Frost Days Research Articles

Biogeographic distribution of bacterial, archaeal and methanogenic communities and their associations with methanogenic capacity in Chinese wetlands

Natural wetlands and anthropogenic paddy fields are the dominant biogenic sources of atmospheric methane emission which have been speculated as the most probable sources for the increase of post-2006 atmospheric methane. Regional differences in CH4 emission is possibly due to microbial biogeographic distribution. Here we collected soils from 19 wetlands from different regions in China. The methane production capacity (MPC) was measured for each soil samples and varied from 1.11 to 841.94mg/kg dry soil. High throughput sequencing was employed to investigate the diversity and composition of bacterial, archaeal and methanogenic communities. Similar biogeographic patterns for bacterial, archaeal and methanogenic communities along the latitudinal gradient were observed, and the biogeographic assemblies of different microbial groups were driven by concurrent factors, including edaphic variables (total organic carbon, total phosphorus and pH) and climatic variables (annual frost days, mean annual temperature, direct solar radiation and mean annual precipitation). MPC was significantly correlated with TOC concentration, and in addition, various functional taxa were positively correlated with MPC (P<0.05), for example, Sphingomonas, Syntrophomonas, Methanospirillum and Methanoregula, indicating their potential contributions in the methanogenic process, and many of them were fermentative bacteria and methanogens. Network analysis showed that some syntrophs, sulfate-reducers and methanogens were tightly co-occurred in one module, suggesting their involvements in cross-linked functional processes. Our study implicated both temperature and substrate availability altered the biogeographic patterns of microbial community as well as methane production potential in Chinese wetlands.

The Effects of Forest Area Changes on Extreme Temperature Indexes between the 1900s and 2010s in Heilongjiang Province, China

Land use and land cover changes (LUCC) are thought to be amongst the most important impacts exerted by humans on climate. However, relatively little research has been carried out so far on the effects of LUCC on extreme climate change other than on regional temperatures and precipitation. In this paper, we apply a regional weather research and forecasting (WRF) climate model using LUCC data from Heilongjiang Province, that was collected between the 1900s and 2010s, to explore how changes in forest cover influence extreme temperature indexes. Our selection of extreme high, low, and daily temperature indexes for analysis in this study enables the calculation of a five-year numerical integration trail with changing forest space. Results indicate that the total forested area of Heilongjiang Province decreased by 28% between the 1900s and 2010s. This decrease is most marked in the western, southwestern, and northeastern parts of the province. Our results also reveal a remarkable correlation between change in forested area and extreme high and low temperature indexes. Further analysis enabled us to determine that the key factor explaining increases in extreme high temperature indexes (i.e., calculated using the number of warm days, warm nights, as well as tropical nights, and summer days) is decreasing forest area; data also showed that this factor caused a decrease in extreme low temperature indexes (i.e., calculated using the number of cold days and cold nights, as well as frost days, and ice days) and an increase in the maximum value of daily minimum temperature. Spatial data demonstrated that there is a significant correlation between forest-to-farmland conversion and extreme temperature indexes throughout most of our study period. Spatial data demonstrated that there is a significant correlation between forest-to-farmland conversion and extreme temperature indexes throughout most of our study period. Positive correlations are also present between decreasing forest area, the more frequent occurrence of extreme high temperature events, and a rise in the maximum value of daily minimum temperature. At the same time, we found clear negative correlations between decreasing forest area and less frequent occurrence of extreme low temperature events.

