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Under extreme conditions, such as wars, pandemics, and climate events, the role of open space and public rituals alters dramatically. Extreme conditions remind us that daily life is fragile. What should dictate the development of public spaces? What does Covid-19 teach us about public space, its use and future design? Should planners and designers address the unexpected when designing public spaces? These questions are the departure point for discussing the social value and design of public space during both extreme conditions and calm times. © 2021. All Rights Reserved.

The magnitude of temperature changes in the Early Jurassic are not well known. Clumped isotope measurements can potentially be used to provide better constrains, but unfortunately many of the well-studied sedimentary successions that preserve Lower Jurassic fossils experienced burial temperatures above the limits of preservation of Δ47, which for geological timescales is thought to be between 80–120 °C. Samples from these basins are expected to be partially reordered and yield apparent clumped isotope temperatures that are warmer than original values. Here, we explore whether useful paleoclimate information can be recovered from these samples. We test the hypothesis that relative temperature differences are preserved in partially reordered samples when they experience a common burial history. This was done with the use of reordering models and Δ47 measurements of early Jurassic belemnites from the Aubach section of the SW German Basin, a basin that has a relatively well constrained burial history with maximum burial temperatures above 90 °C. We find that even though partial reordering progressively erases the Δ47 difference between samples, the majority (>50%) of the signal is preserved when samples are buried at temperatures as high of 150 °C for up to 200 Ma. Moreover, the models demonstrate that – regardless of burial conditions – partially reordered samples always preserve minimum records of temperature change across climate events. These inferences are supported by the belemnite Δ47 data that show partially reordered compositions and warming/cooling patterns across the Early Jurassic that closely mimic observations from independent proxies. Model observations are used to interpret a 13 ± 4 °C (95% ci) temperature increase that is observed in the belemnite data across the Early Toarcian. The large magnitude of the temperature excursion is explained as a combination of warming and a change in belemnite habitat before and after the Toarcian Ocean Anoxic Event. Our results demonstrate the usefulness of partially reordered samples and further open the use of this proxy in deep time settings., Geochimica et Cosmochimica Acta, 293, ISSN:0016-7037, ISSN:1872-9533

Plague is an infectious disease found worldwide and has been responsible for pandemics throughout history. Yersinia pestis, the causative bacterium, survives in rodent hosts with flea vectors that also transmit it to humans. It has been endemic in Madagascar for a century but the 1990s saw major outbreaks and in 2006 the WHO described the plague as re-emerging in Madagascar and the world. This review highlights the variety of factors leading to plague re-emergence in Madagascar, including climate events, insecticide resistance, and host and human behaviour. It also addresses areas of concern for future epidemics and ways to mitigate these. Pinpointing and addressing current and future drivers of plague re-emergence in Madagascar will be essential to controlling future outbreaks both in Madagascar and worldwide.

Climate downscaling is a way to provide finer resolution data at local scales, which has been widely used in meteorological research. The two main approaches for climate downscaling are dynamical and statistical. The traditional dynamical downscaling methods are quite time- and resource-consuming based on general circulation models (GCMs). Recently, more and more researchers construct a statistical deep learning model for climate downscaling motivated by the single-image superresolution (SISR) process in computer vision (CV). This is an approach that uses historical climate observations to learn a low-resolution to high-resolution mapping and produces great enhancements in terms of efficiency and effectiveness. Therefore, it has provided an appreciable new insight and successful downscaling solution to multiple climate phenomena. However, most existing models only make a simple analogy between climate downscaling and SISR and ignore the underlying dynamical mechanisms, which leads to the overaveraged downscaling results lacking crucial physical details. In this paper, we incorporate the a priori meteorological knowledge into a deep learning formalization for climate downscaling. More specifically, we consider the multiscale spatial correlations and the chaos in multiple climate events. Depending on two characteristics, we build up a two-stage deep learning model containing a stepwise reconstruction process and ensemble inference, which is named climate downscaling network (CDN). It can extract more local/remote spatial dependencies and provide more comprehensive captures of extreme conditions. We evaluate our model based on two datasets: climate science dataset (CSD) and benchmark image dataset (BID). The results demonstrate that our model shows the effectiveness and superiority in downscaling daily precipitation data from 2.5 degrees to 0.5 degrees over Asia and Europe. In addition, our model exhibits better performance than the other traditional approaches and state-of-the-art deep learning models.

Increasing the concentration of greenhouse gases causes rising in global warming and carbon dioxide emissions. With further efforts to reduce carbon dioxide, it is possible to prevent the warming of the earth, but the effects of climate change that we have already created can not be reduced. Recent observed and predicted alterations in the global climate require a double policy to react to the decline in climate alteration and its adjustment (coexistence) to explain the key factors and their effects. Measures to reduce climate alteration through decreasing greenhouse gas releases or removing them from the atmosphere are possible. Execution of more reduction measures at the present time will require less adaptation in the future. Meanwhile, inadequate measures to curb climate change presently increase the risk of catastrophic consequences, so that adjustment costs will rise unreasonably and adaptive capacity will face further constraints. Climate change adaptation measures concentrate in increasing our capability to deal with or prevent damaging effects or the use of new circumstances. Increasing temperature and changes visible today due to climate change mean that adaptation strategies should be applied. In this paper, strategies for reducing climate change and adaptation are reviewed and various strategies are presented. Meanwhile, this paper looks at the economies affected by climate change, our involvement to climate alteration, and the ways in which the economy has influenced climate change and the ways in which it can provide logical options.

