Modeling of Extreme Events and Regional Climate Variability on the Territory of the Caucasus (Georgia)

2020 ◽  
pp. 61-82
Author(s):  
Teimurazi Davitashvili ◽  
Inga Samkharadze ◽  
Meri Sharikadze
Keyword(s):  
Climate Variability ◽  
Extreme Events ◽  
Regional Climate ◽  
The Caucasus

Impact of local and regional climate variability on fungi production from Pinus sylvestris forests in Soria, Spain

2021 ◽  
Author(s):  
Elena García‐Bustamante ◽  
J. Fidel Fidel González‐Rouco ◽  
Elena García‐Lozano ◽  
Fernando Martinez‐Peña ◽  
Jorge Navarro
Keyword(s):  
Climate Variability ◽  
Pinus Sylvestris ◽  
Regional Climate

scholarly journals Long-term changes of river discharge regime in Latvia

2008 ◽  
Vol 39 (2) ◽  
pp. 133-141 ◽  
Author(s):  
Maris Klavins ◽  
Valery Rodinov
Keyword(s):  
Climate Variability ◽  
River Discharge ◽  
Water Resource Management ◽  
Regional Climate ◽  
Hydrological Regime ◽  
High Water ◽  
Regime Changes ◽  
Long Term Changes ◽  
Discharge Regime

The study of changes in river discharge is important for regional climate variability characterization and for development of an efficient water resource management system. The hydrological regime of rivers and their long-term changes in Latvia were investigated. Four major types of river hydrological regimes, which depend on climatic and physicogeographic factors, were characterized. These factors are linked to the changes observed in river discharge. Periodic oscillations of discharge, and low- and high-water flow years are common for the major rivers in Latvia. A main frequency of river discharge regime changes of about 20 and 13 years was estimated for the studied rivers. A significant impact of climate variability on the river discharge regime has been found.

Investigating the effects of climate change on structural resistance and actions

2021 ◽  
Author(s):  
Andre Orcesi ◽  
Emilio Bastidas-Arteaga ◽  
Olga Markogiannaki ◽  
Yue Li ◽  
Franck Schoefs ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Natural Hazards ◽  
Extreme Events ◽  
Performance Indicator ◽  
Design Life ◽  
Structural Durability ◽  
Structural Resistance ◽  
Physical And Chemical ◽  
Life Function

<p>One major issue when considering the effects of climate change is to understand, qualify and quantify how natural hazards and the changing climate will likely impact infrastructure assets and services as it strongly depends on current and future climate variability, location, asset design life, function and condition. So far, there is no well-defined and agreed performance indicator that isolates the effects of climate change for structures. Rather, one can mention some key considerations on how climate change may produce changes of vulnerability due to physical and chemical actions affecting structural durability or changes of the exposure in terms of intensity/frequency of extreme events. This paper considers these two aspects and associated challenges, considering some recent activities of members of the IABSE TG6.1.</p>

scholarly journals Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability

2011 ◽  
Vol 15 (12) ◽  
pp. 3785-3808 ◽  
Author(s):  
Y. Wada ◽  
L. P. H. van Beek ◽  
M. F. P. Bierkens
Keyword(s):  
Water Stress ◽  
Climate Variability ◽  
Water Use ◽  
Extreme Events ◽  
Water Availability ◽  
Water Scarcity ◽  
Water Demand ◽  
Developing Economies ◽  
Blue Water ◽  
Global Population

