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Changes in daily extreme temperatures have been identified in many studies conducted at local, regional or global scales. For Romanian territory, only little research on this issue was done. In this article, the extra-Carpathians regions of Romania located southward and eastward from the Carpathians Chain were considered. This study is focused on analyzing daily extreme temperature trends at a regional scale (eastern, southern and southeastern regions of Romania) across 50 years . Data sets of daily minimum and maximum temperature recorded in 14 weather stations were analyzed. The main goal was to find changes in extreme daily temperatures using a set of 20 indices adopted from the core indices developed by ETCCDMI with appropriate modifications to suit to the analyzed territory. The main results suggest that regional temperature trends at the scale of extra-Carpathians areas of Romania are similar to those calculated for global and European continental scales; the climate has become warmer during the last decades. It has been identified that both extreme daily maximum and minimum temperatures have increased in the analyzed areas. For all the indices related to hot temperature most trends are significantly positive. The strongest increase was detected for hot related extremes such as summer days and tropical nights as well as for maximum values of maximum and minimum daily temperatures. For indices related to cold there are different sign slopes, but negative slopes prevail, especially for number of days under a defined threshold. This is also an evidence of the important warming in the area. Generally, it was found that the daily maximum temperature is getting more extreme, whereas the minimum is getting less extreme. Copyright  2012 Royal Meteorological Society KEY WORDS daily extreme temperature indices; daily maximum and minimum temperatures; trend; Mann-Kendall test andSen's slope; extra-Carpathians areas of Romania

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Air temperature variability and trends in Romania were analysed using monthly, seasonal, and annual datasets. Temperature data of winter wheat season were also analysed. The Mann-Kendall test, Sen's slope estimate, the sequential version of the Mann-Kendall test, the Pettitt test and spatial and temporal hierarchical cluster analyses were used. First, the datasets were checked for changing points. The 106-year period was divided into two long periods of 100 years each to verify the importance of a very short interval in changing of general trends; after that it was divided into three shorter periods of 35-36 years each. The main conclusions are as follows: the 6 years making up the difference between the two long periods are very important in the context of the recent global warming; the three shorter periods analysis indicate some fluctuations rather than continuous warming. The latest short period is the most relevant for global warming. Spatial hierarchical cluster analysis indicated the existence of two distinctive groups. One of them, which includes stations in the south-east part of the country, seems to be influenced by the Black Sea surface temperature. Temporal hierarchical cluster analysis reveals that annual data series have the closest relation with the summer data series. Further, the impact of temperature changes on winter wheat phenology was determined using a phenology simulation performed with the model from the Decision Support System for Agrotechnology Transfer v. 4.0.2.0 platform. Earlier occurrences of anthesis and maturity were noticed for several regions in the country.

In this paper, we investigated changes in heat and cold waves in Romania over the period 1961–2015 by employing a new and superior approach. It consists in using excess heat factor to identify heat waves and excess cold factor to identify cold waves. Five indices were calculated and then analysed for both heat waves and cold waves resulting in a set of ten indices. Indices for heat waves were analysed for the extended summer season (May–September), whereas those for cold waves were assessed for the extended winter (November–March). The intensity threshold was set to be equal or above the 90th percentile for heat waves, and equal or below the 10th percentile for cold waves, while the duration threshold for both heat and cold waves was of at least three consecutive days. For a better comparison with other studies conducted worldwide, and to get more information from the data sets, the percentile thresholds for heat and cold waves identification were calculated based on three reference periods: 1961–1990, 1971–2000, and 1981–2010. Trends were calculated using ordinary least square method, whereas statistical significance was assessed by the t‐test. The main results indicated that changes are more substantial in the case of indices calculated based on excess heat factor compared to those based on excess cold factor, suggesting that the warming process is more reflected in heat waves rather than in cold waves. Thus, heat waves became more frequent, longer, and more intense, while cold waves became less frequent, but more intense. When the reference period for percentile threshold calculation was changed from the earliest to the most recent ones, the frequency of increasing and significant increasing trends decreased for some of the heat wave indices, while for the cold wave indices the significant downward trends increased.

Abstract:Heat waves and warm spells are extreme meteorological events that generate a significant number of casualties in temperate regions, as well as outside of temperate regions. For the purpose of this paper, heat waves and warm spells were identified based on daily maximum temperatures recorded at 27 weather stations located in Romania over a 55-year period . The intensity threshold was the 90th percentile, and the length of an event was of minimum three consecutive days. We analyzed 111 heat wave and warm spell events totaling 423 days. The classification of synoptic conditions was based on daily reanalysis at three geopotential levels and on the online version of a backward trajectories model. The main findings are that there are two major types of genetic conditions. These were identified as: (i) radiative heat waves and warm spells (type A) generated by warming the air mass due to high amounts of radiation which was found dominant in warm season; and (ii) advective heat waves and warm spells (type B) generated mainly by warm air mass advection which prevails in winter and transition seasons. These major types consist of two and three sub-types, respectively. The results could become a useful tool for weather forecasters in order to better predict the occurrence of heat waves and warm spells.