Climate Phenomena Research Articles

Diatom-based indications of an environmental regime shift and droughts associated with seasonal monsoons during the Holocene in Biển Hồ maar lake, the Central Highlands, Vietnam

The interactions of the different monsoon systems across Southeast Asia create extreme climate phenomena. Central Vietnam, located near the centre of this transitional region, has encountered numerous effects. As a result, its sediments from lakes or speleothems are valuable archives for interpreting past climate variability. However, there is still a lack of high-resolution paleoenvironmental and palaeoclimatic reconstructions during the Holocene in Vietnam. Our study presents a paleoenvironmental diatom-based record of sediment cores collected from Biển Hồ maar lake (14°03′N, 108°00′E) in the Central Highlands of Vietnam covering nearly the entire Holocene. Based on changes in diatom assemblages in the sediment sequence, we identified two periods of the Early Holocene (~11,700–7800 cal BP) and the Mid- to Late-Holocene (~7800–360 cal BP), which mark a remarkable shift in the environment around Biển Hồ. Alternations of key diatom species during the Early Holocene indicate intensity variations between water-mixing and thermal stratification mechanisms in meso-eutrophic conditions. During the Mid- to Late-Holocene, the complete dominance of Aulacoseira granulata var. granulata implies year-round destratification and intense mixing of the lake water column in a permanently eutrophic environment. Its morphological variability reveals intervals of dry environmental conditions driven by pronounced droughts across the Asian continent.

Climate Change Impacts on Human Health

Our environment provides us with natural resources that are important for our survival and livelihoods. The Earth’s species are dependent on the ecosystem service functions of our planet which is driven by climate stability. Health is a very important aspect and is most essential for life. Health is directly related to the nature of the environment, weather and climate. Changes in weather and climate have influenced the health of human populations in the past and caused several epidemics. Weather and climate can affect the distribution and survival of several arthropods, such as mosquitoes or mammals that are vectors for various diseases. Recently many people in Kerala and some parts of South India were affected by the West Nile virus which is attributed to the changing weather and vector borne influences. This fever is a mosquito-borne zoonotic disease and is caused by the flavivirus — West Nile Virus. The state of Kerala was on high alert as a seven year old boy from Mallapuram died in Kozikode due to the virus. In the same way, the water quality can be impacted giving rise to health problems. We are observing changes in the frequency and severity of weather and climate phenomena. This is seen as heavy rains, droughts, and also extreme cold or hot temperatures in different geographical regions. All this can lead to new climate-related health threats. Therefore, climate variability can pose threats to human health in several ways. The impacts of climate change are already being witnessed and will further increase in the coming decades. It may also lead to several emerging infectious diseases. Scientists study the exposure pathways in humans and animals for understanding the impacts of climate change on health. This involves conducting studies over time and in different locations, among different communities. In this research paper will discuss about the various impacts of climate change on human health.

CLIMATE PLANNING AND LOCAL GOVERNMENT: ACTORS AND CLIMATE CHANGE MEASURES

Urban development based on anthropogenic systems led to evident urban transformations on a global and local scale. Climate change is the product of these transformations, characterized by weather patterns and ecological systems alterations. These alterations cause impacts on urban dynamics, which generate severe social consequences. It becomes imperative to assume the inevitability of the climate phenomenon and adopt a new management model with adaptation and mitigation actions. The research addresses the climatic phenomenon in Ecuador, specifically in the urban area of Riobamba, emphasizing its planning instruments. The objective is to recognize the scope of local instruments and plans related to climate change and to identify actors involved through a map of actors according to their level of engagement and support for climate change action. The research contemplates a descriptive methodology with a qualitative approach using theoretical and argumentative techniques. The research considers documentary and fieldwork through methods such as documentary analysis, unstructured observation, in-depth interviews with strategic actors, case studies, and self-completed perception surveys of available subjects, corresponding to an exploratory and descriptive level. The results show that the local government did not consider initiatives aimed at climate planning and, despite programs and projects that seek to solve environmental problems, they need to be developed in detail or linked as measures against climate change.

