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The purpose of this research work was to analyze cereals cultivated area, yields, production and price at farm gate in Romania during the last decade, 2012-2021 and also in the year 2022 in order to identify the main trends and causes which affected the performances. The data provided by National Institute of Statistics and Eurostat were processed using indices methods, regression equations and r square, and comparisons between maize and wheat. The results emphasized that, compared to 2012 level, in 2021, Romania achieved 27.79 million tonnes cereals (+116.27%), 14.82 million tonnes maize grains (+149.07%), and 10.43 million tonnes wheat (+96.79%). Maize and wheat represent 92.8% of Romania's cereals production. The high record is explained by the large surfaces cultivated with cereals, accounting for 5.35 million ha in 2021 (-1.6% less than in 2012), of which maize 47.6% and wheat 40.6%, all together 88.2%. Yields are still below the levels achieved by France, Germany, Poland, Italy and Spain, which are its EU main competitors in producing cereals. Compared to 2012, in 2021, cereals yield was 5,188 kg/ha (+120%), maize 5,802 kg grains/ha (+166.16%), wheat 4,797 kg/ha (+78.85%), reflecting the efforts made by farmers to increase production. These results were carried out under the impact of intense climate variations and extreme phenomena like: high air temperatures, heat waves, long droughts, low precipitations. High price volatility for Diesel, seeds, fertilizers, products for plant protection etc had a deep impact on the increase of production costs. Cereals price at the farm gate also increased, under the influence of the unbalance demand/supply ratio in the international market, cereals quotations at the international stock exchange, and hostilities between Russia and Ukraine. Un uncertain future is for the coming agricultural years, when farmers have to strengthen their efforts as their business to survive. They have to set up new technological alternatives for crop structure, cultivated areas, amendments, conservative agriculture, lower farms inputs, environmentally friendly solutions to sustain soil fertility, extend biodiversity, and also to keep production costs under strict control and to assure a lower risk for their business. [ABSTRACT FROM AUTHOR]

It has long been recognized that there is a link between sustainable development, poverty and consistent access to useable water. Increased population is requiring more water and changing climate is altering the hydrological cycle making the water less accessible at the time when it is required. Combining the measurement of water availability and the socioeconomic capacity towards its access gives new insights in the fields of water resources management and poverty alleviation, which ultimately address the agenda of sustainable development. This paper customizes the water poverty index (WPI) indicators to encompass the climatic extremes and social settings to analyse the water stresses to the community people and their capacity to manage the water extremes focusing on the water availability in climatic variability condition in Karnali river basin in western Nepal. The indicators of the WPI were based on the multiple aspects of water focusing to water quantity and availability. The WPI is not only a useful tool to monitor progress; but it can even be used to identify areas of greatest need, thereby enabling prioritization of action in the water sector. [ABSTRACT FROM AUTHOR]

Faced with increasing climate extremes and climate change impacts, local governments in California are eager to advance their adaptation measures and build local resilience. However, as previous studies and day-to-day interactions with local leaders make clear, identifying ways to resource adaptation is one of the most significant barriers to progress. This paper draws on selected findings from a study that aimed to better describe the nature of the adaptation finance challenges local governments face so as to find ways to overcome them. Building on initial findings from an online survey and nine stakeholder workshops to deepen the understanding of the nature of funding and financing challenges for local governments, we use a methodological innovation in archetype analysis, grounded theory, to develop a suite of 15 archetypal adaptation finance challenges, i.e., repeatedly found patterns of interrelated causal factors, traits, and outcomes ranging from establishing a matter of concern worthy of attention (and funding) to acquiring, using, and managing adaptation finance. These archetypes are found across different types and sizes of local governments facing different climate change threats. The resulting deeper understanding of local adaptation funding challenges represents an important contribution to the literature and opens up new avenues for intervention beyond the prevailing focus on creating new funding vehicles. We offer archetype-specific recommendations to overcome or reduce these critical finance challenges in local climate change adaptation. [ABSTRACT FROM AUTHOR]

Highlights • Simplified formulation of the metastatistical extreme value is proposed. • Parsimonious handling of extremes emerging from multiple underlying processes. • Computationally efficient sensitivity analyses to changes in the underlying processes. • Robust framework for explanatory models, nonstationary analyses, climate projections. Abstract This paper presents a Simplified Metastatistical Extreme Value formulation (SMEV) able to model hydro-meteorological extremes emerging from multiple underlying processes. The formulation explicitly includes the average intensity and probability of occurrence of the processes allowing to parsimoniously model changes in these quantities to quantify changes in the probability of occurrence of extremes. SMEV allows (a) frequency analyses of extremes emerging from multiple underlying processes and (b) computationally efficient analyses of the sensitivity of extreme quantiles to changes in the characteristics of the underlying processes; moreover, (c) it provides a robust framework for explanatory models, nonstationary frequency analyses, and climate projections. The methodology is applied to daily precipitation data from long recording stations in the eastern Mediterranean, using Weibull distributions to model daily precipitation amounts generated by two classes of synoptic systems. At-site application of SMEV provides spatially consistent estimates of extreme quantiles, in line with regional GEV estimates and generally characterized by reduced uncertainties. The sensitivity of extreme quantiles to changes and uncertainty in the intensity and yearly occurrences of events generated by different synoptic classes is examined, and an application of SMEV for the projection of future extremes is provided. [ABSTRACT FROM AUTHOR]

Extreme precipitation can have significant adverse impacts on infrastructure and property, human health, and local economies. This paper examines recent changes in extreme precipitation in the northeast United States. Daily station data from 58 stations missing less than 5% of days for the years 1979–2014 from the U.S. Historical Climatology Network were used to analyze extreme precipitation, defined as the top 1% of days with precipitation. A statistically significant (95% confidence level) increasing trend of the threshold for the top 1% of extreme precipitation events was found (0.3 mm yr−1). This increasing trend was due to both an increase in the frequency of extreme events and the magnitude of extreme events. Rainfall events ≥ 150 mm (24-h accumulation) increased in frequency from 6 events between 1979 and 1996 to 25 events between 1997 and 2014, a 317% increase. The annual daily maximum precipitation, or the highest recorded precipitation amount in a given year, increased by an average of 1.6 mm yr−1, a total increase of 58.0 mm. Decreasing trends in extreme precipitation were observed east of Lake Erie during the warm season. Increasing trends in extreme precipitation were most robust during the fall months of September, October, and November, and particularly at locations further inland. The analysis showed that increases in events that were tropical in nature, or associated with tropical moisture, led to the observed increase in extreme precipitation during the fall months. [ABSTRACT FROM AUTHOR]

Abstract This paper explores the relationship between past climate and prehistoric Mediterranean agriculture by adapting a process-based dynamic vegetation model to estimate potential agricultural productivity under climate scenarios that characterize the extremes of Mediterranean climate in the Holocene. We adapt LPJmL (the Lund-Potsdam-Jena-managed-land model [Bondeau et al., 2007]), a process-based dynamic vegetation model, to the modeling of potential agricultural productivity in the past. Calibrating this model for past crops and agricultural practices and using a downscaling approach to produce high spatiotemporal resolution paleoclimate data, we produce quantitative estimates of potential yields under past climatic conditions derived from four Holocene climatic extremes (warm/wet, warm/dry, cold/wet, and cold/dry) under two different assumptions (approximate high and low limits) about the intensity of agricultural practice. We here discuss this process with reference to a case study in Provence, examining the methodology and data requirements for modeling past agriculture using LPJmL and considering the implications of the range of variability in potential agricultural productivity under distinct climate conditions. We focus particularly on comparing the range of variability induced by climatic shifts with that achievable through changes in agricultural practices as a means of approaching questions of past vulnerability and resilience. [ABSTRACT FROM AUTHOR]

