Vol. 128, No. 1 * Pages 1–141 * January - March 2024

Microclimate has a substantial impact on plant composition, survival, and growth, as well as ecosystem processes. Although microclimatic conditions in anthropogenically fragmented ecosystems have received considerable scientific attention, they are understudied in naturally fragmented ecosystems, including forest-steppes. In addition, earlier investigations in these mosaics only measured microclimate parameters for a very short period (i.e., 24 hours on a single summer day). In the present study, the long-term microclimatic conditions were described in multiple habitat types, both woody and non-woody, in a sandy forest-steppe ecosystem in the Kiskunság, central Hungary. The aim of this study was to answer (1) how air humidity and temperature conditions differ among the studied habitats during the growing season and (2) which habitats are more stressed to vegetation growth regarding vapor pressure deficit (VPD). Wireless sensors recording air temperature and humidity values were used to monitor microclimatic parameters. VPD values were calculated based on the obtained air temperature and humidity, and two thresholds at 1.2 and 3.0 kPa were defined. To compare mean air temperature and humidity variables, as well as above-threshold VPD rate among habitat types, general linear models were used. Our results indicated that open grasslands were the warmest and driest habitats. Among woody habitats, south-facing edges had the harshest microclimatic conditions. The current work also found that small forest patches and larger forest patches had similar air temperature and humidity variables. Regarding VPD, open grasslands were the most stressed for vegetation growth from May to October. During the summer season, forest patches had a small moderating effect at the limiting threshold of 1.2 kPa VPD, but a stronger moderating effect at the 3.0 kPa threshold. With ongoing climate change, this role of forest patches is expected to become increasingly important in forest-steppes. Therefore, it is suggested that the remaining near-natural forest stands in sandy forest-grassland ecosystems should be prioritized for protection, and that scattered trees or groups of trees of native species should be established in extensive treeless grasslands.

The subject of the study was the effect of teleconnection patterns on cloudiness in Poland in the period 1990–2020. The analysis was conducted based on daily cloudiness values from 34 measurement stations of Institute of Meteorology and Water Management - National Research Institute and monthly North Atlantic Oscillation (NAO) and Scandinavia (SCAND) indices from the collection of Climate Prediction Center (CPC). The course of cloudiness values in winter in the multiannual period was analyzed together with its averaged spatial distrubution for the entire winter and for particular winter months. Next, the coefficient of correlation of cloudiness with a given teleconnection pattern index was calculated. The analysis also covered cloudiness in the positive and negative teleconnection phases. The results confirm a variable course and increasing trend of winter cloudiness in Poland. The average cloudiness reached 76% in the studied multiannual period. The correlation coefficient for the North Atlantic Oscillation primarily adopted negative values, and positive for the Scandinavian circulation. The strongest correlation between the teleconnection pattern and cloudiness was observed in February for NAO and in December for SCAND. Cloudiness showed no considerable differences between the positive and negative teleconnection phases.

Soil temperature is the main factor in determining the germination of maize seeds and the emergence time of the crop. It controls the rate of phenological development while the meristem is underground, which is until the V6 (six leaf collar) stage of maize. The research performed by the authors aimed to model maize seedbed temperatures at sowing depth (soil temperature at 5 cm depth) during the sowing-emergence-early development period. The research is based on measurements in ploughed plots of the maize experiments at the Látókép Experiment Site of the University of Debrecen (Eastern Hungary) in two growing seasons of 2021–2022. Two types of empirical models were established, a multilinear regression model (M1) and a dynamic-empirical model (M2), where the daily increase and decrease of soil temperature are determined by multilinear regression. Candidates for input variables for both models were various, easily available daily meteorological parameters. M2 model performed better than M1 when applied to an independent database of 2022. This is particularly valid for the maximum and minimum soil temperatures. It was found that both M1 and M2 can be used to predict the soil temperature of the maize seedbed before shading by the plants. For daily mean temperature, M1 and M2 give a similarly good estimation, while the dynamic-empirical model has to be preferred for the maximum and minimum temperatures. M2, which is based on daily temperature, global radiation and wind speed data, predicts the daily mean (RMSE = 1.4 °C), maximum (RMSE = 2.2 °C), and minimum (RMSE = 1.6 °C) of seedbed temperature not worse than many earlier soil temperature models do, even hybrid or mechanistic ones with a large number of parameters.