Infectious disease outbreaks emerged across the globe during the recent 2015-2016 El Niño event, re-igniting research interest in how climate events influence disease dynamics. While the relationship between long-term warming and the transmission of disease-causing parasites has received substantial attention, we do not yet know how pulse heat events - common phenomena in a warming world - will alter parasite transmission. The effects of pulse warming on ecological and evolutionary processes are complex and context dependent, motivating research to understand how climate oscillations drive host health and disease. Here, we develop a framework for evaluating and predicting the effects of pulse warming on parasitic infection. Specifically, we synthesize how pulse heat stress affects hosts, parasites, and the ecological interactions between them.

A core taken in a tree today can reveal climate events from centuries past. Here we adapt this idea to record histories of neural activation. We engineered slowly growing intracellular protein fibers which can incorporate diverse fluorescent marks during growth to store linear ticker tape-like histories. An embedded HaloTag reporter incorporated user-supplied HaloTag-ligand dyes, leading to colored stripes whose boundaries mapped fiber growth to wall-clock time. A co-expressed eGFP tag driven by the cFos immediate early gene promoter recorded the history of neural activity. High-resolution multispectral imaging on fixed samples read the cellular histories. We demonstrated recordings of cFos activation in ensembles of cultured neurons with a single-cell absolute accuracy of approximately 39 min over a 12-hour interval. Protein-based ticker tapes have the potential to achieve massively parallel single-cell recordings of multiple physiological modalities.

As the cost and societal impacts of extreme weather, water, and climate events continue to rise across the United States, the National Weather Service (NWS) has adopted a strategic vision of a Weather-Ready Nation that aims to help all citizens be ready, responsive, and resilient to extreme weather, water, and climate events. To achieve this vision and to meet the NWS mission of saving lives and property and enhancing the national economy, the NWS must improve the accuracy and timeliness of forecasts and warnings, and must directly connect these forecasts and warnings to critical life- and property-saving decisions through the provision of impact-based decision support services (IDSS). While the NWS has been moving in this direction for years, the shift to delivering IDSS holistically requires an agency-wide transformation. This article discusses the elements driving the need for change at the NWS to build a Weather-Ready Nation; the foundational basis for IDSS; ongoing challenges to provide IDSS across federal, state, local, tribal, and territorial levels of government; the path toward evolving the NWS to deliver more effective IDSS; the importance of partnerships within the weather, water, and climate enterprise and with those responsible for public safety to achieve the Weather-Ready Nation vision; and initial supporting evidence and lessons learned from early efforts.

The lower Ribeira de Iguape stream – located in Sao Paulo, Brazilian southern coast, exhibits complex geomorphologic characteristics that resulted from multiple processes developed during the late Holocene. The present study proposes discussions about the possible relations between short-term climate events from the late Holocene (Climate Pulses) promoting the coastal dynamics and genesis of different levels of low fluvial-marine and marine terraces located in the study area, a subject rarely considered in other studies in humid tropical regions. The procedure of work included grain-size analyses and optically stimulated luminescence (OSL) dating of sediment samples collected from different depositional packages. Four depositional events resulted from transgressive and regressive events geochronologically related with climate pulses from the late Holocene were identified. The events can be summarized as follows: I) Marine Transgression (∼3.5–2.7 ka); II) Marine Regression (2.7–1.8 ka); III) Marine Transgression (1.8–0.65 ka); IV) Marine Regression (0.65–0.10 ka).

The interaction between planetary-scale wave and synoptic-scale wave in atmospheres is important in understanding the physical mechanism of short or long term weather or climate events, such as the blocking phenomena. Kinds of physical factors are disclosed to affect the interaction processes, such as the topography, background current. The effect of beta parameter is investigated in the present paper, it is called the generalized beta effect. By using methods of multiple scales and perturbation expansions, a new nonlinear forced Schrodinger equation is obtained in describing the evolution of planetary-scale envelope Rossby solitary waves, and a modified equation for synoptic-scale waves is derived. By constructing the numerical solution for the nonlinear Schrodinger equation, it reveals that the generalized beta can shift phase and modify the magnitude of planetary-scale envelope solitary waves. An analytical expression for synoptic-scale waves, including the generalized beta effect, is also obtained. It shows that the asymmetry, intensity and persistence of both planetary-scale wave and synoptic-scale wave depend strongly upon the generalized beta. The results provide new theoretical explanations for our understanding of wave-wave interaction.

Este ensaio vem discorrer sobre a mudança do clima, em que consiste e como esta afeta adversamente a fruição dos direitos humanos. Descreve de que modo o clima age como fator de violação de direitos humanos, as iniciativas de cidadãos para demandar mais efetividade no combate ao problema e as respostas da comunidade internacional para proteger os direitos humanos diante da mudança climática. A seguir, trata das migrações provocadas pelos eventos climáticos e dos instrumentos jurídicos existentes para proteção dos direitos humanos nesse contexto. Expõe como alguns grupos populacionais estão mais expostos aos impactos da mudança do clima que outros, apesar de terem contribuído menos para o problema. Prossegue discorrendo sobre a relação entre a mudança climática e os conflitos e apresenta a contribuição que os recursos naturais oferecem para a construção da paz e proteção dos direitos humanos. Por fim, apresenta conclusões e recomendações.