Development of an evaluation indicator for highway climate change adaptation projects based on analytical hierarchy process in South Korea

AbstractOwing to climate change, abnormal climate phenomena occur frequently, damaging aging highway facilities. Therefore, it is necessary to develop adaptation projects for highway systems. Adaptation projects focus on mitigating the impact of climate change on highway facilities and enabling safe use. The present study aims to develop quantified evaluation indicators that are necessary for planning and selecting appropriate climate change adaptation projects. By analysing previous studies, the most important factors to be considered in the evaluation process of climate change adaptation projects were defined, and 20 preliminary evaluation indicators were divided into three layers. A feasibility study for each class was performed on the preliminary evaluation indicators by an expert panel; 16 evaluation indicators were selected through a feasibility study, and the weight of each indicator was calculated using the analytical hierarchy process (AHP) method. The priority of the evaluation indicators was service improvement through adaptation projects (weight 8.76), cost reduction and job creation (weight 8.46), and climate change impact reduction and vulnerability reduction (weight 8.31). These quantified evaluation indicators can help organizations that manage highways respond to climate change and establish adaptation projects.

Upper thermal tolerance and population implications for the Magdalena River stingray Potamotrygon magdalenae.

Knowledge of thermal tolerance limits provides important clues to the capacity of a species to withstand acute and chronic thermal changes. Climate models predict the increase and intensification of events such as heat waves, therefore understanding the upper thermal limits that a species can tolerate has become of utmost importance. We measured the upper thermal tolerance of the endemic Magdalena river stingray Potamotrygon magdalenae acclimated to experimental conditions, and then used critical thermal methodology to find the temperature at which an organism reaches a critical endpoint where locomotory activity becomes disorganized and the animal loses its ability to escape from conditions that will promptly lead to its death. We also describe the behavioral response of individuals to acute thermal stress and infer the possible consequences of temperature increases in the habitats of P. magdalenae populations. There were no significant differences between sexes in temperature tolerance or behavior. The critical thermal maximum (39°C) was 5.9°C above the maximum recorded temperature for the study area. Although P. magdalenae was tolerant to high temperature and currently is not living at its upper thermal limit, its survival in Guarinocito Pond will be threatened if temperatures continue to increase, considering the warming scenarios predicted for tropical regions due to climate change, even including short-term climate phenomena such as El Niño.

Refugees, Climate Litigation in the Global South and Climate Change: Facing the Gap in the Protection of Climate Refugees in International Law

Climate change, as the main catalyst for catastrophes in this century, is closely linked to large groups of human beings in forced displacement. This group, called climate migrants - people who, against their will, have to leave their places of origin due to climate phenomena. However, this group of human beings, which tends to expand expressively in the coming decades, reaching somewhere between 200 million to 1.2 billion people by 2050, still does not enjoy specific protection, for what they could be considered: refugees. Despite this, the recognition of this category of migrants as refugees is of immediate importance, due to the need for protection, which has not yet been reflected in international law. Thus, at the moment, what advances have been achieved regarding the protection of climate “refugees” and regarding the evolution of the use of the expression? The present work is developed through bibliographic and documentary research as a research technique, and the analytical-deductive method for analyzing information. In this context, climate strategic litigation, a mechanism through which climate impacts on human rights can be claimed in international courts, could be a possible short-term solution to the legislative gap for refugee protection.

Responses of annual streamflow variability to annual precipitation, extreme climate events and large-scale climate phenomena in the Qinghai-Tibet Plateau