Abstract In view of risk assessments this paper proposes a stochastic diffusion model to characterise statistics of extreme events when climate- or environmental variables surpass critical thresholds. The proposed three-factor model captures trend and volatility of such statistics and could prove valuable for climate and environmental impact analysis in many systems such as human health, agriculture or ecology. The model supports decisions in view of lowering risks to acceptable levels. We illustrate the development of the model for heatwave impacts on human health in the context of climate change. We propose a generic model composed of three random processes characterising annual statistics of heatwaves: a Poisson process characterising the number of heatwaves, a Gamma process characterising mean duration and a truncated Gaussian process capturing mean excess temperature of heatwave days. Additionally, potential correlations between the three processes are taken into account. The model is calibrated with data obtained from a regional climate model for two cities in Spain. The suitability of the model for probabilistic analysis is tested with Monte Carlo simulations. We assess the time-dependent probability distributions of heatwave-related mortality and demonstrate how to obtain relevant risk metrics such as the 95th percentile and the average of the 5% of worst cases (ES (95%)). Graphical abstract Unlabelled Image Highlights • Probabilistic assessment of evolution of annual characteristics of heatwaves • Stochastic diffusion models to represent annual statistics of heatwaves • Long-term high-resolution time series contain information on stochasticity. • Assessment of human health impacts from heatwaves in the context of climate change • Risk metrics such as Value at Risk and Expected Shortfall are proposed. [ABSTRACT FROM AUTHOR]

This paper provides a detailed description of how ENSO events affect seasonal and extreme precipitation over Indonesia. Daily precipitation data from 97 stations across Indonesia covering the period from 1981 to 2012 were used to investigate the effects of El Niño and La Niña on extreme precipitation characteristics including intensity, frequency and duration, as defined based on a subset of the Expert Team on Climate Change Detection and Indices (ETCCDI). Although anomalous signals in these three indices were consistent with those of total rainfall, anomalies in the duration of extremes [i.e., consecutive dry days (CDD) and consecutive wet days (CWD)] were much more robust. El Niño impacts were particularly prominent during June-July-August (JJA) and September-October-November (SON), when anomalously dry conditions were experienced throughout the country. However, from SON, a wet anomaly appeared over northern Sumatra, later expanding eastward during December-January-February (DJF) and March-April-May (MAM), creating contrasting conditions of wet in the west and dry in the east. We attribute this apparent eastward expansion of a wet anomaly during El Niño progression to the equatorial convergence of two anti-cyclonic circulations, one residing north of the equator and the other south of the equator. These anti-cyclonic circulations strengthen and weaken according to seasonal changes and their coupling with regional seas, hence shaping moisture transport and convergence. During La Niña events, the eastward expansion of an opposite (i.e., dry) anomaly was also present but less prominent than that of El Niño. We attribute this to differences in regional ocean—atmosphere coupling, which result in the contrasting seasonal evolution of the two corresponding anomalous cyclonic circulations and in turn suggests the strong nonlinearity of El Niño and La Niña responses over the Maritime Continent. Based on the seasonal behaviour of anomalous CDD and CWD, we propose five sub-divisions of the Indonesian region for both El Niño and La Niña. [ABSTRACT FROM AUTHOR]

• The environmental policy impact climate (EPIC) model is capable of simulating crop productivity for hundreds of years under a variety of climate scenarios, environmental conditions, and management systems and is often used to study the impact of climate change on agriculture. • The application of EPIC crop growth model can be divided into three categories: the improvement of crop growth model accuracy, the applied research on the effects of climate change, and the mitigation of agricultural drought risk. • Four aspects of research hot spots in the future: applications of extreme climate change, application of agricultural drought risk assessment and early warning, application of an agricultural catastrophe management system, application of drought relief operations. Climate change is breaking global food supplies. The Environmental Policy Impact Climate (EPIC) model is capable of simulating crop productivity for hundreds of years under a variety of climate scenarios, environmental conditions, and management systems and is often used to study the impact of climate change on agriculture. Combined with systematic evaluation and meta-analysis, this paper reviews the application of EPIC crop growth model. Those research can be divided into three categories: the improvement of crop growth model accuracy, the applied research on the effects of climate change, and the mitigation of agricultural drought risk. In addition, the paper puts forward four aspects of research hot spots in the future: applications of extreme climate change, application of agricultural drought risk assessment and early warning, application of an agricultural catastrophe management system, application of drought relief operations. Research shows the accuracy of the model is greatly improved by determining the genetic parameters of crops, modifying the parameters according to the weather, land use and technical conditions, and establishing the local and even global model parameter database; the uncertainty of model parameters, input data and model structure is analyzed to improve the stability of the model. In the process of discussing the influence mechanism and sensitivity analysis of climate change on crop growth, the analysis of various meteorological factors is concentrated from multi-factor analysis to temperature and precipitation. With the development of computing technology, the emergence of GIS technology and GCMs technology makes it possible to predict the impact of different meteorological factors on crop growth under future climate change. In some studies, EPIC crop growth model has been performed to reduce the risk of agricultural drought. [ABSTRACT FROM AUTHOR]

A growing body of research shows that extreme climatic events, e.g. heatwave, rainstorms and droughts, are becoming more frequent and intensified across various regions of the world. Australia is not isolated from these changes with marked increase in both rainfall and temperature extremes. Inherently, we understand that exposure to these extreme events could encourage decisions about population flow, and quantifying this linkage is challenging, especially for communities in small areas with an average of 10,000 people. Using spatio-temporal statistical techniques, this paper examines the possible environmental and socio-economic drivers associated with population flows of small communities as well as the possible predictive scenarios due to the effects introduced by climatic extremes. The analysis has been undertaken for a case-study region in the Murray-Darling Basin, Australia, where the economy is underpinned by agriculture and is sensitive to climate variability and extremes. The analysis reveals that in addition to the socio-economic factors, the environmental variables have a statistically significant association on shaping the distribution of the population flows in the study area. This statistical analysis can direct further data collection and causality analysis and be beneficial for policy makers, stakeholders and local communities to work together to adapt the Basin to climate extremes and changes. [ABSTRACT FROM AUTHOR]

The sparse nature of observational records across the mid- to high latitudes of the Southern Hemisphere limits the ability to place late-twentieth-century environmental changes in the context of long-term (multidecadal and centennial) variability. Historical records from subantarctic islands offer considerable potential for developing highly resolved records of change. In 1905, a whaling and meteorological station was established at Grytviken on subantarctic South Georgia in the South Atlantic (54°S, 36°W), providing near-continuous daily observations through to present day. This paper reports a new, daily observational record of temperature and precipitation from Grytviken, which is compared to regional datasets and historical reanalysis. The authors find a shift toward increasingly warmer daytime extremes commencing from the mid-twentieth century and accompanied by warmer nighttime temperatures, with an average rate of temperature rise of 0.13°C decade-1 over the period 1907-2016 (p < 0.0001). Analysis of these data and reanalysis products suggest a change of pervasive synoptic conditions across the mid- to high latitudes since the mid-twentieth century, characterized by stronger westerly airflow and associated warm föhn winds across South Georgia. This rapid rate of warming and associated declining habitat suitability has important negative implications for biodiversity, including the survival of key marine biota in the region. [ABSTRACT FROM AUTHOR]