Increasingly unstable climate events such as floods and other natural disasters have become part of the grand narratives of the Anthropocene that create distance, fear, anxiety, hysteria and apathy that are part of our everyday lives. In asking how can we-as-humans survive both the real and grand narratives of this epoch, my own survival story of Desperado (memories of our family sailing boat) became an anchor for COPE (Choreographies of Participatory Ecologies). These choreographies, as series of guided performances/survival tours, involved tactics and strategies/mechanisms that contributed to an ecology of participatory practice. The instructional video Lilo Safely drew together actions of rafting, resting and recovery as a way to take care of other, to deconstruct the instrumental way of being-with the planet, encouraging us to include the non-human, the neuro-diverse, into our own stories of surviving with and beyond, through the practice of Rafting-with.

With high temporal resolution and accurate age control, tree-ring width is a good proxy for recording past climate variations from interannual to centennial time scales. The complex network method, widely used in analyses of modern meteorological observations, is an effective method to demonstrate synchronizations within climate events, thus revealing potential climate teleconnections. In this study, we tested to use the complex network in analyzing extremes recorded in time serials of tree-ring width in East Asia during the past 600 years. Our study indicates that this method is a valuable approach to reveal synchronizations in climate-sensitive tree-ring width records, though the ability of this method is dependent on the quality of the tree-ring data. Furthermore, our study shows stronger synchronizations in extremes of tree-ring width records during the CE 1850–1950 period in the Modern Warm Period than the CE 1450–1650 period in the Little Ice Age. A remarkable shift in synchronization types within the south part and the inland East Asia sites appears during the year CE 1850–1950. These changes in synchronizations suggest potential reorganizations in climate teleconnections, which is worthy being addressed in further studies with detrending and statistical significance testing methods involved.

We present new high-resolution absolute-dated stalagmite δ18O and δ13C records from the southeastern United States (SE US) spanning the last 12 thousand years (ka). A local relationship between annual rainfall amount and its amount-weighed δ18O composition exists on interannual timescales, driven mostly by an amount effect during summer and spring seasons, and by an isotopically depleted composition of fall and winter precipitation. Based on a novel interpretation of modern rainfall isotopic data, stalagmite δ18O variability is interpreted to reflect the relative contribution of summer and spring precipitation combined relative to combined fall and winter precipitation. Precipitation amount in the SE US increases during the Younger Dryas, the 8.2 ka and Little Ice Age abrupt cooling events. High precipitation during these events reflects enhancement of spring and summer precipitation while the contribution of fall and winter rainfall remained unchanged or decreased slightly. Results from this study support model simulation results that suggest increased precipitation in the SE US during Atlantic Meridional Overturning Circulation (AMOC) slowdown/shutdown (LeGrande et al., 2006; Renssen et al., 2002; Vellinga and Wood, 2002). In association with Northern Hemisphere mid-latitude cooling from the Early to mid-Holocene, annual precipitation in the SE US decreases, a pattern distinctive from that observed during abrupt cooling events related to AMOC shifts. Long-term hydroclimate change in the SE US is likely sensitive to summer insolation reduction as inferred for other tropical and subtropical regions. This study has implications for our understanding of the sensitivity of subtropical hydroclimate to factors both internal and external to the climate system in a warmer climate.

Extreme weather and climate events, such as heat waves, cyclones, and floods, are an expression of climate variability. These events and events influenced by climate change, such as wildfires, continue to cause significant human morbidity and mortality and adversely affect mental health and well-being. Although adverse health impacts from extreme events declined over the past few decades, climate change and more people moving into harm's way could alter this trend. Long-term changes to Earth's energy balance are increasing the frequency and intensity of many extreme events and the probability of compound events, with trends projected to accelerate under certain greenhouse gas emissions scenarios. While most of these events cannot be completely avoided, many of the health risks could be prevented through building climate-resilient health systems with improved risk reduction, preparation, response, and recovery. Conducting vulnerability and adaptation assessments and developing health system adaptation plans can identify priority actions to effectively reduce risks, such as disaster risk management and more resilient infrastructure. The risks are urgent, so action is needed now.

This book contributes to previous and ongoing action to initiate and inform conversations about climate risk and the need for adaptation and resilience building. This involves blending insights from climate science about what the future climate will look like with experiences of the social science of response through adaptation, based on practical applications in a variety of contexts. In this chapter, we reflect on these conversations and what they mean for the growing adaptation agenda. We consider who needs to be involved in conversations about adaptation, how such conversations can be structured and the need to assess their outcomes. We profile important considerations relevant for tailoring climate information to make adaptation decisions and discuss the outcomes of different types of conversations. We conclude by noting the significance of recent major climate events and the rapidly evolving risk landscape in sub-Saharan Africa, and arguing that the need for these conversations is ever more evident. The experiences outlined in this book provide a starting point for conversations about adaptation that aim to inform future action.

Considerable research has been devoted to the relationship of climate change and the Late Bronze Age (LBA) Aegean ‘collapse’ in ca. 1200 BCE. Less attention has been paid to other factors that may have contributed in this crisis. Here we investigate the risk management strategies of the LBA people against the changing climate and another potential stress factor, monumental construction. Our case study area, the Argive Plain (Greece), accommodated several palatial centres which were active in monumental construction during the LBA. Since agriculture was the predominant subsistence strategy, resource-demanding building efforts may have affected the local economies profoundly. Simultaneously, changes in climate could have added pressure to maintain livelihood. Our study examines the area through a cross-craft interactions perspective, describing how different human activities were co-dependent. Our results emphasize the adaptive skills of the local population to the wide range of demanding tasks they faced in the LBA.

