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Crucial role of Black Sea warming in amplifying the 2012 Krymsk precipitation extreme
Abstract
Over the past 60 years, both average daily precipitation intensity and extreme precipitation have increased in many regions 1–3. Part of these changes, or even individual events 4,5 , have been attributed to anthropogenic warming 6,7. Over the Black Sea and Mediterranean region, the potential for extreme summertime convective precipitation has grown 8 alongside substantial sea surface temperature increase. A particularly devastating convective event experienced in that region was the July 2012 precipitation extreme near the Black Sea town of Krymsk 9. Here we study the eeect of sea surface temperature (SST) increase on convective extremes within the region, taking the Krymsk event as a showcase example. We carry out ensemble sensitivity simulations with a convection-permitting atmospheric model and show the crucial role of SST increase in the extremeness of the event. The enhancement of lower tropospheric instability due to the current warmer Black Sea allows deep convection to be triggered, increasing simulated precipitation by more than 300% relative to simulations with SSTs characteristic of the early 1980s. A highly nonlinear precipitation response to incremental SST increase suggests that the Black Sea has exceeded a regional threshold for the intensification of convective extremes. The physical mechanism we identify indicates that Black Sea and Mediterranean coastal regions may face abrupt amplifications of convective precipitation under continued SST increase, and illustrates the limitations of thermodynamical bounds for estimating the temperature scaling of convective extremes.
... The aim of variety (b) is to explore the causal chain describing hazardous and/or LLHI events, such as droughts or intense rainfall events, unfolding over relatively short temporal scales and across different spatial scales under different climatic conditions, and it has been taken up extensively (see, e.g., Chen et al., 2020;Gutman et al., 2018;Hibino et al., 2018;Kanada et al., 2017;Lackmann, 2015;Lau et al., 2016;Lawal et al., 2016;Meredith et al., 2015;Pall et al., 2017;Patricola & Wehner, 2018;S anchez-Benítez et al., 2022;van Garderen et al., 2021;Wehrli et al., 2020). This particular method to construct PCS is described as an alternative framework for extreme event attribution studies (e.g., Shepherd, 2016;van Garderen & Mindlin, 2022) or as what has been called a "pseudo global warming study" (Doblas-Reyes et al., 2021, sect. ...
... PCS that follow varieties (b)-(d) are generally developed by first identifying a causal chain for a reference weather event, from observational data or model output, forming the factual storyline. Counterfactual storylines may then be constructed to investigate, for example, how an event would have unfolded in the absence of (the thermodynamic component of) anthropogenic forcing (e.g., Meredith et al., 2015;Pall et al., 2017;Patricola & Wehner, 2018;Takayabu et al., 2015; downward arrow in Figure 2(ii)), how an event would unfold in a climate with higher global mean temperature (see, e.g., Hegdahl et al., 2020, van der Wiel et al., 2021 Figure 2(ii)), how a different (predicted) realization of an extreme event would impact a specified system in a warmer climate (Ciullo et al., 2021, Figure 2(iii)), or how the frequency of unrealized forecast extreme events has changed over time (Coughlan de Perez et al., 2023). Some PCS construct both analog pasts and futures (Chen et al., 2020;Lackmann, 2015). ...
... One way constructs a causal description of a regional climate or weather event, separating dynamic and thermodynamic components at different spatial scales, and then intervenes on the thermodynamic component to construct the counterfactual storyline (Figure 2(ii)). This way of constructing a PCS is motivated by epistemic considerations regarding uncertainty of local responses to global warming (e.g., Shepherd, 2014;Trenberth et al., 2015), the representational accuracy of models of higher resolution (e.g., Meredith et al., 2015;Pall et al., 2017), or the inability of free-running GCMs to capture the target event (Chan et al., 2022;Hazeleger et al., 2015;van Garderen et al., 2021). In other words, the approach promotes values related to scientific understanding of climatic phenomena. ...
The physical climate storyline (PCS) approach is increasingly recognized by the physical climate research community as a tool to produce and communicate decision‐relevant climate risk information. While PCS is generally understood as a single concept, different varieties of the approach are applied according to the aims and purposes of the PCS and the scientists that build them. To unpack this diversity of detail, this article gives an overview of key practices and assumptions of the PCS approach as developed by physical climate scientists, as well as their ties to similar approaches developed by the broader climate risk and adaptation research community. We first examine varieties of PCSs according to the length of the causal chain they explore, and the type of evidence used. We then describe how they incorporate counterfactual elements and the temporal perspective. Finally, we examine how value judgments are implicitly or explicitly included in the aims and construction of PCSs. We conclude the discussion by suggesting that the PCS approach can further mature in the way it incorporates the narrative element, in the way it incorporates value judgments, and in the way that the evidence chosen to build PCSs constrains what is considered plausible.
This article is categorized under: Assessing Impacts of Climate Change > Scenario Development and Application
Climate, History, Society, Culture > Technological Aspects and Ideas
Paleoclimates and Current Trends > Modern Climate Change
... Recent studies show that some mesoscale thunderstorms and extreme convective events can also result from the rapid and abnormal fluctuations in SSTs (Brossier et al., 2006;Ma et al., 2015;Senatore et al., 2014Senatore et al., , 2020a. In addition, the orographic forcing, which refers to the reduction/exclusion of mountain barriers, can considerably contribute to these types of events (Brossier et al., 2006;Hong and Lee, 2009;Smith et al., 2010;Flesch and Reuter, 2012;Meredith et al., 2015). Therefore, the SST forcing is usually considered a crucial component for the heavy precipitation incidents over the regions, particularly for the Mediterranean (Pastor et al., 2017). ...
... The findings of Meredith et al. (2015) indicate that the SST increase has a vital role in the abrupt amplification of extreme summertime convective precipitation over the Mediterranean and the Black Sea coastal regions. Onur et al. (2019) examined the SSTprecipitation relation for the extreme summer precipitation case in the Eastern Black Sea region by increasing and decreasing the initial SST value of the event. ...
... Overall, similar to many studies (Lorenz, 1963;Majewski, 1997;Warner et al., 1997;Vié et al., 2011;Singh and Mandal, 2015), the results obtained from this study also prove that the SST is a very important forcing in the atmosphere which can significantly affect the lower boundary layer processes of the model forecasts. As stated by Meredith et al. (2015) and Senatore et al. (2020a), enabling the cumulus parameterization at finer resolution domain may further enhance the humidity and static instability at the lower troposphere near the surface. The initial and lateral boundary conditions are accepted as serious limitations to the weather predictability due to the large-scale flow of atmospheric waves and disturbances. ...
This study investigates the impact of sea surface temperature (SST) describing the lower boundary of Weather Research and Forecasting (WRF) model on the extreme weather events that occurred on the Mediterranean (MED) and the Eastern Black Sea (EBS) regions of Turkey. For each region, one extreme event case is selected and characterized as a summer convective system in EBS and as a winter synoptic system in MED region. The SST impact on the WRF model forecasts of these events is accomplished in two ways. First, the SST analysis is conducted by making a 10-days simulation for each event with and without activating the SST options (update and skin options) available in the model configuration. In these runs, the selected initial and boundary condition datasets, Global Forecasting System (GFS) for the MED region and the ERA5 for the EBS regions, provide corresponding internal SST data. Second, the prediction performance of the model is evaluated among the simulations of non-external, time-varying (GFS and ERA5 SST) and external, time–varying, high-resolution SST products (The Group for High Resolution Sea Surface Temperature; GHRSST, Medspiration, and NCEP) for each event. The results show that the WRF model simulations, even for short-term event predictions, are highly sensitive to time-variant SST options. The overestimation and high spreading feature of maximum and total precipitation are realistically reduced by time-variant SST products. The Medspiration and the NCEP sources for the MED region and the GHRSST and the Medspiration sources for the EBS region yielded warmer SSTs among the simulations. By establishing the amplified air-sea interactions, these sources provide more appropriate peak precipitation distributions in both regions. Furthermore, based on this study, the effect of using high-resolution SST (GHRSST and Medspiration) is more prominent in predicting convective event developed over complex topography of the EBS while the resolution effect is not much critical for synoptic system simulation even under the complex topography in MED. Lastly, the highest mean correlation of conditional hourly rain is calculated as 0.65 with the Medspiration product on MED and 0.48 with the GHRSST product on the EBS region.
... Increasing precipitation intensities and the occurrence of heavy rain events could cause devastating flash floods and affect economies and societies (e.g. Meredith et al 2015a, Mokhov and Semenov 2016, Martinkova and Kysely 2020. A better understanding of extreme precipitation formation processes will improve their prediction and accuracy in climate model simulations (Sillmann et al 2017). ...
... A large number of extreme precipitation events have led to substantial economic and social consequences in Russia in recent decades (e.g. Meredith et al 2015a, Mokhov and Semenov 2016, Zolotokrylin and Cherenkova 2018. Understanding the processes determining extreme precipitation is important for more accurate weather forecasts and climate projections. ...
... Intensification of convective processes over Northern Eurasia is also manifested in increase of convective clouds (Chernokulsky and Esau 2019), major convective-related windthrow (Shikhov et al 2020), convective initiating environments (Chernokulsky et al 2017). However, occurrence of convective inhibiting environments has also increased, at least over European Russia (Taszarek et al 2021), which may be associated with sea surface warming (Meredith et al 2015a). No estimates for mutual changes of convective inhibiting and convective initiating environments have been carried out for other Russian regions though. ...
Precipitation extremes are widely thought to intensify with global warming due to an exponential growth following the Clausius-Clapeyron (C-C) equation which links the atmosphere water vapor saturation pressure with air temperature. However, a number of recent studies based on station and reanalyses data for the contemporary period showed that scaling rates between extreme precipitation and temperature strongly depend on temperature range, moisture availability, and a region of interest. Being performed for some regions, such estimates, however, lack for Northern Eurasia, where prominent temperature changes and rapid shift from large-scale to convective precipitation are observed. Here, we examine the scaling between daily precipitation extremes and surface air temperature over Russia for 1966–2017 using meteorological station data and for 1979–2020 using ERA5 reanalysis. The precipitation-temperature relation is examined for total precipitation and, separately, for convective and large-scale precipitation types. In winter, we reveal a general increase in extreme precipitation of all precipitation types according to the C-C relationship. For the Russian Far East region, the stratiform precipitation extremes scale with surface air temperature following even super C-C rates, about two times as fast as C-C. However, in summer we find a peak-like structure of the precipitation-temperature scaling, especially for the convective precipitation in the southern regions. Extreme precipitation reaches their peak values at the temperature range between 15°C and 20°C. At higher temperatures, the negative scaling prevails. Analyzed data show a pronounced decrease in relative humidity with increasing surface temperatures beyond the 15–20°C threshold. This indicates that moisture availability is the major factor for the peak-shaped relationship between extreme precipitation and temperature revealed by our analysis.
... times higher than the global ocean warming trend of 0.11°C per decade during the period from 1971 to 2010 (Pachauri et al., 2015). A model simulation carried out by Meredith et al. (2015) showed that warming of the Black Sea surface plays an essential role in amplifying the extreme precipitation events on surrounding lands, including devastating event in 2012 in the town of Krymsk, located about 100 km east of the Crimean peninsula. Warmer sea surface temperature triggered deep moist convection, which increased precipitation by 300% in comparison to 1980s sea surface temperature (Meredith et al., 2015). ...
... A model simulation carried out by Meredith et al. (2015) showed that warming of the Black Sea surface plays an essential role in amplifying the extreme precipitation events on surrounding lands, including devastating event in 2012 in the town of Krymsk, located about 100 km east of the Crimean peninsula. Warmer sea surface temperature triggered deep moist convection, which increased precipitation by 300% in comparison to 1980s sea surface temperature (Meredith et al., 2015). Analysis of the water flux over the Mediterranean and Black Sea depicts an increasing deficit in the 1988-2005 period, due to enhanced evaporation (Romanou et al., 2010). ...
... To illustrate the absolute changes of moisture supply from each moisture source area, absolute amounts of the monthly moisture contribution were plotted. In contrast to the reported sea surface warming trend of the Mediterranean and Black Seas (e.g., Meredith et al., 2015;Pisano et al., 2020), temporal changes of evaporation and precipitation (Romanou et al., 2010;Skliris et al., 2018;Voskresenskaya & Vyshkvarkova, 2016), and observations of a multi-decadal salinification of the Mediterranean Sea (Skliris et al., 2018), no statistical significant trend can be identified for any major moisture source region from 1979 to 2017 by a non-parametric Mann-Kendall test. Meredith et al. (2015) hypothesized amplification of convective precipitation events in Mediterranean and Black Sea coastal regions due to the sea surface warming. ...