Extreme climate warmth (hyperthermal) events through deep-time offer prescient insights into how the Earth may respond to present-day warming related to greenhouse gas emissions. This special issue deals with Paleoenvironmental changes across the Mesozoic–Paleogene hyperthermal events and comprises 25 interdisciplinary research articles. In this review paper, we summarise the contents of the special issue, placing it into a wider context, and demonstrate that Mesozoic–Paleogene hyperthermal events were among the most devastating and extreme climate modes in the geological record. Key findings are as follows: (1) Multi-proxy geochemical and sedimentological analyses reveal that widespread deoxygenation of oceans and megalakes was a common accompanying feature of most hyperthermals. (2) Evidence exists for complex linkages between volcanism, warm climate conditions, contemporary carbon cycles, aquatic biogeochemical cycles, wildfire activities, and climate-modulated hydrological and terrestrial weathering changes operating at seasonal, orbital and/or tectonic timescales. (3) Pronounced and rapid biological turnovers in the ocean during hyperthermals may have been linked to seawater acidification and shifts in nutrient availability, while promoting significant alterations in primary productivity, biological pump and ecosystem structures. Despite these advances, future interdisciplinary studies are needed to deliver a more comprehensive understanding of the nature and mechanism of complex environmental interactions within the Earth system, as well as the internal and external drivers that may have triggered hyperthermal events. • Marine and lacustrine deoxygenation was a common feature of Mesozoic–Paleogene hyperthermal events. • The temporal link is often observed between hyperthermals and Large igneous province emplacement and intense volcanism. • Large-scale greenhouse gas emissions induced strong positive climate feedbacks and global–scale biogeochemical extremes. [ABSTRACT FROM AUTHOR]

The Mediterranean Basin has been identified as a climate change "hotspot", a region where increased warming and drying are expected to occur at rates faster than the global average. Increasing scientific attention has therefore been drawn to the repercussions of climate change for the Mediterranean's diverse and valued agricultural sector. The extent to which these repercussions vary throughout the region, owing both to a non-uniform distribution of climatic hazards and to uneven adaptive capacities of farmers, remains however unquantified. We hereby provide a comprehensive spatial assessment of the potential to implement different farm-based land and water management adaptations across the Mediterranean's croplands, and evaluate the extent to which different regions see a match or a mismatch between areas of adaptation need and areas of adaptation capacity. This approach made use of spatial multi-criteria analysis to evaluate the suitability of different farm adaptations, and relied on the Ecocrop climate suitability model and climate data on changing duration or frequency of extremes to identify areas of adaptation need under a high-end climate change scenario. The adaptations explored in this work span a range of sustainable approaches addressing different components of the farming system (soil-based, water-based, and crop-based adaptations). For each sub-system, we compared the potential to implement an adaptation representing an incremental change vs. one involving greater transformation. Results indicate a worsening of climatic conditions for all croplands in the region, and particularly within the Mediterranean extents of Egypt, Turkey, Greece, Spain, Morocco, Bosnia and Herzegovina, and Israel. In more than half of these countries, >60% of highly affected Mediterranean areas, on average, see no tangible potential to implement adaptations. Importantly, potentials for adaptation, and particularly of transformational adaptations having the greatest hypothesized capacity to buffer against the effects of climate change, are found to be lower within areas where the most adverse climate change hazards are forecast to occur. For regions found to be approaching so-called limits to adaptation, this research contributes to growing calls for consideration of more transformational options, alongside the opportunities and sacrifices these options entail. For regions where considerable (yet unrealized) adaptation capacity is found to match areas of adaptation need, this paper instead presents a basis for further investigation on how to bridge adaptation capacity and preparedness. [Display omitted] • Mediterranean croplands will witness increased drought and heat stress under RCP 8.5. • Croplands in the south-west and east will face the greatest increases in climatic extremes. • Most regions have a > 50% spatial mismatch between adaptation potential and needs. • Adaptation potential is lower where most needed, especially for transformational adaptations. • Greater reflection on transformation needed as limits to adaptation are approached. [ABSTRACT FROM AUTHOR]

ABSTRACT Non-stationary modelling of climate extremes has attracted significant attention in recent years. Generalized extreme value ( GEV) distribution is the standard approach for modelling block extremes. The non-stationary form of GEV distribution with location and scale parameters linearly regressing to time has been widely used for single-site time series of climate extremes. In the present paper, such a model is extended to be geoadditive for regional climate extremes with nonparametric spatially varying temporal effects. The model is implemented through the Bayesian hierarchical approach and is applied to the annual minimum surface air temperature in Mainland China as a demonstration. The five bivariate functions representing the regional regression parameters in the model are approximated by low-rank thin plate regression splines. All the necessary software tools for producing a thin plate regression spline basis and Markov Chain Monte Carlo sampling can be seamlessly integrated and called through the R software environment. Results show that the model can capture the spatial inhomogeneity and temporal non-stationarity features of regional climate extremes. Expressions for return levels with different return periods and their trends are also derived accordingly. Trends in different return levels, especially those in the 'extreme state' (e.g., 50-year return level) that cannot be inferred by usual observational trend analysis, can also be derived through samples drawn from posterior predictive distributions. The regional trend in a 50-year return level is quite different to that in a 2-year return level. More attention should be paid to trends in the extreme state of climate under climate change. [ABSTRACT FROM AUTHOR]

[Display omitted] • Current land management can lead to more severe BAP conditions. • Regulating fertilizer application rate can offset HAB risks from extreme climate. • Regulating P was more effective in reducing HAB risks in freshwater watersheds. • Regulating N was more effective in controlling HAB downstream of watershed. This paper was aimed at assessing the risk of HAB occurrence in a highly cultivated watershed and evaluating the effectiveness of N and P fertilizer reduction practices in mitigating this risk under future climate projections. To achieve this objective, a modelling framework was developed for HAB risk assessment under different environmental stressors including climate changes and different land management practices. The modelling framework used a fully distributed physical-based hydrologic model, MIKE SHE, and a hydrodynamic river model, MIKE 11, coupled with ECO-Lab to simulate the fate and transport of different forms of N and P in the Upper Sangamon River Basin (USRB), a highly cultivated watershed in central Illinois. Three different land management scenarios based on the N and P reduction target in "The Gulf Hypoxia Action Plan" were simulated to assess the P nonpoint source behavior and HAB risk level in the USRB from 2020 to 2050 under extreme climate projections. Our results predicted that the HAB risk in USRB is relatively low even with increased bioavailable P (BAP) concentration and longer duration with high BAP concentration due to low water temperature. Reducing N or P application rates by 50% was able to offset the negative effects on HAB occurrence from extreme climate projections apart from spring. Within P and N, regulating P was found to be more effective in reducing HAB risks in the USRB while regulating N was more effective in controlling HAB downstream. Understanding the dynamics of N and P in causing the occurrence of HAB was expected to improve the mitigation measures that we implement at the field level. [ABSTRACT FROM AUTHOR]

Abstract: Cities are becoming increasingly vulnerable to flooding because of rapid urbanization, installation of complex infrastructure, and changes in the precipitation patterns caused by anthropogenic climate change. The present paper provides a critical review of the current state-of-the-art methods for assessing the impacts of climate change on precipitation at the urban catchment scale. Downscaling of results from global circulation models or regional climate models to urban catchment scales are needed because these models are not able to describe accurately the rainfall process at suitable high temporal and spatial resolution for urban drainage studies. The downscaled rainfall results are however highly uncertain, depending on the models and downscaling methods considered. This uncertainty becomes more challenging for rainfall extremes since the properties of these extremes do not automatically reflect those of average precipitation. In this paper, following an overview of some recent advances in the development of innovative methods for assessing the impacts of climate change on urban rainfall extremes as well as on urban hydrology and hydraulics, several existing difficulties and remaining challenges in dealing with this assessment are discussed and further research needs are described. [Copyright &y& Elsevier]