Bangladesh is a small country of South Asia which is considered as one of the most vulnerable countries in the world to climate change and it is affected by severe weather and climate events. In th...

Accurate and reliable gridded datasets are important for analyzing extreme weather and climate events. Specifically, these datasets should produce extreme value statistics that are close to reality. Here we use various statistical methods to evaluate the quality of four gridded data products in representing daily precipitation extremes. The data products are the COSMO-REA6 regional reanalysis, the ERA5 global reanalysis, and the E-OBS and HYRAS gridded observation-based datasets. The statistical methods we use offer a thorough insight into the quality of the different datasets by providing temporal and spatial extreme value statistics of daily precipitation. Our results show that all datasets except HYRAS underestimate the magnitude of daily precipitation extremes when compared with weather station data. Moreover, the reanalysis datasets give generally worse extreme value statistics of daily precipitation than the gridded observation-based datasets. In particular, the reanalysis datasets often fail in reproducing the accurate timing of observed daily precipitation extremes.

This study aimed to assess the impact of abnormal climate events on the production of Italian ryegrass (IRG), such as autumn low-temperature, severe winter cold and spring droughts in the central inland, southern inland and southern coastal regions. Seasonal climatic variables, including temperature, precipitation, wind speed, relative humidity, and sunshine duration, were used to set the abnormal climate events using principal component analysis, and the abnormal climate events were distinguished from normal using Euclidean-distance cluster analysis. Furthermore, to estimate the impact caused by abnormal climate events, the dry matter yield (DMY) of IRG between abnormal and normal climate events was compared using a t-test with 5% significance level. As a result, the impact to the DMY of IRG by abnormal climate events in the central inland of Korea was significantly large in order of severe winter cold, spring drought, and autumn low-temperature. In the southern inland regions, severe winter cold was also the most serious abnormal event. These results indicate that the severe cold is critical to IRG in inland regions. Meanwhile, in the southern coastal regions, where severe cold weather is rare, the spring drought was the most serious abnormal climate event. In particular, since 2005, the frequency of spring droughts has tended to increase. In consideration of the trend and frequency of spring drought events, it is likely that drought becomes a NEW NORMAL during spring in Korea. This study was carried out to assess the impact of seasonal abnormal climate events on the DMY of IRG, and it can be helpful to make a guideline for its vulnerability.

This study applied an untargeted–targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu′erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu′erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu′erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages.

There is a growing interest in the climate community to improve the prediction of high impact climate events, for instance ENSO (El-Ni\~no--Southern Oscillation) or extreme events, using a combination of model and observation data. In this talk we present a machine learning approach for predicting the committor function, the relevant concept. Because the dynamics of the climate system is chaotic, one usually distinguishes between time scales much shorter than a Lyapunov time for which a deterministic weather forecast is relevant, and time scales much longer than a mixing times beyond which any deterministic forecast is irrelevant and only climate averaged or probabilistic quantities can be predicted. However, for most applications, the largest interest is for intermediate time scales for which some information, more precise than the climate averages, might be predicted, but for which a deterministic forecast is not relevant. We call this range of time scales \it{the predictability margin}. We stress in this talk that the prediction problem at the predictability margin is of a probabilistic nature. Indeed, such time scales might typically be of the order of the Lyapunov time scale or larger, where errors on the initial condition and model errors limit our ability to compute deterministically the evolution. In this talk we explain that, in a dynamical context, the relevant quantity for predicting a future event at the predictability margin is a committor function. A committor function is the probability that an event will occur or not in the future, as a function of the current state of the system. We compute and discuss the committor function from data, either through a direct approach or through a machine learning approach using neural networks. We discuss two examples: a) the computation of the Jin and Timmerman model, a low dimensional model proposed to explain the decadal amplitude changes of El-Ni\~no, b) the computation of committor function for extreme heat waves. We compare several machine learning approaches, using neural network or using kernel-based analogue methods.From the point of view of the climate extremes, our main conclusion is that one should generically distinguish between states with either intrinsic predictability or intrinsic unpredictability. This predictability concept is markedly different from the deterministic unpredictability arising because of chaotic dynamics and exponential sensivity to initial conditions.

Abrupt climate events are generally believed to be characteristic of glacial (intermediate-to-large cryosphere) climate states, requiring either sizeable ice-sheets or large freshwater pulses to act as triggers for abrupt climate changes to occur. Amplification occurs when these triggers bear upon the Atlantic Meridional Overturning Circulation (AMOC). However, the focus on glacial climate states in abrupt climate change research has led to an underrepresentation of research into interglacial periods. It thus remains unclear whether high-magnitude climate variability requires large cryosphere-driven feedbacks or whether it can also occur under low ice conditions. Here we present a high resolution analysis of surface and deep water components of the AMOC spanning the transition from Marine Isotope Stage (MIS) 19c to 19a to test if orbital boundary conditions similar to our current Holocene can accommodate abrupt climate events. Sediment core DSDP 610B (53°13.297N, 18°53.213W), located approximately 700-km west of Ireland, was specifically chosen due to its high sedimentation rate during interglacial periods, excellent core recovery over the Quaternary and its unique geographical location. Above the core site, the dominant oceanographic feature is the North Atlantic Current and at 2417-m water depth, 610B is influenced by Wyville Thomson Overflow Water flowing southwards. A multiproxy approach including paired grain size analysis, planktic foraminifer assemblage counts, and ice-rafted debris counts within the same samples allows us to resolve the timing between both surface and bottom components of the AMOC and their response to abrupt climate events during MIS-19 in the eastern subpolar gyre. This study is societally relevant as future freshwater inputs from a melting Greenland ice sheet may impact ocean circulation, potentially causing shifts in climate for many European countries.

