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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]

In his article Willems (Clim Chang 120(4):931-944, ) proposed a methodology to analyse extremes in rainfall series. When applying it to artificially generated, non-cyclic random variables we were able to detect cyclic behavior. Therefor we had a closer look on the methodology. Here we discuss our considerations, why this method generates cycles, depending on chosen subperiods and their coherence between detected cycle lengths. To verify these relationships some examples based on random data samples are given. [ABSTRACT FROM AUTHOR]

Based on the government's historical records and personal documents of the pre-modern Chosŏn Dynasty, this paper examines the socio-economic impacts in Korea in response to climatic variability from 1809 until 1819 that may have been influenced to some degree by the eruption of the "unknown volcano" (1809) and the Tambora eruption (1815). In the early 1800s, when volcanic eruptions occurred successively, the Korean Peninsula experienced a temporal precipitation variation—drought, abundant rainfall, and normalcy—twice. The precipitation variation in this period had a heavy impact on the yields of rice, major crop on the peninsula. In the phase of drought in 1809 and extreme climatic anomalies in 1814, the country suffered record poor harvests, and in the abundant rainfall phase in 1810 and 1816–1817, it had bumper crops. For this reason, 1816–1817 were the halcyon years for Korea, unlike the case of Europe and the northeastern USA which suffered from extreme climatic anomalies in those years. This case of the Korean Peninsula indicates that the climate change and natural disasters of the 1810s were influenced by not only of the single event of the Tambora eruption but of the successive eruptions of volcanoes in the 7 years from 1809 to 1815, which also affected other areas on the globe for 11 years (1809–1819). [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]

Comments on the paper `Towards an Interpretation of Historical Droughts in Northern Nigeria,' by Aondover Tarhule and Ming-Ko Woo. Confusion regarding the use of standard deviation of the long-term mean rainfall in the interpretation of their data; Probability of rainfall deficit.

This paper examines changes in rainfall effectiveness indices of the Awun basin in Nigeria during the late twenty-first century for agricultural applications with outputs from high-resolution regional climate model (RCM) simulations. The RCM simulations are driven by two global climate models for a reference period (1985-2004) and a future period (2080-2099) and for RCP4.5 (a scenario with some mitigation) and RCP8.5 (a business as usual scenario) forcings. Simulations are provided for the control (1985-2004) and scenario (2080-2099) periods. Observations from synoptic station are used for bias-correction. Three indices being local onset date, seasonality index (SI), and hydrologic ratio (HR) are analyzed. Onset and HR are tested with two evapotranspiration (ETp) models. Farmers' perceptions are also collected to validate trends of rainfall indices for the present-day climate. We found that onset dates do not depend much on the ETp models used, and farmers' perceptions are consistent with predicted rainfall patterns. Present-day climate trend shows an early onset. However, onset is projected to be late in future and the delay will be magnified under the business as usual scenario. Indeed, average onset date is found on the 5th May for present-day while in the future, a delay about 4 and 8 weeks is projected under RCP4.5 and RCP8.5 scenarios respectively. SI is between 0.80 and 0.99, and HR is less than 0.75 for all scenarios, meaning respectively that (i) the rainy season will get shorter and (ii) the area will get drier in the future compared to the present-day. Local stakeholders are forewarned to prepare for potential response strategies. A continuous provision of forecast-based rainfall indices to support farmer's decision making is also recommended. [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]

Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south-central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century over south-central Canada under a changing climate. The implications of these increases need be taken into consideration and integrated into policies and planning for adaptation strategies, including measures to incorporate climate change into engineering infrastructure design standards and disaster risk reduction measures. This paper briefly summarized these climate change research projects, focusing on the modeling methodologies and results, and attempted to use plain language to make the results more accessible and interesting to the broader informed audience. These research projects have been used to support decision-makers in south-central Canada when dealing with future extreme weather events under climate change. [ABSTRACT FROM AUTHOR]

