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This paper explores the operationalization of climate-related indicators in violent conflict research. The climate-conflict narrative gained traction in recent decades and climate change is often referred to as a 'threat multiplier' by both policy makers and scholars. Yet, the relationships between climate-related phenomena and violent conflict are complex and context-specific. However, limited attention has been given to the climatic indicators applied in climate-conflict research. This paper addresses that gap by analyzing 32 studies published from 2004 to 2020 on the operationalization of climatic indicators and their relationship with violent conflict. It first categorizes climate indicators operationalization into five clusters: natural disasters, basic climate variability, advanced climate variability, freshwater availability, and the ENSO. The study evaluates the climate indicators for each cluster and shows that at an aggregate level these clusters examine 68 different climate representations. When paired with their respective conflict types, it finds a total of 113 climate-conflict combinations. Most operationalizations represent various forms of climate-related phenomena and variability rather than climate change. Some indicators are advancements over time, for example moving from changes in average rainfall to standardized precipitation indices. However, other indicators refer to various natural processes, making it challenging to determine whether climatic variability impacts conflict. The paper then demonstrates a discrepancy between the pathways through which climate may affect violent conflict and the representation of these pathways in the selected climate indicators. It discusses how the selection and operationalization of climate indicators requires careful consideration, and the phenomena researched should be well-specified in research findings. [ABSTRACT FROM AUTHOR]

An important and under-quantified facet of the risks associated with human-induced climate change emerges through extreme weather. In this paper, we present an initial attempt to quantify recent costs related to extreme weather due to human interference in the climate system, focusing on economic costs arising from droughts and floods in New Zealand during the decade 2007–2017. We calculate these using previously collected information about the damages and losses associated with past floods and droughts, and estimates of the "fraction of attributable risk" that characterizes each event. The estimates we obtain are not comprehensive, and almost certainly represent an underestimate of the full economic costs of climate change, notably chronic costs associated with long-term trends. However, the paper shows the potential for developing a new stream of information that is relevant to a range of stakeholders and research communities, especially those with an interest in the aggregation of the costs of climate change or the identification of specific costs associated with potential liability. [ABSTRACT FROM AUTHOR]

On 21-22 July 2012, torrential rains hit North China, with the daily precipitation record at Beijing station reaching 160.6 mm; this event is named the Beijing 7-21 case. This paper assesses the likelihood of the occurrence of local torrential rains, such as the Beijing 7-21 case, from the perspective of climate variability. In particular, the influence of the Pacific Decadal Oscillation (PDO) is assessed. There were five extreme events, with daily precipitation records equal to or larger than 160.6 mm, at Beijing station during the period 1951-2012; all of these events happened during negative phases of the PDO. The present analysis indicates that precipitation events more extreme than the Beijing 7-21 case should happen more than once per decade during negative phases of the PDO, but only about once every four decades during positive PDO phases. The negative phase of the PDO is found to be associated with a much greater probability of daily records of southerly winds in North China during summer. Strong southerly summer monsoons are deemed favorable for increasing the occurrence of local extreme rainfall over North China. [ABSTRACT FROM AUTHOR]

Given its high dependence on rainfed agriculture and its comparatively low adaptive capacity, Africa is frequently invoked as especially vulnerable to climate change. Within Africa, there is likely to be considerable variation in vulnerability to climate change both between and within countries. This paper seeks to advance the agenda of identifying the hot spots of what we term 'climate security' vulnerability, areas where the confluence of vulnerabilities could put large numbers of people at risk of death from climate-related hazards. This article blends the expertise of social scientists and climate scientists. It builds on a model of composite vulnerability that incorporates four 'baskets' or processes that are thought to contribute to vulnerability including: (1) physical exposure, (2) population density, (3) household and community resilience, and (4) governance and political violence. Whereas previous iterations of the model relied on historical physical exposure data of natural hazards, this paper uses results from regional model simulations of African climate in the late 20th century and mid-21st century to develop measures of extreme weather events-dry days, heat wave events, and heavy rainfall days-coupled with an indicator of low-lying coastal elevation. For the late 20th century, this mapping process reveals the most vulnerable areas are concentrated in Chad, the Democratic Republic of the Congo, Niger, Somalia, Sudan, and South Sudan, with pockets in Burkina Faso, Ethiopia, Guinea, Mauritania, and Sierra Leone. The mid 21st century projection shows more extensive vulnerability throughout the Sahel, including Burkina Faso, Chad, Mali, northern Nigeria, Niger, and across Sudan. [ABSTRACT FROM AUTHOR]