Droughts have adverse socioeconomic, agricultural, and environmental impacts that can be reduced by assessing and forecasting drought behavior. The paper presents detailed analyses of both meteorological and vegetative droughts over the period from 1970 to 2005. Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI) have been used to quantify drought according to severity, magnitude and spatial distribution at the Hashemite Kingdom of Jordan. Results suggest that the country faced during the past 35 years frequent non-uniform drought periods in an irregular repetitive manner. Drought severity, magnitudes and life span increased with time from normal to extreme levels especially at last decade reaching magnitudes of more than 4. Generated NDVI maps spatial analyses estimate crop-area percentage damage due to severe and extremely severe drought events occurred during October, December, and February of 2000 to be about 10%, 45%, and 30%, respectively. In response to drought spatial extent, the paper suggest the presence of two drought types, local drought acting on one or more geographical climatic parts and national drought, of less common but more severe, that extend over the whole country. Droughts in Jordan act intensively during January, February and March and tend to shift position with time by alternative migrations from southern desert parts to northern desert parts and from the eastern desert parts to highlands and Jordan Rift Valley (JRV) at the west. The paper also investigates the potential use of Global Climate Model's (GCM) to forecast future drought events from 2010 till 2040. Tukey HSD test indicates that ECHAM5OM GCM is capable to predicted rainfall variation at the country and suggests future droughts to become more intensive at the northern and southern desserts with 15% rainfall reduction factor, followed by 10% reduction at the JRV, and 5% at the highlands. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides estimates of rates of change in mean sea level around the English Channel, based on an extensive new hourly sea level data set for the south coast of the UK, derived from data archaeology. Mean sea level trends are found to vary by between 0.8 and 2.3mm/yr around the Channel. The rates of mean sea level change are calculated by removing the coherent part of the sea level variability from the time series of annual mean sea level before fitting linear trends. The improvement in accuracy gained by using this approach is assessed by comparing trends with those calculated using the more traditional method, in which linear trends are fitted directly to the original records. Removal of the coherent part of the sea level variability allows more precise trends to be calculated from records spanning 30 years. With the traditional approach 50 years is required to obtain the same level of accuracy. Rates of vertical land movement are approximated by subtracting the mean sea level trends from the most recent regional estimate of change in sea level due to oceanographic processes only. These estimated rates are compared to measurements from geological data and advanced geodetic techniques. There is good agreement around most of the UK. However, the rates estimated from the sea level records imply that the geological data suggest too much submergence along the western and central parts of the UK south coast. Lastly, the paper evaluates whether the high rates of mean sea level rise of the last decade are unusual compared to trends observed at other periods in the historical record and finds that they are not. [Copyright &y& Elsevier]

Quantifying the urbanization effect on trends in climate extremes is important both for detection and attribution studies and for human adaptation; however, a fundamental problem is how to accurately estimate a trend and its statistical significance, especially for non-Gaussian and serially dependent data. In this paper, the choice of trend estimation and significance testing method is suggested as important for these kinds of studies, as illustrated by quantifying the urbanization effect on trends in seven hot-extreme indices for the megacity of Shanghai during 1961-2013. Both linear and nonlinear trend estimation methods were used. The trends and corresponding statistical significances were estimated by taking into account potential non-Gaussian and serial dependence in the extreme indices. A new method based on adaptive surrogate data is proposed to test the statistical significance of the ensemble empirical mode decomposition (EEMD) nonlinear trend. The urbanization contribution was found to be approximately 34 % (43 %) for the trend in the non-Gaussian distributed heat wave index based on nonparametric linear trend (EEMD nonlinear trend) estimation. For some of the other six hot-extreme indices analyzed, the urbanization contributions estimated based on linear and nonlinear trends varied greatly, with as much as a twofold difference between them. For the linear trend estimation itself, the ordinary least squares fit can give a substantially biased estimation of the urbanization contribution for some of the non-Gaussian extreme indices. [ABSTRACT FROM AUTHOR]

Agricultural production, which takes place in rural areas, is the sector of the economy, which is the most dependent on the natural conditions of weather. The climate changes, which are taking place, and the extreme phenomena, which are their consequence, affect precisely these areas the most. The content of the present work is the exploration of the definitions of natural variability, extreme phenomena and disasters, and the analysis of the statistics on natural disasters. In the final part of the paper, we have indicated, which support instruments for farmers are available in such events on the part of the State. Climate change is a fact, and unless we realize that, it will be difficult to take any action allowing us to adapt to the new conditions. [ABSTRACT FROM AUTHOR]

This paper suggests possible evidence of climate change in Mexico at the watershed level, based solely on historical data. The official Mexican climate dataset was used to find the best set of stations for each watershed. Maximum and minimum temperatures and rainfall in ten watersheds are analyzed from 1970 to 2009. Maximum temperature trends show a significant increment in most of these watersheds. Furthermore, Daily Temperature Range (DTR) exhibits a positive trend (increments), thus implying an increase in temperature extremes. This study also shows that the difference between maximum and minimum monthly temperature trends is negatively correlated with monthly precipitation trends. As a result, land-use and land-cover changes could be the main drivers of climate change in the region. [ABSTRACT FROM AUTHOR]

Increase in temperature extremes is one of the main expected impacts of climate change, as well as one of the first signs of its occurrence. Nevertheless, results emerging from General Circulation Models, while sufficient for large scales, are not enough for forecasting local trends and, hence, the IPCC has called for local studies based on on-site data. Indeed, it is expected that climate extremes will be detected much earlier than changes in climate averages. Heat waves are among the most important and least studied climate extremes, however its occurrence has been only barely studied and even its very definition remains controversial. This paper discusses the observed changes in temperature trends and heat waves in Northwestern Mexico, one of the most vulnerable regions of the country. The climate records in two locations of the region are analyzed, including one of the cities with extreme climate in Mexico, Mexicali City in the state of Baja California and the Yaqui River basin at Sonora State using three different methodologies. Results showed clear trends on temperature increase and occurrence of heat waves in both of the study zones using the three methodologies proposed. As result, some policy making suggestion are included in order to increase the adaptability of the studied regions to climate change, particularly related with heat wave occurrence. [ABSTRACT FROM AUTHOR]

Climate change is occurring in the Southeastern United States, and one manifestation is changes in frequency and intensity of extreme events. A vulnerability assessment is performed in the state of Georgia (United States) at the county level from 1975 to 2012 in decadal increments. Climate change vulnerability is typically measured as a function of exposure to physical phenomena (e.g., droughts, floods), sensitivity to factors affecting the social milieu, and the capacity of a given unit to adapt to changing physical conditions. The paper builds on previous assessments and offers a unique approach to vulnerability analyses by combining climatic, social, land cover, and hydrological components together into a unified vulnerability assessment, which captures both long-term and hydroclimatic events. Climate change vulnerability indices are derived for the 1980s, 1990s, 2000s, and 2010s. Climate change exposure is measured as: 1) departure of decadal mean temperature and precipitation from baseline temperature and precipitation (1971–2000) using the United States Historical Climatology Network version 2.5 and 2) extreme hydroclimatic hazards indicated by flood, heat wave and drought events. Sensitivity and adaptive capacity are measured by well-established conceptualizations and methods built derived from socioeconomic variables. Impervious surface and flood susceptibility area are also incorporated to account for place-based vulnerability. Anomalies in temperature and precipitation with an overall trend towards drying and warming have been observed. The anomalous cooling period in Georgia during the 1970–1980 period as well as the post-1980 warm-up have been captured with a clearly established increase in extreme hydroclimatic events in recent decades. Climate vulnerability is highest in some metropolitan Atlanta and coastal counties. However, the southwestern region of Georgia, and part of the rural Black belt region are found to be especially vulnerable to climate change. [ABSTRACT FROM AUTHOR]

The Changbaishan volcano, located in northeast China, produced a large amount of charcoal during the "Millennium Eruption" (c. 946 CE). In this paper, we report a high-resolution date for the eruption using multiple methods applied to the fossil charcoal and living trees, including wood anatomy, radiocarbon dating and tree-ring cross-dating. In addition, we develop a new floating annual-resolution tree-ring chronology spanning nearly 200 years that provides information about paleoclimate conditions. In our study, we identified 60 samples of charcoal as Larix olgensis based on anatomical characteristics and geographical location. Using these materials, we dated the eruption to the winter of 946 CE based on a combination of radiocarbon dating, traditional dendrochronological cross-dating and cambial cell growth status. This allowed us to develop an L. olgensis tree-ring width chronology covering 764–946 CE and 1715–2016 CE, with significant sensitivities to April–September temperature (p < 0.05). The tree-ring data have great potential to indicate extreme climate events; for example, we identify an extremely cold year in 903 CE. Such marker years can improve the reliability and accuracy of tree-ring data. Our study provides direct and precise tree-ring evidence for volcanic eruptions and anomalous climate years in the Middle Ages. [Display omitted] • Cambial activity enables us to date the Millennium Eruption to winter 946 CE. • The first chronology reaching the Middle Ages so far developed in northeastern China. • The chronology was assembled from volcanic charcoal and living larch. • This chronology is sensitive to temperature. [ABSTRACT FROM AUTHOR]