In the numerical prediction of weather or climate events, the uncertainty of the initial values and/or prediction models can bring the forecast result’s uncertainty. Due to the absence of true states, studies on this problem mainly focus on the three subproblems of predictability, i.e., the lower bound of the maximum predictable time, the upper bound of the prediction error, and the lower bound of the maximum allowable initial error. Aimed at the problem of the lower bound estimation of the maximum allowable initial error, this study first illustrates the shortcoming of the existing estimation, and then presents a new estimation based on the initial observation precision and proves it theoretically. Furthermore, the new lower bound estimations of both the two-dimensional ikeda model and lorenz96 model are obtained by using the cnop (conditional nonlinear optimal perturbation) method and a pso (particle swarm optimization) algorithm, and the estimated precisions are also analyzed. Besides, the estimations yielded by the existing and new formulas are compared; the results show that the estimations produced by the existing formula are often incorrect.

Data on diatom complexes from bottom deposits of Lake Karakel’ (the Karachayevo-Cherkessian Republic) have been analyzed. The principle of unification of bioindication methods has been applied. The hydrological parameters of lake water (temperature, pH, and saprobithy) have been reconstructed over a period of 2000 years. The results of isotopic dating of bottom sediments have been used. For the first time for the Central Caucasus, the current and Late Holocene diatom alga complexes have been described. Photographs of the most abundant and significant lower taxa of diatom algae are given.

While studies increasingly document long-term change in community composition, whether long-term change occurs gradually or via rapid reorganization events remains unclear. We used Latent Dirichlet Allocation (LDA) and a change-point model to examine the long-term dynamics of a desert rodent community undergoing compositional change over a 38-yr span. Our approach detected three rapid reorganization events, where changes in the relative abundances of dominant and rare species occurred, and a separate period of increased variance in the structure of the community. These events coincided with time periods, possibly related to climate events, where the total abundance of rodents was extremely low. There are a variety of processes that could link low abundance events with a higher probability of rapid ecological transitions, including higher importance of stochastic processes (i.e., competitive interactions or priority effects) and the removal of structuring effects of competitive dominants or incumbent species. Continued study of the dynamics of community change will provide important information not only on the processes structuring communities, but will also provide guidance for forecasting how communities will undergo change in the future.

Shallow-water carbonate deposits are well-known from the Eocene of the US Gulf Coast and Caribbean. These deposits frequently contain abundant larger benthic foraminifera (LBF). However, whilst integrated stratigraphic studies have helped to refine the timing of LBF overturning events within the Tethys and Indo-Pacific regions with respect to global bio- and chemo-stratigraphic records, little recent work has been carried out in the Americas. The American LBF assemblages are distinctly different from those of Europe and the Indo-Pacific. It is therefore essential that the American bio-province is included in studies of LBF evolution, biodiversity and climate events to understand these processes on a global scale. Here we present the LBF ranges from two previously unpublished sections spanning 35 and 29 m of the upper Eocene Ocala limestone, as the early stages of a larger project addressing the taxonomy and biostratigraphy of the LBF of Florida. The study indicates that the lower member of the Ocala limestone may be Bartonian rather than Priabonian in age, with implications for the biostratigraphy of the region. In addition, the study highlights the need for multiple sites to assess the LBF assemblages and fully constrain ranges across Florida and the US Gulf and suggests potential LBF events for future integrated stratigraphic study.

The Late Pleistocene to the Holocene is a time interval that covers the climate transition from a cold to a warm interglacial regime. In the Baltic region, many studies have focused on estimating environmental responses to climatic forcing using palynological and stratigraphic proxies of glacial and periglacial settings. Herein we describe the mixed lacustrine-aeolian succession of the Zervynos-2 section (south-eastern Lithuania), located in the north-eastern part of the European Sand Belt. The succession and the sedimentation styles were characterized by granulometric parameters, structural features, dolomite/calcite ratio, and paleobotanical macro-remains. Our analyses revealed that the Zervynos-2 paleolake formed on the sandur (outwash) plain during the final stage of the Pleistocene. The onset of lake sedimentation was caused by sudden submergence of a sandbody-constrained paleovalley. Carbonate ratios and macro-remains from the lower gyttja material showed the presence of substantial millennial-scale oscillations, which suggests a delayed response to the isotopically derived paleotemperatures. The transition to the fast sand sedimentation started approximately in the Middle Holocene and is interpreted here as being caused by warming and drying of the climate in the Baltic region. The upper Holocene portion of the section represents the transition to exclusively aeolian sedimentation with lower accumulation rates that are likely related to a long-term cooling trend. The obtained results support the conjecture that there is a direct but delayed positive correlation between dolomite and calcite ratios in lake sediments and the climatic signal in the Greenland GISP2 record.