Worldwide climate is likely to become more variable or extreme with increases in intense precipitation. In Mediterranean areas, climate change will increase the risks of droughts, flash floods and soil erosion. Despite rainfall intensity being a key factor in erosive processes, in these areas information on extreme rainfall intensity and the associated erosivity, based on high-temporal resolution data, is either non homogeneous or scarce. These parameters thus need to be assessed in order to highlight suitable adaptation strategies. In this paper, an hourly rainfall intensity (RI) data series is analyzed together with the corresponding 1-min rainfall intensity maximum (RIm) of 23 rainfall gauges located in Tuscany, Italy, in an area highly vulnerable to erosion. The aim is to look for temporal trends (1989-2010) in extreme rainfall intensity and erosivity. Fixed effect logistic regression shows statistically significant temporal increases in the number of RI and RIm exceedances over the 95th percentile threshold. Winter is shown to be the season with the strongest increasing trend in coastal and inland rainfall gauge groups, followed by spring for the coastal group and autumn for the inland group. Linear regressions show that in the inland group there is a temporal increase in rainfall erosivity and on a seasonal basis, the highest increase is observed in autumn. By contrast, for the coastal group this increasing trend is only detectable for spring and winter. Such an increase in rainfall erosivity and its potential continuation could have a strong adverse effect on Mediterranean land conservation. [ABSTRACT FROM AUTHOR]

Existing studies in the context of assessing vulnerability to climate variability and change delineate, rather inadequately, interconnected interactions occurring within the climate-human-environment interaction space. Besides, studies documenting stakeholders' perceptions regarding climate change induced vulnerabilities are limited in terms of providing indicators for decision-making. This paper aims at constructing a livelihood vulnerability index for climate variability and change capturing interconnected interactions based on peoples' perceptions while providing indicators for evidence based decision-making. A semi-quantitative fuzzy cognitive mapping (FCM) approach has been deployed to capture peoples' perceptions of climate induced perturbations and adaptations. This approach helps quantify stakeholders' perspectives while capturing interconnected interactions in order to estimate livelihood vulnerability to climate variability and change of poor agro-pastoralists in the Bhilwara, a district in Western India. Combining the FCM approach with a sustainable livelihood framework warrants an understanding of assets sensitive to climate variability and change along with those serving as adaptive capacities. The findings of this study confirm that financial and natural assets are most susceptible to harm while organisational and financial assets provide resilience against climate variability and change. The results suggest that livelihood vulnerability of agro-pastoralists lie in the range of being 'vulnerable' to climate variability and change while varying across three seasons summer, winter, and rainfall. [ABSTRACT FROM AUTHOR]

This paper addresses deficiencies of stochastic Weather Generators (WGs) in terms of reproduction of low-frequency variability and extremes, as well as the unanticipated effects of changes to precipitation occurrence under climate change scenarios on secondary variables. A new weather generator (named IWG) is developed in order to resolve such deficiencies and improve WGs performance. The proposed WG is composed of three major components, including a stochastic rainfall model able to reproduce realistic rainfall series containing extremes and inter-annual monthly variability, a multivariate daily temperature model conditioned to the rainfall occurrence, and a suitable multi-variate monthly generator to fit the low-frequency variability of daily maximum and minimum temperature series. The performance of IWG was tested by comparing statistical characteristics of the simulated and observed weather data, and by comparing statistical characteristics of the simulated runoff outputs by a daily rainfall-runoff model fed by the generated and observed weather data. Furthermore, IWG outputs are compared with those of the well-known LARS-WG weather generator. The tested characteristics are a variety of different daily statistics, low-frequency variability, and distribution of extremes. It is concluded that the performance of the IWG is acceptable, better than LARS-WG in the majority of tests, especially in reproduction of extremes and low-frequency variability of weather and runoff series. [ABSTRACT FROM AUTHOR]

Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases in the occurrence of rainfall extremes of over a 150-year period, but significantly different changes in the magnitudes. The physical processes behind convective rainfall extremes generate a distinctive spatial inter-site correlation structure for extreme events. All analysed RCM rainfall extremes, however, show a clear deviation from this correlation structure for sub-daily rainfalls, partly because RCM output represents areal rainfall intensities and partly due to well-known inadequacies in the convective parameterization of RCMs. The results highlight the problem urban designers are facing when using RCM output. The paper takes the first step towards a methodology by which RCM performance and other downscaling methods can be assessed in relation to the simulation of short-duration rainfall extremes. [ABSTRACT FROM AUTHOR]

