•GDD models proved to be slightly better than multiple linear regression models.•GDD models with base temperature 5 °C proved to be the best for budburst.•GDD with base temperature of 10 °C proved to ...be the best for other stages.•These models could be coupled with climate models for predction in future changes.
In recent decades, there have been significant changes in temperature and precipitation, as well as in the occurrence of phenological stages of the grapevine in most wine-growing regions around the world. These changes are not the same for each variety, nor in all locations. Due to the vulnerability of the viticulture sector, including the possible losses in production in the current winegrowing areas, as well as the planting of vineyards in new areas, it is of great importance to examine the trends in the occurrence of individual stages and to link them as successfully as possible with changes in meteorological parameters. The simplest approach to this is using agrometeorological indices (e.g., Growing degree day, GDD) which can determine the possibility of growing a certain variety. There is also the possibility of developing and testing simple statistical phenological models that serve to predict the occurrence of phenological stages. Four such models were tested for the prediction of four phenological stages (budburst, flowering, veraison, and harvest) for four grape varieties ('Graševina', 'Chardonnay', 'Merlot', and 'Plavac mali') in Croatia. The first two models are commonly used GDD models with a temperature base of 10 °C or 5 °C, and thresholds necessary for phenological stage to start depending on variety or variety and location. The other two models are based on the determination of the best multi-linear regression using as predictors monthly and multi-month averages of minimum temperature, maximum temperature, mean temperature, and total precipitation. The increase in temperature index values from the 1990s to today is particularly significant. Statistical phenological models also proved to be a good indicator of the occurrence of individual phenological stages. GDD models proved to be somewhat better in prediction, GDD models that use a temperature of 5 °C as a base proved to be better for predicting budburst, those that use a base of 10 °C proved to be better for the other stages and particularly for flowering (with agreement index d up to 0.8 and root mean square error of prediction RMSE from 5 to 10 days). Linear regression that uses temperature as a predictor and the same equation regardless of location proved to be very good in predicting the harvest of autochthonous varieties ('Graševina' and 'Plavac mali') with low RMSE (up to 10 days). The presented results indicate that these models could be applied to future scenarios and with that help to make decisions in the wine sector in Croatia and worldwide.
•Minimum temperature in meteorological shelter that best describes frost is 2.5 °C.•Condition that the dew point temperature is less than 0 °C reduces false alarms.•Tmin threshold of 3 °C and Td of ...0 °C gave the best results for frost probability.•These method could be coupled with climate models for frost prediction in future.
Due to the earlier start of phenological cycles among fruit trees, frost represents one of the most notable hazards for agriculture. There is no unique method for forecasting frost, and different methods for describing frost under present and future climate conditions can be found in the literature. Often these methods are applied in a certain area without prior control. Five such frost detection methods were assessed in Croatia. In addition, five new frost estimation methods that rely on measurements of the daily minimum temperature (Tmin) and dew point temperature (Td), calculated using Tmin, relative humidity (RH), and the Clausius Clapeyron equation, as well as machine learning, were introduced in this research and compared to other methods. Overall, the frost prediction results showed that the minimum temperature measured at the meteorological shelter that best describes frost formation is 2.5 °C. Additionally, the condition whereby the dew point temperature is lower than 0 °C results in a reduction in the proportion of false alarms. Methods that introduce additional variables outperform those that rely solely on the temperature. The method in which days are classified as exhibiting frost using a Tmin threshold of 3 °C and Td threshold of 0 °C (ased on Tmin and daily mean RH) could capture the most frost days with the smallest error. This method is the most suited for continental areas with a high probability of detection (POD > 0.9) and a probability of false detection (POFD < 0.3) which conforms with the history of frost occurrence in this type of climate zone. These findings were corroborated by signal detection theory analysis, yielding high values of the accuracy index and beta values below 1, indicating a bias toward estimating frost events (with high hit rate values and high false alarm values). This method could be used to identify geographic areas most susceptible to frost formation and, if coupled with a climate model, enable the study of the frost vulnerability due to climate change.
This study analyzed the hail climatology across Croatia using data from a national network of 199 stations, which recorded a total of 8551 hail cases. The spatio-temporal analyses were made for: (i) ...several different periods, (ii) five additional 121 year long data series and (iii) investigation of the connection between weather types and occurrence of hail. Due to high complexity of Croatian territory (which includes the northern lowland, the central mountainous area and the long Adriatic coast with numerous islands and the Istrian peninsula), the spatial and temporal variability of hail as well as the limited number of hail data, three types of stations were defined. The types represent sets of stations with similar annual cycles of hail occurrence. Trend analysis using Mann–Kendall trend significance tests with Theil–Sen trend estimates was performed for three periods: from 1900 to 2020, from 1964 to 2019, and from 1995 to 2019. The first two periods showed a negative and significant trend in the number of hail days, while the most recent one, 25-year-long trend showed a change in sign toward a positive but not significant trend.