This paper presents the first interdecadal and interannual periodisation of the climate in West Africa between 1750 and 1800. The climatic synthesis is founded on previously unexploited British documents written at Cape Coast Castle, Cape Coast, Ghana and travel journals, which are combined with previous research on the Sahel. By combining historical evidence with the most recently identified rainfall patterns in the Sahel and the Guinea coast, the climatic periodisation distinguishes between wetter and drier periods. The results show that there was great interannual and interdecadal variability in the West African rainfall regime in the 18th century. The historical evidence suggests that the climate in the Sahel and the Guinea coastal interior alternated between five wet and dry periods, whereas the coastal dry zone alternated between three wet and dry periods. The most pronounced changes in the climate are found in the 1780s and 1790s. The Guinea coastal interior and the Sahel experienced a wet period in the 1780s and a dry period in the 1790s, whereas the coastal dry zone was drier in the 1780s and wetter in the 1790s. The investigation shows that the secondary rainy season on the Gold coast was weak or non-existent. [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]

People's perceptions of changes in local weather patterns are an important precursor to proactive adaptation to climate change. In this paper, we consider public perceptions of changes in average rainfall in India, analyzing the relationship between perceptions and the instrumental record. Using data from a national sample survey, we find that local instrumental records of precipitation are a strong predictor of perceived declines in rainfall. Perceptions of decreasing rainfall were also associated with perceptions of changes in extreme weather events, such as decreasing frequency of floods and severe storms, increasing frequency of droughts, and decreasing predictability of the monsoon. Higher social vulnerability-including low perceived adaptive capacity and greater food and livelihood dependence on local weather-was also associated with perceptions of decreasing rainfall. While both urban and rural respondents were likely to perceive local changes in precipitation, we show that rural respondents in general were more sensitive to actual changes in precipitation. Individual perceptions of changes in local climate may play an important role in shaping vulnerability to global climate change, adaptive behavior, and support for adaptation and mitigation policies. Awareness of local climate change is therefore particularly important in regions where much of the population is highly exposed and sensitive to the impacts of climate change. [ABSTRACT FROM AUTHOR]

The Upper Brahmaputra River Basin is prone to natural disasters and environmental stresses (floods, droughts and bank erosion, delayed rainfall, among others) creating an environment of uncertainty and setting the basin back in terms of socio-economic development. The climate change literature shows that agriculture and ecosystems and their services are highly climate sensitive, yet they are the main sources of livelihood that supports a large proportion of residents of the tributaries of the Brahmaputra River Basin. The continuous depletion of ecosystems and loss of agricultural outputs resulting from environmental stressors has a substantial impact on the socio-economic wellbeing of the basins residents, particularly the vulnerable rural poor. This paper uses spatially explicit data from Census, Household Surveys and Earth Observation to develop a transferable methodological approach which investigates the extent of dependence on agriculture and ecosystems as a source of livelihood in the contrasting sub-basins of the Brahmaputra River in the State of Assam, India and Bhutan, and the risk to these livelihood dependencies in these sub-basins due to potential environmental impacts of climate change. The results from this study constitute a case study in the development of a systematic and spatially explicit set of tools that inform and assist policy makers in the appropriate interventions to secure the livelihood benefits of sustainably managed agriculture in the face of environmental change. [ABSTRACT FROM AUTHOR]

