Special Issue: Climate change and impacts from global processes to local effects
Guest Editor: Mónika Lakatos
There are some parallelisms and similarities since the 1960s in the identification, attribution, scientific communication, and the subsequent initial policy setting processes of the acidification, ozone layer depletion, and climate change hazards. The anthropogenic factors behind the latter one were hypothesized well before the discovery of the cause-effect relations of the two other problems; nevertheless, later on the policy approaches to address the "acid rain" and "ozone shield" issues served to some extent as precedents for building up the international climate policy mechanisms. The analysis of these knowledge and policy development cases is of particular interest in light of the widening climate change science-policy gap, whilst efficient international policy and legal regimes have been built up for tackling the acidification and ozone depleting phenomena. Concerning the global climate policy regime, the consideration of its progress covers the time period since the early 1970s by 2015 when its most recent building block was adopted.
Mónika Lakatos, Zita Bihari, Tamás Szentimrey, Jonathan Spinoni , and Sándor Szalai
The harmonized data derived in CARPATCLIM project has enabled the presentation of the most comprehensive picture of trends of extreme temperatures in the Carpathian Region. A set of climate change indicators derived from daily temperature data, focusing on extreme events, was computed and analyzed in this study. Annual extreme indices for the period 1961–2010 were examined. Trends in the gridded fields were calculated, mapped, and tested for statistical significance. Results showed significant changes mainly in temperature extremes associated with warming. A large part of the region showed a significant decrease in the annual occurrence of cold nights and an increase in the annual occurrence of warm nights. The growing season starts earlier in more than third part of the region. The trend and proportion of the area that sign significant change of warm extremes strengthen the obvious warming in the Carpathian Region.
Csilla Péliné Németh, Judit Bartholy, Rita Pongrácz, and Kornélia Radics
Due to intense human presence and various anthropogenic activities, global climate change has been detected. Increasing temperature values and an overall warming are projected, which will certainly affect the global circulation patterns and regional climatic conditions throughout Europe. As an indirect consequence, global warming may also alter the wind conditions in the Carpathian Basin. In order to provide reliable projections for the future, the first task is to analyze wind climatology of the recent past using various tools from mathematical statistics.
In this paper, detailed analysis of observed wind fields, trends of different percentiles, return values, wind related climate indices, and their spatial distributions are discussed over Hungary using the homogenized Hungarian synoptic data sets and the homogenized and gridded CARPATCLIM database. Wind related climate indices are defined to evaluate the frequency occurrence and the trend of moderate and strong wind days at the stations in the last few decades. The annual daily maxima of wind speed and wind gust are determined on the basis of available time series fitted to the generalized extreme value distribution at every station and grid cell. 50-year and 100-year return values are estimated from these fitted distributions.
In addition, simulated wind climate variability is evaluated for the future periods of 2021–2050 and 2071–2100 relative to the 1961–1990 reference period. Since projected wind speed is highly overestimated by the simulation of the regional climate model RegCM for the reference period (1961–1990), a bias correction is necessary to apply to the raw simulated wind data using CARPATCLIM as a reference database. The bias correction method is based on fitting the empirical cumulative density functions of simulated daily time series to the observations for each gridcell using monthly multiplicative correction factors.
Márton Jolánkai, Ákos Tarnawa, Csaba Horváth, Ferenc H. Nyárai, and Katalin Kassai
Weather impacts may have direct or indirect influence on the performance of agricultural production and food industry. The present problems are various, however, they can be sorted into two major groups: (1) factors that can be related to climate change processes like water scarcity, drought, meteorological extremities (temperature anomalies – frost, heat days, duration of unfavorable periods; precipitation – heavy rains, hail storms, land slide; air – storms, high wind, alterations of radiation and its postulates, (2) economic, social, and policy problems, that may have negative impact on the adaptability to meteorological factors in general and climate change processes in particular regarding food and agricultural production.
Changes in temperature may be of less importance concerning agriculture. Apart from a wide range of physiological problems, warming may have beneficial impacts as well; 1 oC rise in mean temperature may induce some 7 to 9 days of increment of the vegetation period, which could give a chance to use a +100 FAO group in maize production. On the other hand, warming of the summer period can be considered unfavorable. That may result in deterioration of sexual reproduction of most annual plants.
Changes in precipitation have more severe and determining consequences for crop production. Limited availability to water in the vegetation period may cause various direct deteriorating effects in cropping. Also, mild and dryer winter periods can be harmful contributing to epidemics and gradations of pests and diseases. Weed cenoses are also affected by climate change processes.
Economic vulnerability of agriculture in general and that of crop production in particular can be detected in most fields of the food chain. It is hard to estimate losses, but trends and the magnitude of these can be assessed. Grain crops represent a major source of arable output in Hungary. Half of the arable land is used for wheat and maize cropping. The grain yield of these two crops range from 9 to 15 million tons annually due to weather influences of the very crop year. The gap between them represents some 270 billion HUF on today’s prices.
Angéla Anda and Gábor Soós
Food production is largely affected by weather variables; the year-to-year yield variations are due to changes in air temperatures, precipitation, and other meteorological elements. The crop-weather relationship is interaction, therefore, the agriculture is also responsible for greenhouse gas emissions (land clearing, fossil fuel use, rice cultivation, livestock production, N fertilization). The advantage of agricultural models is that they could simulate the above relations quantitatively. However, there are a variety of dynamic models dealing with crop-environment interactions in different levels from local to global one. The start of the studies used to be the cognition of crop growth and development by description of governing physiological and physical processes. The economic models close the range of investigations through impact estimation of climate change on the whole agricultural sector.
The first part of this study is devoted to some selected basic crop-environment relations from the literature. The second half of the work is dealing with on-site case study for maize, whereby different scenarios were established to project the crop response (stomatal resistance, photosynthesis) to various aspects of global climate change. The results of the crop microclimate simulation model were treated with restraint, because the majority of weather influences might have additive or synergistic impacts causing more severe damages than simulation models ever estimate. A simple example may be a stressed crop that become more sensitive to damaging pests and diseases excluding fully from most of the dynamic models. Despite known weaknesses of crop-environment models, the end-users (farmers, politicians) can respond more specifically to climate change besides such widely applied interventions as using warmth- or drought tolerant species, altering dates of planting and harvesting, irrigation, modification of cultivation systems, etc.
Árpád Rózsás, Nauzika Kovács, László Gergely Vigh, and Miroslav Sýkora
Climate change affects not only the natural but also the built environment. The latter comprises large part of societal wealth, and it is a crucial component of developed economies. The focus of this paper is the quantitative assessment of the reliability of load bearing structures in changing climate. Despite its significance, relatively few quantitative studies are available on this topic, and particularly the Carpathian Region has been analyzed insufficiently. Therefore, the aim of this paper is (i) to present two quantitative studies on structures and climate change for the Carpathian Region, and (ii) to give an overview about approaches in civil engineering in relation to climate sciences, thus to trigger and facilitate future cooperation. The first part of the study is about the carbonation-induced corrosion of reinforced concrete structures analyzed considering six climate change scenarios. The results show that the depassivation probability can double from the beginning to the end of the 21st century. For structures executed in 2000, the effects will be subtle within the first half of the century, whilst the considerable changes are expected in the other 50 years. The second part of the study is about ground snow load and its effect on structural failure probability. It focuses on probabilistic models and statistical uncertainties, and draws attention to the significance of uncertainties arising from the insufficient number of observations. These uncertainties are typically neglected in current civil engineering practice, and they are especially important for climate change, for which the historical observations are not representative of the future environment. Bayesian statistical approach is used to handle these uncertainties. The analyses show that statistical uncertainties can have several order of magnitude effect on failure probability, thus their neglect is not justified. Additionally, long-term trends in historical snow observations are analyzed using stationary and non-stationary generalized extreme value distributions. Statistically significant decreasing trends (p < 10%) are found for numerous locations, but they are practically significant only for a few in respect of structural reliability. The results of both studies indicate that climate change can have significant practical consequences on structures and should be considered by civil engineering profession. Revision of design standards and further research in cooperation with meteorologist seem to be needed to explore and reduce the impacts of climate change on load bearing structures in the Carpathian Region.