Solar activity and large-scale climate phenomena have significant effects on extreme climate events and streamflow variability. As the roof of the world and the water tower of Asia, the Qinghai-Tibet Plateau (QTP) is highly sensitive to climate change. Therefore, it is of great significance to study the relationship between extreme hydrometeorological events of the QTP and climate change for global hydroclimate research. In this study, we analyzed the spatiotemporal variation and significant oscillation period of several hydrometeorological variables such as extreme precipitation indices (EPIs), extreme temperature indices (ETIs) and annual streamflow variability based on the observation data of hydrometeorological stations in the QTP during 1962–2019 using Sen’s slope estimator, Mann-Kendall test and continuous wavelet analysis (CWT). And the teleconnection patterns and the lead-lag relationship between annual precipitation, extreme climate events, multiple nonstationary climate mode and annual streamflow were evaluated using wavelet coherence (WTC). The results show that the climate of the QTP has been wetter and warmer in the past 58 years. The annual streamflow of several natural rivers in the QTP mainly show an increasing trend over the last 60 years. The annual streamflow of natural river (except Yellow River) increases significantly in three-rivers headwater region, and the rivers in the northeast and northwest also show a significant increase trend, but there is no significant change in the natural river streamflow in the south of QTP. In addition, the annual streamflow of natural rivers had significant periodicities in the bands of 2–4 years, 4–7 years and 7–11 years. The significant coherence of WTC spectra between annual precipitation and streamflow indicate that precipitation is the main reason for annual streamflow variation in the QTP. The variation of extreme climate events significantly regulates the regional annual streamflow. All EPIs except consecutive dry days show an in-phase correlation with annual streamflow of most headwater. Annual streamflow of Naijin River is positively and negatively correlated with extreme warm and extreme cold, respectively, and has a clearer lead-lag relationship than that with EPIs. Annual streamflow of headwater has higher correlations with EI Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) than with sunspot number (SSN). Solar activity may first affect ENSO and PDO, and then this effect is transferred sequentially to the hydrological cycle of the QTP by SSN-modulated PDO and PDO-SSN co-modulated ENSO. It is of great significance to investigate the response of streamflow variation to annual precipitation, extreme climate events and large-scale climate phenomena for water resources management, flood control, ecosystem restoration, and the well-being of surrounding residents and sustainable development in the QTP.

The Effect of Geoclimatic Factors on the Distribution of Paracoccidioidomycosis in Mato Grosso do Sul, Brazil.

The incidence of paracoccidioidomycosis (PCM) varies in Latin America, and it is influenced by environmental factors. This study evaluated the distribution of PCM acute/subacute form (AF) cases and their correlation with geoclimatic factors in the Mato Grosso do Sul (MS) state. The study included 81 patients diagnosed with the PCM/AF at the University Hospital of the Federal University of Mato Grosso do Sul between January 1980 and February 2022. Geographic coordinates, health microregion of patient's residence, compensated average temperature, relative air humidity (RH), El Niño Southern Oscillation (ENSO), and average global temperature were analyzed. The highest incidence was observed in the Aquidauana (7/100,000 inhabitants), while Campo Grande, the state's capital, had the highest number (n = 34; 42.4%) and density (4.4 cases/km2) of cases. The number of cases increased during extended periods of the El Niño phenomenon. A positive correlation was found between higher RH and PCM/AF cases. Most PCM/AF cases were found in areas with loamy soils and RH ranging from 60.8 to 73.6%. In MS, the health microregions of PCM/AF patients are characterized by deforestation for agricultural and pasture use, coupled with loamy soils and specific climatic phenomena leading to higher soil humidity.

Enhancing ENSO predictions with self-attention ConvLSTM and temporal embeddings

El Niño-Southern Oscillation (ENSO), a cyclic climate phenomenon spanning interannual and decadal timescales, exerts substantial impacts on the global weather patterns and ecosystems. Recently, deep learning has brought considerable advances in the accurate prediction of ENSO occurrence. However, the current models are insufficient to characterize the evolutionary behavior of the ENSO, particularly lacking comprehensive modeling of local-range and longrange spatiotemporal interdependencies, and the incorporation of calendar monthly and seasonal properties. To make up this gap, we propose a Two-Stage SpatioTemporal (TSST) autoregressive model that couples the meteorological factor prediction with ENSO indicator prediction. The first stage predicts the meteorological time series by leveraging self-attention ConvLSTM network which captures both the local and the global spatial-temporal dependencies. The temporal embeddings of calendar months and seasonal information are further incorporated to preserves repeatedly-occurring-yet-hidden patterns in meteorological series. The second stage uses multiple layers to extract higher level of features from predicted meteorological factors progressively to generate ENSO indicators. The results demonstrate that our model outperforms the state-of-the-art ENSO prediction models, effectively predicting ENSO up to 24 months and mitigating the spring predictability barrier.