Spatiotemporal and joint probability behavior of temperature extremes over the Himalayan region under changing climate

In this study, temperature extremes are analyzed for observed (1979–2005) and projected scenarios using three global climate models (GCMs) and their Representative Concentration Pathways (RCPs) based on Coupled Model Intercomparison Project Phase 5 (CMIP5) datasets, to investigate the spatio-temporal variations and possible changes in joint probability behavior of temperature extremes over North Sikkim Himalaya, India. Statistical downscaling model (SDSM) and copulas are applied to downscale the GCM outputs and to construct joint probability distribution of extremes, respectively. A set of ten climate extreme indices are selected to understand the inter-annual variability. Joint return period of extreme indices was calculated using six temperature extreme indices (based on days). Linear trends were estimated using Mann Kendall test with statistical significance and indicated widespread significant changes in temperature extremes. The significant changes in temperature extremes such as the temperature of warmest night and day have increased by 1.41 and 1.83 °C, and the temperature of coldest night and day has decreased by 3.61 and 4.83 °C, respectively, during 2006–2100 with the baseline period of 1979–2005. The spatial distribution of 5-year return periods and 10-year return periods is almost similar during 1979–2005. There is less co-occurrence of warm nights and days, but higher chance to co-occurrence of cool and warm nights in the same year during 2021–2100. The change in joint return periods under the RCP8.5 shows frequent co-occurrence of cool days and nights, ice and frost days, and cool and frost days than RCP2.6 and RCP4.5. This study implies that the warm days, cool days, warmer nights, and cool nights are decreased with increased warming intensity, which shows the overall warming trend over the North Sikkim Himalaya, India.

To what extent does high-resolution dynamical downscaling improve the representation of climatic extremes over an orographically complex terrain?

The Weather Research and Forecasting (WRF) model was applied as a downscaling tool over an orographically complex terrain along the Eastern Mediterranean. It was forced with the National Centers for Environment Prediction (NCEP) Final Analysis (FNL) (resolution 1°) for the years 2003 (a cold and wet year) and 2010 (a hot and dry year) and nested at sequential horizontal resolutions of 9 and 3 km. This study focuses on the assessment of simulated temperature and precipitation against data from an observational network over the study area. The observations comprise rain gauges and temperature stations with records of both daily average and/or maximum and minimum temperatures. The yearly precipitation validation shows that the WRF simulation has good agreement with the observed data, with a percentage bias of 3.80% in 2010. The errors in various extreme indices (such as minimum and maximum temperatures, number of hot or frost days, and rainfall intensity) were reduced by the downscaling, marking a large improvement over FNL analysis data in the description of temperature variability and extremes. These improvements support the benefits of dynamic downscaling over complex terrain, which can reduce the errors associated with mesoscales that are not resolved by the coarser driving model, and establish the skill of WRF for such downscaling.

Modeling monthly meteorological and agronomic frost days, based on minimum air temperature, in Center-Southern Brazil

Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F MET) and agronomic (F AGR) frost day models, based on minimum shelter air temperature (T MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T MN, once the frost day models were based on this variable. All T MN regression models were statistically significant (p < 0.001), presenting adjusted R 2 between 0.69 and 0.90. Center-Southern Brazil is mainly hit by frosts from mid-fall (April) to mid-spring (October). The period from November to March is considered as frost-free, being very rare a frost day within that period. Monthly F MET and F AGR presented significant sigmoidal relationships with T MN (p < 0.0001), with adjusted R 2 above of 0.82. The residuals of the frost day models were random, which means that the sigmoidal models performed quite well for interpreting the frost day variability throughout the study area. The highlands of Santa Catarina, Rio Grande do Sul, Sao Paulo, and Minas Gerais had in average more than 25 and 13 frosts per year, respectively, for F MET and F AGR. The F MET and F AGR maps developed in this study for Center-Southern Brazil is a useful tool for farmers, foresters, and researchers, since they contribute to reduce frost spatial and temporal uncertainty, helping in planning project for strategic purposes. Furthermore, the monthly F MET and F AGR maps for this Brazilian region are the first zoning of these variables for the country.