Despite the extreme events impact on various climate events frequency and intensity in many developing countries, there has been dearth information on daily climate trends and climatic extremes. This study comes to characterize the climate type and its evolution in Morocco, specially the two regions Beni Mellal-Khenifra and Daraa-Tafilalt. RClimdex software has been used to calculate pluvio-thermal and ombro-thermic indices in the studied stations to reveal climate type in the two regions, their evolutions, and the daily extreme temperatures and precipitations. A cartographic representation has been done for the calculated indices and climatic trends in the stations from 1970 to 2016. As results, the temperature trend for hot day’s number shows a significant increase, while the cold night’s numbers, warm sequences, and precipitation are gradually decreases especially at Khouribga and Midelt. These observed modifications influence negatively the annual rainfall total in the year, the consecutive wet days, the maximums rainy days, and the increase of consecutively dry days. As a conclusion, the Martonne aridity and ombro-thermic indices, show that the temperatures and precipitations evolutions do not induce a change in the climate type for the studied regions.

Os fenômenos climáticos El Niño e La Niña atualmente recebem mais atenção devido ao fato de seus acontecimentos ocorrerem com maior frequência influenciando o clima regional e global. Na metodologia analisaram-se cálculos estatísticos de dados no período histórico de 1985 a 2016, identificando as variações divergentes da média calculada encontrando assim as anomalias dos regimes pluviométricos, correlacionando com anos de registros dos eventos climáticos El Niño e La Niña foram identificadas anomalias climáticas de grande impacto nos municípios de Manaus, Itacoatiara, Eirunepé e São Gabriel da Cachoeira, motivo este que o cidadão e a indústria deve-se atentar para o registro de tais eventos, pois os regimes pluviométricos influenciam desde produção de alimento a geração de energia, enchentes ou secas dos rios do Amazonas.

Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.

The present paper examines variability of characteristics of snow cover (snow cover depth, number of days with snow cover and dates of beginning and end of snow cover) in Poland. The study makes use of a set of 43 long time series of observation records from the stations in Poland, from 1952 to 2013. To describe temporal changes in snow cover characteristics, the intervals of 1952–1990 and of 1991–2013 are compared and trends in analysed data are sought (e.g., using the Mann–Kendall test). Observed behaviour of time series of snow-related variables is complex and not easy to interpret, for instance because of the location of the research area in the zone of transitional moderate climate, where strong variability of climate events is one of the main attributes. A statistical link between the North Atlantic Oscillation (NAO) index and the snow cover depth, as well as the number of snow cover days is found.

It is recognized that biodiversity changes across the planet latitudinally; however, the timing of and reasons for diversity loss at higher latitudes are not well understood. Meseguer and Condamine investigate phylogenies and fossil evidence of reptilian species and determine that global warming and cooling events allowed asymmetric extinction and dispersion across latitudes, suggesting a hypothesis where climate profoundly shapes the latitudinal diversity gradient in certain taxa.

Background Extreme weather and climate events impact public health in multiple ways and extreme heat is one of the major environmental challenges for public health in Thailand. Objective We assessed the effects of heat stress on occupational health among agricultural workers who are exposed to the heat at different levels for both males and females in different age groups. We further investigated the responses to extreme heat among the government agencies. Methods A cross-sectional study was used to identify heat exposure situations that create heat stress-related health risks. The question guidelines have been developed to assess occupational heat impacts in the study site and used semi-structured interviews to describe how agricultural workers experience heat exposures where they work. The Wet Bulb Globe Temperature (WBGT) index and temperatures were measured by WBGT monitors in both winter and summer. Twenty-nine participants aged 24–76 were recruited to the study. Results All participants had one or more signs and symptoms of heat stress; however, they had concerns about work-related heat stress prevention. Outdoor WBGT was found to be highest between 11:00 AM and 11:59 AM, and 13:00 PM and 13:59 PM in winter and summer, respectively. Our findings revealed that study sites had heat indices necessitating extreme caution, where sunstroke, muscle cramps, and/or heat exhaustion were possible with prolonged exposure. Conclusions A heat health warning system is essential to reduce the negative impacts of extreme weather.

The North Atlantic Oscillation (NAO) as a prominent atmospherical mode is of great research value since its significant impact on global climate change. The contributing factor of NAO events is research hotspot of atmospheric sciences. The study of optimal precursor (OPR) which can trigger the NAO events is conducive to improving the predictability. Conditional nonlinear optimal perturbation (CNOP) method is a useful tool to solve this kind of nonlinear initial value problem, and has been widely applied in identifying OPRs of different climate events with various numerical models. In this work, the OPRs of NAO events are identified using Community Earth System Model (CESM). However, solving CNOP in such a high-dimension model with data scale of more than 5 millions is a relatively difficult and computationally expensive task. Thus, we extend the dimensionality reduction idea to a swarm intelligence algorithm called Bacterial Foraging Optimization Algorithm (BFOA) to explore the OPRs of NAO events. The task is transformed into the problem in low-dimensional space with principal component analysis (PCA). To speed up the process, we implement the parallelization of algorithm and atmospheric component. Message Passing Interface (MPI) is adopted to make bacteria search in parallel, and Compute Unified Device Architecture (CUDA) is utilized to port massive matrix computation onto GPUs. With NVIDIA Tesla K80 on the Tianhe-2 supercomputer, the PCA-based BFOA (PBFOA) achieves a speed-up of 41.8× compared with its serial version. Moreover, the OPRs obtained by the proposed PBFOA can trigger the NAO events stably. The results indicate that the proposed method can solve CNOP in complicated models effectively and fleetly.