A new tool for studying seasonality and spatio-temporal structure of ENSO cycles in data and ESM simulations

Abstract In this work, we present a new diagnostic tool for El Niño Southern Oscillation (ENSO) simulations in Earth System Models (ESMs) based on the analysis of upper ocean heat content data. It allows us to identify the seasonally dependent structure of temperature anomalies in the equatorial Pacific Ocean in the form of a dominant spatio-temporal pattern. We demonstrate the results of applying a tool to analysis of real data as well as climate simulations in two versions of the Institute of Numerical Mathematics ESM. We find that the latest version of the model, with improved parameterizations of clouds, large-scale condensation, and aerosols, provides significantly better reproduction of ENSO-related structure of anomalies, as well as the phase locking of ENSO to the annual cycle. We recommend to use the tool for diagnostic analysis of ESMs regarding simulation of climate phenomena with strong seasonality.

Relationship between chlorophyll-a, rainfall, and climate phenomena in tropical archipelagic estuarine waters

Similar to many estuaries worldwide with sources receiving nitrogen and phosphorus, i.e., nutrients, from point and diffuse sources, the waters in Jakarta Bay, Musi Estuary, and Rokan Estuary in Indonesia are facing negative impacts on water quality and ecosystems, i.e., eutrophication, because of rapid urbanization and human activities. The transport of nutrients through rivers and tributaries depends on rainfall and climate phenomena, ultimately dictating chlorophyll-a (Chl-a) concentrations and trophic levels in estuaries. The relationship between trophic level, Chl-a concentration, rainfall, and climate phenomena was explored in this study by examining monthly Chl-a concentrations from 2003 to 2021 in the three estuaries. Remote sensing Chl-a concentrations data from the NASA Aqua MODIS mission was subjected to Geographic Information System (GIS) and statistical analyses. The dynamic fluctuations of Chl-a concentrations in all estuaries showed eutrophic zones appearing at specific times, influenced by local rainfalls and their patterns. The first principal components of the Empirical Orthogonal Function (EOF) analysis of Chl-a concentration anomalies showed significant correlations with rainfall anomalies and the Indian Ocean Dipole (IOD) index. These relationships exhibited distinct patterns influenced by unique climate factors in each estuary. The study highlights the crucial role of wide-area continuous monitoring and early warning systems, facilitated by satellite remote sensing, in preserving the health of coastal ecosystems. The findings also offer valuable insights for designing future monitoring programs and targeted conservation efforts.

Retaining Short‐Term Variability Reduces Mean State Biases in Wind Stress Overriding Simulations

AbstractPositive feedbacks in climate processes can make it difficult to identify the primary drivers of climate phenomena. Some recent global climate model (GCM) studies address this issue by controlling the wind stress felt by the surface ocean such that the atmosphere and ocean become mechanically decoupled. Most mechanical decoupling studies have chosen to override wind stress with an annual climatology. In this study we introduce an alternative method of interannually varying overriding which maintains higher frequency momentum forcing of the surface ocean. Using a GCM (NCAR CESM1), we then assess the size of the biases associated with these two methods of overriding by comparing with a freely evolving control integration. We find that overriding with a climatology creates sea surface temperature (SST) biases throughout the global oceans on the order of ±1°C. This is substantially larger than the biases introduced by interannually varying overriding, especially in the tropical Pacific. We attribute the climatological overriding SST biases to a lack of synoptic and subseasonal variability, which causes the mixed layer to be too shallow throughout the global surface ocean. This shoaling of the mixed layer reduces the effective heat capacity of the surface ocean such that SST biases excite atmospheric feedbacks. These results have implications for the reinterpretation of past climatological wind stress overriding studies: past climate signals attributed to momentum coupling may in fact be spurious responses to SST biases.

An Assessment of Human Opportunistic Pathogenic Bacteria on Daily Necessities in Nanjing City during Plum Rain Season.

The plum rain season is a special climatic phenomenon in east Asia, which is characterized by persistent rainfall, a high temperature, and humidity, providing suitable environmental conditions for certain pathogenic bacteria, thus increasing the incidence of respiratory, gastrointestinal, and urinary diseases. However, studies on human opportunistic pathogenic bacteria communities during the plum rain season are still limited. In this study, the characteristics of human opportunistic pathogenic bacterial communities on daily necessities during the non-plum and plum rain seasons were investigated using high-throughput sequencing technology. The results revealed that the relative abundance of human opportunistic pathogenic bacteria was higher in the plum rain season (cotton cloth: 2.469%, electric bicycles: 0.724%, rice: 3.737%, and washbasins: 5.005%) than in the non-plum rain season (cotton cloth: 1.425%, electric bicycles: 0.601%, rice: 2.426%, and washbasins: 4.801%). Both temperature and relative humidity affected human opportunistic pathogenic bacterial communities. Stochastic processes dominated the assembly process of human opportunistic pathogenic bacterial communities, and undominated processes prevailed. The stability of the co-occurrence network was higher in the non-plum rain season than that in the plum rain season. In addition, the proportion of deterministic processes showed the same trend as the complexity of the co-occurrence network.