Does long-term warming affect C and N allocation in a Mediterranean shrubland ecosystem? Evidence from a 13C and 15N labeling field study

In the Mediterranean basin the effects of climate warming on ecosystem functioning will strongly depend on the warming intensity directly but also on its effects on evapotranspiration and nutrient cycling. Climate manipulation experiments under field conditions are a source of unique empirical evidence regarding climate-related modifications of biotic processes.A field night-time warming experiment, simulating the predicted near-future increase in ambient temperatures (+0.3 up to 1°C), was established in a Mediterranean shrub community located in Porto Conte (Italy) in 2001. After 11 years of continuous treatment, we labeled the dominant shrub Cistus monspeliensis with 13CO2 and studied the dynamics of the label allocation between aboveground and belowground pools and fluxes in warmed and ambient plots within 2 weeks of the chasing period. The interactions between C and N metabolism were assessed by parallel labeling of soil with K15NO3.Most of the assimilated 13C was respired by Cistus shoots (28–51%) within two weeks. Cistus under warming respired more 13C label and tended to allocate less 13C to leaves, branches and roots. The higher C and N content in microbial biomass in warming plots, combined with the higher N content in plant tissues and soil, evidenced a greater N mobilization in soil and a better nutrient status of the plants as compared to the ambient treatment. Acceleration of N cycling is probably responsible for higher respiratory C losses, but combined with the reduction in the number of frost days, should also positively affect plant photosynthetic performance.We conclude that, although Cistus plants are already growing in conditions close to their thermal optimum, long-term warming will positively affect the performance of this species, mainly by reducing the nutrient constraints. This positive effect will highly depend on the frequency and amount of rain events and their interactions with soil N content.

Changes in extreme temperature events over the Hindu Kush Himalaya during 1961–2015

This study uses the CMA (China Meteorological Administration) global land-surface daily air temperature dataset V1.0 (GLSATD V1.0) to analyze long-term changes in extreme temperature events over the Hindu Kush Himalaya (HKH) during 1961–2015. Results show there was a significant decrease in the number of extreme cold events (cold nights, cold days, and frost days) but a significant increase in the number of extreme warm events (warm nights, warm days, and summer days) over the entire HKH during 1961–2015. For percentile-based indices, trends of extreme events related to minimum temperature (Tmin) were greater in magnitude than those related to maximum temperature (Tmax). For absolute-value based indices, maximum Tmax, minimum Tmin, and summer days all show increasing trends, while frost days and the diurnal temperature range (DTR) show significant decreasing trends. In addition, there was a decrease in extreme cold events in most parts of east HKH, particularly in Southwest China and the Tibetan Plateau, while there was a general increase in extreme warm events over the entire HKH. Finally, the change in extreme cold events in the HKH appears to be more sensitive to elevation (with cold nights and cold days decreasing with elevation), whereas the change in warm extremes (warm nights, warm days, and maximum Tmax) shows no detectable relationship with elevation. Frost days and minimum Tmin also have a good relationship with elevation, and the trend in frost days decreases with an increase in elevation while the trend in minimum Tmin increases with an increase in elevation.

Spatial and temporal analysis of trends in extreme temperature indices in Iran over the period 1960–2014

ABSTRACTThe recent years have witnessed a rapid increase in frequency, severity, duration and geographical extent of extreme weather events. Having an area of 1 648 195 km2, Iran spans over a wide latitudinal range and enjoys a diverse terrain in terms of topography and elevation. The combination of this topographic complexity with the effects of extensive water bodies in the north and the south plays a major role in the distribution of temperature over this country. This study analysed the temporal trend of extreme temperature indices observed in 33 synoptic stations across Iran over the period 1960–2014, and then examined their relationship with elevation and latitude. The results showed a significant warming trend in extreme temperature indices of many stations, especially the indices that are based on daily minimum temperature. At low elevations, the trends of indices exhibited the features of a warming climate, but at higher elevations, these indices showed a mixture of positive and negative trends. Examining the relationship between the trends of indices and elevation showed that in the altitudinal band E1 [elevations lower than 23 m above sea level (ASL)], only the trend of growing season length is correlated with elevation; but in the altitudinal band E2 (elevations higher than 700 m ASL), elevation exhibited significant correlation with the trends of percentage of cool nights, frequency of frost days, diurnal temperature range, cold spell duration, percentage of warm nights and frequency of tropical nights. The analysis did not show any meaningful relationship between extreme temperature indices trends with latitude. Considering the high heterogeneity of the trends of indices and the limited number of stations with sufficient data, generalizing the results and predicting the wider trend patterns require further studies using a denser network of stations.