Food security in India is tightly linked to rainfall variability. Trends in Indian rainfall records have been extensively studied but the subject remains complicated by the high spatiotemporal variability of rainfall arising from complex atmospheric dynamics. For various reasons past studies have often produced inconsistent results. This paper presents an analysis of recent trends in monthly and seasonal cumulative rainfall depth, number of rainy days and maximum daily rainfall, and in the monsoon occurrence (onset, peak and retreat). A modified version of the Mann-Kendall test, accounting for the scaling effect, was applied to 29 variables derived from square-degree-resolution daily gridded rainfall (1951-2007). The mapping of gridded trend slopes and the regional average Kendall test were used concurrently to assess the field significance of regional trends in areas exhibiting spatial homogeneity in trend directions. The statistics we used account for temporal and spatial correlations, and thus reduce the risk of overestimating the significance of local and regional trends. Our results i/ improve available knowledge (e.g. 5 %-field-significant delay of the monsoon onset in Northern India); ii/ provide a solid statistical basis to previous qualitative observations (e.g. 1 %-field-significant increase/decrease in pre-monsoon rainfall depth in northeast/southwest India); and, iii/ when compared to recent studies, show that the field significance level of regional trends (e.g. in rainfall extremes) is test-dependent. General trend patterns were found to align well with the geography of anthropogenic atmospheric disturbances and their effect on rainfall, confirming the paramount role of global warming in recent rainfall changes. [ABSTRACT FROM AUTHOR]

Many studies have observed changes in the frequency and intensity of precipitation extremes and floods during the last decade(s). Natural variability by climate oscillations partly determines the observed evolution of precipitation extremes. Based on a technique for the identification and analysis of changes in extremes, this paper shows that precipitation extremes have oscillatory behaviour at multidecadal time scales. The analysis is based on a unique dataset of 108 years of 10-minute precipitation intensities at Uccle (Brussels), not affected by instrumental changes. We also checked the consistency of the findings with long precipitation records at 724 stations across Europe and the Middle East. The past 100 years show for northwestern Europe, both in winter and summer, larger and more precipitation extremes around the 1910s, 1950-1960s, and more recently during the 1990s-2000s. The oscillations for southwestern Europe are anti-correlated with these of northwestern Europe, thus with oscillation highs in the 1930-1940s and 1970s. The precipitation oscillation peaks are explained by persistence in atmospheric circulation patterns over the North Atlantic during periods of 10 to 15 years. [ABSTRACT FROM AUTHOR]

Communicating information about consistency in projections is crucial to the successful understanding, interpretation and appropriate application of information from climate models about future climate and its uncertainties. However, mapping the consistency of model projections in such a way that this information is communicated clearly remains a challenge that several recently published papers have sought to address in the run up to the IPCC AR5. We highlight that three remaining issues have not been fully addressed by the literature to date. Allen and Ingram () While additional information about regions where projected changes in rainfall are not 'statistically significant' can provide useful information for policy, the spatial scale at which changes are assessed has a substantial impact on the signal-to-noise ratio, and thus the detectability of changes. We demonstrate that by spatially smoothing the model projections we can provide more information about the nature of the signal for larger regions of the world. Christensen et al. () Combining information about magnitude, consistency and statistical significance of projected changes in a single map can cause reduced legibility. We demonstrate the difficulty in finding a 'universal' method suitable for a wide range of audiences DEFRA () We highlight that regions where projected changes in average rainfall are not statistically significant, changes in variability may still cause significant impacts. We stress the need to communicate this effectively in order to avoid mis-leading users. Finally, we comment on regions of the world where messages for users of climate information about ensemble consistency have changed since AR4, noting that these changes are due largely to changes in the methods of measuring consistency rather than any discernable differences between the CMIP3 and CMIP5 ensembles. [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]

Climate models project large changes in rainfall, but disagree on their magnitude and sign. The consequences of this uncertainty on optimal dam dimensioning is assessed for a small mountainous catchment in Greece. Optimal dam design is estimated using a Cost-Benefit Analysis (CBA) based on trends in seasonal temperature and precipitations from 19 IPCC-AR4 climate models driven by the the SRES A2 emission scenario. Optimal reservoir volumes are modified by climate change, leading to up to 34% differences between optimal volumes. Contrary to widely-used target-based approaches, the CBA suggests that reduced rainfall should lead to smaller water reservoirs. The resulting change in the Net Present Value (NPV) of water supply is also substantial, ranging from no change to a large 25% loss, depending on the climate model, even assuming optimal adaptation and perfect foresight. In addition, climate change uncertainty can lead to design errors, with a cost ranging from 0.3 to 2.8% of the NPV, depending on site characteristics. This paper proposes to complement the CBA with a robust decision-making approach that focuses on reducing design-error costs. It also suggests that climate change impacts in the water sector may reveal large, that water reservoirs do not always provide a cost-efficient adaptation strategy, and that alternative adaptation strategies based on water conservation and non-conventional water production need to be considered. [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]