For many developing countries, agriculture is the cornerstone of their economy. Whilst extreme weather events are an accepted phenomenon in some Latin American countries, others such as Bolivia and Peru are not so used to their apparently increasing frequency. Developing new policies and strategies to cope with climate change and its associated extreme events therefore requires robust knowledge on the reported impacts, consequences and implications. This paper presents the findings from a systematic review of published evidence on the impacts of climate change on cropping systems and rural livelihoods across a range of agricultural and socio-technical dimensions. Adaptation measures need to consider not only the weather and physical dimensions of climate change, but also its social consequences. Factors influencing agriculture, including water resource impacts, crop profitability, environmental constraints, social and political transformations, and traditional knowledge and practices, were identifed and reviewed to provide a comprehensive assessment of these key aspects, which are highly relevant to the region. [ABSTRACT FROM AUTHOR]

ABSTRACT Recent special reports on climate extremes have shown evidences of changes in the patterns of climate extremes at global, regional and local scales. Understanding the characteristics of climate extremes at regional and local levels is critical not only for the development of preparedness and early warning systems, but is also fundamental in the development of any adaptation strategies. There is still very limited knowledge regarding the past, present and future patterns of climate extremes in the Greater Horn of Africa (GHA). This study, which was supported by the World Bank Global Facility for Disaster Reduction and Recovery (WB-GFDRR) and implemented by the World Meteorological Organization, was organized in terms of three workshops with three main objectives; (1) analysis of daily rainfall and temperature extremes for ten countries in the GHA region using observed in situ data running from 1971 to 2006, (2) assessing whether the United Kingdom Met-office and Hadley centre Providing REgional Climates for Impact Studies (UK-PRECIS) modelling system can provide realistic representation of the past and present climate extremes as observed by available in situ data, and (3) studying the future regional climate extremes under different scenarios to further assess the expected changes in climate extremes. This paper, therefore, uses the outputs of these workshops and also includes post-workshop analyses to assess the changes of climate extremes within the GHA. The results showed a significant decrease in total precipitation in wet days greater than 1 mm and increasing warm extremes, particularly at night, while cold extremes are decreasing. Considering a combination of geophysical models and satellite gravimetry observations from the Gravity Recovery and Climate Experiment (GRACE) mission in the frame of GRACE daily Kalman-smoothing models, for the years 2002 to 2010, we explored a decline in total water storage variations over the GHA. [ABSTRACT FROM AUTHOR]

Abstract: The southern extent of the South China Sea (SCS) is an important natural resource epicenter for Malaysia which experiences climate extremes. This paper documents the variability of extremes in the equatorial SCS through selected ground-based observations of precipitation in Malaysia and ship-based observations of wind data in the Maritime Continent region, to elucidate the interrelationship between precipitation variability over Malaysia and wind variability over the ocean. The data have been carefully inspected and analyzed, and related to the real-time multivariate Madden–Julian Oscillation (MJO) time series. The analysis suggests that the northeast or boreal winter monsoon dominates extreme rainfall in eastern Malaysian cities. Further, the west coast of Peninsular Malaysia and Borneo Malaysia are affected by the MJO differently than the east coast of Peninsular Malaysia. From the wind analysis we found that average zonal wind is westerly from May to September and easterly from November to April. When the active (convective) phase of the MJO is centered over the Maritime Continent, the strong westerly wind bursts are more frequent in the South China Sea. While more investigation is needed, these results suggest that the status of the Madden–Julian Oscillation can be used to help forecast climate extremes in areas of Malaysia. [Copyright &y& Elsevier]

Climate change has the potential ability to alter the occurrence and severity of extreme events. Though predicting changes of such extreme events is difficult, understanding them is important to determine the impacts of climate change in various sectors. This paper presents the change in rainfall extremes in the monsoon season in south-west Indian peninsula. Daily rainfall data were analysed for the entire Kerala state in India to determine if the extreme rainfall had changed over the 50-year period. Several indices were derived from the data to identify the extreme rainfalls. The trends of all the extreme indices were assessed by parametric ordinary least square regression technique, which were tested for significance at 95% level. Results showed significant decrease in monsoon rainfall extremes in Kerala that would affect the tendency of change in seasonal total rainfall. This study provides a comprehensive knowledge on extreme monsoon precipitation in Kerala, which could also be employed to study changing climate at local scale in other regions. [ABSTRACT FROM AUTHOR]

Extreme climate and weather events are increasingly being recognized as key aspects of climate change. Pre-monsoon season (March–May) is the hottest part of the year over almost the entire South Asian region, in which hot weather extremes including heat waves are recurring natural hazards having serious societal impacts, particularly on human health. In the present paper, recent trends in extreme temperature events for the pre-monsoon season have been studied using daily data on maximum and minimum temperatures over a well-distributed network of 121 stations for the period 1970–2005. For this purpose, time series of extreme temperature events have been constructed for India as a whole and seven homogeneous regions, viz., Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP). In general, the frequency of occurrence of hot days and hot nights showed widespread increasing trend, while that of cold days and cold nights has shown widespread decreasing trend. The frequency of the occurrence of hot days is found to have significantly increased over EC, WC and IP, while that of cold days showed significant decreasing trend over WH and WC. The three regions EC, WC and NW showed significant increasing trend in the frequency of hot nights. For India as whole, the frequency of hot days and nights showed increasing trend while cold days and nights showed decreasing trends. Day-to-day fluctuations of pre-monsoon daily maximum and minimum temperatures have also been studied for the above regions. The results show that there is no significant change in day-to-day magnitude of fluctuations of pre-monsoon maximum and minimum temperatures. However, the results generally indicate that the daily maximum and minimum temperatures are becoming less variable within the season. [ABSTRACT FROM AUTHOR]

When will least developed countries be most vulnerable to climate change, given the influence of projected socio-economic development? The question is important, not least because current levels of international assistance to support adaptation lag more than an order of magnitude below what analysts estimate to be needed, and scaling up support could take many years. In this paper, we examine this question using an empirically derived model of human losses to climate-related extreme events, as an indicator of vulnerability and the need for adaptation assistance. We develop a set of 50-year scenarios for these losses in one country. Mozambique, using high-resolution climate projections, and then extend the results to a sample of 23 least-developed countries. Our approach takes into account both potential changes in countries' exposure to climatic extreme events, and socio-economic development trends that influence countries' own adaptive capacities. Our results suggest that the effects of socio-economic development trends may begin to offset rising climate exposure in the second quarter of the century, and that it is in the period between now and then that vulnerability will rise most quickly. This implies an urgency to the need for international assistance to finance adaptation. [ABSTRACT FROM AUTHOR]

Summary: Recent news on the occurrence of off-seasonal natural disasters, such as pre-monsoon drought and post-monsoon flooding in India and particularly in the peninsular region, highlight the urgent need to look at the patterns of change in seasonal extremes at the local level. Kerala, the south-western state of the Indian peninsula, comprising of a total of six gridded areas, was chosen for this study focusing on the variability and changes in rainfall extremes in the different seasons. Since other studies by the authors have focused on the monsoon season, this paper considers the winter, spring and autumn seasons only. A set of indices derived from the daily rainfall time series is defined and used to examine the changes in extreme rainfall through assessing long-term trends by non-parametric Mann–Kendall technique. The trends are determined over the period of 1954–2003, which are also tested for significance. The results show that there are large intra-regional differences in the trends in different seasons. Local changes were found different from the large spatial scale averages in Kerala. Winter and autumn extreme rainfall were found having an increasing tendency with statistically significant changes in some regions indicating more occurrences of winter and autumn floods. On the other hand the spring seasonal extreme rainfall showed decreasing trends, which together with increasing frequency of the dry days is mainly affecting the total seasonal precipitation, which mainly point towards the vulnerability of Kerala to increasing probability of water scarcity in the pre-monsoon time and a delaying monsoon onset. Overall, the results of this study are good indicators of local climate changes over the five decades that will assist in seasonal forecasting and risk management. [Copyright &y& Elsevier]