In the present study, four global climate models MRI-ESM2-0, IPSL-CM6A-LR, CanESM5, and GFDL-ESM4 from the set of CMIP6 models are assessed to select the best model and determine the effects of climate change on temperature and precipitation parameters under three shared socioeconomic pathway scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the base period (1988–2017) and a future period (2020–2049) in the Samalghan basin. Statistical measures such as mean absolute error, root mean square error, mean bias error are applied to test the models, and the correlation coefficient is used to compare the results of the historical period of the models with the observational data of the selected stations. Taking the obtained results into account, the global climatic model IPSL-CM6A-LR is chosen to study the trend of temperature and precipitation changes in the future period under scenarios. The results of this study indicate an increasing trend of the average annual precipitation in the desied period compared to the base period for the SSP1-2.6 and SSP2-4.5 scenarios at all stations. Also, it increases in the SSP5-8.5 scenario for all stations except Besh Ghardash, Hesegah and Darkesh stations. The predictions of temperature show an increase in the minimum and maximum temperature values under all scenarios compared to the base period.

Studying the spatiotemporal precipitation characteristics in North Macedonia (1951–2010) is important as no spatially concurrent precipitation changes across the Balkan Peninsula have been identified. North Macedonia lies at the intersection between Mediterranean and continental climate zones and an improved understanding might help to better understand the regional precipitation patterns. The analysis shows a spatially consistent, high inter-annual variability, which makes trend detection difficult. Statistically significant decreasing trends were only found in seasonal precipitation at three stations. Changes in all other precipitation series were non-significant. Trends in winter, spring, and at annual scale are generally decreasing, whereas in summer are increasing. To better understand possible mechanisms behind the observed variability and change, correlations with the North Atlantic Ocsillation (NAO) were assessed. Significant and regionally concurrent correlations were detected. A strong correlation of the previous winter NAO-index with spring precipitation was found, which is valuable information for anticipatory water resources management in the region.

National parks in Serbia are sensitive to various types of natural hazards that are becoming more frequent and having a significant negative impact on the environment. The present study examines the effects of weather conditions on wildfires in the national parks (NPs) Tara, Djerdap, and Kopaonik using data from meteorological stations and applying climate indices based on air temperatures and precipitation. It examines the variability of fire occurrence dynamics, which depend on changes in the forest aridity index (FAI), the De Martonnearidity index (I_DM), and the Lang’s rain factor (AI_Lang) during the period 2005-2021.
The highest number of fire occurrences was recorded in NP Tara and NP Djerdap, and the lowest in NP Kopaonik. The risk of fire was greatest during September (27.5%) and August (18.1%), when air temperatures were high and precipitation was low. The fire season was longest in NP Djerdap (February-December) and NP Tara (March-November), and shortest in NP Kopaonik (April-August).
Due to the weak correlation between the annual number of fires and individual values of climate variables and climate indices, multiple linear regression (MLR) models were developed. The highest correlation and coefficient of determination were obtained using temperature, precipitation, I_DM, and AI_Lang as predictors for NP Tara and NP Djerdap but not NP Kopaonik, where only three wildfires were recorded.

Increasing thermal risk in cities is endangering the health and well-being of urban population and is driven by climate change and intensive urbanization. Therefore, if we plan to enlarge the capacities of cities to be more climate resilient in the 21st century, more detailed monitoring of urban climate on local and micro scales is needed. For this research we performed two microclimate measurement campaigns in urban area of Belgrade, during hot summer days in 2021. In total, five measurement sites were chosen in different urban designs and different local climate zones (LCZs). For thermal monitoring (air temperature – Ta and globe temperature – Tg) the Kestrel heat stress tracker sensor with 1-min measurement resolution was used, but we used 10-min average values. Obtained results showed distinct thermal differences (up to 7 °C on average) between densely built-up areas and green areas. Differences between built-up LCZs are lower with values from 2 to 4 °C. Important part of this research was microclimate monitoring on sites within the same LCZ (intra-LCZ variability). Results showed that shadows and short- and longwave radiation play a paramount role in thermal variability. Direct and reflected radiations on one measurement site increased Ta up to 6 °C and Tg up to 12 °C when compared to other measurement site (in a similar urban design), which was in the shadow.