Ethiopia's agriculture is predominantly rainfed and hence any irregularity in weather conditions has adverse welfare implications. Using panel data, this paper analyzes the effect of rainfall shocks on Ethiopian rural households' food security and vulnerability over time while controlling for a range of other factors. To this end, we generate a time-variant household food security index which is developed by principal components analysis. Based on this index, households are classified into relative food security groups and their socioeconomic differences are assessed. The exploratory results show that compared to the less secured households, the more secured ones have male and literate household heads, tend to have a greater number of economically active household members, own more livestock, experience better rainfall outcome, and participate in local savings groups. Using the food security index as the dependent variable, we use a fixed effects instrumental variable regression model to identify determinants of households' food security over time and find that rainfall variability is an important factor. Moreover, household size, participation in local savings groups, and livestock ownership positively affect food security. Results from multinomial logistic regression model complement the fixed effects instrumental variable regression results by showing that the level and variability of rainfall are important determinants of persistent food insecurity and vulnerability. The results highlight the need for efficient risk reduction and mitigation programs to improve risk exposure and coping ability of rural households. Careful promotion of investment in infrastructure to support irrigation and water resources development is one aspect worth considering. [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]

This paper explores changes in climatic variables, including solar radiation, rainfall, fraction of diffuse radiation (FDR) and temperature, during wheat season (October to May) and maize season (June to September) from 1961 to 2003 at four sites in the North China Plain (NCP), and then evaluates the effects of these changes on crop growth processes, productivity and water demand by using the Agricultural Production Systems Simulator. A significant decline in radiation and rainfall was detected during the 43 years, while both temperature and FDR exhibit an increasing trend in both wheat and maize seasons. The average trend of each climatic variable for each crop season from the four sites is that radiation decreased by 13.2 and 6.2 MJ m−2 a−1, precipitation decreased by 0.1 and 1.8 mm a−1, minimum temperature increased by 0.05 and 0.02°C a−1, maximum temperature increased by 0.03 and 0.01°C a−1, FDR increased by 0.21 and 0.38% a−1 during wheat and maize season, respectively. Simulated crop water demand and potential yield was significantly decreased because of the declining trend in solar radiation. On average, crop water demand was decreased by 2.3 mm a−1 for wheat and 1.8 mm a−1 for maize if changes in crop variety were not considered. Simulated potential crop yields under fully irrigated condition declined about 45.3 kg ha−1 a−1 for wheat and 51.4 kg ha−1 a−1 for maize at the northern sites, Beijing and Tianjin. They had no significant changes in the southern sites, Jinan and Zhengzhou. Irrigation, fertilization development and crop variety improvement are main factors to contribute to the increase in actual crop yield for the wheat–maize double cropping system, contrasted to the decline in the potential crop yield. Further research on how the improvement in crop varieties and management practices can counteract the impact of climatic change may provide insight into the future sustainability of wheat–maize double crop rotations in the NCP. [ABSTRACT FROM AUTHOR]

This paper presents results from a 40 year Weather Research and Forecasting (WRF) based dynamical downscaling experiment performed at 12 km horizontal grid spacing, centered on the state of California, and forced by a 1° × 1.25° finite-volume current-climate Community Climate System Model ver. 3 (CCSM3) simulation. In-depth comparisons between modeled and observed regional-average precipitation, 2 m temperature, and snowpack are performed. The regional model reproduces the spatial distribution of precipitation quite well, but substantially overestimates rainfall along windward slopes. This is due to strong overprediction of precipitation intensity; precipitation frequency is actually underpredicted by the model. Moisture fluxes impinging on the coast seem to be well-represented over California, implying that precipitation bias is caused by processes internal to WRF. Positive-definite moisture advection and use of the Grell cumulus parameterization result in some decrease in precipitation bias, but other sources are needed to explain the full bias magnitude. Surface temperature is well simulated in all seasons except summer, when overly-dry soil moisture results in a several degree warm bias in both CCSM3 and WRF. Additionally, coastal temperatures appear to be too warm due to a coastal sea surface temperature bias inherited from CCSM3. Modeled snowfall/snowmelt agrees quite well with observations, but snow water equivalent is found to be much too low due to monthly reinitialization of all regional model fields from CCSM3 values. [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]

This paper analyses the role played by the North Atlantic Oscillation (NAO) in the creation of drought conditions in a semi-arid region of north-east Spain (the middle Ebro valley), from 1600 to the year 2000. The study used documents from ecclesiastical archives for the seventeenth, eighteenth and nineteenth centuries. For the twentieth century, instrumental precipitation records were used as well. A December-August drought index from 1600 to 1900 was compiled from the historical documentary sources (rogation ceremonies). The index was validated by means of precipitation records between 1858 and 1900 and independent precipitation data from 1600 reconstructed by means of dendrochronological records. Using instrumental data a drought index was also calculated (Standardized Precipitation Index, SPI) for the 1958-2000 period. We found that the NAO was important in explaining the droughts identified in the study area from documents and instrumental data. Positive values of the winter NAO index are prone to cause droughts in the middle Ebro valley. This finding has been verified since 1600 by means of two independent reconstructions of the winter NAO index. The same behaviour has been observed during the nineteenth and twentieth centuries by means of instrumental records. The climatic and geographic factors that explain the high influence of North Atlantic Oscillation on droughts in this region are discussed in depth. [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]

Damaging rainfall and rain-induced flooding occur from time to time in the drought-prone Sahel savanna zone of Niger in West Africa but official records of these events and their socioeconomic impacts do not exist. This paper utilized newspaper accounts between 1970 and 2000 to survey and illustrate the range of these flood hazards in the Sahel. During the study interval, 53 newspaper articles reported 79 damaging rainfall and flood events in 47 different communities in the Sahel of Niger. Collectively, these events destroyed 5,580 houses and rendered 27,289 people homeless. Cash losses and damage to infrastructure in only three events exceeded $4 million. Sahel residents attribute these floods to five major causes including both natural and anthropogenic, but they view the flood problem as driven primarily by land use patterns. Despite such awareness, traditional coping strategies appear inadequate for dealing with the problems in part because of significant climatic variability. Analysis of several rainfall measures indicates that the cumulative rainfall in the days prior to a heavy rain event is an important factor influencing whether or not heavy rainfall results in flooding. Thus, despite some limitations, newspaper accounts of historical flooding are largely consistent with measured climatic variables. The study demonstrates that concerted effort is needed to improve the status of knowledge concerning flood impacts and indeed other natural and human hazards in the Sahel. [ABSTRACT FROM AUTHOR]

Abstract Annual maxima of daily rainfall data dating from 1901 to 2003 are modeled for fourteen locations in West Central Florida. The generalized extreme value (GEV) distribution is fitted to data from each location. The location parameter of the GEV is formulated as a function of time to adequately describe the extremes of rainfall and to predict their future behavior. We find evidence of non-stationarity in the form of trends for eight of the fourteen locations considered. We quantify the change in extreme rainfall for each location and provide return levels for the years 2010, 2020, 2050 and 2100. We also derive estimates of return levels for daily rainfall and provide a classification of the fourteen locations based on the degree of severity of these estimates. This paper provides the first application of extreme value distributions to rainfall data specifically from Florida. [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]