This paper compares precipitation, maximum and minimum air temperature and solar radiation estimates from the Hadley Centre's HadRM3 regional climate model (RCM), (50x50 km grid cells), with observed data from 15 meteorological station in the UK, for the period 1960-90. The aim was to investigate how well the HadRM3 is able to represent weather characteristics for a historical period (hindcast) for which validation data exist. The rationale was to determine if the HadRM3 data contain systematic errors and to investigate how suitable the data are for use in climate change impact studies at particular locations. Comparing modelled and observed data helps assess and quantify the uncertainty introduced to climate impact studies. The results show that the model performs very well for some locations and weather variable combinations, but poorly for others. Maximum temperature estimations are generally good, but minimum temperature is overestimated and extreme cold events are not represented well. For precipitation, the model produces too many small events leading to a serious under estimation of the number of dry days (zero precipitation), whilst also over- or underestimating the mean annual total. Estimates represent well the temporal distribution of precipitation events. The model systematically over-estimates solar radiation, but does produce good quality estimates at some locations. It is concluded that the HadRM3 data are unsuitable for detailed (i.e. daily time step simulation model based) site-specific impacts studies in their current form. However, the close similarity between modelled and observed data for the historical case raises the potential for using simple adjustment methods and applying these to future projection data. [ABSTRACT FROM AUTHOR]

In August 2003, Western Europe experienced a deadly heat wave. It is estimated that 15,000 people died in France from its direct effects. Applying an indirect estimation technique to the monthly number of deaths by sex, age, and place of residence for the period 1996-2003, we estimate the number of years that would have remained to those who died from the heat wave had they been spared. The paper also evaluates the role of the 'harvesting' effect of the 2003 heat wave in explaining the deficit of deaths recorded in 2004 - estimated at 23,000 out of an expected total of 535,000 deaths. The harvesting effect was modest and accounted for fewer than 5,000 of the 'missing' deaths in 2004. The mortality decline in 2004 is thus due mainly to other factors. One hypothesis is that special efforts have been directed towards isolated older people as a consequence of the heat wave. [ABSTRACT FROM AUTHOR]

This paper builds on existing theory and proposes a framework to identify vulnerability to climate change in food systems by examining historic cases where common environmental problems caused famine. Cases presented are (1) Ireland's Potato Famine, (2) El Niño induced famines during the Colonial period, and (3) Ethiopia between 1965 and 1997. Three factors stand out as common in each. Prior to each famine: (1) there were very few ways that people could obtain a living in the worst affected regions; (2) livelihoods in famine stricken communities came to depend on highly specialized agro-ecosystems that were sensitive to environmental change; (3) institutions failed to provide adequate safety nets to protect livelihoods from failure. This analysis suggests that vulnerability to climate change in food systems can be assessed by looking at agro-ecosystems, livelihoods and institutions. Local conditions, however, mean that ways of measuring these three factors will vary from place to place. As a result, direct comparisons are difficult. By conceptualizing these three variables as the axes of a three dimensional "vulnerability" space, it is possible to compare regions and look at trends over time by studying the paths through this "space" as traced by changes at the agroecosystem, livelihood, and institutional scale. [ABSTRACT FROM AUTHOR]

In this paper, unpublished archival documentary sources are used to explore the vulnerability to--and implications of--climatic variability and extreme weather events in colonial Mexico. Attention focuses on three regions covering a variety of environmental, social, economic, and political contexts and histories and located at key points along a north-south rainfall gradient: Chihuahua in the arid north, Oaxaca in the wetter south and Guanajuato located in the central Mexican highlands. A number of themes are considered. First, the significance of successive, prolonged, or combined climate events as triggers of agrarian crisis. Second, a case study demonstrating the national and regional impacts of a particularly devastating climate induced famine, culminating with the so-called 'Year of Hunger' between 1785 and 1786, is presented. The way in which social networks and community engagement were rallied as a means of fortifying social resilience to this and other crises will be highlighted. Third, the impacts of selected historical flood events are explored in order to highlight how the degree of impact of a flood was a function of public expectation, preparedness and also the particular socio-economic and environmental context in which the event took place. An overview of the spatial and temporal variations in vulnerability and resilience to climatic variability and extreme weather events in colonial Mexico is then provided, considering those recorded events that could potentially relate to broader scale, possibly global, climate changes. [ABSTRACT FROM AUTHOR]

Abstract: Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its ‘normal’ variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005). [Copyright &y& Elsevier]

Since extreme values of climatic actions are commonly derived assuming the climate being stationary over time, engineering structures and infrastructures are designed considering design actions derived under this assumption. Owing to the increased relevance of the expected climate change effects and the correlated variations of climate actions extremes, ad hoc strategies for future adaption of design loads are needed. Moreover, as current European maps for climatic actions are generally based on observations collected more than 20 years ago, they should be updated. By a suitable elaboration of the projections of future climate changes, the evolution over time of climatic actions can be assessed; this basic and crucial information allows us to facilitate future adaptations of climatic load maps, thus improving the climate resilience of structures and infrastructures. In this paper, current trends of climatic actions in Europe, daily maximum and minimum temperatures, daily precipitation, and ground snow loads, are investigated based on available gridded datasets of observations (E-OBS) and regional reanalysis (Uncertainties in Ensembles of Regional Re-Analyses, UERRA), to assess their suitability to be used in the elaboration of maps for climatic actions. The results indicate that the E-OBS gridded datasets reproduce trends in extreme temperatures and precipitation well in the investigated regions, while reanalysis data, which include snow water equivalent, show biases in the assessment of ground snow load modifications over the years in comparison with measurements. As far as climate change effects are concerned, trends of variation of climatic actions are estimated considering subsequent time windows, 40 years in duration, covering the period 1950–2020. Results, in terms of factors of change, are critically discussed, also in comparison with the elaborations of reliable datasets of real observations, considering a case study covering Germany and Switzerland. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to examine the beef value chain and identify climate change adaptation and investment options in the semi-arid areas of northern Kenya. The research uses an innovative approach to value chain analysis, namely the three-step Value Chain Analysis for Resilience in Drylands (VC-ARID) that considers the specific characteristics of semi-arid systems. All the respondents interviewed along the value chain have perceived changes in rainfall, temperature and climate extremes – especially drought – over the past 15 years and have experienced the impacts of these changes on their livestock. The findings show that pastoralist producers need to invest in fattening programmes at their ranches or via feedlots to increase the quality of the beef they produce. There is significant potential to improve the fattening stage in the value chain, since it would contribute towards meeting demand in the expanding high-end markets that require finished, top-quality meats. • Pastoralists beef value chain is more informal, traditional, extensive pastoralism. • Private ranches value chain is formal and incorporates fattening of livestock. • Pastoralists rely on mobility for coping with climate risk. • Climate change has negatively impacted on semi-Arid livestock production. • There is potential to improve and expand the fattening stage of the value chain. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate the projected regional responses of univariate and bivariate behaviors of extreme precipitation to climate change over the upper-middle Huaihe River Basin. Based on twelve GCM outputs under historical, RCP4.5 and the observations at 32 rainfall stations, the equidistant cumulative distribution function matching method (EDCDFm) was utilized to bias correct daily precipitation during the historical (1961–2005) and future (2021–2080) periods. Four precipitation indices combinations were introduced based on eight precipitation indices to characterize the regional-scale changes of precipitation events, which designate the duration, intensity and amount of heavy and weak precipitation in a year. Their dependence structures were captured by Copulas. Kendall return period (KRP) were applied to discuss hazard scenarios and we quantified the spatial variability of KRPs under different marginal values. The results indicated that projected precipitation characteristics including the average intensity, the amount of annual precipitation, the intensity and amount of extreme precipitation together with annual extremes displayed increasing trends, while the changes of consecutive wet and dry days did not present pronounced trends. Decreased KRPs in the vast majority of the territory manifested that the frequency of simultaneous floods and droughts in a year as well as that of extreme heavy precipitation events would augment. Obvious spatial heterogeneity of the changes of KRP was partly attributed to the topography difference, especially the coastal areas along the main stream of the Huaihe River. Consequently, there will be a higher risk of water resources-related issues in this region for upcoming decades. • Significant decreases will occur in the intensity and amount of heavy precipitation for upcoming decades. • Change rates of precipitation indices combinations illustrate obvious spatial heterogeneity. • The frequency of simultaneous floods and droughts in a year and that of extreme heavy precipitation events will augment. [ABSTRACT FROM AUTHOR]

