scholarly journals Expressions of climatic change in Slovak Republic

Author(s):  
Iveta Marková ◽  
Mikuláš Monoši

The development of climate change is evaluated on the basis of trends in a long-term time series (1951–2018) of individual climatic elements by comparing values from individual years with the normal period in climatology of 1961–1990. The aim of the article is to present the manifestations of climate change in Slovakia (since its inception) according to selected indicators: (1) average annual air temperature, (2) soil temperature, (3) total atmospheric precipitation and (4) drought index over the last decade. The data presented in the article were obtained from public reports on the state of the environment in the Slovakia and other related documents. Slovakia, during the years 1881–2018, underwent significant changes in all monitored climatic elements. The most significant changes were in 2017 and 2018.

2021 ◽  
Vol 20 (2) ◽  
pp. 16-24
Author(s):  
Iveta Marková ◽  
◽  
Mikuláš Monoši

The development of climate change is evaluated based on trends in long-term time series (1951 - 2018) of individual climatic elements, comparing values of individual years with the standard period in climatology 1961 - 1990 (SAŽP, 2019). The aim of the article is to evaluate climate elements, namely the production of greenhouse gases, average annual air temperature, annual total atmospheric precipitation, drought index and annual soil temperature (soil index). Data presented in the article are obtained from public reports on the state of the environment in the Slovak Republic and other related documents. In 1881 - 2018, Slovakia underwent significant changes in all monitored climatic elements. The most crucial changes occurred in 2017 and 2018.


2021 ◽  
Author(s):  
Thibault Mathevet ◽  
Cyril Thébault ◽  
Jérôme Mansons ◽  
Matthieu Le Lay ◽  
Audrey Valery ◽  
...  

<p>The aim of this communication is to present a study on climate variability and change on snow water equivalent (SWE) and streamflow over the 1900-2100 period in a mediteranean and moutainuous area.  It is based on SWE and streamflow observations, past reconstructions (1900-2018) and future GIEC scenarii (up to 2100) of some snow courses and hydrological stations situated within the French Southern Alps (Mercantour Natural Parc). This has been conducted by EDF (French hydropower company) and Mercantour Natural Parc.</p><p>This issue became particularly important since a decade, especially in regions where snow variability had a large impact on water resources availability, poor snow conditions in ski resorts and artificial snow production or impacts on mountainous ecosystems (fauna and flora). As a water resources manager in French mountainuous regions, EDF developed and managed a large hydrometeorological network since 1950. A recent data rescue research allowed to digitize long term SWE manual measurements of a hundred of snow courses within the French Alps. EDF have been operating an automatic SWE sensors network, complementary to historical snow course network. Based on numerous SWE observations time-series and snow modelization (Garavaglia et al., 2017), continuous daily historical SWE time-series have been reconstructed within the 1950-2018 period. These reconstructions have been extented to 1900 using 20 CR (20<sup>th</sup> century reanalyses by NOAA) reanalyses (ANATEM method, Kuentz et al., 2015) and up to 2100 using GIEC Climate Change scenarii (+4.5 W/m² and + 8.5 W/m² hypotheses). In the scope of this study, Mercantour Natural Parc is particularly interested by snow scenarii in the future and its impacts on their local flora and fauna.</p><p>Considering observations within Durance watershed and Mercantour region, this communication focuses on: (1) long term (1900-2018) analyses of variability and trend of hydrometeorological and snow variables (total precipitation, air temperature, snow water equivalent, snow line altitude, snow season length, streamflow regimes) , (2) long term variability of snow and hydrological regime of snow dominated watersheds and (3) future trends (2020 -2100) using GIEC Climate Change scenarii.</p><p>Comparing old period (1950-1984) to recent period (1984-2018), quantitative results within these regions roughly shows an increase of air temperature by 1.2 °C, an increase of snow line height by 200m, a reduction of SWE by 200 mm/year and a reduction of snow season duration by 15 days. Characterization of the increase of snow line height and SWE reduction are particularly important at a local and watershed scale. Then, this communication focuses on impacts on long-term time scales (2050, 2100). This long term change of snow dynamics within moutainuous regions both impacts (1) water resources management, (2) snow resorts and artificial snow production developments or (3) ecosystems dynamics.Connected to the evolution of snow seasonality, the impacts on hydrological regime and some streamflow signatures allow to characterize the possible evolution of water resources in this mediteranean and moutianuous region This study allowed to provide some local quantitative scenarii.</p>


2021 ◽  
Vol 25 (5) ◽  
pp. 65-71
Author(s):  
V.V. Drozdov ◽  
G.T. Frumin ◽  
A.V. Kosenko

The review and analysis of the long-term variability of the average annual and average air temperature for winter and summer, as well as the values of the amounts of atmospheric precipitation in St. Petersburg were carried out. The correlation between the dynamics of the values of these indicators and the intensity of atmospheric circulation over the North Atlantic in the form of the NAO1 index (North Atlantic Oscillation) was estimated. The possible environmental consequences of climate change in the region of St. Petersburg are justified.