Temporal and spatial variations of extreme climatic events in Songnen Grassland, Northeast China during 1960-2014

Fourteen extreme climatic indices related with main regional meteorological disasters and vegetation growth were calculated based on daily data from 13 meteorological stations during 1960-2014 in Songnen Grassland, Northeast China. Then, the variation trend and the spatial and temporal patterns of climatic extreme events were analyzed by using regression analysis, break trend analy-sis, Mann-Kendall test, Sen's slope estimator and moving t-test method. The results indicated that summer days (SU25), warm days (TX90P), warm nights (TN90P) and warm spell duration (WSDI) representing extremely high temperatures showed significant increasing trends (P<0.05). Meanwhile, frost days (FD0), cold days (TX10P), cold nights (TN10P) and cold spell duration indicator (CSDI) representing extremely low temperatures showed obviously decreasing trends. The magnitudes of changes in cold indices (FD0, TX10P, TN10P and CSDI) were clearly greater than those of warm indices (SU25, TX90P, TN90P and WSDI), and that changes in night indices were larger than those of day indices. Regional climate warming trend was obvious from 1970 to 2009, and the most occurrences of the abrupt changes in these indices were identified in this period. The extreme precipitation indices did not show obvious trend, in general, SDII and CDD experienced a slightly decreasing trend while RX5D, R95P, PRCPTOT and CWD witnessed a mildly increasing trend. It may be concluded that regional climate changed towards warming and slightly wetting in Songnen Grassland. The most sensitive region for extreme temperature was distributed in the south and north region. Additionally, the extreme temperature indices showed clearly spatial difference between the south and the north. As for the spatial variations of extreme precipitation indices, the climate could be characterized by becoming wetter in northern region, and getting drier in southern region, especially in southwestern region with a high drought risk.

Biogeographical drivers of ragweed pollen concentrations in Europe

The drivers of spatial variation in ragweed pollen concentrations, contributing to severe allergic rhinitis and asthma, are poorly quantified. We analysed the spatiotemporal variability in 16-year (1995–2010) annual total (66 stations) and annual total (2010) (162 stations) ragweed pollen counts and 8 independent variables (start, end and duration of the ragweed pollen season, maximum daily and calendar day of the maximum daily ragweed pollen counts, last frost day in spring, first frost day in fall and duration of the frost-free period) for Europe (16 years, 1995–2010) as a function of geographical coordinates. Then annual total pollen counts, annual daily peak pollen counts and date of this peak were regressed against frost-related variables, daily mean temperatures and daily precipitation amounts. To achieve this, we assembled the largest ragweed pollen data set to date for Europe. The dependence of the annual total ragweed pollen counts and the eight independent variables against geographical coordinates clearly distinguishes the three highly infected areas: the Pannonian Plain, Western Lombardy and the Rhone-Alpes region. All the eight variables are sensitive to longitude through its temperature dependence. They are also sensitive to altitude, due to the progressively colder climate with increasing altitude. Both annual total pollen counts and the maximum daily pollen counts depend on the start and the duration of the ragweed pollen season. However, no significant changes were detected in either the eight independent variables as a function of increasing latitude. This is probably due to a mixed climate induced by strong geomorphological inhomogeneities in Europe.

Bayesian multi-model projections of extreme hydroclimatic events under RCPs scenarios

A Bayesian multi-model inference framework was used to assess the changes in the occurrence of extreme hydroclimatic events in four major river basins in China (i.e., Liaohe River Basin, Yellow River Basin, Yangtze River Basin, and Pearl River Basin) under RCP2.6, RCP4.5, and RCP8.5 scenarios using multiple global climate model projections from the IPCC Fifth Assessment Report. The results projected more summer days and fewer frost days in 2006–2099. The ensemble prediction shows the Pearl River Basin is projected to experience more summer days than other basins with the increasing trend of 16.3, 38.0, and 73.0 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively. Liaohe River Basin and Yellow River Basin are forecasted to become wetter and warmer with the co-occurrence of increases in summer days and wet days. Very heavy precipitation days (R20, daily precipitation ≥20 mm) are projected to increase in all basins. The R20 in the Yangtze River Basin are projected to have the highest change rate in 2006–2099 of 1.8, 2.5, and 3.8 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively.