The northernmost parts of the coast (i.e., inner Istria) and lowland of Croatia had greater hail activity during summer. In contrast, along the southern and central Croatian coast, the highest hail activity was present in the colder part of the year. There was also a transitional area located in between, that recorded the most hail in spring and fall. Diurnal cycle of hail showed a shift in the daily maximum from morning to afternoon hours from the coast toward Croatian lowland.
The coastal part of Croatia generally recorded higher hail frequencies than the continental part. The climatology of hail duration revealed a log-normal distribution pattern, further suggesting that most hail cases last between 1 and 5 min with peek duration of about 4 min. The most dominant air masses (over 80% of time) responsible for hail come from the SW, W and NW directions, and 83% of hail is associated with cyclonic influence in the region.
•Negative trend of hail is observed on the 121 and 55 year long time series.•Three different patterns of annual and diurnal cycle were identified.•Hail duration in Croatia follows log-normal distribution.•In Croatia 60% of hail cases is related to southwesterly synoptic flow.
Since changes in temperature and precipitation have different effects on (a) all developmental stages of grapevines in most of the wine regions worldwide (i.e., on their phenological characteristics) ...and (b) different varieties, a comprehensive database of bioclimatic indices has been calculated and analysed for Croatian wine producing regions. The database consists of the average growing season temperature, growing degree‐days, Huglin index, dryness index and cool night index that are based on all available meteorological measurements as well as the outputs of regional climate models (RCMs) from the EURO‐CORDEX database. The horizontal grid spacing of 0.11° from the RCM ensembles enabled a fine‐scale determination of bioclimatic indices for the present and future climate in Croatia. In addition, statistical analyses (standard statistical parameters and Bayesian method) were carried out to examine trends in sugar content, total acidity and date of harvest. Calculations were performed for the present and future climate on the basis of data from seven selected vineyards/wineries and four varieties (‘Graševina’, ‘Plavac mali’, ‘Chardonnay’ and ‘Merlot’). The results show whether the part of Croatia that is suitable for grape cultivation in the present climate will continue to be favourable in the future within the Mediterranean area. In general, projections suggest further warming and drying of the climate in Croatia and an earlier harvest, with some variations among varieties that show latitude dependence. Projections for the future climate also suggest that the existing viticultural zoning will be much less adequate for the Croatian territory because it reduces the economically sustainable production of wine in certain areas.
Spatial distributions of temperature‐based bioclimatic indices (e.g., growing degree‐days GDD) for high‐end climate change scenarios are pointing to further warming in the period 2041–2070. Differences between the two periods P2 (2041–2070) and P0 (1971–2000) clearly show that some indices in certain regions will likely cross into higher (warmer) classes within the index scale. All grape varieties examined indicated an increase in the number of earlier harvests and a reduction in the number of later harvests, regardless of location.
The aim of this work was to classifie vine growing regions of Croatia using bioclimatic indices. For the analysis of climatic conditions, linear trends of bioclimatic indices were determined using ...meteorological observations for all avaliable climatological stations located in vine growing regions of Croatia. Analysis were performed for two different climatological periods: 1961-1990 and 1988-2017. Four commonly used bioclimatic indices were determined: the Winkler index, the Huglin index, Cool night index and Growing season average temperature.
U ovom radu analizirana je vremenska situacija za vrijeme dvaju šumskih požara na poluotoku Pelješcu. Požari su namjerno izazvani u noći s 20. na 21. srpanj 2015. Cilj je rada proučiti vremensku ...situaciju koja je, uz ljudski čimbenik, dovela do početka požara. Analizirani meteorološki podaci s najbliže glavne meteorološke postaje Ploče pokazali su da je srpanj 2015. bio najtopliji mjesec u razdoblju 1981.–2014. U srpnju je bilo 30 vrućih dana što je dvostruko više od prosjeka. Izostanak oborina i ekstremno topao srpanj pridonijeli su dolasku najgoreg mogućeg požara - požara krošnji. Produkti modela ALADIN za vrijeme šumskog požara su pokazali malo sniženi tlak zraka nad južnim Jadranom, a topao zrak se protezao sve do 1 km u vis. Vrijeme je bilo pretežno vedro, na sam dan izbijanja požara izmjerena je u Kuni i apsolutna vrijednost temperature 38.8 °C, a i idućih se dana maksimalna temperatura nije spuštala ispod 30°C na Pelješcu. Relativna vlažnost zraka tijekom dana najčešće je iznosila oko 40%. U noći kada su požari podmetnuti vjetar je bio slab. Indeks meteorološke opasnosti od šumskog požara FWI tijekom svih dana požara bio je vrlo velik, ali to je i očekivano za vrijeme sezone požara. Dugotrajno suho i vrlo vruće vrijeme koje je prethodilo šumskim požarima te vrlo strmi teren poluotoka Pelješca su pogodovali vrlo brzom širenju požara, otežavali gašenje požara što je ugrozilo ljudske živote i stambene objekte.
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