Data Availability: The data underlying the results presented in the study are available from JIRAMA (http://www.jirama.mg/). They are pubic third party data available through regular request to the office. Requests can be sent to: dexo-dqo@jirama.mg. The person in charge of the data is the head of the data unit: pascale.rakotomahanina@jirama.mg.; International audience; Low-income cities that are subject to high population pressure and vulnerable to climate events often have a low capacity to continuously deliver safe drinking water. Here we reported the results of a 32-year survey on the temporal dynamics of drinking water quality indicators in the city of Antananarivo. We analyzed the long-term evolution of the quality of the water supplied and characterized the interactions between climatic conditions and the full-scale water supply system. A total of 25,467 water samples were collected every week at different points in the supplied drinking water system. Samples were analyzed for total coliforms (TC), Escherichia coli (EC), intestinal Enterococci (IE), and Spores of Sulphite-Reducing Clostridia (SSRC). Nine-hundred-eighty-one samples that were identified as positive for one or more indicators were unevenly distributed over time. The breakpoint method identified four periods when the time series displayed changes in the level and profile of contamination (i) and the monthly pattern of contamination (ii), with more direct effects of rainfall on the quality of supplied drinking water. The modeling showed significantly different lags among indicators of bacteria occurrence after cumulative rainfall, which range from 4 to 8 weeks. Among the effects of low-income urbanization, a rapid demographic transition and the degradation of urban watersheds have gradually affected the quality of the water supplied and resulted in the more direct effects of rainfall events. We focused on the need to adopt an alternative perspective of drinking water and urban watersheds management.

Indian Ocean Dipole (IOD) in the Indian Ocean is one of the climatic phenomena that affects climate conditions in western Indonesia. West of Aceh Regency is one of the districts in Aceh Province which borders and faces the Indian Ocean directly, so it has a significant impact due to climate events caused by the IOD phenomenon. Analysis for examines the occurrence of climate phenomena is needed to minimize the adverse effects due to the IOD phenomenon. Spectral analysis by calculating the periodogram and the SARIMA model for forecasting historical data. The data used are monthly data on the Indian Ocean IOD index and rainfall in West of Aceh in the period January 2010 to December 2019. The purpose of this study was to determine the periodicity of the IOD index data and rainfall, get a model and obtain the results of forecasting the IOD index and rainfall, and see the relationship of IOD to rainfall in West of Aceh. The results obtained in the spectral analysis are the characteristics of changes in the IOD index tend to increase or decrease in the IOD index every 17 months and the characteristics of changes in rainfall in West of Aceh tend to increase or decrease in rainfall every 6 months. The best model for predicting IOD index data is the SARIMA model (2,1,3)(0,1,1)17. Forecasting for 2020 and 2021 tend to show a downward trend in 2020 and an upward trend in 2021. While the best model for predicting West of Aceh rainfall data is the SARIMA model (2,0.2)(0,1,1)6. Forecasting for 2020 and 2021 tend to experience high rainfall in April and October for each year. The relationship obtained by the IOD index to rainfall in West of Aceh is when the IOD index is in a positive phase, rainfall in the West of Aceh region tends to decrease. Conversely, when the IOD index is in the negative phase, rainfall in the West of Aceh region tends to increase.

The Last Termination (19 000–11 000 a BP) with its rapid and distinct climate shifts provides a perfect laboratory to study the nature and regional impact of climate variability. The sedimentary succession from the ancient lake at Hässeldala Port in southern Sweden with its distinct Lateglacial/early Holocene stratigraphy (>14.1–9.5 cal. ka BP) is one of the few chronologically well‐constrained, multi‐proxy sites in Europe that capture a variety of local and regional climatic and environmental signals. Here we present Hässeldala's multi‐proxy records (lithology, geochemistry, pollen, diatoms, chironomids, biomarkers, hydrogen isotopes) in a refined age model and place the observed changes in lake status, catchment vegetation, summer temperatures and hydroclimate in a wider regional context. Reconstructed mean July temperatures increased between c. 14.1 and c. 13.1 cal. ka BP and subsequently declined. This latter cooling coincided with drier hydroclimatic conditions that were probably associated with a freshening of the Nordic Seas and started a few hundred years before the onset of Greenland Stadial 1 (c. 12.9 cal. ka BP). Our proxies suggest a further shift towards colder and drier conditions as late as c. 12.7 cal. ka BP, which was followed by the establishment of a stadial climate regime (c. 12.5–11.8 cal. ka BP). The onset of warmer and wetter conditions preceded the Holocene warming over Greenland by c. 200 years. Hässeldala's proxies thus highlight the complexity of environmental and hydrological responses across abrupt climate transitions in northern Europe.

This article offers a chronology of climate events in Iran over the last millennium to challenge traditional chronologies of the Iranian past based on politics, war, and economics. Using insights gleaned from the historiography of climate in Iran, and from neighboring regions, especially the Ottoman Empire, four episodes of climate cooling show how climate-induced environmental processes affected more people for longer in Iran than did the policies of the empires ostensibly ruling over them. Thus, the article aims to put climate more squarely on the agenda of historians of Iran so that the conjectures advanced here can be confirmed, revised, or discarded through future empirical research. Moreover, the article seeks to bring Iran into wider conversations in environmental and global history.