The atmospheric water cycle is a key component of the global energy and moisture exchange. In order to gain better understanding of the atmospheric processes and temporal variability and trends affecting precipitation in Crimea, we use a Lagrangian moisture source detection technique based on reanalysis data from the European Center for Medium‐Range Weather Forecasts. The study presents a quantitative picture of the major moisture sources that feed precipitation on the Crimean peninsula from February 1979 to January 2017. In total 51.3% of moisture stems from marine sources. Specifically, the main individual contributors are the Mediterranean Sea (15.3%), the Black Sea (14.4%), and the North Atlantic Ocean (13.9%). Continental moisture recycling contributes additional 46.9%. The amounts of moisture contribution from marine and continental sources and their respective moisture transport pathways are subject to strong seasonality. Winter precipitation in Crimea is predominantly sourced by the Mediterranean Sea. Long‐term temporal trends in contribution from any of the major moisture sources are absent during the study period. Statistically significant negative correlation between the North Atlantic Oscillation (NAO) index and contribution from moisture sources exists in winter for the Mediterranean (R = −0.22) and Black Seas (R = −0.23), and for the southern continental moisture source (R = −0.37). The North Atlantic Ocean moisture source exhibits a statistically significant positive correlation with NAO index during spring (R = 0.32).
... The current global warming is often stated (e.g., [22,23]) to be accompanied by an increase in the frequency and intensity of dangerous weather events and significant temperature anomalies in various regions of the planet. In temperate latitudes, the rise in the number of temperature and humidity anomalies is primarily associated with the ...
... The current global warming is often stated (e.g., [22,23]) to be accompanied by an increase in the frequency and intensity of dangerous weather events and significant temperature anomalies in various regions of the planet. In temperate latitudes, the rise in the number of temperature and humidity anomalies is primarily associated with the warming in the Arctic. ...
A 54-year-long series of continuous instrumental measurements of mass balance and its main components has already been accumulated at the Djankuat Glacier, which is representative of the Caucasus and the most studied glacier in Russia. The anomalies of these indicators in 2017/2018–2020/2021 were evaluated against an analysis of meteorological reasons that predetermined them. Each of the four balance years under consideration represents a particular anomaly of varying severity. As for conditions of mass income, three years saw accumulation higher than average, and in one year (2018/2019) it approached the norm. As for summer ablation conditions, similarly, in one season (2019) the melting differed from the average only slightly, but in the other three it was much higher. Consequently, in one year (2020/2021) the state of the glacier was close to normal, in another (2017/2018) the budget situation was much more favorable for Djankuat, and in the other two the final losses significantly exceeded the average annual mass loss rate. At the same time, in 2019/2020, an absolute record of ablation since the beginning of monitoring in 1967/1968 was recorded (4360 mm w.e.). Nevertheless, although negative mass balance values continue to be recorded annually, signs of an inevitable slowdown in the rate of glacier degradation in the Caucasus have appeared in the last 4-year-long period: the continued growth of winter snow accumulation overlaps the ongoing intensification of summer melting. The growth of debris cover in terms of area and thickness also affects this mass loss slowdown to some extent. This inhibits ablation, exerting a heat-insulating effect. Because of this, the congruence of mass balance parameters vs. altitude curves is distorted. Also, a tendency toward increasing annual glacier mass turnover was revealed for the last half-century. This fact gradually increases the energy of glaciation and indirectly indicates a weakening of continentality in the climate of the Caucasian highlands.
... The general idea of analogues is to find a close to identical present and past dynamic situation, for instance a storm that caused a flood, to study the difference that climate change must have caused in the impact of the present event compared to the past event. Another way of conditional attribution is by dynamically constraining through boundary conditions applied to a regional model (Meredith et al., 2015) or by controlling the initial conditions in a weather forecast model (Patricola and Wehner, 2018). A new development along that line is the application of storylines in a weather forecast model by Leach et al. (2021), which is beneficial for high-resolution but short timescale event attribution, as it depends on short lead times to create the atmospheric conditioning. ...
... In previous applications of the storyline approach, individual extreme weather events have been dynamically constrained through boundary conditions applied to a regional model (Meredith et al., 2015) or by controlling the initial conditions in a weather forecast model (Patricola and Wehner, 2018). More recently, nudging the free atmosphere to reanalysis data (leaving the boundary layer free to respond) has been applied in a global medium-resolution atmospheric model to constrain the dynamical conditions leading to heatwaves, first to determine the effect of soil moisture changes on selected recent heatwaves (Wehrli et al., 2019) and subsequently to determine the effect of past and projected future warming on the 2018 Northern Hemisphere heatwave (Wehrli et al., 2020). ...
https://www.publicatie-online.nl/uploaded/flipbook/162174-Linda-van-Garderen/
Heatwaves, droughts, floods, storms and other types of extreme weather events cause significant human suffering as well as material and economic damages. Discerning how climate change is influencing different extremes is a prerequisite to understand what we may expect in the future and how we can reduce loss of life and damage. A generally accepted method for attributing extreme weather events to climate change is the probabilistic approach, which is a statistical analysis of the unusual dynamical conditions that steer the extreme. It computes the probability of such an event in a world with and without climate change. However, the signal-to-noise ratio of the dynamical aspects of climate change appears to be small, which means that the results of the unconditional probabilistic approach are generally quite uncertain. The thermodynamic aspects of climate change, on the other hand, are readily apparent from observations and are far more certain since they are anchored in agreed-upon physical understanding. A novel conditional attribution approach, which is not based on probabilities, is the ‘storyline’ approach which quantitatively estimates the magnitude of thermodynamic aspects of climate change, taking the dynamical conditions as a given. Each storyline places a particular extreme event in different circumstances, e.g. a world without or with increased global warming, and quantifies the effect climate change has on the thermodynamic aspects of the event. The main goal of the work presented here is thus to obtain high-quality conditional climate change attribution of singular extreme weather events by developing a conditional storyline method.
The spectrally nudged event storylines presented here have globally enforced dynamical conditions by spectrally nudging the large-scale vorticity and divergence in the free atmosphere towards reanalysis data, leaving the lower atmosphere free to respond. Historical extreme weather events are then simulated in three storylines: 1) the factual storyline, which is the world as we know it with a changing climate, 2) the pre-industrial counterfactual storyline which is defined as an imagined modern world without climate change and 3) the plus 2 °C counterfactual storyline which is a world that might be, a world with 2 °C global warming compared to pre-industrial.
The results show a consistent increase in both global average temperature and precipitation due to climate change, which is in line with well established results using unconditional methods and indicates that nothing is lost when applying a conditional setup. Regional seasonal precipitation characteristics are changing, for example the Mexican monsoons of 2012 and 2014 became dryer and the Indian monsoons of 2011 and 2014 became wetter. Temperature extremes show robust results on small spatial and temporal scales. The 2003 European heatwave was on average 0.6 °C warmer due to climate change and the 2010 Russian heatwave was on average 2 °C warmer which is an amplified climate-change signal. The southeastern South American drought of 2011/2012 was at risk of intensification due to climate change, but was counter balanced by the general background wetting trend also due to climate change.
Spectrally nudged event storylines provide both a continuous and specific event attribution by enabling a robust separation of climate change from natural variability on small temporal and spatial scales. The drought example proves the method is capable of distinguishing between opposing climate signals on different time scales. The method is widely applicable as it is not limited to the technical setup presented here, which means a convection permitting model can be included to enable accurate attribution of local precipitation extremes. Moreover, the ensemble size required for robust results is small, reducing computational costs. The methodology has the great potential to be used for realistic stress testing of resilience strategies for climate impacts when coupled to an impact model. Furthermore, the spectrally nudged event storylines can be used for operationalising extreme event attribution, which until now has been difficult. In conclusion, the nudged global storyline method is an important step towards a holistic approach within the attribution of individual extreme events, which can quantify the role of both dynamical variability and known thermodynamic aspects of climate change, and the interplay between them.
... Hoerling et al. (10) used two seasonal forecast ensembles to examine the predictability of the 2011 Texas drought/heatwave within a comprehensive attribution analysis involving several different types of climate simulation. Meredith et al. (11) used a triply nested convection-permitting regional forecast model to investigate the role of historical sea surface temperature (SST) warming within an extreme precipitation event. They conditioned their analysis on the large-scale dynamics of the event through nudging in the outermost domain. ...
... While this does provide useful information, it does not answer the question of how much more likely anthropogenic activities have contributed to the specific heatwave that occurred, but rather the question of how much more likely anthropogenic activities have contributed to a mixture of events that share one or more characteristics. Studies have attempted to provide a more satisfactory answer to this first question by including a level of conditioning on the set of events considered by using circulation analogs (31) or by nudging model simulations toward the specific dynamical situation that occurred during the event in question (11,12). Here we are evidently performing an attribution study of the specific recordbreaking heatwave that occurred in February 2019 due to the use of these successful forecasts that captured not only the heat experienced at the surface, but also the dynamical drivers behind the heat. ...
Significance
The question of how humans have influenced individual extreme weather events is both scientifically and socially important. However, deficiencies in climate models’ representations of key mechanisms within the process chains that drive weather reduce our confidence in estimates of the human influence on extreme events. We propose that using forecast models that successfully predicted the event in question could increase the robustness of such estimates. Using a successful forecast means we can be confident that the model is able to faithfully represent the characteristics of the specific extreme event. We use this forecast-based methodology to estimate the direct radiative impact of increased CO 2 concentrations (one component, but not the entirety, of human influence) on the European heatwave of February 2019.
... Climate change alters atmospheric circulation patterns (Herrera-Lormendez et al., 2023) and increases sea surface temperatures (SST), notably in the Mediterranean Sea (Pastor et al., 2020;Pastor & Khodayar, 2023), contributing to significant high-impact weather events (González-Alemán et al., 2023;Lau et al., 2016;Ludwig et al., 2013;Meredith et al., 2015). The increase in SST influences intensity and frequency of marine heatwaves (MHW). ...
A severe hailstorm that occurred in Spain on 30 August 2022, caused material and human damage, including one fatality due to giant hailstones up to 12 cm in diameter. By applying a pseudo‐global warming approach, here we evaluate how a simultaneous marine heatwave (and anthropogenic climate change) affected a unique environment conductive to such giant hailstones. The main results show that the supercell development was influenced by an unprecedented amount of convective available energy, with significant contributions from thermodynamic factors. Numerical simulations where the marine heatwave is not present show a notable reduction in the hail‐favorable environments, related mainly to modifications in thermodynamic environment. Our simulations also indicate that the environment in a preindustrial‐like climate would be less favorable for convective hazards and thus the hailstorm event would likely not have been as severe as the observed one, being possible to perform a novel attribution of such kind.
... The accumulation rate history at Mt. Elbrus can be inferred from depth profiles of annual layer thicknesses in the WP ice core when corrected for thinning of ice layers due to ice flow. Density measurements, as reported by Mikhalenko et al. (2015), reveal kinks in the curves of the studied ice cores, corresponding to critical density values of 550 and 840 kg m −3 (Maeno and Ebinuma, 1983). The third critical density value of 730 kg m −3 , which marks the transition of firn into ice by complete closure of air inclusions, is not clearly visible on the density curve. ...
In this study, we present a seasonally resolved accumulation record spanning from 1750 to 2009 Common Era (CE), based on a 181.8 m ice core obtained from the Elbrus Western Plateau in the Caucasus. We implemented various methods to account for uncertainties associated with glacier flow, layer thinning, and dating. Additionally, we applied a novel approach to calculate a seasonal calendar for meteorological data, enabling comparison with ice core records. The reconstructed accumulation data were compared with available meteorological data, gridded precipitation records, and paleo-reanalysis data. Reconstructed accumulation is representative for a large region south of the Eastern European plain and Black Sea region with summer precipitation being the primary driver of precipitation variability. We identified a statistically significant relationship between changes in regional precipitation and fluctuations in the North Atlantic Oscillation (NAO) index, which is, however, not stable over the entire period covered by the ice core.
... Bu hataların m n m ze ed leb lmes ç n atılab lecek adımlardan b r , düşük tems l oranına sah p olan ekstrem olayların arka planında yer alan ve meydana gelmeler nde etk s olan f z ksel etk leş mler n ncelenmes olarak değerlend r leb l r. Bu doğrultuda, ortalama den z suyu sıcaklığı le ekstrem olaylar arasındak l şk ler nceleyen yayınlar d kkat çek c d r [11,12]. Ayrıca, y ne l teratürde, Hazar Den z 'n hesaba katan kl msel modeller n Türk ye üzer nde daha başarılı oldukları görülmekted r [13]. ...