Estimating extreme precipitation events over complex terrain is challenging but crucial for evaluating the performance of climate models for the present climate and expected changes of the climate in the future. New satellites operating in the microwave wavelengths have started to open new opportunities for performing such estimation at adequate temporal and spatial scales and within sensible error limits. This paper illustrates the feasibility and limits of estimating precipitation extremes from satellite data for climatological applications. Using a high-resolution gauge database as ground truth, it was found that global precipitation measurement (GPM) constellation data can provide valuable estimates of extreme precipitation over the southern slopes of the Pyrenees, a region comprising several climates and a very diverse terrain (a challenge for satellite precipitation algorithms). Validation using an object-based quality measure showed reasonable performance, suggesting that GPM estimates can be advantageous reference data for climate model evaluation. [ABSTRACT FROM AUTHOR]

Climate warming and subsequent climate extremes have a wide impact on ecosystems and economic society. Scientifically quantitative assessment on climate change risks is an urgent issue attracted the attention of academics and decision-makers. In this paper, the theory of climate change risks was sorted out based on the three component elements of hazard, vulnerability, and exposure. Moreover, the idiomatic assessment methods and their applicability were systematically summarized. Comprehensive analysis found that the impacts of climate change generally showed a negative trend that was more harm than benefit, and further warming would aggravate the risk over China which was manifested to be more prominent in some sensitive sectors and key regions to climate change. Accessible management of the climate change risk should be engaged in effectively improving the methods of comprehensive identification, strengthening the mechanism and quantitative assessment, recognizing the temporal and spatial variation of components related to climate change risk, and reducing the uncertainty of climate change projection. • Theoretical framework of climate change risk was formed based on hazard, vulnerability, and exposure. • Assessment methods of climate change risk and their applicability were systematically summarized. • Climate change risk levels were analyzed in sensitive sectors and key regions over China. • In China, impacts of climate change were more harm than benefit while more warming was very likely to aggravate the risk. [ABSTRACT FROM AUTHOR]

• Future change in extreme droughts over 5797 North American watersheds was studied. • Two climate model large ensembles were used to assess the change of frequency. • Changes in meteorological droughts are mostly correlated to mean precipitation. • Large increases in the frequency of hydrological droughts are observed over NA. • Projected changes in future extreme droughts get worse for longer return periods. This paper describes projected frequency changes in extreme summer meteorological and hydrological droughts over North American catchments. It uses two large ensemble climate models (50-member CanESM2 and 40-member CESM1) under the RCP 8.5 scenario to robustly assess frequency changes up to the 100-year drought, relative to the 1980–2009 reference period. Meteorological droughts, linked solely to precipitation deficit, are represented by the 1-month Standardized Precipitation Index (SPI), whereas hydrological droughts are characterized by the 1-month Streamflow Drought Index (SDI), based on hydrological simulation using a lumped hydrological model. Results show widely different patterns for future changes in extreme meteorological versus hydrological droughts. Future meteorological droughts show patterns of increasing and decreasing frequency that roughly match future expected changes of mean summer precipitation, although some regions are nonetheless projected to see more frequent extreme meteorological droughts despite increases in mean summer precipitation. The frequency changes for the 100-year meteorological droughts can be quite severe, with up to a 20-fold increase observed over some watersheds. On the other hand, hydrological droughts, which combine the effect of precipitation and temperature changes, show a mostly uniform pattern of large to very large increases in drought frequency. This shows that the projected temperature increase is a main driver of future extreme hydrological droughts, enough to overcome the projected increase in mean summer precipitation for many North American catchments. Projected changes in both meteorological and hydrological droughts get consistently worse for the longer considered return periods. In other words, frequency changes for the 100-year droughts are more significant than those expected for the 2- and 20-year droughts. This gradual worsening toward larger extremes has potentially large societal and economic impacts. The large projected increases in the frequency of extreme hydrological drought frequency (up to 27 times) are likely to severely stress water management systems across North America. [ABSTRACT FROM AUTHOR]

Climate is a key factor in agriculture, but we are unable to adequately predict future climates. Although some studies have addressed the short and long-run impacts of climate change on agriculture, few of them specifically focused on the analysis of its thermal component. Climatic regions with an extreme thermal range are a special case, as seasonal contrasts complicate the picture. Based on the above, the purpose of the paper is twofold. First, we review methods and indices used for the estimation of changes in the thermal component of the climate and demonstrate the usefulness of a sensitivity assessment methodology that gives some indication of the likely spatial extent of areas of high or low sensitivity to climate change and the size of the potential impact of that change, which is specifically beneficial in regions with high temperature extremes. Secondly, we constructed a composite indicator, called the Growing Degree Day Sensitivity Index (GDDSI) and defined as the percentage change in Growing Degree Day (GDD) for warming scenarios +1, +2 and +3 °C. GDDs were calculated for threshold base air temperatures of 0, 5, 10 and 15 °C, and a high-temperature limit of 30 °C. A GDD sensitivity analysis was applied to the thermally extreme climate of the Russian Far East. We analyzed the data of 50 weather stations across the study region over the period 1966–2017. The results show a strong GDDSI north-to-south gradient. In most cases, the sensitivity does not increase significantly as the warming rate increases. The higher the base threshold, the higher the sensitivity: GDDs with a threshold at 15 °C had the highest sensitivity in the far north of the study area where conditions are currently marginal for crop growth. The sensitivity analysis circumnavigates the difficulty of uncertainty in knowing what future climate to expect and informs planning decisions. The mapped results are useful for identifying areas of high sensitivity to climate change as well as the magnitude of the potential impact of that change. [ABSTRACT FROM AUTHOR]

The flora and vegetation of the archipelago of Cabo Verde is dominated by Macaronesian, Mediterranean, and particularly by African tropical elements, resulting from its southernmost location, when compared to the other islands of the Macaronesia (i.e., Azores, Madeira, Selvagens, and Canary Islands). Very likely, such a geographical position entailed higher susceptibility to extreme climatic fluctuations, namely those associated with the West African Monsoon oscillations. These fluctuations led to a continuous aridification, which is a clear trend shown by most recent studies based on continental shelf cores. Promoting important environmental shifts, such climatic fluctuations are accepted as determinant to explain the current spatial distribution patterns of taxa, as well as the composition of the plant communities. In this paper, we present a comprehensive characterization of the main plant communities in Cabo Verde, and we discuss the role of the climatic and topoclimatic diversity in shaping the vegetation composition and distribution of this archipelago. Our study reveals a strong variation in the diversity of plant communities across elevation gradients and distinct patterns of richness among plant communities. Moreover, we present an overview of the biogeographical relationships of the Cabo Verde flora and vegetation with the other Macaronesian Islands and northwestern Africa. We discuss how the distribution of plant communities and genetic patterns found among most of the endemic lineages can be related to Africa's ongoing aridification, exploring the impacts of a process that marks northern Africa from the Late Miocene until the present. [ABSTRACT FROM AUTHOR]