Holocene climatic and tectonic forcing of decadal hydroclimate variation on the north-eastern Tibetan Plateau

A better understanding of past climate and landscape variability in high resolution on the Tibetan Plateau is of critical importance for the understanding of fundamental mechanisms and interactions in the global climate system. However, due to relatively few datasets in decadal-resolution available for analyzing possible seasonal effects and seismic activity on the northeastern Tibetan Plateau, further high-resolution lake records as an integration need to be explored to test the significance of the seasonal variations of surface processes and climatic phenomena as well as tectonic impact on a decadal scale. The rhomb-shaped pull-apart Lake Donggi Cona along the modern monsoon marginal zone on the north-eastern TP is considered an excellent archive that monitors neotectonic and climatic changes through time. We obtained new high-resolution (mean 20 yr) proxy records from a 488 cm-long sediment core from the lake and compare them directly with paleoclimate records from nearby lakes. A decadal-resolution oxygen stable isotope (δ18O) record co-varies positively with carbonate content and demonstrates the profound and varying contribution of glacier/snow melt (winter/spring moisture) to lake hydrology at different lake evolution stages. This is also indicated by the grain size composition and related endmember modelling (EMMA) results. During 11.8–9.4 cal Ka BP, the lake experienced a swamp status, apart from the major lake body followed by water rise towards the littoral zone until 7.5 cal Ka BP. Glacier melt water supply started to be active since the late Younger Dryas and led to the strong excursions of carbonate contents and δ18O values according to insolation increase. This phase was dominated by the westerlies and characterized as low seasonality with long winter duration. Water rose to its highest level during 7.5–6.5 cal Ka BP and fluctuated with deep water phases until 4.7 cal Ka BP, due to glacier melt maxima and potential increase of summer (convective) moisture preserved in the oxygen isotopic signals. Water cover dropped and remained low until 2.9 cal Ka BP due to the reduced glacier melt and colder climate. However, the low δ18O values at a reduced water budget points to the still active contribution of spring glacier/snow melt that kept the lake not dry-up unlike other lakes with no glacier melt water supply. After 2.9 cal Ka BP water level dropped towards a pond/lagoon situation until 2.0 cal Ka BP, albeit temperature rise after a long cold climatic interlude. It might be caused by another phase of lake deepening triggered by subsidence and related sediment relocation from the shore, rather than by climatic factors. However, water level increased again afterwards and fluctuated towards the present level due to non-summer moisture supply in long freezing winters. We assume profound signatures of high seasonality in climate after 7.5 cal Ka BP and the lake became open since1.3 cal Ka BP. We suggest that combined thermal forcing by glacier/snow melt and tectonics play a significant role together with solar forcing, governing hydroclimate changes on the north-eastern Tibetan Plateau with decadal to millennial cycles.

Quality evaluation of Nothofagus pumilio seeds linked to forest management and climatic events

Abstract Background Forest ecosystems undergo significant transformations due to harvesting and climate fluctuations, emphasizing the critical role of seeding in natural regeneration and long-term structural preservation. Climate change further amplifies these dynamics, affecting phenology across species and regions. In Tierra del Fuego (Argentina), Nothofagus pumilio (lenga) forests represent the most important timber resource, and it is managed through different silvicultural strategies. This species demonstrates notable post-disturbance regeneration, yet seed fall exhibits significant variability, leading to variations in seed quality (e.g., viability). This study aims to assess fluctuations in N. pumilio seed quality, determine how it varies concerning forest management strategies, annual productivity, and the co-occurrence of climatic phenomena including El Niño-Southern Oscillation (ENSO) and the Southern Annular Mode (SAM). Results Viable seeds represented 18.4% of the total, notably higher in unharvested than in managed areas. Conversely, empty seeds were more prevalent in harvested areas (> 75%). Seed quality exhibited significant differences across silvicultural treatments, except for insect-predated seeds, which had similar proportions across all areas, though dispersed retention showed higher predation. When considering years with varying production levels, high-production years favoured full and viable seeds, particularly in unharvested forests and aggregated retention, while low-production years saw reduced viability across all treatments. Quadratic models revealed that viability increased with seed production, where unharvested forests achieved the highest values. Climate variability influenced seed proportions, where ENSO+/SAM+ promoting more full and viable seeds, while ENSO–/SAM+ favoured non-predated seeds, especially in unharvested stands. Conclusions Seed quality varies among treatments and years with different levels of seeding. Variations in seed quality, linked to climatic events, influence seed viability. Seed quality plays a critical role in forest regeneration, ensuring a seedling bank for harvested stands to face climate variability. These findings are relevant for forest management and ecosystem services, considering the increasing climate variability and extreme events. Understanding these influences is crucial for Nothofagus pumilio forests' sustainability and global forest adaptation strategies.