This paper assesses future climate changes over East and South Asia using a regional climate model (RegCM4) with a 50 km spatial resolution. To evaluate the model performance, RegCM4 is driven with 'perfect boundary forcing' from the reanalysis data during 1970-1999 to simulate the present day climate. The model performs well in reproducing not only the mean climate and seasonality but also most of the chosen indicators of climate extremes. Future climate changes are evaluated based on two experiments driven with boundary forcing from the European-Hamburg general climate model (ECHAM5), one for the present (1970-1999) and one for the SRES A1B future scenario (2070-2099). The model predicts an annual temperature increase of about 3°-5° (smaller over the ocean and larger over the land), and an increase of annual precipitation over most of China north of 30°N and a decrease or little change in the rest of China, India and Indochina. For temperature-related extreme indicators in the future, the model predicts a generally longer growing season, more hot days in summer, and less frost days in winter. For precipitation-related extremes, the number of days with more than 10 mm of rainfall is predicted to increase north of 30°N and decrease in the south, and the maximum five-day rainfall amount and daily intensity will increase across the whole model domain. In addition, the maximum number of consecutive dry days is predicted to increase over most of the model domain, south of 40°N. Most of the Yangtze River Basin in China stands out as 'hotspots' of extreme precipitation changes, with the strongest increases of daily rain intensity, maximum five-day rain amount, and the number of consecutive dry days, suggesting increased risks of both floods and droughts. [ABSTRACT FROM AUTHOR]

The paper discusses long-term change in snowfall, rainfall and mixed precipitation viewed in conjunction with air temperature and North Atlantic Oscillation (NAO) in winter (December-February). In the study of contemporary climate change and its effect on the hydrological cycle it is useful to focus on winter precipitation forms. A 146-year secular observation series from Kraków, spanning the period 1863-2008, was used to extract data on the number of days with precipitation and on precipitation amount broken down by form. Statistically significant trends were found in total and mixed precipitation, but not in snowfall and rainfall. The climate warming effect has contributed to a material decrease in the snowfall to total winter precipitation ratio during the second half of the 20th c. The highest impact of air temperature was found in the wintertime variation in number of days with snowfall while the NAO had a significant influence on the frequency and amount of both rainfall and snowfall. [ABSTRACT FROM AUTHOR]

Based on observational meteorological data since A.D. 1864 and tree-ring records of debris-flow activity, this paper assesses changes in rainfall characteristics and their impact on the triggering of geomorphic events in a high-elevation watershed of the Swiss Alps since the end of the Little Ice Age. No trends are visible in the frequency of heavy rainfall events, but we observe a reduced number of heavy, short-lived rainfalls in summer and a concentration of advective storms is recorded in late summer and early fall since the late 1980s. These changes in triggering meteorological conditions resulted in a cluster of debris flows in the early decades of the twentieth century and a lowering of debris-flow activity since the mid 1990s, and may be mirroring the observed changes in persistent high-pressure systems over the Alps. We also observe intra-seasonal differences in debris-flow system response reflecting the state of the permafrost body in the source area of debris flows, allowing for very small debris flows to be released by limited rainfall inputs (<20 mm) in June and July. The same quantities of rain will not trigger debris flows in August or September, when a thick active layer of the permafrost body is capable of absorbing water. With the projected amplitude of climatic change, seasonality, return intervals and volumes of debris flows are likely to be altered. RCM projections based on the IPCC A2 scenario suggest a decrease in heavy summer rainfalls which will most likely result in a (further) reduction of the overall frequency of debris flows, leaving more time for sediment to accumulate in the channel. Such an increase of channel accumulation rates along with the projected destabilization of the steep rock-glacier body is likely, in turn, to exert control ultimately on sediment volumes released from the source areas during future events. Observations from adjacent catchments suggest that extremely large debris flows, beyond historical experience, could occur at the study site and in similar debris-flow systems of the Valais Alps originating from periglacial environments. [ABSTRACT FROM AUTHOR]

Forecasting austral summer rainfall in southern Africa is hampered by a lack of long-term instrumental data. This paper extends the historical record for the subcontinent by presenting the first extensive 19th century climate history for Lesotho derived from documentary evidence. The data sources included unpublished English-, French- and Sesotho-language materials archived in Lesotho, South Africa and the UK. These included letters, journals and reports written by missionaries and colonial authorities, which were supplemented by newspapers, diaries, travelogues and other historical sources. Each source was read in chronological order, with any climate information recorded verbatim. Observations were classified into five categories (Very Wet, Relatively Wet, ‘Normal’, Relatively Dry, and Very Dry) based upon the predominant documented climate during each ‘rain-year’ (July to June). The latter portion of the chronology was then compared for accuracy against available instrumental precipitation records from Maseru (1886–1900). The results yield a semi-continuous record of climate information from 1824 to 1900. Data are restricted to lowland areas, but reveal drought episodes in 1833–34, 1841–42, 1845–47, 1848–51, 1858–63, 1865–69, 1876–80, 1882–85 and 1895–99 (the most severe drought years being 1850–51 and 1862–63) and wet periods or floods in 1835–36, 1838–41, 1847–48, 1854–56, 1863–65, 1873–75, 1880–81, 1885–86 and 1890–94. The rainfall chronology is compared with similar records for South Africa, Botswana and Zimbabwe. Linkages to possible forcing mechanisms, including ENSO teleconnections and historical coral-derived southwest Indian Ocean sea surface temperature variations are also explored. [ABSTRACT FROM AUTHOR]