Errata - Contemporary changes of thermal conditions in Poland, 1951-2015

Errata - The main subject of the research whose outcomes are presented in this paper is the spatial and temporal variability of thermal conditions in Poland during the period from 1951 to 2015. The analysis revealed the occurrence of symptoms indicating a systematic and sustained warming. Significant growth is observed in mean and extreme temperatures and their extreme percentiles, as well as in annual number of hot days, warm waves and their duration. In turn, downward trends are noted in series of the annual number of frost days, as well as in the number of cold waves and their duration. The results obtained confirm the thermal pattern determined for the whole region, especially for the southern part of the Baltic Sea Basin.

Consideration of land-use and land-cover changes in the projection of climate extremes over North America by the end of the twenty-first century

Changes in the essential climate extremes indices and surface variables for the end of the twenty-first century are assessed in this study based on two transient climate change simulations, with and without land-use and land-cover changes (LULCC), but identical atmospheric forcing. The two simulations are performed with the 5th generation of the Canadian Regional Climate Model (CRCM5) driven by the Canadian Earth System Model for the (2006–2100)-Representative Concentration Pathway 4.5 (RCP4.5) scenario. For the simulation with LULCC, land-cover data sets are taken from the global change assessment model (GCAM) representing the RCP4.5 scenario for the period 2006–2100. LULCC in RCP4.5 scenario suggest significant reduction in cultivated land (e.g. Canadian Prairies and Mississippi basin) due to afforestation. CRCM5 climate projections imply a general warming by the end of the twenty-first century, especially over the northern regions in winter. CRCM5 projects more warm spell-days per year over most areas of the continent, and implicitly more summer days and tropical nights at the expense of cold-spell, frost and ice days whose number is projected to decrease by up to 40% by the end of the twenty-first century with respect to the baseline period 1971–2000. Most land areas north of 45°N, in all seasons, as well as the southeastern United States in summer, exhibit increases in mean precipitation under the RCP4.5 scenario. In contrast, central parts of the continent in summer and much of Mexico in all seasons show reduced precipitation. In addition, large areas of North America exhibit changes of 10 to 40% (depending on the season and geographical location) in the number of heavy precipitation days. Results also suggest that the biogeophysical effects of LULCC on climate, assessed through differences between the two simulations, lead to warmer regional climates, especially in winter. The investigation of processes leading to this response shows high sensitivity of the results to changes in albedo as a response to LULCC. Overall, at the seasonal scale, results show that intense afforestation may contribute to an additional 25% of projected changes.

Physical controls on frost events in the central Andes of Peru using in situ observations and energy flux models

Radiative frosts are a major hazard to agriculture in the tropical Andes of Peru, but there are very few studies of their physical controls. In this study we focus on identifying and approximately estimating the effect that physical variables have on both the downward surface longwave flux (LW↓) and the minimum temperature (Tmin). Through a combination of case studies and statistical analysis of in situ data in the IGP Huancayo Observatory, we found that low cloud cover (CC), surface specific humidity (q), and soil moisture are key factors controlling the day-to-day variability of Tmin, which is more pronounced in the dry/cool season. We found that all frost days had q<7g/kg in the dry season and q<5g/kg in the wet season, although it should be emphasized that q covaries with CC and soil moisture.We successfully validated a numerical soil heat diffusion model with data from a field campaign in July 2010 and we used it, together with a radiative transfer model, to estimate the sensitivities of Tmin and LW↓ to atmospheric and soil variables. With these results we estimated the partial contributions of these variables to the overall day-to-day variability in Tmin and LW↓. We found that low cloud cover is the dominant factor, although specific humidity has a comparable role in the wet season. Lack of information on the cloud liquid water path is an important source of uncertainty. Enhanced soil moisture has a strong mitigating effect on frosts, although strong variability of soil moisture in the wet season could contribute substantially to the development of frosts.