Unmanaged wild reindeer populations tend to follow cyclical behaviour, and domesticatedreindeer populations often show cyclical behaviour, too. In this contribution, we intendto use the long-term development of two areas in northern Scandinavia to explore howexternally imposed policies and winter climate variability have influenced the reindeer herdsize and pasture state. We do this by comparing the development in two areas that are rathersimilar ecologically: Torneträsk in northernmost Sweden and Kautokeino (Vest-Finnmark)in northernmost Norway.Climatic and ecological studies as well as commons theory have been useful tools forunderstanding the inherent socio-ecological dynamics. Especially the time from 1850 to1940 includes several short periods when historical sources document combinations ofevents such as (1) closure of national borders to cross-border herding migrations, (2) relo-cations of herder households, (3) overutilization of lichen pastures, (4) catastrophic winters,and (5) forced herd reductions. The high number of incidents and actions during this eramakes it challenging to disentangle causes and effects.Our main findings are based on the documented effects of international events and con-sequent government policies and actions in Fennoscandia from 1852 to 1921 which haddramatic consequences, including excessive numbers of reindeer and people in north-ernmost Sweden, leading to more or less forced relocation southwards in Sweden withcascading effects in large parts of Sápmi. We have found clear indications that this con-tributed to overutilization of lichen pastures and beyond any reasonable doubt must alsohave reinforced the effects of several of the documented catastrophic climatic events, espe-cially in areas like Torneträsk to where many families from Finnmark were relocated. Fromthe first border closure in 1852 to the Second World War it thus seems as if the shocks fromthe political events were the main factor determining the development of reindeer herdingin large parts of Sápmi. The political and administrative history is well documented. Ourclimate data are a unique compilation of climate events based on multiple sources duringtwo centuries, which contribute to the validity of our findings. Our pasture state data fromthe late-1800s are also based on several sources which support each other. Reindeer herding, Adaptation, Political shocks, Climate events, Pasture state acceptedVersion

The Late Pliocene–Quaternary Great Caspian, in addition to the positive transgressive rhythmics shows regressions of different scales: balakhanskaya, domashkinskaya, tyurkyanskaya, venedskaya, chelekenskaya, chernoyarskaya, atel’skaya, enotaevskaya, mangyshlakskaya, and izerbashzkaya. In these periods, large-scale natural phenomena took place on the Caspian shelf, coasts, and adjacent inundated territories, including sea level drop, drying of a part of seabed, and change of landscapes and the sedimentation character. The neaped water area showed changes in water salt composition and temperature regime, along with a change in faunistic complexes. Different hierarchic state of sea level and different correlation with climate events on the surrounding territories was shown to take place during the regression with predominance of warm (interglacial) periods among them.

Much of the literature on climate change has focused on the physical science basis – the biophysical elements of exposure, probability and impacts of climate hazards on people and places. In 1995, the Intergovernmental Panel on Climate Change (IPCC) released its Second Assessment Report, which moved the climate discussion beyond the analytical focus on impacts to emphasize the properties of a social system (the assets, protections, institutions, and relationships) that mediate the outcome of a hazard and influence the capacity to adapt in the face of climate events. Since then the literature on the social dimensions of climate change has burgeoned. These studies have largely been global and national in scope, but there has also been a recent expansion of literature centering on the local and regional scales spearheaded by high-profile global urban resilience initiatives, such as the United Nation’s International Strategy for Disaster Reduction (UNISDR) Resilient Cities Campaign and the Rockefeller Foundation’s 100 Resilient Cities. While these studies have made important contributions to knowledge about how climate change may affect cities and regions by measuring vulnerability and articulating impacts, there is substantial room for new engagement. There is a clear need for more textured analyses of vulnerability to understand how risk is framed and how the framing articulates with rationale for risk reduction solutions. This paper examines two main approaches to vulnerability. It aims to generate insight on how risk is conceptualized and framed in order to open up discussions on the politics of framing risk and the possibilities for more integrative and equitable risk reduction solutions.

The Iguape River estuary – located on the southern coast of Sao Paulo state (Brazil) – presents geomorphological records of the complex processes operating during the Late Holocene. Dating the top deposits of coastal (fluvial, transition and marine deposits) low terraces, contributes to the understanding of the erosive-depositional events resulting from autogenic and allogenic processes. Optically stimulated luminescence (OSL) dating, grain-size and morphostructural analysis were used to investigate the Late Holocene geomorphological evolution of the Iguape estuary. The results suggest that formation of the Iguape estuary is consistent with a marine incursion triggered by climate pulses by around 2.7 ka. However, the coastline displacement was controlled by base-level adjustments and fluvial incision phases probably induced by fault activity associated with the Guapiara Lineament. Finally, the results show that the estuarine systems in humid tropical regions are significantly sensitive to short time-scale climate events during the Holocene.

This research is devoted to the response of the southern taiga oligotrophic Iksinskoe bog to extreme Holocene climatic events. Based on data of preliminary geological exploration and 14 C-dated cores-analogues of this bog, a spatio-temporal model of paludification and vegetation succession from 11 paleosurface chrono-slices is created. It has been shown that the global dry cooling events of about 8200, 5900, 4900, and 2800 cal yr BP influenced the bog dynamics. Their direct impact is through the formation of a long-term thawing seasonal frost and permafrost water pressure as well as palsa. Their indirect impact is through a permafrost degradation and a subsequent warming. The cooling of 2800 cal yr BP had the maximum effect due to a drying and cryogenic peat accumulation stopping over a large area of the bog. During the subsequent warming of 2450 and 1900 cal yr BP there was a significant increase in the water content of the bog surface, and a phased oligotrophization of paleophytocenoses took place. The direct and indirect impacts of extremely dry Holocene cooling caused active paludificating, catastrophic changes in the paleophytocenoses, high water content of the surface, and reduced the depth of peat deposits of the Iksinskoe bog.

This study applied an untargeted&ndash, targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC&times, GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu&prime, erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu&prime, erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu&prime, erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages.