the early ice season significantly affected the ice thickness. The freeze-up date exhibits the highest correlation with the 2-month average daily minimum air temperature centered at the end of October, while the ice breakup date exhibits the highest correlation with the 2-month average daily maximal air temperature centered in mid May. A 1°C increase in the surface air temperature corresponds to a freeze-up later by 3.4?days and an ice breakup earlier by 3.6?days. Snow cover is a critical factor in lake-ice climatology. For cumulative November to March precipitation of less than 0.13?m, the insulating effect of the snow dominated, while higher rates of precipitation favored thicker ice due to the formation of snow ice. Variations in ice records of Lake Kilpisj?rvi can serve as an indicator of climate variations across the northern Europe. The North Atlantic Oscillation (NAO) does not significantly affect the ice season there, although both the local air temperatures and winter precipitation contain a strong NAO signal.     

Estimation of relative humidity based on artificial neural network approach in the Aegean Region of Turkey

The aim of this study is to estimate the monthly mean relative humidity (MRH) values in the Aegean Region of Turkey with the help of the topographical and meteorological parameters based on artificial neural network (ANN) approach. The monthly MRH values were calculated from the measurement in the meteorological observing stations established in Izmir, Mugla, Aydin, Denizli, Usak, Manisa, Kutahya and Afyonkarahisar provinces between 2000 and 2006. Latitude, longitude, altitude, precipitation and months of the year were used in the input layer of the ANN network, while the MRH was used in output layer of the network. The ANN model was developed using MATLAB software, and then actual values were compared with those obtained by ANN and multi-linear regression methods. It seemed that the obtained values were in the acceptable error limits. It is concluded that the determination of relative humidity values is possible at any target point of the region where the measurement cannot be performed.     

Criteria for heat and cold wave duration indexes

Many areas of society are susceptible to the effects of extreme temperatures. Without an adequate definition of what constitutes heat and cold waves, it is impossible to assess either their changes in the past or their possible consequences for the future. The Intergovernmental Panel on Climate Change recommended criteria for heat wave duration indexes based on two arbitrarily defined constants. The principal weakness of this approach is that it does not yield comparable results for different geographical locations. This paper remedies the current lack of a meteorologically based definition of heat and cold waves and offers a preliminary test of its performance. Having previously shown that maximum daily temperature values follow normal frequency distribution, we derive statistical thresholds (e.g., below and above normal) from that distribution. These thresholds are thus climate specific and their change can be compared across geographical locations. These criteria are then tested on the homogeneous time series of maximum daily temperature observed for the period 1961–2008 with respect to three different geographical locations. The results obtained show an increase in the frequency of heat waves for the period 1991–2008 in comparison with the normal climatological period 1961–1990.     

Determination of surface layer parameters at the edge of a suburban area

Vertical wind and air temperature profile related parameters in the surface layer at the edge of suburban area of Zagreb (Croatia) have been considered. For that purpose, adopted Monin–Obukhov similarity theory and a set of observations of wind and air temperature at 2 and 10?m above ground, recorded in 2005, have been used. The root mean square differences (errors) principle has been used as a tool to estimate the effective roughness length as well as standard deviations of wind speed and wind gusts. The results of estimation are effective roughness lengths dependent on eight wind direction sectors unknown before. Gratefully to that achievement, representativeness of wind data at standard 10-m height can be clarified more deeply for an area of at least about 1?km in upwind direction from the observation site. Extrapolation of wind data for lower or higher levels from standard 10-m height are thus properly representative for a wider inhomogeneous suburban area and can be used as such in numerical models, flux and wind energy estimation, civil engineering, air pollution and climatological applications.     

Performance of ENSEMBLES regional climate models over Central Europe using various metrics

We show the evaluation of ENSEMBLES regional climate models (RCMs) driven by reanalysis ERA40 over a region centered at the Czech Republic. Attention is paid especially to the model ALADIN-CLIMATE/CZ, being used as the basis of the new climate change scenarios simulation for the Czech Republic. The validation criteria used here are based on monthly or seasonal mean air temperature and precipitation. We concentrate not only on spatiotemporal mean values but also on temporal standard deviation, inter-annual variability, the mean annual cycle, and the skill of the models to represent the observed spatial patterns of these quantities. Model ALADIN-CLIMATE/CZ performs quite well in comparison to the other RCMs; we find its performance satisfactory for further use for impact studies. However, it is also shown that the results of evaluation of the RCMs’ skill in simulating observed climate strongly depend on the criteria incorporated for the evaluation.     

Subarea characteristics of the long-range correlations and the index χ for daily temperature records over China

Daily temperature records including daily minimum, maximum, and average temperature from 190 meteorological stations over China during 1951–2000 are analyzed from two perspectives: (a) long-term persistence in direction of time varies, and (b) standard deviation in direction of amplitude varies. By employing the detrended fluctuation analysis (DFA), we find all the temperature records are long-term correlated, while the exponent α obtained from DFA varies from different districts of China due to different climate conditions, such as the southwest monsoon, subtropical high, northeast cold vortex, and the Tibetan plateau, etc. After we take the standard deviation into account, a new index χ?=?α?×?σ, which has been proposed recently, can be obtained. By further rescaling it as $ \chi = \overline \chi - {{1} \left/ {5} \right.} \times {\sigma_{{\overline \chi }}} $ , we find an obvious change of χ for these three kinds of time series, from which the whole China can be divided into two groups, which are comparatively consistent with dry/wet distributions in the south–north areas over China.     

The climate tourism potential of Alpine destinations using the example of Sonnblick, Rauris and Salzburg

The climate tourism potential of a region can be described by methods used in human biometeorology and applied climatology. Frequency analyses based on complex thermal bioclimatic indices (e.g. physiologically equivalent temperature) and diagrams of precipitation patterns based on thresholds offer new approaches of visualisation. An integral approach for tourism climatologic analyses is provided by the climate?Ctourism/transfer?Cinformation?Cscheme that also bases on frequency distributions of relevant factors and parameters which are important for a destination. The knowledge about the vertical variability of tourism climatologic factors is of high importance because of the several kinds of tourism activities affected by weather. The same holds for a quantification of extreme events like heat waves because of their possible effects on health and recreation over a year's course. The results show that the vertical gradient of bioclimatic and tourism-related parameters can be of value when developing strategies of adaption to climate change.