Employing an urban meteorological network to monitor air temperature conditions in the ‘local climate zones’ of Szeged, Hungary

ABSTRACTWe analyse the average annual and seasonal air temperature conditions in the ‘local climate zones’ (LCZs) of Szeged, Hungary. The basis of our analysis is a 1‐year dataset from 2014 to 2015 for a 20‐station urban meteorological network. The network and its corresponding LCZ classes put temperature studies in Szeged into a new spatial framework to assess local climate and urban heat island (UHI) conditions. The stations were installed at locally representative sites using a Geographic Information System (GIS) method based on the standard surface parameters of the LCZ classification. The network was purposely designed to monitor thermal differences among LCZ classes in Szeged. We provide detailed site metadata for each of the monitoring stations used in the analysis. Our results show that the densely built‐up LCZ classes have higher annual and monthly mean and minimum air temperatures than structurally open and more vegetated classes, with nocturnal differences of &gt;4 °C observed under calm, clear skies. Among select temperature indices measured in the urban LCZ classes, frost days, cooling degree‐days, and tropical nights differ markedly from the background rural LCZ classes. This difference suggests that local climatologies exist within Szeged, and that these have implications for thermal comfort, urban energy use, and urban agriculture. Finally, the evaluation of heating and cooling rates in Szeged shows an important role for LCZs in UHI analysis.

Long-Term Climate Trends and Extreme Events in Northern Fennoscandia (1914–2013)

We studied climate trends and the occurrence of rare and extreme temperature and precipitation events in northern Fennoscandia in 1914–2013. Weather data were derived from nine observation stations located in Finland, Norway, Sweden and Russia. The results showed that spring and autumn temperatures and to a lesser extent summer temperatures increased significantly in the study region, the observed changes being the greatest for daily minimum temperatures. The number of frost days declined both in spring and autumn. Rarely cold winter, spring, summer and autumn seasons had a low occurrence and rarely warm spring and autumn seasons a high occurrence during the last 20-year interval (1994–2013), compared to the other 20-year intervals. That period was also characterized by a low number of days with extremely low temperature in all seasons (4–9% of all extremely cold days) and a high number of April and October days with extremely high temperature (36–42% of all extremely warm days). A tendency of exceptionally high daily precipitation sums to grow even higher towards the end of the study period was also observed. To summarize, the results indicate a shortening of the cold season in northern Fennoscandia. Furthermore, the results suggest significant declines in extremely cold climate events in all seasons and increases in extremely warm climate events particularly in spring and autumn seasons.

Dynamic changes in temperature extremes and their association with atmospheric circulation patterns in the Songhua River Basin, China

Understanding dynamic changes in climate extremes is important in forecasting extreme climate events and reducing their associated impacts. The objectives of this study were to analyze the spatiotemporal variations in temperature extremes and their association with atmospheric circulation, based on daily maximum (TX) and minimum temperatures (TN) collected from 60 meteorological stations in the Songhua River Basin (SRB) and its surroundings from 1960 to 2014. Following the ETCCDI (Expert Team on Climate Change Detection and Indices), eight extreme temperature indices, including three warm indices, three cold indices and two extreme indices, were chosen to quantify temperature extremes. The Mann-Kendall method and linear trend analysis were used to examine the trends, and Pearson correlation analysis was used to analyze the correlation between the temperature extremes and each atmospheric circulation. The results showed that warm indices, including the number of warm nights, warm days, and summer days, and extreme indices, including minimum TN and maximum TX, showed increasing trends in the SRB from 1960 to 2014. On the other hand, cold indices, including the number of cold nights, cold days and frost days, showed decreasing trends; Warm indices and maximum TX showed significant positive correlations with latitude (P<0.01). The Arctic Oscillation index (AO) displayed significant negative correlations with the cold indices (P<0.01) and positive correlations with the warm indices. The warm indices and extreme indices had positive correlations with the Northern Hemisphere Subtropical High area and intensity indices, while the reverse relationship was found between the cold indices and Northern Hemisphere Subtropical High. The Asia polar vortex area and intensity indices showed negative correlations with warm indices and extreme indices, while they were positively correlated to cold indices. The multivariate ENSO index (MEI) showed no linear correlation with any of the temperature extremes. These findings will provide useful information in forecasting extreme climate events and taking measures to reduce their associated impacts.