Deniz suyu sıcaklığının atmosferik değişkenlerle etkileşiminin incelenmesi sırasında zamansal kaymalar görülebilmektedir. Bu kaymalar, çalışma yapılan bölge ile sıcaklığı incelenen deniz arasındaki topoğrafya, mesafe ve atmosferik parametrelere bağlı olarak değişkenlik göstermektedir. Aynı zamanda, deniz suyu sıcaklığı ile ekstrem meteorolojik olaylar arasında ilişki kurmuş olan çalışmalar literatürde yer almaktadır. İklim değişikliğinin bir sonucu olarak ekstrem meteorolojik olayların frekanslarının artması da göz önünde bulundurulduğunda bu zamansal kaymalarının yerel ölçekte analiz edilmeleri önem kazanmaktadır. Bu çalışmada, Türkiye’deki yağışlar üzerinde etkili olduğu değerlendirilen Hazar, Karadeniz, Marmara Denizi, Ege Denizi ve Doğu Akdeniz’deki deniz suyu sıcaklıklarının anomalileri ile Türkiye’deki 26 havzadaki günlük toplam yağışların ilişkileri incelenmiştir. Çalışma dönemi olarak Ocak-1982 ile Haziran-2020 arası kullanılmıştır. Deniz suyu sıcaklığı anomalileri için NOAA’nın uzaktan algılama tabanlı 0,25 derecelik Optimum İnterpole Günlük Deniz Suyu Sıcaklığı Analizleri (2. sürüm) kullanılmış olup günlük toplam yağış verileri ise ERA5 günlük agrege veriseti üzerinden temin edilmiştir. Çalışma kapsamında her denizin her havza üzerindeki ilişkisi 0-30 gün aralığındaki zaman kaymalarına göre ayrı ayrı değerlendirilerek en iyi sonuç veren zamansal kayma, en yüksek mutlak korelasyon baz alınarak seçilmiştir. Çalışma kapsamında pearson ve spearman korelasyon katsayıları hesaplanmıştır. Bulgulara göre deniz suyu sıcaklığındaki anomaliler ile günlük toplam yağış arasındaki ilişkinin yüksek bir lineerite göstermediği fakat nispeten daha iyi bir monotonik bir etkileşim içerdiği ifade edilebilir. Ayrıca, lineer ve monotonik etkileşimlerin zamansal kaymalarını farklı olduğu durumlarda genellikle önce lineer etki görülmekte, ardından ise monotonik etki gözlemlenmektedir. Dikkat çekici bir başka bulgu olarak ise Hazar Denizi’ndeki anomalilerin Van Gölü Havzası’nın toplam günlük yağışı üzerinde 24 saat içinde, Aras Havzası’ndaki toplam günlük yağış üzerinde ise bir gün sonra hem lineer hem de monotonik olarak etkili olduğu bulunmuştur.
English:
Temporal shifts can be observed when examining the interaction of sea surface temperature with atmospheric variables. These shifts vary depending on the topography, the distance between the study area and the sea whose surface temperature is examined, and atmospheric parameters. At the same time, studies in the literature have established a relationship between sea surface temperature and extreme meteorological events. Considering the increased frequency of extreme meteorological events due to climate change, analyzing these temporal shifts on a local scale is essential. This study examined the relationships between sea surface temperature anomalies in the seas considered influential on precipitation in Türkiye (Caspian, Black Sea, Marmara Sea, Aegean Sea, and Eastern Mediterranean Sea) and the daily total precipitation in 26 basins in Türkiye. The study period was used between January 1982 and June 2020. NOAA's remote sensing-based 0.25-degree Daily Optimum Interpolation Sea Surface Temperature (2nd edition) was used for sea water temperature anomalies, and daily total precipitation data were obtained from the ERA5 daily aggregate dataset. Within the scope of the study, the relationship of each sea on each basin was individually evaluated according to temporal shifts in the range of 0-30 days. Pearson and Spearman correlation coefficients were calculated within the study's scope. The temporal shift with the best results was selected based on the highest absolute correlation. According to the results, the relationship between sea surface temperature anomalies and daily total precipitation does not show a high linearity but contains a relatively stronger monotonic interaction. In addition, in cases where the temporal shifts of linear and monotonic interactions are different, the linear influence is generally observed first, and then the monotonic effect is observed. Another remarkable finding is that the anomalies in the Caspian Sea have linear and monotonic relations to the total precipitations of Lake Van Basin (within 24 hours) and Aras Basin (with a temporal shift of one day).
... Cattiaux et al., 2010), analogues (Ginesta et al., 2023;Faranda et al., 2022), nudging a weather or climate model (e.g. Meredith et al., 2015;van Garderen et al., 2021;Sánchez-Benítez et al., 2022), and forecast-based approaches (e.g. Wehner et al., 2019;Leach et al., 2021). ...
... In particular, the increase in precipitation and the related rise in summer accumulation during 2000-2009 may be a response to the increase in sea surface temperature in the eastern part of the Black Sea which could be a cause of the observed precipitation increase in southern Russia (Aleshina et al., 2018). The role of positive sea surface temperature anomalies in the Black Sea in the formation of synoptic situations leading to extreme precipitation in the Western Caucasus is clearly demonstrated in the study by (Meredith et al., 2015). Additionally, the increase in summer accumulation 450 in the first decade of the 21st century is generally consistent with the overall positive trend of convective precipitation (Chernokulsky et al., 2019). ...
In this study, we present a seasonal-resolution accumulation record spanning the period from 1750 to 2009 Common Era (CE), based on a 181.8-m ice core obtained from the Elbrus Western Plateau in the Caucasus. We implemented various methods to account for uncertainties associated with glacier flow, layer thinning, and dating. Additionally, we developed a novel approach to calculate a seasonal calendar for meteorological data, enabling comparison with ice core records. The reconstructed accumulation data were compared with available meteorological data, gridded precipitation records, and paleo reanalysis data. Reconstructed accumulation is representative for a large region south of Eastern European plain and Black sea region. Summer precipitation was found to be the primary driver of precipitation variability. We identified a statistically significant but unstable in time relationship between changes in precipitation in the region and fluctuations of the North Atlantic Oscillation (NAO) index.
... The concept of event-based storyline differs from that of climate storyline introduced above, as the former refers to a plausible individual event (e.g., a very intense storm or crop failure and its consequences), and the latter to a plausible future climate over a long period (e.g. 30 years). The concept of eventbased storylines has been employed to study several types of rare highimpact events over recent years [68][69][70][71][72] . Event-based storylines can be used to improve our understanding of the physical drivers of very extreme events and, through collaborations between climate scientists and impact modellers, the event's socio-economic consequences 66 . ...
Societally relevant weather impacts typically result from compound events, which are rare combinations of weather and climate drivers. Focussing on four event types arising from different combinations of climate variables across space and time, here we illustrate that robust analyses of compound events — such as frequency and uncertainty analysis under present-day and future conditions, event attribution to climate change, and exploration of low-probability-high-impact events — require data with very large sample size. In particular, the required sample is much larger than that needed for analyses of univariate extremes. We demonstrate that Single Model Initial-condition Large Ensemble (SMILE) simulations from multiple climate models, which provide hundreds to thousands of years of weather conditions, are crucial for advancing our assessments of compound events and constructing robust model projections. Combining SMILEs with an improved physical understanding of compound events will ultimately provide practitioners and stakeholders with the best available information on climate risks.
... Our method is flexible and could, for example, be used as a complement to extreme event attribution studies conditioned on the circulation (35,36), or to the storyline approach (37). The latter approach has been criticized for not taking into account the role of climate change-induced circulation changes (38), and we provide a readily applicable toolkit to address this problem. ...
Diagnosing dynamical changes in the climate system, such as those in atmospheric circulation patterns, remains challenging. Here, we study 1950 to 2021 trends in the frequency of occurrence of atmospheric circulation patterns over the North Atlantic. Roughly 7% of atmospheric circulation patterns display significant occurrence trends, yet they have major impacts on surface climate. Increasingly frequent patterns drive heatwaves across Europe and enhanced wintertime storminess in the northern part of the continent. Over 91% of recent heatwave-related deaths and 33% of high-impact windstorms in Europe were concurrent with increasingly frequent atmospheric circulation patterns. While the trends identified are statistically significant, they are not necessarily anthropogenic. Atmospheric patterns which are becoming rarer correspond instead to wet, cool summer conditions over northern Europe and wet winter conditions over continental Europe. The combined effect of these circulation changes is that of a strong, dynamically driven year-round warming over most of the continent and large regional and seasonal changes in precipitation and surface wind.
... Other types of attribution studies have shown that, e.g., the severe Sahel drought in the 1970s and 80s was mainly driven by a natural fluctuation of North Atlantic sea surface temperatures (Giannini, 2003). Similar sensitivity experiments have highlighted the role of low soil moisture for the severity of the 2003 European heatwave (Fischer et al., 2007), and the influence of Black Sea warming on a devastating rainfall event in Russia (Meredith et al., 2015). ...
Climate is changing and human influence has been the dominant cause of global warming since the mid-twentieth century. Climate change is mostly experience at the regional scale with impacts affecting ecosystems and many societal and economic sectors. Successful adaptation to climate change is thus important to meet the United Nations Development Goals (SGDs), and several SDGs are directly relevant for mitigating climate change. Regional climate information is relevant for many users ranging from climate impact modellers to decision makers. But the provision of climate information is scientifically challenging. Here I lay out the process of regional climate research with a focus on the construction of user relevant information. I start with an overview of the context of regional climate research and then discuss the foundations and sources of climate information in detail, including the use of observations, climate models and process understanding. A synthesis highlights the importance of user collaboration and integration of different sources of climate information to distil relevant and trustworthy information. I argue that international collaboration between scientists is also key in this process.
... В [108] проведены расчеты с региональной моделью атмосферы высокого пространст-венного разрешения WRF по моделированию экстремальных осадков в районе г. Крымска 6-7 июля 2012 г. ...
This review outlines the most significant results of research in dynamic meteorology performed by Russian scientists in 20152018. It is part of the Russian National Report on Meteorology and Atmospheric Sciences submitted to the International Association of Meteorology and Atmospheric Sciences (IAMAS). The review is supplemented by a list of main publications of Russian scientists on dynamic meteorology in 20152018.
... In terms of the Black Sea, it is the largest land-locked basin in the world and has a maximum depth of 2,200 m, a surface area of 4.2 × 10 5 km 2 and a volume of 5.3 × 10 5 km 3 (Özsoy and Ünlüata, 1997). Due to the significant sea-land interactions, numerous researches were conducted up till now by focusing on the impacts of the Black Sea surface temperatures to the precipitation/snowfall occurrences (Kindap, 2010;Bozkurt and Sen, 2011;Baltacı et al., 2015;Meredith et al., 2015;Baltacı et al., 2017;Akkoyunlu et al., 2019;Baltaci et al., 2020). Apart from these studies, it is well known that the Black Sea sourced fog events frequently affect the Black Sea coasts of Turkey and cause disruption in transportation. ...
In this study, climatological properties of fog types, their association with surrounding environment and background synoptic mechanisms triggering fog formation are investigated for Turkey. For this purpose, SYNOP (surface synoptic observations) and METAR (meteorological aerodrome report) codes of 105 stations are used for the period 2014–2019. While fog types are separated to the fog, quasi‐fog, and dense fog events according to horizontal visibility conditions, stations are classified as mountain, seaside, urban, and rural by considering the surrounding environment. Synoptic mechanisms causing the occurrence of springtime marine fog events over Black Sea are investigated using NCEP/NCAR Reanalysis. According to the main results, highest numbers of fog events are observed during winter, spring, fall, and summer months, respectively. Radiation fog frequently occurs in the mountainous regions (i.e., central and eastern part) of Turkey during winter. As a result of the rainfall during daytime, significant amount of moisture begins to saturation at night owing to rapid cooling processes and fog layer forms just above the surface. During spring, Black Sea‐effect marine fog events are frequently shown in the seaside stations of the Black Sea and northeastern Marmara regions. On the western Black Sea, winds from northeast enable rising of cold sea water to the surface (upwelling) and transfer it to the relatively warm land areas. Denser humid and cold air settling on the surface forces warm land air to rise. Additionally, warm air advection at 850 hPa (low level) creates a thick inversion layer over the region. For the eastern Black Sea, relatively cold and humid sea surface transferred to the coasts by light local northwesterly winds encounters with the mountain barrier and is trapped in the region. Furthermore, southerly winds (850 hPa) cross over the Kaçkar Mountains cause föehn effect and generate an inversion layer over the fog layer.