Recent increases in the accuracy of climate models have enhanced the possibilities for analyzing the impacts of climate change on society. This paper explores how the local, economic impacts of climate change can be modeled for a specific eco-region, the Western Sahel. The people in the Sahel are highly dependent on their natural resource base, and these resources are highly vulnerable to climate change, in particular to changes in rainfall. Climate models project substantial changes in rainfall in the Sahel in the coming 50 years, with most models predicting a reduction in rainfall. To connect climate change to changes in ecosystem productivity and local income, we construct an ecological–economic model that incorporates rangeland dynamics, grazing and livestock prices. The model shows that decreased rainfall in the Sahel will considerably reduce local incomes, in particular if combined with increases in rainfall variability. Adaptation to these climate change projections is possible if reductions in rainfall are followed by destocking to reach efficient grazing levels. However, while such a strategy is optimal from the perspective of society, the stocking rate is determined by individual pastoralists that face few incentives to destock. [ABSTRACT FROM AUTHOR]

The high variability of the Mediterranean climate from year to year and within each year makes it difficult to assess changes that could be associated with a climate change. In this paper some indices, such as changes in the precipitation concentration during the year, maximum 1-day and 5-day precipitation, number of wet days (total and those with precipitation higher than the 75th and 95th percentile), magnitude and frequency of extreme events (considered as the rainfall higher than that corresponding to the 99th percentile), fraction of annual total precipitation due to events exceeding the 95th and 99th percentile, strength of the events, and length and frequency of dry period (days between consecutive rains) are evaluated for the Penedès-Anoia region (NE Spain). A 80-year daily dataset (1923-2002) and two 40-year series were used to assess possible trends. The indices indicate an increase in precipitation in winter and summer and a positive trend of concentration in autumn, with a higher number of extreme events separated by longer dry periods. The total number of wet days per year increased, although it was irregularly distributed over the year, with an increase in the extremes and in the fraction of total rainfall that these events represent in autumn and winter, and with an increase of the strength of the events in autumn. These changes in rainfall distribution have negative effects on water availability for crops and contribute to accelerate erosion processes in the area. [ABSTRACT FROM AUTHOR]

Abstract This paper contributes to the literature underscoring the importance of climatic variance by developing a framework for incorporating the means and tails of the distributions of rainfall and temperature into empirical models of agricultural production. The methodology is applied to estimate the impact of climate change on the discrete choice decision to adopt irrigation since it is an important adaptation to climate change. We develop a discrete choice model for the decision to install irrigation capacity that captures the effects of both climate means and extremes. Climatic means and frequencies of climatic events in the upper tails of the temperature and precipitation distributions are used to estimate the parameters of a normal distribution for temperature and a Weibull distribution for precipitation. Using estimates from a probit model, we examine the independent effects of changing climatic mean and variance on the probability of adopting irrigation. Increasing the mean temperature, holding variance constant, shifts the entire distribution toward warmer temperaturesincreasing the frequency of extreme temperatures. For precipitation, the specification captures the separate effects of mean rainfall, frequency of rainfall, and frequency of extreme events. The results show that the tails of the temperature and precipitation distributions, not the means, are the dominant climatic determinants in irrigation adoption. The results also show that water availability, soil characteristics, farm size and operator demographics are important determinants of irrigation. [ABSTRACT FROM AUTHOR]

Climate change is a problem which is global both in terms of causes and consequences. The uncertainties are large and likely to persist. Meanwhile, the political and economic stakes of both action and inaction are much higher than those in other transboundary concerns such as acid rain and ozone depletion. The public policy impact of scientific opinions on climate change, therefore, not only depends upon what is being said, but also, who is advancing those conclusions and how they were arrived at. This was the rationale behind the setting up of the Intergovernmental Panel on Climate Change (IPCC) in 1988. The paper examines the IPCC in the context of prior assessment efforts. It attempts to unravel the processes which caused the IPCC to be set up when it was and how it was, as opposed to different times and different forms. [ABSTRACT FROM AUTHOR]