Reconstruction of the winter weather in east Friesland at the turn of the sixteenth and seventeenth centuries (1594–1612)

Historical climatology research dealing with the pre-instrumental period has rarely been able to include the weather on a daily scale. Other than for specific, extremely well-documented events, reconstructions only concern longer-term weather patterns (monthly, seasonal or annual). Yet at the end of the sixteenth century, David Fabricius recorded the weather, day after day, in his notebooks. In the middle of the Little Ice Age, he was a pastor in east Friesland (currently in the northwest of Germany) and a meteorology enthusiast. This documentary source is one of the richest available for reconstructing the weather at a time before measuring instruments gave systematic readings. Fabricius observed the weather and noted in his diary some terms that were more or less objective (such as cloudy, rain, snow) whilst others were more subjective (such as hot, warm, beautiful weather). We are therefore obliged, in this paper, to propose quantitative climatic reconstructions produced by “making do” with these notes about the weather as Fabricius perceived it. Our paper is focused on the reconstruction of winter weather (December, January and February) during the period covered by Fabricius’ notebook (1594–1612). Thanks to this notebook, it is possible to discern reasonably accurately the number of days of frost and snow and also to suggest a summary of winter weather types according to the number of days of precipitation. We compare Fabricius’ observations with other climatic reconstructions in Europe and also look at whether blockage phases, able to generate advection of cold air, happened frequently, this being one of the possibilities that could explain the cooling in Europe during the Little Ice Age.

Przyszłe zmiany wybranych wskaźników klimatycznych dla Polski na podstawie wyników dynamicznego downscalingu

The paper shows the expected changes in selected climatic indices on the basis of the results of dynamic downscaling for the 2041–2070 period with regard to the 1971–2000 period in the Polish territory. Results of the EURO CORDEX simulations with a resolution of 50 km and 12.5 km and regional models HIRHAM5, RACMO22E and the RCA4 driven by EC EARTH global climate model and RCP4.5 and RCP8.5 scenarios have been used. The maps showing absolute differences in the following climatic indices: number of frost days, ice days, summer days, wet days and days with precipitation exceeding 10 and 20 mm, between the values obtained in the scenarios and the values obtained for the reference period have been analysed. All the model results show an increase in the global temperature resulting in a decrease in the number of frost and ice days and an increase in the number of summer days. The models also show an increase in the frequency of extreme precipitation. Despite general similarities between the results of the simulations, some differences are evident, mainly due to model-specific setup.

Trends in frost days in Bosnia and Herzegovina

The paper analyzes the recent trends in the occurrence of frost days in Bosnia and Herzegovina. Trends during the 1961-2015 periods were determined based on data from fourteen meteorological stations. MAKESENS procedure, which uses the nonparametric Mann-Kendall test and the nonparametric Sen?s method, was applied on time series of annual number of frost days to assess trends magnitude and its statistical significance. Given the results, negative and largely significant trends are present all over Bosnia and Herzegovina territory. The estimated decreasing trend was in the range of 2.1-6.4 days per decade. The percentile analysis of the annual number of frost days in Bosnia and Herzegovina suggests that a decreasing trend has become more pronounced since 1990s and particularly since the beginning of the 21st century. The observed downward trends were primarily a consequence of high negative trends in the coldest winter months - in January and December. The most prominent decrease in annual number of frost days was observed in Banja Luka, Bugojno, Zenica and Bjelasnica area. Further research on the effects of the determined trends in the frost occurrence on plants is necessary particularly due to the observed changes in plant phenology as a result of climate system warming.