... A typical study of this type was carried out by Wehrli et al. (2019), who quantitatively estimated the contribution of recent GHG emissions, atmospheric circulation, the land surface, and oceans to five heatwaves from 2010 to 2016 based on the Community Earth System Model. The last category is based on regional climate models, from which high-resolution simulation results can be obtained (Meredith et al., 2015;Michaelis et al., 2019;Reed et al., 2020). One useful method in this category is the "pseudo-global warming" method, in which control simulations are conducted to reproduce the observed extreme events, and then "deltas" are applied to the initial and boundary conditions to re-simulate and assess changes in the characteristics of the event (Michaelis et al., 2019). ...
There have been considerable high-impact extreme events occurring around the world in the context of climate change. Event attribution studies, which seek to quantitatively answer whether and to what extent anthropogenic climate change has altered the characteristics—predominantly the probability and magnitude—of particular events, have been gaining increasing interest within the research community. This paper reviews the latest approaches used in event attribution studies through a new classification into three major categories according to how the event attribution question is framed—namely, the risk-based approach, the storyline approach, and the combined approach. Four approaches in the risk-based framing category and three in the storyline framing category are also reviewed in detail. The advantages and disadvantages of each approach are discussed. Particular attention is paid to the ability, suitability, and applicability of these approaches in attributing extreme events in China, a typical monsoonal region where climate models may not perform well. Most of these approaches are applicable in China, and some are more suitable for analyzing temperature events. There is no right or wrong among these approaches, but different approaches have different framings. The uncertainties in attribution results come from several aspects, including different categories of framing, different conditions in climate model approaches, different models, different definitions of the event, and different observational data used. Clarification of these aspects can help to understand the differences in attribution results from different studies.
... Recent modeling studies have shown amplification of extreme precipitation under a warmer ocean condition in some coastal regions (e.g., Dong et al., 2019;Meredith et al., 2015;Volosciuk et al., 2016). Generally, warmer SST leads to enhanced evaporation and atmospheric moisture transport with potential impacts on such coastal extreme precipitation (e.g., Tomassini & Elizalde, 2012;Volosciuk et al., 2016). ...
This study investigated the impact of sea surface temperature (SST) on extreme precipitation events in North Japan and its relation to synoptic weather patterns using large‐ensemble climate simulations. Eight weather patterns were identified by applying cluster analysis to sea level pressure anomalies for selected days with extreme precipitation derived from a 3000‐year historical climate experiment. Interannual variability of extreme precipitation days associated with two specific weather patterns, characterized by a weak low‐pressure system and an atmospheric river (AR), significantly correlated with that of SST over the Sea of Japan, with a correlation coefficient of 0.37 and 0.53, respectively. In higher SST years, the increased atmospheric moisture can increase the extreme precipitation in the inland area of Hokkaido for the weather pattern associated with a weak low‐pressure system, whereas it appears to enhance orographic precipitation along the western slopes of mountains for the pattern resembling AR. These results indicate that the effect of local SST on extreme precipitation strongly depends on the weather patterns. In the future projection, the two weather patterns that are sensitive to SST over the Sea of Japan show a sharp increase of more than 4 times under the 4 K warming climate. Moreover, the magnitude of extreme precipitation was also found to increase with SST, broadly following the Clausius–Clapeyron relation in both historical and warmed climates. These results suggest increased risk of heavy precipitation associated with such weather patterns over North Japan in the future.
... Îäíà êî ïðè îò ñó òñòâèè ñòà òèñ òè ÷åñ êè çíà ÷è ìî ãî òðåí äà â ÷àñ òî òå Îß [4], äîñ òî âåð íûõ äàí íûõ îá èç ìå íå íèè èí òåí ñèâ íîñ òè (ìàñ øòà áîâ) ýòèõ ÿâ ëå íèé çà íå ñêîëü êî äå ñÿòêîâ ëåò (îá ùåï ðè íÿ òûé ïå ðè îä îöåí êè ñðåä íèõ êëè ìà òè ÷åñ êèõ ïî êà çà òåëåé -30 ëåò) ôàêò èõ âîç íèê íî âå íèÿ ìî aeåò áûòü ñëå äñòâè åì åñ òåñ òâåííîé èç ìåí ÷è âîñ òè êëè ìà òà. Âîï ðîñ àò ðè áó öèè îò äåëü íî ãî ÿâ ëå íèÿ èç ìå íåíèþ êëè ìà òà òðå áó åò òùà òåëü íî ãî àíà ëè çà [17]. ...
The development of territorial plans for adaptation to climate change requires an analysis of the combined impact of emerging primary climate hazards. At the initial stage, this should be done at the level of the subjects of the Russian Federation to identify priority regions for the development and implementation of adaptation measures. At the same time, the increase in the annual social and economic damage caused by climate change is the main criterion for financing additional measures for mitigation and adaptation to climate change. In this paper, primary climate hazards quantified by trends in the following five indicators: - the average annual temperature and annual precipitation for 1976-2019; - the number of days of the calendar year with temperatures above the 90th percentile for the summer season for 1976-2018; - the number of extreme weather events in 1991-2019 and extreme events on soil drought in 2004-2019 that caused social or economic damage. A comprehensive analysis of these indicators indicates that the most densely populated and leading agricultural regions of the central and southern regions of the European part of Russia are under the increasing pressure of modern climate change. This is true even in the absence of a statistically significant trend in the total number of extreme weather events that caused material damage on the territory of the Russian Federation in the 21st century, as shown in this paper.
... Meredith [4] , 2015; Onol vd. [5] , 2019). ...
ÖZET
Değişen iklim şartları ve Karadeniz deniz yüzey sıcaklığı artışı kaynaklı olarak son yıllarda özellikle Temmuz ve Ağustos aylarında Orta ve Doğu Karadeniz sahil şeridinde aşırı yağış kaynaklı meydana gelen hadiseler sel ve heyelan gibi afetlere yol açarak can ve mal kayıplarına neden olmaktadır. Bu periyot içerisinde 8-9 Ağustos 2018 tarihlerinde Ordu'nun Perşembe, Ünye, Fatsa ve Çaybaşı ilçelerinde meydana gelen yağış da etkili olarak yaralanmalara, su baskınlarına, farklı ilçelerde köprülerin yıkılmasına ve harmana serilen fındıkların denize akması gibi can ve mala zarar verici olaylara sebep olmuştur. Bu çalışmada 8-9 Ağustos 2018 tarihlerinde Ordu'nun ilçelerinde meydana gelen yağış ve sel olayı Meteoroloji Genel Müdürlüğü (MGM)'den elde edilen 5 istasyona ait veriler ve MSG uydu verileri ile analiz edilmiştir. Aynı zamanda meydana gelen hadise WRF modeli ile simüle edilmiştir. Meydana gelen yağışın detaylı analizi ile ilgili olarak, belirtilen bölgeleri kapsayan radar ürünlerinin incelenmesi neticesinde bu iki güne dair yağış tipine uygun Z-R ilişkisi literatür taraması sonucu tespit edilerek, belirlenen denklemde Samsun radarı reflektivite değerleri kullanılmıştır. Bu işlem sonucunda hesaplanan yağış miktarının gün içerisinde ulaştığı maksimum değerleri SRI ürünü aracılığıyla gösterilmiştir. Hesaplanan yağış miktarlarının gün içerisindeki değerlerinin istasyon gözlemleri ile de karşılaştırılması yapılarak, kullanılan Z-R ilişki denkleminin tutarlılığı analiz edilmiştir. Bunlara ek olarak Uydu ve YTTS verileri ile de bölgede meydana gelen yağış tipi tespitinde ve yağışın yoğunlaştığı bölgelerin analizinde kullanılmıştır.
Anahtar Kelimeler-Ordu; Doğu Karadeniz; konvektif yağış.
... За последние 7 лет на территории юга России произошло несколько катастрофических наводнений. В работе [6] авторы на основе данных метеонаблюдений Средиземноморья и Причерноморья за последние 30-40 лет и при помощи составленной ими климатической модели пришли к выводу о том, как глобальное потепление и стабильный рост температур воздуха и морской воды влияли на региональный климат. Дестабилизация системы ветров над Черным морем летом 2012 г. и особое стечение других климатических факторов привели в тот сезон к тому, что уровень осадков на юго-восточном Черноморье вырос на 300 %, то есть в три раза. ...
... The Mediterranean and the Black Sea regions have seen a steady increase in summertime SST since the early 1980s, by over 2°K in some places (Meredith et al., 2015). The Mediterranean Sea and the Black Sea act as a reservoir of heat and moisture which modifies and destabilizes the lower layers of the atmosphere through sensible and latent-heat fluxes. ...
Absolute gravity is of utmost importance for the realization of the unit of force, pressure according to
their definition as well as mass unit according to the new definition to be made in 2018, and also for the
researches in the field of geodesy and geology. Thus it is a necessity for the realization of the unit of
absolute gravity in metrology. Prove of the quality of the absolute gravity measurements in the country
and their validation is ensured by participation in international comparisons. This paper presents the
information about the establishment of gravity and participated international comparison on gravity.
... For instance, Wehrli et al. (2019) quantify the influence of sea surface temperatures (SSTs) and soil moisture to five recent heat waves in both subtropical and extratropical regions using global atmospheric simulations with atmospheric circulation nudged to reanalysis (using grid-point nudging). Based on nudged regional model experiments, Meredith et al. (2015) have shown that recent Black Sea sea surface temperature (SST) warming has been a key contributor and amplifier in the magnitude of the Krymsk July 2012 precipitation extreme. Another recent example about heat wave attribution is the application of a methodology based on spectral nudging of the free atmosphere within a global model and applied to both factual and counterfactual worlds (van Garderen et al., 2021). ...
Here we demonstrate that dynamical adjustment allows a straightforward approach to extreme event attribution within a conditional framework. We illustrate the potential of the approach with two iconic extreme events that occurred in 2010: the early winter European cold spell and the Russian summer heat wave. We use a dynamical adjustment approach based on constructed atmospheric circulation analogues to isolate the various contributions to these two extreme events using only observational and reanalysis datasets. Dynamical adjustment results confirm previous findings regarding the role of atmospheric circulation in the two extreme events and provide a quantitative estimate of the various dynamic and thermodynamic contributions to the event amplitude. Furthermore, the approach is also used to identify the drivers of the recent 1979–2018 trends in summer extreme maximum and minimum temperature changes over western Europe and western Asia. The results suggest a significant role of the dynamic component in explaining temperature extreme changes in different regions, including regions around the Black and Caspian seas as well as central Europe and the coasts of western Europe. Finally, dynamical adjustment offers a simple and complementary storyline approach to extreme event attribution with the advantage that no climate model simulations are needed, making it a promising candidate for the fast-track component of any real-time extreme event attribution system.
... Наибольший положительный (и статистически значимый) линейный тренд повторяемости отмечен над внутренними морями, причем наибольшие значения тренда выявлены в июле-августе, когда в данном регионе наблюдается наибольшее количество водных смерчей. Одной из основных причин роста конвективной неустойчивости является рост температуры морской поверхности, который за последние 30 лет составил более 2 градусов (Meredith et al. 2015). Повторяемость критических значений индексов статистически значимо растёт и на юге Дальнего Востока (где в последнее время также наблюдаются смерчи и отмечен значимый рост величины и интенсивности ливневых осадков). ...
This article presents the results of the analysis of some application-relevant climatic indices, calculated on
data of 93 meteorological stations in Kazakhstan for 2017, using the base period from 1981 to 2010, and trends
for the period 1976–2017. Before indices computing all daily input data were checked for quality and homoge�neity. In this study the RHTest software was used for daily air temperature data and the RHtests_dlyPrcp soft�ware for daily precipitation data. These software packages developed by the experts of the WMO Commission
for Climatology
Rapid rise of salinity is observed in the Black Sea in recent years, with the largest positive trend (0.07 psμ per 10 years) detected in the pycnocline. We use long-term hydrological measurements for 1985–2019 to show that salinity of pycnocline has intense seasonal and interannual variability modulated by the mechanical and convective mixing. In the warm period of a year, shear turbulence driven by strong winds and intense geostrophic currents causes the penetration of warm waters into the lower density layers. This is accompanied by the rise in their salinity, the source of which is the deep saline waters situated below the halocline. This process is most intense in the areas of downwelling and intensifies in the autumn period, when thermal stratification is relatively weak. Another important reason is the entrainment of salty Mediterranean waters in the upper part of the Black Sea halocline, which is modulated by the deepening of the seasonal thermocline near the Bosphorus strait and mechanical mixing.