Delving into flash droughts in Vietnam during the last two decades using the standardized evaporative stress ratio

A flash drought is a recently defined extreme event that has destructive impacts on agriculture as well as other elements of society and ecosystems. Understanding where and when flash droughts occur can improve predictability and mitigation strategies for countries with economies that rely on agriculture. This study represents the first investigation of flash drought occurrences in Vietnam, one of the largest agricultural exporters in the world, using the standardized evaporative stress ratio (SESR). Monthly SESR data captured historical sustained drought events across the study period and exhibited a pattern similar to that shown by the standardized precipitation evapotranspiration index over most of the study region, with Pearson’s correlations mostly ranging from 0.52 to 0.82. Results of the SESR analysis at a pentad timescale indicate that flash droughts did occur in the country over the last two decades, with the northern regions and a majority of the south-central coast experiencing fewer than 9 flash drought events that covered less than 20% of each region. The remaining southern areas of the country were subjected to a much higher flash drought frequency, with 12 to 21 occurrences covering from 30% to more than 50% of the area in each region, typically during the dry season and exacerbated by anomalies of potential evapotranspiration and temperature. This research also revealed that flash droughts in Vietnam were correlated with the El Niño Southern Oscillation climate phenomenon, particularly in the southern regions, where a high flash drought frequency could take place under either El Niño or neutral conditions. This study provides new evidence to support the development of a comprehensive overview of drought in Vietnam, the country’s drought mitigation strategies, and water management policies.

Historical Projection of the Rainfall Distribution in the North Region of Brazil

From a set of primary and secondary monthly data from 1991 to 2022, the annual and seasonal climatological pattern of the North region of Brazil, where most of the Amazon Biome is located, was analyzed. An incomplete Gamma distribution model was applied to the climatological precipitation data (mm); atmospheric pressure (mb); incidence of solar radiation (kJ/m²); air temperature and dew (ºC); relative humidity (%); wind intensity (m/s) with direction and maximum gust. Data normalization techniques and spatial similarity identified different patterns and trends of precipitation in the region, with significant seasonality, especially in terms of rainfall. The highest precipitation rates occurred in the N-NW axis, inside the northern Amazonian area, while the lowest values were observed in the southern equatorial zone, on the limits of the Pará State with the Cerrado Biome. Four zones and one climate range were established: southern, central, northern west and northern east zones and extreme north area, all with significant similarity in precipitation and humidity. A trend was observed in the number of days with precipitation between 25 and 50% in the southern and central zones, and an increase in precipitation of 50 to 75% for the northern zone. The wind distribution model showed a tendency towards the presence of isotropic climate phenomena, presenting the same properties or characteristics. The results obtained are relevant to support research aimed at understanding global warming and its consequences, in addition to contributing to forest management programs, and establishing more effective protocols for cultivation in agricultural areas in the Amazon.