Abstract. During the past decades, human water use has more than doubled, yet available freshwater resources are finite. As a result, water scarcity has been prevalent in various regions of the world. Here, we present the first global assessment of past development of water stress considering not only climate variability but also growing water demand, desalinated water use and non-renewable groundwater abstraction over the period 1960–2001 at a spatial resolution of 0.5°. Agricultural water demand is estimated based on past extents of irrigated areas and livestock densities. We approximate past economic development based on GDP, energy and household consumption and electricity production, which are subsequently used together with population numbers to estimate industrial and domestic water demand. Climate variability is expressed by simulated blue water availability defined by freshwater in rivers, lakes, wetlands and reservoirs by means of the global hydrological model PCR-GLOBWB. We thus define blue water stress by comparing blue water availability with corresponding net total blue water demand by means of the commonly used, Water Scarcity Index. The results show a drastic increase in the global population living under water-stressed conditions (i.e. moderate to high water stress) due to growing water demand, primarily for irrigation, which has more than doubled from 1708/818 to 3708/1832 km3 yr−1 (gross/net) over the period 1960–2000. We estimate that 800 million people or 27% of the global population were living under water-stressed conditions for 1960. This number is eventually increased to 2.6 billion or 43% for 2000. Our results indicate that increased water demand is a decisive factor for heightened water stress in various regions such as India and North China, enhancing the intensity of water stress up to 200%, while climate variability is often a main determinant of extreme events. However, our results also suggest that in several emerging and developing economies (e.g. India, Turkey, Romania and Cuba) some of past extreme events were anthropogenically driven due to increased water demand rather than being climate-induced.

scholarly journals Compound extremes in a changing climate – a Markov chain approach

2016 ◽  
Vol 23 (6) ◽  
pp. 375-390 ◽  
Author(s):  
Katrin Sedlmeier ◽  
Sebastian Mieruch ◽  
Gerd Schädler ◽  
Christoph Kottmeier
Keyword(s):  
Extreme Events ◽  
Climate Models ◽  
Heat Waves ◽  
Dynamic Change ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Northern Germany ◽  
Russian Region ◽  
Climate Simulations ◽  
Potential Impact

Abstract. Studies using climate models and observed trends indicate that extreme weather has changed and may continue to change in the future. The potential impact of extreme events such as heat waves or droughts depends not only on their number of occurrences but also on "how these extremes occur", i.e., the interplay and succession of the events. These quantities are quite unexplored, for past changes as well as for future changes and call for sophisticated methods of analysis. To address this issue, we use Markov chains for the analysis of the dynamics and succession of multivariate or compound extreme events. We apply the method to observational data (1951–2010) and an ensemble of regional climate simulations for central Europe (1971–2000, 2021–2050) for two types of compound extremes, heavy precipitation and cold in winter and hot and dry days in summer. We identify three regions in Europe, which turned out to be likely susceptible to a future change in the succession of heavy precipitation and cold in winter, including a region in southwestern France, northern Germany and in Russia around Moscow. A change in the succession of hot and dry days in summer can be expected for regions in Spain and Bulgaria. The susceptibility to a dynamic change of hot and dry extremes in the Russian region will probably decrease.

Determination of seasonal forecast skill in identifying extreme events of temperature, wind speed, and SPI

2021 ◽  
Author(s):  
Massimiliano Palma ◽  
Franco Catalano ◽  
Irene Cionni ◽  
Marcello Petitta
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Climate Variability ◽  
Extreme Events ◽  
Bias Correction ◽  
Skill Score ◽  
Seasonal Forecast ◽  
Energy Sector ◽  
Seasonal Forecasts ◽  
Weather Forecasts

&lt;p&gt;Renewable energy is the fastest-growing source of electricity globally, but climate variability and impacting events affecting the potential productivity of plants are obstacles to its integration and planning.&amp;#160;Knowing a few months in advance the productivity of plants and the impact of extreme events on productivity and infrastructure can help operators and policymakers make the energy sector more resilient to climate variability, promoting the deployment of renewable energy while maintaining energy security.&lt;/p&gt;&lt;p&gt;The energy sector already uses weather forecasts up to 15 days for plant management; beyond this time horizon, climatologies are routinely used. This approach has inherent weaknesses, including the inability to predict extreme events, the prediction of which is extremely useful to decision-makers. Information on seasonal climate variability obtained through climate forecasts can be of considerable benefit in decision-making processes.&amp;#160;The Climate Data Store of the Copernicus Climate Change Service (C3S) provides seasonal forecasts and a common period of retrospective simulations (hindcasts) with equal spatial temporal resolution for simulations from 5 European forecast centres (European Centre for Medium-Range Weather Forecasts (ECMWF), Deutscher Wetterdienst (DWD), Meteo France (MF), UK Met Office (UKMO) and Euro-Mediterranean Centre on Climate Change (CMCC)), one US forecasting centre (NCEP) plus the Japan Meteorological Agency (JMA) model.&lt;/p&gt;&lt;p&gt;In this work, we analyse the skill and the accuracy of a subset of the operational seasonal forecasts provided by Copernicus C3S, focusing on three relevant essential climate variables for the energy sector: temperature (t2m), wind speed (sfcWind, relevant to the wind energy production), and precipitation. The latter has been analysed by taking the Standard Precipitation Index (SPI) into account.&lt;/p&gt;&lt;p&gt;First, the methodologies for bias correction have been defined. Subsequently, the reliability of the forecasts has been assessed using appropriate reliability indicators based on comparison with ERA5 reanalysis dataset.&amp;#160;The hindcasts cover the period 1993-2017. For each of the variables considered, we evaluated the seasonal averages based on monthly means for two seasons: winter (DJF) and summer (JJA). Data have been bias corrected following two methodologies, one based on the application of a variance inflation technique to ensure the correction of the bias and the correspondence of variance between forecast and observation; the other based on the correction of the bias, the overall forecast variance and the ensemble spread as described in Doblas-Reyes et al. (2005).&lt;/p&gt;&lt;p&gt;Predictive ability has been assessed by calculating binary (Brier Skill Score, BSS hereafter, and Ranked Probability Skill Score, RPSS hereafter) and continuous (Continuous Ranked Probability Skill Score, CRPSS hereafter) scores.&amp;#160;Forecast performance has been assessed using ERA 5 reanalysis as pseudo-observations.&amp;#160;&lt;/p&gt;&lt;p&gt;In this work we discuss the results obtained with different bias correction techniques highlighting the outcomes obtained analyzing the BSS for the first and the last terciles and the first and the last percentiles (10th and 90th). This analysis has the goal to identify the regions in which the seasonal forecast can be used to identify potential extreme events.&lt;/p&gt;

scholarly journals Climate Perspectives in the Intra–Americas Seas

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 959
Author(s):  
Ana María Durán-Quesada ◽  
Rogert Sorí ◽  
Paulina Ordoñez ◽  
Luis Gimeno
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
Large Scale ◽  
Negative Impact ◽  
Current Knowledge ◽  
Regional Climate ◽  
Climate Projections ◽  
Economic Activities ◽  
Weather And Climate ◽  
The Impact

The Intra–Americas Seas region is known for its relevance to air–sea interaction processes, the contrast between large water masses and a relatively small continental area, and the occurrence of extreme events. The differing weather systems and the influence of variability at different spatio–temporal scales is a characteristic feature of the region. The impact of hydro–meteorological extreme events has played a huge importance for regional livelihood, having a mostly negative impact on socioeconomics. The frequency and intensity of heavy rainfall events and droughts are often discussed in terms of their impact on economic activities and access to water. Furthermore, future climate projections suggest that warming scenarios are likely to increase the frequency and intensity of extreme events, which poses a major threat to vulnerable communities. In a region where the economy is largely dependent on agriculture and the population is exposed to the impact of extremes, understanding the climate system is key to informed policymaking and management plans. A wealth of knowledge has been published on regional weather and climate, with a majority of studies focusing on specific components of the system. This study aims to provide an integral overview of regional weather and climate suitable for a wider community. Following the presentation of the general features of the region, a large scale is introduced outlining the main structures that affect regional climate. The most relevant climate features are briefly described, focusing on sea surface temperature, low–level circulation, and rainfall patterns. The impact of climate variability at the intra–seasonal, inter–annual, decadal, and multi–decadal scales is discussed. Climate change is considered in the regional context, based on current knowledge for natural and anthropogenic climate change. The present challenges in regional weather and climate studies have also been included in the concluding sections of this review. The overarching aim of this work is to leverage information that may be transferred efficiently to support decision–making processes and provide a solid foundation on regional weather and climate for professionals from different backgrounds.

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