2010 ◽  
Vol 11 (1) ◽  
pp. 46-68 ◽  
Author(s):  
Vimal Mishra ◽  
Keith A. Cherkauer ◽  
Shraddhanand Shukla

Abstract Understanding the occurrence and variability of drought events in historic and projected future climate is essential to managing natural resources and setting policy. The Midwest region is a key contributor in corn and soybean production, and the occurrence of droughts may affect both quantity and quality of these crops. Soil moisture observations play an essential role in understanding the severity and persistence of drought. Considering the scarcity of the long-term soil moisture datasets, soil moisture observations in Illinois have been one of the best datasets for studies of soil moisture. In the present study, the authors use the existing observational dataset and then reconstruct long-term historic time series (1916–2007) of soil moisture data using a land surface model to study the effects of historic climate variability and projected future climate change on regional-scale (Illinois and Indiana) drought. The objectives of this study are to (i) estimate changes and trends associated with climate variables in historic climate variability (1916–2007) and in projected future climate change (2009–99) and (ii) identify regional-scale droughts and associated severity, areal extent, and temporal extent under historic and projected future climate using reconstructed soil moisture data and gridded climatology for the period 1916–2007 using the Variable Infiltration Capacity (VIC) model. The authors reconstructed the soil moisture for a long-term (1916–2007) historic time series using the VIC model, which was calibrated for monthly streamflow and soil moisture at eight U.S. Geological Survey (USGS) gauge stations and Illinois Climate Network’s (ICN) soil moisture stations, respectively, and then it was evaluated for soil moisture, persistence of soil moisture, and soil temperature and heat fluxes. After calibration and evaluation, the VIC model was implemented for historic (1916–2007) and projected future climate (2009–99) periods across the study domain. The nonparametric Mann–Kendall test was used to estimate trends using the gridded climatology of precipitation and air temperature variables. Trends were also estimated for annual anomalies of soil moisture variables, snow water equivalent, and total runoff using a long-term time series of the historic period. Results indicate that precipitation, minimum air temperature, total column soil moisture, and runoff have experienced upward trends, whereas maximum air temperature, frozen soil moisture, and snow water equivalent experienced downward trends. Furthermore, the decreasing trends were significant for the frozen soil moisture in the study domain. The results demonstrate that retrospective drought periods and their severity were reconstructed using model-simulated data. Results also indicate that the study region is experiencing reduced extreme and exceptional droughts with lesser areal extent in recent decades.


Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.


Author(s):  
Ye Yuan ◽  
Stefan Härer ◽  
Tobias Ottenheym ◽  
Gourav Misra ◽  
Alissa Lüpke ◽  
...  

AbstractPhenology serves as a major indicator of ongoing climate change. Long-term phenological observations are critically important for tracking and communicating these changes. The phenological observation network across Germany is operated by the National Meteorological Service with a major contribution from volunteering activities. However, the number of observers has strongly decreased for the last decades, possibly resulting in increasing uncertainties when extracting reliable phenological information from map interpolation. We studied uncertainties in interpolated maps from decreasing phenological records, by comparing long-term trends based on grid-based interpolated and station-wise observed time series, as well as their correlations with temperature. Interpolated maps in spring were characterized by the largest spatial variabilities across Bavaria, Germany, with respective lowest interpolated uncertainties. Long-term phenological trends for both interpolations and observations exhibited mean advances of −0.2 to −0.3 days year−1 for spring and summer, while late autumn and winter showed a delay of around 0.1 days year−1. Throughout the year, temperature sensitivities were consistently stronger for interpolated time series than observations. Such a better representation of regional phenology by interpolation was equally supported by satellite-derived phenological indices. Nevertheless, simulation of observer numbers indicated that a decline to less than 40% leads to a strong decrease in interpolation accuracy. To better understand the risk of declining phenological observations and to motivate volunteer observers, a Shiny app is proposed to visualize spatial and temporal phenological patterns across Bavaria and their links to climate change–induced temperature changes.


2021 ◽  
pp. 87-99
Author(s):  
G. KH. ISMAIYLOV ◽  
◽  
N. V. MURASCHENKOVA ◽  
I. G. ISMAIYLOVA

The results of the analysis and assessment of changes in annual and seasonal characteristics of hydrometeorological processes in a private catchment area of the Kuibyshev hydroelectric complex of the Volga river are presented. To analyze the temporal dynamics of the variability of the annual and seasonal characteristics of the hydrometeorological processes in the considered territory of the river basin we used more than 100 years of observations of annual and seasonal fluctuations of lateral inflow, total atmospheric precipitation and air temperature regimes on the Volgariver. Relationship equations for annual and seasonal changes in hydrometeorological characteristics in time are obtained. It was found that long-term fluctuations of hydrometeorological processes (lateral inflow, total atmospheric precipitation and air temperature) are characterized by tendencies (trends). The analysis of these trends showed that the non-standard climatic situation, starting from the 70s of the last century, had a very significant impact on the distribution of annual and especially on the seasonal (low-water and winter) characteristics of hydrometeorological processes. It has been established that non-standard unidirectional changes are found in the fluctuations in the total atmospheric precipitation. If the winter total precipitation is characterized over the 100-year period in question by a continuously decreasing trend,the summer-autumn period is an increasing trend. This leads to the fact that long-term fluctuations in total precipitation during the period of low water are formed as a stationary process. At the same time, the total precipitation of the spring flood and inflowing to the Kuibyshev hydroelectric unit is characterized by a constantly increasing trend.


10.5219/1196 ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 906-914
Author(s):  
Ivana Váryová ◽  
Zuzana Poláková ◽  
Iveta Košovská ◽  
Alexandra Ferenczi Vaňová ◽  
Renáta Krajčírová

The paper is focused on the evaluation of the price development of raw cow milk in the Slovak Republic. The aim of the paper is to analyse the development of average prices of the raw Q class cow´s milk in 2006 – 2018 and to forecast the trend of these prices by June 2019. Monthly data from the Market Report of Milk and Dairy Products issued by the Agricultural Information Department – ATIS, as part of the Agricultural Paying Agency, were the base of our information resource. These data were analyzed by using the statistical software called SAS. Box-Jenkins methodology was used to model the future trend of average purchase prices of the raw Q class cow´s milk, designed for modeling stationary and non-stationary time series and time series with seasonal components. During the period of 2006 – 2018 the Slovak dairy market showed significant changes in the prices of raw Q class cow´s milk. Three crisis periods of the dairy sector have been identified, during which the milk price has fallen below 0.30 € per kilogram. Long-term low prices of raw cow milk led to the liquidation of primary milk producers. In the next forecast period, by February 2019 a moderate increase in the average purchase price of raw Q class cow´s milk is expected, followed by a decrease by June 2019.


Author(s):  
V. V. Hrynchak

The decision about writing this article was made after familiarization with the "Brief Climatic Essay of Dnepropetrovsk City (prepared based on observations of 1886 – 1937)" written by the Head of the Dnipropetrovsk Weather Department of the Hydrometeorological Service A. N. Mikhailov. The guide has a very interesting fate: in 1943 it was taken by the Nazis from Dnipropetrovsk and in 1948 it returned from Berlin back to the Ukrainian Hydrometeorological and Environmental Directorate of the USSR, as evidenced by a respective entry on the Essay's second page. Having these invaluable materials and data of long-term weather observations in Dnipro city we decided to analyze climate changes in Dnipropetrovsk region. The article presents two 50-year periods, 1886-1937 and 1961-2015, as examples. Series of observations have a uniform and representative character because they were conducted using the same methodology and results processing. We compared two main characteristics of climate: air temperature and precipitation. The article describes changes of average annual temperature values and absolute temperature values. It specifies the shift of seasons' dates and change of seasons' duration. We studied the changes of annual precipitation and peculiarities of their seasonable distribution. Apart from that peculiarities of monthly rainfall fluctuations and their heterogeneity were specified. Since Dnipro city is located in the center of the region the identified tendencies mainly reflect changes of climatic conditions within the entire Dnipropetrovsk region.


2018 ◽  
Author(s):  
Athanasia Iona ◽  
Athanasios Theodorou ◽  
Sarantis Sofianos ◽  
Sylvain Watelet ◽  
Charles Troupin ◽  
...  

Abstract. We present a new product composed of a set of thermohaline climatic indices from 1950 to 2015 for the Mediterranean Sea such as decadal temperature and salinity anomalies, their mean values over selected depths, decadal ocean heat and salt content anomalies at selected depth layers as well as their long times series. It is produced from a new high-resolution climatology of temperature and salinity on a 1/8° regular grid based on historical high quality in situ observations. Ocean heat and salt content differences between 1980–2015 and 1950–1979 are compared for evaluation of the climate shift in the Mediterranean Sea. The spatial patterns of heat and salt content shifts demonstrate in greater detail than ever before that the climate changes differently in the several regions of the basin. Long time series of heat and salt content for the period 1950 to 2015 are also provided which indicate that in the Mediterranean Sea there is a net mean volume warming and salting since 1950 with acceleration during the last two decades. The time series also show that the ocean heat content seems to fluctuate on a cycle of about 40 years and seems to follow the Atlantic Multidecadal Oscillation climate cycle indicating that the natural large scale atmospheric variability could be superimposed on to the warming trend. This product is an observations-based estimation of the Mediterranean climatic indices. It relies solely on spatially interpolated data produced from in-situ observations averaged over decades in order to smooth the decadal variability and reveal the long term trends with more accuracy. It can provide a valuable contribution to the modellers' community, next to the satellite-based products and serve as a baseline for the evaluation of climate-change model simulations contributing thus to a better understanding of the complex response of the Mediterranean Sea to the ongoing global climate change. The product is available here: https://doi.org/10.5281/zenodo.1210100.


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