Effective reduced models from delay differential equations: Bifurcations, tipping solution paths, and ENSO variability

Conceptual delay models have played a key role in the analysis and understanding of El Niño-Southern Oscillation (ENSO) variability. Based on such delay models, we propose in this work a novel scenario for the fabric of ENSO variability resulting from the subtle interplay between stochastic disturbances and nonlinear invariant sets emerging from bifurcations of the unperturbed dynamics.To identify these invariant sets we adopt an approach combining Galerkin–Koornwinder (GK) approximations of delay differential equations and center-unstable manifold reduction techniques. In that respect, GK approximation formulas are reviewed and synthesized, as well as analytic approximation formulas of center-unstable manifolds. The reduced systems derived thereof enable us to conduct a thorough analysis of the bifurcations arising in a standard delay model of ENSO. We identify thereby a saddle–node bifurcation of periodic orbits co-existing with a subcritical Hopf bifurcation, and a homoclinic bifurcation for this model. We show furthermore that the computation of unstable periodic orbits (UPOs) unfolding through these bifurcations is considerably simplified from the reduced systems.These dynamical insights enable us in turn to design a stochastic model whose solutions – as the delay parameter drifts slowly through its critical values – produce a wealth of temporal patterns resembling ENSO events and exhibiting also decadal variability. Our analysis dissects the origin of this variability and shows how it is tied to certain transition paths between invariant sets of the unperturbed dynamics (for ENSO’s interannual variability) or simply due to the presence of UPOs close to the homoclinic orbit (for decadal variability). In short, this study points out the role of solution paths evolving through tipping “points” beyond equilibria, as possible mechanisms organizing the variability of certain climate phenomena.

A GIS-Based Emotion Detection Framework for Multi-Risk Analysis in Urban Settlements

The application of sentiment analysis approaches to information flows extracted from the social networks connected to particular critical periods generated by pandemic, climatic and extreme environmental phenomena allow the decision maker to detect the emotional states of citizens and to determine which areas are most at risk and require specific resilient adaptation interventions. Of particular relevance today is the need to analyze the multiple risks generated by extreme phenomena in urban settlements in order for the decision maker to identify which areas are most at risk and prepare resilient intervention plans with respect to all the phenomena analyzed. In recent years, the COVID 19 pandemic emergency has forced citizens to undergo specific restrictions to protect their health; to these were added critical issues due to the occurrence of extreme climatic or environmental phenomena. In order to monitor pandemic and climate/environmental multi-risks in urban settlements, we propose a GIS-based framework in which an emotion detection method is applied to determine the prevailing emotional categories in urban study areas during pandemic periods and in the presence of extreme climatic phenomena. The framework was tested on a study area based in the six districts of the city of Bologna (Italy) in order to detect, based on the emotions expressed on social channels, which were the most critical city neighborhoods in pandemic periods and in the presence of extreme heat wave climatic events. The results show that the proposed model can represent a valid tool to support decision makers in identifying the most critical urban areas in the presence of pandemic and climate/environmental multi-risks.

Probabilistic skill of statistically downscaled ECMWF S2S forecasts of maximum and minimum temperatures for weeks 1–4 over South Africa

AbstractThe probabilistic forecast skill level of statistically downscaled European Centre for Medium‐Range Weather Forecasts (ECMWF) subseasonal‐to‐seasonal (S2S) forecasts is determined in predicting maximum and minimum temperatures for weeks 1–4 lead times during 20‐year December–January–February (DJF) seasons from 2001 to 2020 over South Africa. Skilful S2S forecasts are vital in assisting decision‐makers in the development of contingency planning for any eventualities that may arise because of weather and climate phenomena. Extreme high‐ and low‐temperature events over a prolonged period can lead to hyperthermia and hypothermia, respectively, and can lead to loss of life. The results from the relative operating characteristic (ROC) and reliability diagrams indicate that the ECMWF S2S model has skill in predicting maximum temperature up to week 3 ahead, particularly over the central and eastern parts of South Africa. The ROC scores indicate that the model has skill in predicting minimum temperature up to week 4 ahead for the above‐normal category, particularly over the central and eastern parts of South Africa. Reliability diagrams indicate that the model has a tendency of overestimating the below‐normal category when predicting both maximum and minimum temperatures for weeks 1–4 lead times over South Africa. Furthermore, canonical correlation analysis (CCA) pattern analysis suggests that when there are anomalously positive and negative predicted 850‐hPa geopotential heights located over South Africa, there are anomalously hot and cold conditions during the DJF seasons over most parts of South Africa, respectively. These results suggests that statistical downscaling of model forecasts can improve forecast skill. Moreover, the results suggest that there is potential for S2S predictions in South Africa, and as such, S2S prediction system for maximum and minimum temperatures can be developed.