The increase of salinity is compensated during cold winters, when convective mixing transports fresher water influenced by river discharge into lower density layers of the basin and causes a decrease in pycnocline salinity. This process is most intense in the center of the cyclonic gyres, where pycnocline is located closer to the surface and winter temperature reaches minimal values.
Due to the long-term warming of the Black Sea, the process of freshening of deep layers now is observed only in rare cold years. At the same time, an intensification of wind speed, vorticity, and geostrophic circulation processes promote the blurring of the halocline and the rise of the salinity of the Black Sea upper layers. Such rise begins after 2007 in the upper part of Black Sea halocline (depth 50–100 m) and is traced down to 250 m by 2020.
Heavy precipitation is a challenging phenomenon with high impact on human lives and infrastructure, and thus a better modelling of its characteristics can improve understanding and simulation at climate timescales. The achievement of convection-permitting modelling (CPM) resolutions (Δx<4 km) has brought relevant advancements in its representation. However, further research is needed on how the very high resolution and switching-off of the convection parameterization affects the representation of processes related to heavy precipitation. In this study, we evaluate reanalysis-driven simulations for the greater Alpine area over the period 2000–2015 and assess the differences in representing heavy precipitation and other model variables in a CPM setup with a grid size of 3 km and a regional climate model (RCM) setup at 25 km resolution using the COSMO-CLM model. We validate our simulations against high-resolution observations (E-OBS (ENSEMBLES observations), HYRAS (Hydrometeorologische Rasterdatensätze), MSWEP (Multi-Source Weighted-Ensemble Precipitation), and UWYO (University of Wyoming)). The study presents a revisited version of the precipitation severity index (PSI) for severe event detection, which is a useful method to detect severe events and is flexible for prioritizing long-lasting events and episodes affecting typically drier areas. Furthermore, we use principal component analysis (PCA) to obtain the main modes of heavy precipitation variance and the associated synoptic weather types (WTs). The PCA showed that four WTs suffice to explain the synoptic situations associated with heavy precipitation in winter, due to stationary fronts and zonal flow regimes. Whereas in summer, five WTs are needed to classify the majority of heavy precipitation events. They are associated with upper-level elongated troughs over western Europe, sometimes evolving into cutoff lows, or with winter-like situations of strong zonal circulation. The results indicate that CPM represents higher precipitation intensities, better rank correlation, better hit rates for extremes detection, and an improved representation of heavy precipitation amount and structure for selected events compared to RCM. However, CPM overestimates grid point precipitation rates, which agrees with findings in past literature. CPM systematically represents more precipitation at the mountain tops. However, the RCMs may show large intensities in other regions. Integrated water vapour and equivalent potential temperature at 850 hPa are systematically larger in RCM compared to CPM in heavy precipitation situations (up to 2 mm and 3 K, respectively) due to wetter mid-level conditions and an intensified latent heat flux over the sea. At the ground level, CPM emits more latent heat than RCM over land (15 W m−2), bringing larger specific humidity north of the Alps (1 g kg−1) and higher CAPE (convective available potential energy) values (100 J kg−1). RCM, on the contrary simulates a wetter surface level over Italy and the Mediterranean Sea. Surface temperatures in RCM are up to 2 ∘C higher in RCM than in CPM. This causes outgoing longwave radiation to be larger in RCM compared to CPM over those areas (10 W m−2). Our analysis emphasizes the improvements of CPM for heavy precipitation modelling and highlights the differences against RCM that should be considered when using COSMO-CLM climate simulations.
—Flash floods are one of the most dangerous hydrometeorological events all over
the World. In the current paper stochastic parameters of flash floods formation are studied
on the basis of data on flash floods in 1990–2021 in the small river basins of the Caucasus
and Crimea Black Sea Coast. The main factor of flash floods formation is heavy rain, but in
some cases its occurrence could depend on critical combination of various factors. Flash
floods are usually formed in summer-autumn period in the studied region with the maximum of observed events in August. They are characterised by very rapid water level rise of
about 1.2–1.3 m/h. Sediment yield during one flash flood could be compared with mean
annual values. Statistical analysis of precipitation long ranges demonstrates probability of
more often flash floods occurrence in the region in comparison with observed events.
Mesoscale convective systems (MCSs) and associated hazardous meteorological phenomena cause considerable economic damage and even loss of lives in the mid-latitudes. The mechanisms behind the formation and intensification of MCSs are still not well understood due to limited observational data and inaccurate climate models. Improving the prediction and understanding of MCSs is a high-priority area in hydrometeorology. One may study MCSs either employing high-resolution atmospheric modeling or through the analysis of remote sensing images which are known to reflect some of the characteristics of MCSs, including high temperature gradients of cloud-top, specific spatial shapes of temperature patterns, etc. However, research on MCSs using remote sensing data is limited by inadequate (in size) databases of satellite-identified MCSs and poorly equipped automated tools for MCS identification and tracking. In this study, we present (a) the GeoAnnotateAssisted tool for fast and convenient visual identification of MCSs in satellite imagery, which is capable of providing AI-generated suggestions of MCS labels; (b) the Dataset of Mesoscale Convective Systems over the European Territory of Russia (DaMesCoS-ETR), which we created using this tool, and (c) the Deep Convolutional Neural Network for the Identification of Mesoscale Convective Systems (MesCoSNet), constructed following the RetinaNet architecture, which is capable of identifying MCSs in Meteosat MSG/SEVIRI data. We demonstrate that our neural network, optimized in terms of its hyperparameters, provides high MCS identification quality (mAP=0.75, true positive rate TPR=0.61) and a well-specified detection uncertainty (false alarm ratio FAR=0.36). Additionally, we demonstrate potential applications of the GeoAnnotateAssisted labelling tool, the DaMesCoS-ETR dataset, and the MesCoSNet neural network in addressing MCS research challenges. Specifically, we present the climatology of axisymmetric MCSs over the European territory of Russia from 2014 to 2020 during summer seasons (May to September), obtained using MesCoSNet with Meteosat MSG/SEVIRI data. The automated identification of MCSs by the MesCoSNet artificial neural network opens up new avenues for previously unattainable MCS research topics.
In this study, a series of numerical analyses of meteorology, runoff, river flow, and inundation were performed to quantitatively evaluate the effects of historical warming on precipitation, discharge, water level, and flood inundation. This study was on the flood inundation of the Chikuma River Basin in Japan caused by Typhoon Hagibis in 2019. The historical warming impact on Typhoon Hagibis was analyzed by comparing nonglobal warming experiments (NonWs) and control experiments (CTLs) to reproduce the current situation. Calculated results showed that the ratios of the index of CTLs to that of NonWs (mean CTL to mean NonW) as indicators of the impact of historical warming were 1.08, 1.22, and 1.08–3.08 for total precipitation, peak river discharge, and peak water level (from pre‐flood level and high‐water level), respectively, and 48.1 and 595 for overflow depth and inundation volume for the Chikuma River, respectively. Results of the hydrologic‐sensitivity analysis indicated that the influence of historical warming during the last 40‐year period was already evident on overflow and flooding, whose sensitivities were higher than those of discharge and water level.
The Mediterranean Sea is affected by cyclonic activity often associated with extreme weather. Intense snowfall events are rare, but when they occur they can lead to severe impacts especially due to the lack of infrastructure and public awareness. This study focuses on the mechanisms that can trigger extreme snowstorms over the eastern Mediterranean and the quantification of the influence of sea‐surface temperature (SST) anomalies on them. Different scenarios show that positive SST anomalies lead to more severe snowfall over higher altitudes, whereas negative anomalies lead to longer duration of snow cover on lower altitudes and seaside areas. image
According to our model simulations, anthropogenic climate change enhanced the total precipitation amount during the heavy rainfall event of 19–21 July 2021 in central China by 21.3% (95% confidence interval: 16.5%–29.5%).
The purpose of the work is to analyze the problem of adaptation of various fields of activity to climate change, to formulate the tasks of adapting the agro-industrial complex (AIC) and to analyze the features of information support and methods for solving the tasks of its adaptation plan, to develop a method for solving one of the tasks of this plan the formation and coordination of target indicators of the development of the agro-industrial complex. To solve the above problems, the results of the analysis of climate change in the territory of the North Caucasus, the model for optimizing the functioning of the “crop industry—processing industry” system, developed to form and agree on target indicators for the development of the regional agro-industrial complex, were used. It is noted that at the regional level it is not advisable to limit adaptation to climate change only to agriculture, this problem at this level should be considered for the “agriculture—processing industry” system, taking into account the relationship between its elements, the goals of adapting this system to climate change are formulated. The formulations of the tasks of the adaptation plan for the regional agro-industrial complex are given, the approach to solving the problem of forming and coordinating the target indicators of the agro-industrial complex is outlined, some calculation results are given. The main results of the work are: the formulation of the tasks of adapting the agro-industrial complex to climate change, the model for optimizing the functioning of the “crop industry—processing industry” system, developed to solve the problem of forming and coordinating target indicators for the development of the regional agro-industrial complex.KeywordsClimate changeAgro-industrial complexObjectives of the adaptation planFormation and coordination of target indicators
Sea surface temperature (SST) in the East China Sea (ECS) has undergone a rapid rise in recent decades, but the associated impact on extreme weather remains under debate. Here, using a cloud-permitting model, we assess the impact of the ECS warming observed since the 1980s on a torrential rain event that caused devastating floods and landslides in the Kyushu Island, western Japan, in July 2017. Without the increasing trends of SST and air temperature, the model cannot reproduce the observed extremely high amount of precipitation during the event, i.e., >700 mm/12-h. The SST increase is found more influential in determining the precipitation amount. Without the ocean warming, increases in precipitable water and horizontal moisture transport due to the atmospheric warming would not lead to precipitation increase during this event. The change in the amount of precipitation can be largely explained by the change in the updraft intensity of the convective system. Higher SST suppresses downward surface sensible heat flux and enhances upward latent heat flux along the paths of air parcels flowing into the convective system in this case. This increases the equivalent potential temperature in the lower troposphere, which enhances the convective available potential energy in the lower troposphere, leading to intensification of the convective system and thereby the increase of precipitation. The findings of this case study suggest an important role of the warming ECS in the intensification of torrential rain events around Japan and the necessity of further assessment of the role of the ocean warming in the torrential rains.
Changes in the frequency and intensity of atmospheric severe convective events, including heavy rainfall, thunderstorm, hailstorm, squall, and tornado, in the Russian regions during the warm season are analyzed using different independent sources of information. Based on observations at Russian weather stations in 1966–2020, the frequency of thunderstorm, hailstorm, and strong wind, the contribution of extreme showers to total precipitation, and the cumulonimbus cloud fraction are estimated. Based on satellite data, the frequency and intensity of tornado and squall events that caused windthrows for 1986–2021 and the height of the top of deep convective clouds for 2002–2021 are also evaluated. The ERA5 reanalysis data are used to analyze the frequency of conditions favorable for the development of moderate and intense severe convective events in 1979–2020. The results indicate a general intensification of severe convective events in most Russian regions, except for a number of regions in the south of the European part of Russia. The frequency of moderate hazards has a decreasing trend, and the frequency of the most intense severe hazards has an increasing trend. It is reasonable to take the results into account when developing plans for the adaptation of Russian regions and industries to climate change.
Most societally relevant weather impacts result from compound events, that is, rare combinations of weather and climate drivers. Focussing on four event types arising from different combinations of climate variables across space and time, we illustrate that robust analyses of compound events – such as frequency and uncertainty analysis under present-day and future conditions, event attribution, exploration of low-probability-high-impact events – require very large sample sizes. In particular, the required sample is much larger than that needed for routinely considered univariate extremes. We demonstrate how large ensemble simulations from multiple climate models are crucial for advancing our understanding of compound events and for constructing robust projections. Importantly, this will avoid providing practitioners with potentially misleading information on climate risks.
Heavy Precipitation Events (HPEs) are a challenging atmospheric phenomenon with a high impact on human lives and infrastructures. The achievement of high-resolution simulations for Convection Permitting Modelling (CPM) has brought relevant advancements in the representation of HPEs in climate simulations compared to coarser resolution Regional Climate Models (RCM). However, further insight is needed on the scale-dependency of mesoscale precipitation processes. In this study, we aim at evaluating reanalysis-driven climate simulations of the greater Alpine area in recent climate conditions and assessing the scale-dependency of thermodynamical processes influencing extreme precipitation. We evaluate COSMO-CLM simulations of the period 1971–2015, at resolutions of 25 km (RCM) and 3 km (CPM) downscaled from ERA-40 and ERA-interim. We validate our simulations against high-resolution observations (EOBS, HYRAS, MSWEP, and UWYO). In the methodology, we present a revisited version of the Precipitation Severity Index (PSI) useful for extremes detection. Furthermore, we obtain the main modes of precipitation variance and synoptic Weather Types (WTs) associated with extreme precipitation using Principal Component Analysis (PCA). PCA is also used to derive composites of model variables associated with the thermodynamical processes of heavy precipitation. The results indicate a good detection capability of the PSI for precipitation extremes. We identified four WTs as precursors of extreme precipitation in winter, associated with stationary fronts or a zonal flow regimes. In summer, 5 WTs bring heavy precipitation, associated with upper-level elongated troughs over western Europe, sometimes evolving into cut-off lows, or by winter-like situations of strong zonal circulation. The model evaluation showed that CPM (3 km) represents higher precipitation intensities, better rank correlation, better hit rates for extremes detection, and an improved representation of heavy precipitation amount and structure for selected HPEs compared to RCM (25 km). CPM overestimates grid point precipitation rates especially over elevated terrain fostered by the scale-dependency of convective dynamic processes such as stronger updrafts and more triggering of convective cells. However, at low altitudes, precipitation differences due to resolution are explained through the scale-dependency of thermodynamic variables, where the largest impact is caused by differences in surface moisture up to 1 g kg-1. These differences show a predominant north-south gradient where locations north of the Alps show larger (lower) surface moisture and precipitation in CPM (RCM) and locations south of the Alps show larger (lower) humidity and precipitation in RCM (CPM). The humidity differences are caused by an uneven partition of latent and sensible heat fluxes between RCM and CPM. RCM simulates larger emissions of latent heat flux over the Sea (25 W m-2 more), and CPM emits larger latent heat over land (15 W m-2 more). In turn, RCM emits larger surface sensible heat fluxes over land (30 W m-2 more), showing a warmer surface (0.5 to 1 °C) than CPM. These results provide evidence that CPM is a powerful tool for obtaining accurate high-resolution climate information also pointing at the different scale-dependency of dynamic and thermodynamical precipitation processes at high and low terrain.
This chapter has two aims. First, it explores the implications of current and
future losses and damages from climate change on public finances. These
affect the ability of governments to pursue sustainable development and
poverty reduction priorities under a changing climate. Second, it examines
the critical roles of finance in reducing and managing the risks of losses and
damages, namely in risk reduction, retention and transfer. The chapter also
provides insights on the landscape of development finance directly or
indirectly supporting these efforts, recognising the important role of
humanitarian finance in supporting relief.
Hazardous convective weather events (HCWE), such as heavy rainfall, large hail, squalls and tornadoes, are one of the substantial sources of natural emergencies in Russia. The territory of the Central Federal District (CFD) is characterized by the highest population density in Russia. On the one hand, this leads to increased risks associated with HCWE, but on the other hand, it provides the possibilities for collecting the most detailed information on them (including the events missed by the observation network and reported based on damage assessment). In this study, we consider the structure and information content of the GIS database of HCWE for the territory of the CFD. The main advantage of the developed database comparing with existing analogues is its structure, which includes information on both the events themselves and their consequences, and the conditions of their occurrence. This includes, in particular, the characteristics of meso-scale convective systems (convective storms) based on the images from meteorological satellites and diagnostic variables characterizing the atmospheric environments according to the data from ERA-5 and CFS reanalysis systems. Also, the developed database is associated with previously published databases on tornadoes in Northern Eurasia and large-scale windthrow events in European Russia. At present, we compiled the data on more than 2,000 cases of HCWE in the CFD for the period 2001–2020, most of which were reported based on damage assessment. The open-source PostgreSQL DBMS is used to manage and edit the database. Open access to the database on the Internet is implemented through an online web map service available at http://convective-storms.psu.ru/.
Although climate change is a global phenomenon, its manifestations and consequences are different in different regions, and therefore climate information on spatial scales ranging from sub-continental to local is used for impact and risk assessments. Chapter 10 assesses the foundations of how regional climate information is distilled from multiple, sometimes contrasting, lines of evidence. Starting from the assessment of global-scale observations in Chapter 2, Chapter 10 assesses the challenges and requirements associated with observations relevant at the regional scale. Chapter 10 also assesses the fitness of modelling tools available for attributing and projecting anthropogenic climate change in a regional context starting from the methodologies assessed in Chapters 3 and 4. Regional climate change is the result of the interplay between regional responses to both natural forcings and human influence (considered in Chapters 2, 5, 6 and 7), responses to large-scale climate phenomena characterizing internal variability (considered in Chapters 1–9), and processes and feedbacks of a regional nature.
Approximately 10 years ago, convection‐permitting regional climate models (CPRCMs) emerged as a promising computationally affordable tool to produce fine resolution (1–4 km) decadal‐long climate simulations with explicitly resolved deep convection. This explicit representation is expected to reduce climate projection uncertainty related to deep convection parameterizations found in most climate models. A recent surge in CPRCM decadal simulations over larger domains, sometimes covering continents, has led to important insights into CPRCM advantages and limitations. Furthermore, new observational gridded datasets with fine spatial and temporal (~1 km; ~1 h) resolutions have leveraged additional knowledge through evaluations of the added value of CPRCMs. With an improved coordination in the frame of ongoing international initiatives, the production of ensembles of CPRCM simulations is expected to provide more robust climate projections and a better identification of their associated uncertainties. This review paper presents an overview of the methodology to produce CPRCM simulations and the latest research on the related added value in current and future climates. Impact studies that are already taking advantage of these new CPRCM simulations are highlighted. This review paper ends by proposing next steps that could be accomplished to continue exploiting the full potential of CPRCMs.
This article is categorized under: Climate Models and Modeling > Earth System Models
Across the Indo-Pacific region, rapid increases in surface temperatures, ocean heat content and concomitant hydrological changes have implications for sea level rise, ocean circulation and regional freshwater availability. In this Review, we synthesize evidence from multiple data sources to elucidate whether the observed heat and freshwater changes in the Indian Ocean represent an intensification of the hydrological cycle, as expected in a warming world. At the basin scale, twentieth century warming trends can be unequivocally attributed to human-induced climate change. Changes since 1980, however, appear dominated by multi-decadal variability associated with the Interdecadal Pacific oscillation, manifested as shifts in the Walker circulation and a corresponding reorganization of the Indo-Pacific heat and freshwater balance. Such variability, coupled with regional-scale trends, a short observational record and climate model uncertainties, makes it difficult to assess whether contemporary changes represent an anthropogenically forced transformation of the hydrological cycle. Future work must, therefore, focus on maintaining and expanding observing systems of remotely sensed and in situ observations, as well as extending and integrating coral proxy networks. Improved climate model simulations of the Maritime Continent region and its intricate exchange between the Pacific and Indian oceans are further necessary to quantify and attribute Indo-Pacific hydrological changes.
Here we demonstrate that dynamical adjustment allows a straightforward approach to extreme event attribution within a conditional framework. We illustrate the potential of the approach with two iconic extreme events that occurred in 2010: the early winter European cold spell and the Russian summer heat wave. We use a dynamical adjustment approach based on constructed atmospheric circulation analogues to isolate the various contributions to these two extreme events using only observational and reanalysis datasets. Dynamical adjustment results confirm previous findings regarding the role of atmospheric circulation in the two extreme events and provide a quantitative estimate of the various dynamic and thermodynamic contributions to the event amplitude. Furthermore, the approach is also used to identify the drivers of the recent 1979–2018 trends in summer extreme maximum and minimum temperature changes over western Europe and western Asia. The results suggest a significant role of the dynamic component in explaining temperature extreme changes in different regions, including regions around the Black and Caspian Seas as well as central Europe and the coasts of western Europe. Finally, dynamical adjustment offers a simple and complementary storyline approach to extreme event attribution with the advantage that no climate model simulations are needed, making it a promising candidate for the fast-track component of any real-time extreme event attribution system.
Characteristics of Northern Hemisphere extratropical cyclone activity were compared for five concurrent reanalyses: the NCEP-U.S. Department of Energy (DOE) reanalysis (herein NCEP-DOE), the Japanese 25-year Reanalysis Project (JRA-25), the ECMWF Interim Re-Analysis (ERA-Interim), the National Aeronautics and Space Administration's Modern-Era Retrospective Analysis for Research and Applications (NASA-MERRA), and the NCEP Climate Forecast System Reanalysis (NCEP-CFSR), for the period 1979-2010 using a single cyclone tracking algorithm. The total number of cyclones, ranging from 1400 to more than 1800 yr(-1), was found to depend strongly on the spatial resolution of the respective reanalysis. The largest cyclone population was identified using NASA-MERRA data, which also showed the highest occurrence of very deep cyclones. Of the reanalyses, two (NCEP-DOE and ERA-Interim) are associated with statistically significant positive trends in the total number of cyclones from 1% to 2% decade(-1). These trends result from moderate and shallow cyclones contributing to approximately 90% of the total cyclone count on average. The number of very deep cyclones (<960 hPa) in the North Atlantic increased in most reanalyses until 1990 and then declined during the last decade. In the North Pacific, the number of these events reached a peak in 2000 and then decreased during the last decade. The winter pattern is characterized by robust trends in cyclone numbers, with an enhancement of the North Atlantic storm track and a weakening of the North Pacific subtropical storm track. In the summer, there is a robust intensification of the Mediterranean storm track and a decrease in counts over the North Atlantic. Interannual variability and decadal-scale variations of the cyclone counts are highly correlated among the reanalyses, with the greatest agreement in moderate and deep cyclones.
The intensification of precipitation extremes with climate change(1) is of key importance to society as a result of the large impact through flooding. Observations show that heavy rainfall is increasing on daily timescales in many regions(2), but how changes will manifest themselves on sub-daily timescales remains highly uncertain. Here we perform the first climate change experiments with a very high resolution (1.5 km grid spacing) model more typically used for weather forecasting, in this instance for a region of the UK. The model simulates realistic hourly rainfall characteristics, including extremes(3,4), unlike coarser resolution climate models(5,6), giving us confidence in its ability to project future changes at this timescale. We find the 1.5 km model shows increases in hourly rainfall intensities in winter, consistent with projections from a coarser 12 km resolution model and previous studies at the daily timescale(7). However, the 1.5 km model also shows a future intensification of short-duration rain in summer, with significantly more events exceeding the high thresholds indicative of serious flash flooding. We conclude that accurate representation of the local storm dynamics is an essential requirement for predicting changes to convective extremes; when included we find for the model here that summer downpours intensify with warming.
A global survey of surface temperature anomalies occurring during 2013 (Fig. 8.1a; Supplementary Fig. S8.1) in the HadCRUT4 observations (Morice et al. 2012) reveals pronounced warm annual and seasonal mean anomalies. Two regions with prominent record or near-record annual mean warm anomalies include large regions of Australia and a region in the far western tropical Pacific encompassing the Philippines and part of the Maritime Continent (Fig. 8.1b). The 2013 anomalies appear particularly extreme during austral fall and winter (MAM, JJA) in Australia and during MAM in the far western Pacific (Supplementary Fig. S8.1). Temperatures in these two regions are further assessed in this report for the causes of this extreme warmth. Twenty-three All-Forcing (anthropogenic plus natural) models and control runs and 10 Natural-Forcing models were used from the Coupled Model Intercomparison Project phase 5 (CMIP5; Taylor et al. 2012). See Knutson et al. (2013a,b) for background on our methodology and a global assessment of low-frequency variability and trends.
Precipitation changes can affect society more directly than variations
in most other meteorological observables, but precipitation is difficult
to characterize because of fluctuations on nearly all temporal and
spatial scales. In addition, the intensity of extreme precipitation
rises markedly at higher temperature, faster than the rate of increase
in the atmosphere's water-holding capacity, termed the
Clausius-Clapeyron rate. Invigoration of convective precipitation (such
as thunderstorms) has been favoured over a rise in stratiform
precipitation (such as large-scale frontal precipitation) as a cause for
this increase, but the relative contributions of these two types of
precipitation have been difficult to disentangle. Here we combine large
data sets from radar measurements and rain gauges over Germany with
corresponding synoptic observations and temperature records, and
separate convective and stratiform precipitation events by cloud
observations. We find that for stratiform precipitation, extremes
increase with temperature at approximately the Clausius-Clapeyron rate,
without characteristic scales. In contrast, convective precipitation
exhibits characteristic spatial and temporal scales, and its intensity
in response to warming exceeds the Clausius-Clapeyron rate. We conclude
that convective precipitation responds much more sensitively to
temperature increases than stratiform precipitation, and increasingly
dominates events of extreme precipitation.
Daily Precipitation Concentration Index (CI) was used in this paper to
investigate the statistical structure of daily precipitation across
Europe based on 744 daily rainfall series for the period 1971-2010.
Annual CI shows a global crosswise gradient, form North-West to
South-East of Europe (excluding Turkey and Greece). The same gradient is
also observed in winter, spring and autumn, while in summer the gradient
is North-South. Highest annual and seasonal daily concentration of
rainfall were detected primarily to the western Mediterranean basin,
along Spanish and French coastlands. Relief seems to be one of the most
noticeable factor in the spatial distribution of CI. Mann-Kendall
test identifies no global significant temporal trend patterns across
Europe for 1971-2010 period. French is the only country with increasing
annual and seasonal CI values. These results suggest that no significant
changes have occurred in daily precipitation distribution across Europe
during 1971-2010.
Expected changes to future extreme precipitation remain a key
uncertainty associated with anthropogenic climate change. Recently,
extreme precipitation has been proposed to scale with the precipitable
water content in the atmosphere, which assuming relative humidity stays
constant, will increase at a rate of ˜6.8%/°C as indicated by
the Clausius-Clapeyron (C-C) relationship. We examine this scaling
empirically using data from 137 long-record pluviograph and temperature
gauges across Australia. We find that scaling rates are consistent with
the C-C relationship for surface temperatures up to between 20°C and
26°C and for precipitation durations up to 30 minutes, implying that
such scaling applies only for individual storm systems. At greater
temperatures negative scaling is observed. Consideration of relative
humidity data shows a pronounced decrease in the maximum relative
humidity for land surface temperatures greater than 26°C, indicating
that moisture availability becomes the dominant driver of how extreme
precipitation scales at higher temperatures.
Herein, a summary of the authors' experiences with 36-h real-time explicit ( 4 km) convective forecasts with the Advanced Research Weather Research and Forecasting Model (WRF-ARW) during the 2003-05 spring and summer seasons is presented. These forecasts are compared to guidance obtained from the 12-km operational Eta Model, which employed convective parameterization ( e. g., Betts-Miller-Janjic). The results suggest significant value added for the high-resolution forecasts in representing the convective system mode ( e. g., for squall lines, bow echoes, mesoscale convective vortices) as well as in representing the diurnal convective cycle. However, no improvement could be documented in the overall guidance as to the timing and location of significant convective outbreaks. Perhaps the most notable result is the overall strong correspondence between the Eta and WRF-ARW guidance, for both good and bad forecasts, suggesting the overriding influence of larger scales of forcing on convective development in the 24-36-h time frame. Sensitivities to PBL, land surface, microphysics, and resolution failed to account for the more significant forecast errors ( e. g., completely missing or erroneous convective systems), suggesting that further research is needed to document the source of such errors at these time scales. A systematic bias is also noted with the Yonsei University (YSU) PBL scheme, emphasizing the continuing need to refine and improve physics packages for application to these forecast problems.
Observed changes in intense precipitation (e.g., the frequency of very heavy precipitation or the upper 0.3% of daily precipitation events) have been analyzed for over half of the land area of the globe. These changes have been linked to changes in intense precipitation for three transient climate model simulations, all with greenhouse gas concentrations increasing during the twentieth and twenty-first centuries and doubling in the later part of the twenty-first century. It was found that both the empirical evidence from the period of instrumental observations and model projections of a greenhouse-enriched atmosphere indicate an increasing probability of intense precipitation events for many extratropical regions including the United States. Although there can be ambiguity as to the impact of more frequent heavy precipitation events, the thresholds of the definitions of these events were raised here, such that they are likely to be disruptive. Unfortunately, reliable assertions of very heavy and extreme precipitation changes are possible only for regions with dense networks due to the small radius of correlation for many intense precipitation events.
In this study, we present the collation and analysis of the gridded land-based dataset of indices of temperature and precipitation extremes: HadEX2. Indices were calculated based on station data using a consistent approach recommended by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices, resulting in the production of 17 temperature and 12 precipitation indices derived from daily maximum and minimum temperature and precipitation observations. High-quality in situ observations from over 7000 temperature and 11,000 precipitation meteorological stations across the globe were obtained to calculate the indices over the period of record available for each station. Monthly and annual indices were then interpolated onto a 3.75° × 2.5° longitude-latitude grid over the period 1901–2010. Linear trends in the gridded fields were computed and tested for statistical significance. Overall there was very good agreement with the previous HadEX dataset during the overlapping data period. Results showed widespread significant changes in temperature extremes consistent with warming, especially for those indices derived from daily minimum temperature over the whole 110 years of record but with stronger trends in more recent decades. Seasonal results showed significant warming in all seasons but more so in the colder months. Precipitation indices also showed widespread and significant trends, but the changes were much more spatially heterogeneous compared with temperature changes. However, results indicated more areas with significant increasing trends in extreme precipitation amounts, intensity, and frequency than areas with decreasing trends.
Two new high-resolution sea surface temperature (SST) analysis products have been developed using optimum interpolation (OI). The analyses have a spatial grid resolution of 0.25° and a temporal resolution of 1 day. One product uses the Advanced Very High Resolution Radiometer (AVHRR) infrared satellite SST data. The other uses AVHRR and Advanced Microwave Scanning Radiometer (AMSR) on the NASA Earth Observing System satellite SST data. Both products also use in situ data from ships and buoys and include a large-scale adjustment of satellite biases with respect to the in situ data. Because of AMSR’s near-all-weather coverage, there is an increase in OI signal variance when AMSR is added to AVHRR. Thus, two products are needed to avoid an analysis variance jump when AMSR became available in June 2002. For both products, the results show improved spatial and temporal resolution compared to previous weekly 1° OI analyses.
The AVHRR-only product uses Pathfinder AVHRR data (currently available from January 1985 to December 2005) and operational AVHRR data for 2006 onward. Pathfinder AVHRR was chosen over operational AVHRR, when available, because Pathfinder agrees better with the in situ data. The AMSR– AVHRR product begins with the start of AMSR data in June 2002. In this product, the primary AVHRR contribution is in regions near land where AMSR is not available. However, in cloud-free regions, use of both infrared and microwave instruments can reduce systematic biases because their error characteristics are independent.
The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.
ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF.
It is well known that regional climate simulations are sensitive to the size and position of the domain chosen for calculations. Here we study the physical mechanisms of this sensitivity. We conducted simulations with the Regional Atmospheric Modeling System (RAMS) for June 2000 over North America at 50 km horizontal resolution using a 7500 km × 5400 km grid and NCEP/NCAR reanalysis as boundary conditions. The position of the domain, was displaced in several directions, always maintaining the U.S. in the interior, out of the buffer zone along the lateral boundaries. Circulation biases developed a large scale structure, organized by the Rocky Mountains, resulting from a systematic shifting of the synoptic wave trains that crossed the domain. The distortion of the large-scale circulation was produced by interaction of the modeled flow with the lateral boundaries of the nested domain and varied when the position of the grid was altered. This changed the large-scale environment among the different simulations and translated into diverse conditions for the development of the mesoscale processes that produce most of precipitation for the Great Plains in the summer season. As a consequence, precipitation results varied, sometimes greatly, among the experiments with the different grid positions. To eliminate the dependence of results on the position of the domain, we used spectral nudging of waves longer than 2500 km above the boundary layer. Moisture was not nudged at any level. This constrained the synoptic scales to follow reanalysis while allowing the model to develop the small-scale dynamics responsible for the rainfall. Nudging of the large scales successfully eliminated the variation of precipitation results when the grid was moved. We suggest that this technique is necessary for all downscaling studies with regional models with domain sizes of a few thousand kilometers and larger embedded in global models.
Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 1766, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.3 billion (refs 5, 6). Although the flooding was deemed a 'wake-up call' to the impacts of climate change at the time, such claims are typically supported only by general thermodynamic arguments that suggest increased extreme precipitation under global warming, but fail to account fully for the complex hydrometeorology associated with flooding. Here we present a multi-step, physically based 'probabilistic event attribution' framework showing that it is very likely that global anthropogenic greenhouse gas emissions substantially increased the risk of flood occurrence in England and Wales in autumn 2000. Using publicly volunteered distributed computing, we generate several thousand seasonal-forecast-resolution climate model simulations of autumn 2000 weather, both under realistic conditions, and under conditions as they might have been had these greenhouse gas emissions and the resulting large-scale warming never occurred. Results are fed into a precipitation-runoff model that is used to simulate severe daily river runoff events in England and Wales (proxy indicators of flood events). The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.
The role of land surface–related processes and feedbacks during the record-breaking 2003 European summer heat wave is explored with a regional climate model. All simulations are driven by lateral boundary conditions and sea surface temperatures from the ECMWF operational analysis and 40-yr ECMWF Re-Analysis (ERA-40), thereby prescribing the large-scale circulation. In particular, the contribution of soil moisture anomalies and their interactions with the atmosphere through latent and sensible heat fluxes is investigated. Sensitivity experiments are performed by perturbing spring soil moisture in order to determine its influence on the formation of the heat wave. A multiyear regional climate simulation for 1970–2000 using a fixed model setup is used as the reference period.
A large precipitation deficit together with early vegetation green-up and strong positive radiative anomalies in the months preceding the extreme summer event contributed to an early and rapid loss of soil moisture, which exceeded the multiyear average by far. The exceptionally high temperature anomalies, most pronounced in June and August 2003, were initiated by persistent anticyclonic circulation anomalies that enabled a dominance of the local heat balance. In this experiment the hottest phase in early August is realistically simulated despite the absence of an anomaly in total surface net radiation. This indicates an important role of the partitioning of net radiation in latent and sensible heat fluxes, which is to a large extent controlled by soil moisture. The lack of soil moisture strongly reduced latent cooling and thereby amplified the surface temperature anomalies.
The evaluation of the experiments with perturbed spring soil moisture shows that this quantity is an important parameter for the evolution of European heat waves. Simulations indicate that without soil moisture anomalies the summer heat anomalies could have been reduced by around 40% in some regions. Moreover, drought conditions are revealed to influence the tropospheric circulation by producing a surface heat low and enhanced ridging in the midtroposphere. This suggests a positive feedback mechanism between soil moisture, continental-scale circulation, and temperature.
Secular trends of daily precipitation characteristics are considered in the transient climate change experiment with a coupled atmosphere-ocean general circulation model ECHAM4/OPYC3 for 1900-2099. The climate forcing is due to increasing concentrations of the greenhouse gases in the atmosphere. Mean daily precipitation, precipitation intensity, probability of wet days and parameters of the gamma distribution are analyzed. Particular attention is paid to the changes of heavy precipitation, Analysis of the annual mean precipitation trends for 1900-1999 revealed general agreement with observations with significant positive trends in mean precipitation over continental areas. In the 2000-2099 period precipitation trend patterns followed the tendency obtained for 1900-1999 but with significantly increased magnitudes. Unlike the annual mean precipitation trends for which negative values were found for some continental areas, the mean precipitation intensity and scale parameter of the fitted gamma distribution increased over all land territories . Negative trends in the number of wet days were found over most of the land areas except high latitudes in the Northern Hemisphere. The shape parameter of the gamma distribution in general revealed a slight negative trend in the areas of the precipitation increase. Investigation of daily precipitation revealed an unproportional increase of heavy precipitation events for the land areas including local maxima in Europe and the eastern United States.
The summer of 2003 was probably the hottest in Europe since at latest ad 1500, and unusually large numbers of heat-related deaths were reported in France, Germany and Italy. It is an ill-posed question whether the 2003 heatwave was caused, in a simple deterministic sense, by a modification of the external influences on climate--for example, increasing concentrations of greenhouse gases in the atmosphere--because almost any such weather event might have occurred by chance in an unmodified climate. However, it is possible to estimate by how much human activities may have increased the risk of the occurrence of such a heatwave. Here we use this conceptual framework to estimate the contribution of human-induced increases in atmospheric concentrations of greenhouse gases and other pollutants to the risk of the occurrence of unusually high mean summer temperatures throughout a large region of continental Europe. Using a threshold for mean summer temperature that was exceeded in 2003, but in no other year since the start of the instrumental record in 1851, we estimate it is very likely (confidence level >90%) that human influence has at least doubled the risk of a heatwave exceeding this threshold magnitude.
Human influence on climate has been detected in surface air temperature, sea level pressure, free atmospheric temperature, tropopause height and ocean heat content. Human-induced changes have not, however, previously been detected in precipitation at the global scale, partly because changes in precipitation in different regions cancel each other out and thereby reduce the strength of the global average signal. Models suggest that anthropogenic forcing should have caused a small increase in global mean precipitation and a latitudinal redistribution of precipitation, increasing precipitation at high latitudes, decreasing precipitation at sub-tropical latitudes, and possibly changing the distribution of precipitation within the tropics by shifting the position of the Intertropical Convergence Zone. Here we compare observed changes in land precipitation during the twentieth century averaged over latitudinal bands with changes simulated by fourteen climate models. We show that anthropogenic forcing has had a detectable influence on observed changes in average precipitation within latitudinal bands, and that these changes cannot be explained by internal climate variability or natural forcing. We estimate that anthropogenic forcing contributed significantly to observed increases in precipitation in the Northern Hemisphere mid-latitudes, drying in the Northern Hemisphere subtropics and tropics, and moistening in the Southern Hemisphere subtropics and deep tropics. The observed changes, which are larger than estimated from model simulations, may have already had significant effects on ecosystems, agriculture and human health in regions that are sensitive to changes in precipitation, such as the Sahel.
Executive Summary
This chapter addresses changes in weather and climate events relevant to extreme impacts and disasters. An extreme (weather or climate) event is generally defined as the occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends (‘tails’) of the range of observed values of the variable. Some climate extremes (e.g., droughts, floods) may be the result of an accumulation of weather or climate events that are, individually, not extreme themselves (though their accumulation is extreme). As well, weather or climate events, even if not extreme in a statistical sense, can still lead to extreme conditions or impacts, either by crossing a critical threshold in a social, ecological, or physical system, or by occurring simultaneously with other events. A weather system such as a tropical cyclone can have an extreme impact, depending on where and when it approaches landfall, even if the specific cyclone is not extreme relative to other tropical cyclones. Conversely, not all extremes necessarily lead to serious impacts. [3.1]
Many weather and climate extremes are the result of natural climate variability (including phenomena such as El Niño), and natural decadal or multi-decadal variations in the climate provide the backdrop for anthropogenic climate changes. Even if there were no anthropogenic changes in climate, a wide variety of natural weather and climate extremes would still occur. [3.1]
A changing climate leads to changes in the frequency, intensity, spatial extent, duration, and timing of weather and climate extremes, and can result in unprecedented extremes. Changes in extremes can also be directly related to changes in mean climate, because mean future conditions in some variables are projected to lie within the tails of present-day conditions. Nevertheless, changes in extremes of a climate or weather variable are not always related in a simple way to changes in the mean of the same variable, and in some cases can be of opposite sign to a change in the mean of the variable. Changes in phenomena such as the El Nino-Southern Oscillation or monsoons could affect the frequency and intensity of extremes in several regions simultaneously. [3.1]
Various methodologies are used to explain some extreme events of 2011 from a climate perspective. The Global Precipitation Climatology Centre (GPCC) V5 1° rainfall analyzes was used to estimate severe flooding in 2011 in Thailand. Time series of rainfall in show that the amount of rain that fell in the catchment area was not very unusual. In 2011, East Africa faced a tragic food crisis that led to famine conditions in parts of Somalia and severe food shortages in parts of Ethiopia and Somalia. Research has suggested that continued warming in the IPWP will likely contribute to more frequent East African droughts during the boreal spring and summer. In 2011, the state of Texas experienced an extraordinary heat wave and drought. A spatial, weighted average was calculated from the 27 GCM grid boxes that fell within Texas, with weights proportional to the cosine of the latitude. It was found that the conditions leading to droughts such as the one that occurred in Texas in 2011 are, at least in the case of temperature, distinctly more probable than they were 40-50 years ago.
The paper analyzes the features of the flooding in the town of Krymsk (Krasnodar krai) that led to a large number of victims. Along with the main cause of the disaster, extreme rainfall, a considerable role was played by mudflows and slides sporadically blocking the river beds, as well as anthropogenic factors, including the built-up of the low floodplain of the Adagum River, insufficient throughput capacity of bridge spans for the unhampered passage of flood waters, and littered beds.
Extreme precipitation has been projected to increase more than the mean under future changed climate, but its mechanism is not clear. We have separated the `dynamic' and `thermodynamic' components of the mean and extreme precipitation changes projected in 6 climate model experiments. The dynamic change is due to the change in atmospheric motion, while the thermodynamic change is due to the change in atmospheric moisture content. The model results consistently show that there are areas with small change or decreases in the thermodynamic change for mean precipitation mainly over subtropics, while the thermodynamic change for extreme precipitation is an overall increase as a result of increased atmospheric moisture. The dynamic changes play a secondary role in the difference between mean and extreme and are limited to lower latitudes. Over many parts of mid- to high latitudes, mean and extreme precipitation increase in comparable magnitude due to a comparable thermodynamic increase.
Changes in precipitation extremes under greenhouse warming are commonly assumed to be constrained by changes in the amounts of precipitable water in the atmosphere. Global climate models generally predict only marginal changes in relative humidity, implying that the actual amount of atmospheric precipitable water scales with the water vapour content of saturation, which is governed by the Clausius-Clapeyron relation. Indeed, changes in daily precipitation extremes in global climate models seem to be consistent with the 7% increase per degree of warming given by the Clausius-Clapeyron relation, but it is uncertain how general this scaling behaviour is across timescales. Here, we analyse a 99-year record of hourly precipitation observations from De Bilt, the Netherlands, and find that one-hour precipitation extremes increase twice as fast with rising temperatures as expected from the Clausius-Clapeyron relation when daily mean temperatures exceed 12oC. In addition, simulations with a high-resolution regional climate model show that one-hour precipitation extremes increase at a rate close to 14% per degree of warming in large parts of Europe. Our results demonstrate that changes in short-duration precipitation extremes may well exceed expectations from the Clausius-Clapeyron relation. These short-duration extreme events can have significant impacts, such as local flooding, erosion and water damage.
Cyclone activity and life cycle are analysed in the coupled GCMs ECHAM5/OM and ECHAM4/OPYC3. First, the results for the present climate (1978-1999) are compared with ERA-40 and NCEP/NCAR reanalyses, showing a drastic improvement in the representation of cyclone activity in ECHAM5/OM compared to ECHAM4/OPYC3. The total number of cyclones, cyclone intensity, propagation velocity and deepening rates are found to be much more realistic in ECHAM5/OM relative to ECHAM4/OPYC3. Then, changes in extra tropical cyclone characteristics are compared between present day climate and future climate under the emission-scenario A1B using ECHAM5/OM. This comparison is performed using the 20-year time slices 1978-1999, 2070-2090 and 2170-2190, which were considered to be representative for the various climate conditions. The total number of cyclones does not undergo significant changes in a warmer climate. However, regional changes in cyclone numbers and frequencies are evident. One example is the Mediterranean region where the number of cyclones in summer increases almost by factor 2. Some noticeable changes are also found in cyclone life cycle characteristics (deepening rate and propagation velocity). Cyclones in the future climate scenario tend to move slower and their deepening rate becomes stronger, while cyclone intensity does not undergo significant change in a warmer climate. Generally, our results do not support the hypothesis of enhanced storminess under future climate conditions.
A physically based conceptual framework is put forward that explains why an increase in heavy precipitation events should be a primary manifestation of the climate change that accompanies increases in greenhouse gases in the atmosphere. Increased concentrations of greenhouse gases in the atmosphere increase downwelling infrared radiation, and this global heating at the surface not only acts to increase temperatures but also increases evaporation which enhances the atmospheric moisture content. Consequently all weather systems, ranging from individual clouds and thunderstorms to extratropical cyclones, which feed on the available moisture through storm-scale moisture convergence, are likely to produce correspondingly enhanced precipitation rates. Increases in heavy rainfall at the expense of more moderate rainfall are the consequence along with increased runoff and risk of flooding. However, because of constraints in the surface energy budget, there are also implications for the frequency and/or efficiency of precipitation. It follows that increased attention should be given to trends in atmospheric moisture content, and datasets on hourly precipitation rates and frequency need to be developed and analyzed as well as total accumulation.
This study systematically analyzes the complete IPCC AR4 (CMIP3) ensemble of GCM simulations with respect to changes in extreme
event characteristics at the end of the 21st century compared to present-day conditions. It complements previous studies by
investigating a more comprehensive database and considering seasonal changes beside the annual time scale. Confirming previous
studies, the agreement between the GCMs is generally high for temperature-related extremes, indicating increases of warm day
occurrences and heatwave lengths, and decreases of cold extremes. However, we identify issues with the choice of indices used
to quantify heatwave lengths, which do overall not affect the sign of the changes, but strongly impact the magnitude and patterns
of projected changes in heatwave characteristics. Projected changes in precipitation and dryness extremes are more ambiguous
than those in temperature extremes, despite some robust features, such as increasing dryness over the Mediterranean and increasing
heavy precipitation over the Northern high latitudes. We also find that the assessment of projected changes in dryness depends
on the index choice, and that models show less agreement regarding changes in soil moisture than in the commonly used ‘consecutive
dry days’ index, which is based on precipitation data only. Finally an analysis of the scaling of changes of extreme temperature
quantiles with global, regional and seasonal warming shows that much of the extreme quantile changes are due to a seasonal
scaling of the regional annual-mean warming. This emphasizes the importance of the seasonal time scale also for extremes.
Changes in extreme quantiles of temperature on land scale with changes in global annual mean temperature by a factor of more
than 2 in some regions and seasons, implying large changes in extremes in several countries, even for the commonly discussed
global 2°C-warming target.
An examination of a wide spectrum of hydro-meteorological and biogeochemical records in the Black Sea from the previous century possesses a robust climatic signature at interannual to interdecadal time scales. Superimposed on the first eigenmode of the data with interdecadal changes on the order of 15 to 30-year band, the second mode reflects oscillations with the period of about 10 years. The cold and dry winters generally take place within the first half of each decade, and they switch to mild and warm winters during the second halves. All the water column physical and biogeochemical properties examined respond accordingly to such oscillations. For example, the years with the cold (mild) winters correspond to the periods of increasing (decreasing) nutrient and hydrogen sulfide concentrations, phytoplankton biomass. These variations appear to be governed by the North Atlantic Oscillation (NAO) and East Atlantic-West Russia (EAWR) teleconnection patterns comprising various combinations of the low and high surface pressure anomaly centers over the North Atlantic and Eurasia. The NAO teleconnection to the Black Sea is opposite to that taking place in the eastern North Atlantic and its marginal seas. The relatively cold and dry winters occur during the positive phase of the NAO, and visa versa for the milder and wetter winters. The Black Sea Climate Index, constructed using more than 100-year-long time series of the North Atlantic Oscillation, the sea surface temperature, air temperature, sea level anomaly, provides a composite representation of the dominant mode of regional climate variability, and explains 46% of the total variance. The results point to a very efficient coupling between the anthropogenic and climatic forcing for driving the dramatic ecosystem changes observed during the 1980s and 1990s.
Extremes of weather and climate can have devastating effects on human society and the environment. Understanding past changes in the characteristics of such events, including recent increases in the intensity of heavy precipitation events over a large part of the Northern Hemisphere land area, is critical for reliable projections of future changes. Given that atmospheric water-holding capacity is expected to increase roughly exponentially with temperature--and that atmospheric water content is increasing in accord with this theoretical expectation--it has been suggested that human-influenced global warming may be partly responsible for increases in heavy precipitation. Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model-model comparisons. Here we show that human-induced increases in greenhouse gases have contributed to the observed intensification of heavy precipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas. These results are based on a comparison of observed and multi-model simulated changes in extreme precipitation over the latter half of the twentieth century analysed with an optimal fingerprinting technique. Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavy precipitation with warming.
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Explaining extreme events of 2013 from a climate perspective
- S C Herring
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National Centers for Environmental Prediction/National Weather Service/NOAA/US Department of Commerce