Spatial distribution of decadal average SPEI in the 2030s, 2050s, and 2080s in (a) RCP 2.6 Scenario; (b) RCP 4.5 Scenario; (c)RCP 8.5 Scenario. • Climate change would affect the extent and global distribution of drought. • Global drought would be more aggravated in RCP 8.5 scenario. • Significant increase of ET 0 would occur in most grain producing countries. Drought is the most widespread and most influential natural disaster in the world, especially a threat to agricultural production. In future climate scenarios, the meteorological elements such as precipitation and temperature in each region will change, which will affect the distribution and characteristics of global drought in the future. In this paper, the global drought propensity was evaluated by reformulated Standardized Precipitation Evapotranspiration Index (SPEI-PM) based on Penman-Monteith equation in three future climate scenarios (RCP2.6, RCP4.5 and RCP8.5) of 9 General Circulation Models (GCMs). Mann-Kendall (MK) trend test and empirical orthogonal function (EOF) analysis were used to assess the spatial-temporal distribution and evolution characteristics of the future global drought. Taking reference evapotranspiration (ET 0) of crops as the index, potential effects of global drought on agricultural water use were assessed. The results showed that under the influence of the changes of future temperature, precipitation and other meteorological factors, the global drought has presented regional difference characteristics. In three climate scenarios, the trend of severe drought was detected in Africa, North America, South America and Oceania in three climate scenarios. Spatial distribution of SPEI is consistent and intensified drought was detected in southern, northern and northeast of Africa in three decades in all scenarios. EOF analysis showed that there were more positive time coefficients in RCP8.5 scenario than other scenarios, then parts of South America and Africa would face intensified drought in all climate scenarios. The evolution of future global drought would pose a threat on global water use for agricultural production. The annual average ET 0 of three decades in major grain producing countries would be on the rise compared to the baseline (1976–2005), among which RCP8.5 scenario was most obvious. Large increase rate of ET 0 would occur in Ukraine, Turkey, Russia and Canada in the 2080s in three scenarios. In the future, major grain producing countries would face serious threats of drought, which would pose a great challenge to regional agricultural water use. The study will provide forward-looking information to alleviate the adverse effects of drought on agricultural water use. [ABSTRACT FROM AUTHOR]

• Phytophthora cinnamomi and soil moisture affected Quercus suber performance. • The inoculum density required to cause disease increased at lower soil moisture. • An average drier climate might imply a slower advance of the disease. • On the contrary, more frequent extreme rain events might favor the disease. Climate change and exotic pests and pathogens are causing alarming forest declines worldwide. However, we still lack a comprehensive understanding of how damage caused by exotic pests and pathogens might vary under the different scenarios of water availability imposed by a changing climate, particularly in water-limited forests as those that occupy Mediterranean areas. In this paper we aimed to experimentally analyse the interactive effects of the aggressive exotic pathogen Phytophthora cinnamomi and climate change-related reductions in soil moisture on seedling performance of the Mediterranean host Quercus suber. We conducted a full-factorial greenhouse experiment where the physiology and growth of Q. suber seedlings was measured in soils with different combinations of P. cinnamomi inoculum density (0, 30, 60 and 120 colony forming units per gram of dry soil) and soil moisture (15%, 40%, 50% and 100% soil water holding capacity) simulating different invasion and climate change scenarios. We found additive effects of P. cinnamomi and drought on Q. suber performance aboveground, although these effects were not always negative. In fact, seedlings showed a compensatory physiological response to P. cinnamomi infection by increasing their net photosynthetic rates. Our results also supported important interactive effects of pathogens and soil moisture on belowground performance. Thus, the inoculum density in the soil required to cause significant root damage in experimental seedlings decreased as soil moisture increased. From a climate change perspective, these results suggest that an average drier climate might imply sub-optimal conditions for P. cinnamomi infections allowing for a slower advance of the disease in invaded areas. However, this effect will be modulated by the also predicted more frequent extreme climatic events. A higher frequency of extreme rain events that saturate the soil might be particularly beneficial for P. cinnamomi , boosting its soil density beyond any possible response capacity of susceptible hosts. [ABSTRACT FROM AUTHOR]

As a result of the world-wide attention that global climate change is receiving, laudable attempts are made to increase the share of renewable energies in electricity production around the globe. In addition to climate change issue, the need for bringing electricity to millions of people who live in the least-developed parts of the world act as a stimulus to the development of renewable energy share of electricity generation. Despite all efforts, a considerable number of people in rural and remote areas of Africa are still striving to gain access to energy. This issue has been partly addressed by the introduction and development of off-the-grids (stand-alone power systems) using renewable energy sources, including wind. The key aim of this research is to study wind power as a source of electrification in Africa. Renewable energy supply is very vulnerable to hydro-climatic variability and extreme hydro-meteorological events, and wind energy is no exception. In particular, low wind speeds throughout Africa pose a real challenge to electricity generation from wind. Using hourly estimates of wind speed provided by ERA5 (the latest climate reanalysis produced by ECMWF), this paper evaluates spatial and temporal variability in daily wind power production across Africa, for a 18-year period (from 2000 to 2017), in terms of the capacity factor of wind (the average wind power generated each day divided by the rated peak power), and the minimum required wind speed for power production (useable wind speed). Furthermore, by calculating the low percentile values of daily capacity factors, we gain understanding of the ability of wind turbines to achieve a given level of service quality, and put an economic perspective on wind power production. [ABSTRACT FROM AUTHOR]

A challenge in addressing climate risk in developing countries is that many regions have extremely limited formal data sets, so for these regions, people must rely on technologies like remote sensing for solutions. However, this means the necessary formal weather data to design and validate remote sensing solutions do not exist. Therefore, many projects use farmers' reported perceptions and recollections of climate risk events, such as drought. However, if these are used to design risk management interventions such as insurance, there may be biases and limitations which could potentially lead to a problematic product. To better understand the value and validity of farmer perceptions, this paper explores two related questions: (1) Is there evidence that farmers reporting data have any information about actual drought events, and (2) is there evidence that it is valuable to address recollection and perception issues when using farmer-reported data? We investigated these questions by analyzing index insurance, in which remote sensing products trigger payments to farmers during loss years. Our case study is perhaps the largest participatory farmer remote sensing insurance project in Ethiopia. We tested the cross-consistency of farmer-reported seasonal vulnerabilities against the years reported as droughts by independent satellite data sources. We found evidence that farmer-reported events are independently reflected in multiple remote sensing datasets, suggesting that there is legitimate information in farmer reporting. Repeated community-based meetings over time and aggregating independent village reports over space lead to improved predictions, suggesting that it may be important to utilize methods to address potential biases. [ABSTRACT FROM AUTHOR]

In semi-arid regions of the world, knowledge about the long-term hydroclimate variability is essential to analyze and evaluate the impact of current climate change on ecosystems. We present the first tree-ring δ18O based hydroclimatic reconstruction for northern semi-arid Iran spanning the period 1515–2015. A highly significant correlation between tree-ring δ18O variations of juniper trees and spring (April–June) precipitation reveals a major influence of spring water availability during the early growing season. The driest period of the past 501 years occurred in the 16th century while the 18th century was the wettest, during which the overall highest frequency of wet year events occurred. A gradual decline in spring precipitation is evident from the beginning of the 19th century, pointing to even drier climate conditions. The analysis of dry/wet events indicates that the frequency of years with relatively dry spring increased over the last three centuries, while the number of wet events decreased. Our findings are in accordance with historical Persian disaster records (e.g., the severe droughts of 1870–1872, 1917–1919; severe flooding of 1867, the 1930s, and 1950). Correlation analyses between the reconstruction and different atmospheric circulation indices revealed no significant influence of large-scale drivers on spring precipitation in northern Iran. [ABSTRACT FROM AUTHOR]