ALBERT

Description: The Saudi Arabia (SA) climate varies greatly, depending on the geography and the season. According to K ppen and Geiger, the climates of SA is “desert climate”. The analysis of the seasonal rainfall detects that spring and winter seasons have the highestrainfall incidence, respectively. Through the summer,small quantities of precipitation are observed, while autumn received more precipitation more than summer season considering the total annual rainfall. In all seasons, the SW area receives rainfall, with a maximum in spring, whereas in the summer season, the NE and NW areas receive very little quantities of precipitation. The Rub Al-Khali (the SE region) is almost totally dry. The maximum amount of annual rainfall does not always happen at the highest elevation. Therefore, the elevation is not the only factor in rainfall distribution.A great inter-annual change in the rainfall over the SA for the period (1978–2009) is observed. In addition, in the same period, a linear decreasing trend is found in the observed rainfall, whilst in the recent past (1994–2009) a statistically significant negative trend is observed. In the Southern part of the Arabian Peninsula (AP) and along the coast of the Red Sea, it is interesting to note that rainfall increased, whilst it decreased over most areas of SA during the 2000–2009 decade, compared to 1980–1989.Statistical and numerical models are used to predict rainfall over Saudi Arabia (SA). The statistical models based on stochastic models of ARIMA and numerical models based on Providing Regional Climates for Impact Studies of Hadley Centre (PRECIS). Climate and its qualitative character and quantified range of possible future changes are investigated. The annual total rainfall decreases in most regions of the SA and only increases in the south. The summertime precipitation will be the highest between other seasons over the southern, the southwestern provinces and Asir mountains, while the wintertime rainfall will remain the lowest.The climate in the SA is instructed by the El Niño Southern Oscillation (ENSO) and other circulations such as centers of high and low pressure, the North Atlantic Oscillation (NAO) and SOI. Strength and oscillation of subtropical jet stream play a big role in pulling hot, dry air masses of SA.

Description: Drought is a serious natural hazard with far-reaching impacts including soil damages, economic losses, and threatening the livelihood and health of local residents. The goal of the present work was to monitor the vegetation health across Lebanon in 2014 using remote sensing techniques. Landsat images datasets, with a spatial resolution of 30 m and from different platforms, were used to identify the VCI (Vegetation Condition Index) and TCI (Temperature Condition Index). The VCI was based on the Normalized Difference Vegetation Index (NDVI) datasets. The TCI used land surface temperature (LST) datasets. As a result, the VHI (Vegetation Health Index) was produced and classified into five categories: extreme, severe, moderate, mild, and no drought. The results show practically no extreme drought (~0.27 km2) in the vegetated area in Lebanon during 2014. Moderate to severe drought mainly occurred in the north of Lebanon (i.e., the Amioun region and the plain of Akkar). The Tyr region and the Bekaa valley experienced a low level of drought (mild drought). This approach allows decision makers to monitor, investigate and resolve drought conditions more effectively.

Description: Soil water potential (Ψ) controls the dynamics of water in soils and can therefore affect greenhouse gas fluxes. We examined the relationship between soil moisture content (θ) at five different levels of water potential (Ψ = 0, −0.05, −0.1, −0.33 and −15 bar) and greenhouse gas (carbon dioxide, CO2; nitrous oxide, N2O and methane, CH4) fluxes. The study was conducted in 2011 in a silt loam soil at Freeman farm of Lincoln University. Soil samples were collected at two depths: 0–10 and 10–20 cm and their bulk densities were measured. Samples were later saturated then brought into a pressure plate for measurements of Ψ and θ. Soil air samples for greenhouse gas flux analyses were collected using static and vented chambers, 30 cm in height and 20 cm in diameter. Determination of CO2, CH4 and N2O concentrations from soil air samples were done using a Shimadzu Gas Chromatograph (GC-14). Results showed that there were significant correlations between greenhouse gas fluxes and θ held at various Ψ in the 0–10 cm depth of soil group. For instance, θ at Ψ = 0 positively correlated with measured CO2 (p = 0.0043, r = 0.49), N2O (p = 0.0020, r = 0.64) and negatively correlated with CH4 (p = 0.0125, r = −0.44) fluxes. Regression analysis showed that 24%, 41% and 19% of changes in CO2, N2O and CH4 fluxes, respectively, were due to θ at Ψ = 0 (p 〈 0.05). This study stresses the need to monitor soil water potential when monitoring greenhouse gas fluxes.

Description: Since the 90s, several studies were conducted to evaluate the predictability of the Sahelian rainy season and propose seasonal rainfall forecasts to help stakeholders to take the adequate decisions to adapt with the predicted situation. Unfortunately, two decades later, the forecasting skills remains low and forecasts have a limited value for decision making while the population is still suffering from rainfall interannual variability: this shows the limit of commonly used predictors and forecast approaches for this region. Thus, this paper developed and tested new predictors and new approaches to predict the upcoming seasonal rainfall amount over the Sirba watershed. Predictors selected through a linear correlation analysis were further processed using combined linear methods to identify those having high predictive power. Seasonal rainfall was forecasted using a set of linear and non-linear models. An average lag time up to eight months was obtained for all models. It is found that the combined linear methods performed better than non-linear, possibly because non-linear models require larger and better datasets for calibration. The R2, Nash and Hit rate score are respectively 0.53, 0.52, and 68% for the combined linear approach; and 0.46, 0.45, 61% for non-linear principal component analysis.

Description: Climate change impacts on nature and the environment have been widely discussed and studied. Traditionally, a company’s continuity management is based on risk analysis. There are also attempts to implement scenario-based methods in the risk management procedures of companies. For industrial decision makers, it is vital to acknowledge the impacts of climate change with regards to their adaptation strategies. However, a scenario-based approach is not always the most effective way to analyze these risks. This paper investigates the integration of scenario and risk-based methods for a company’s adaptation planning. It considers the uncertainties of the climate change scenarios and the recognized risks as well as suitable adaptation strategies. The paper presents the results of climate risk analysis prepared for two Finnish hydropower plants. The introduced method was first piloted in 2008 and then again in 2015. The update of the analysis pointed out that at the company level, the climate risks and other risks originating from governmental or political decisions form an intertwined wholeness where the origin of the risk is difficult to outline. It seems that, from the business point of view, the main adaptation strategies suggested by the integrated risk and scenarios approach are those that support buying “safety margins” in new investments and reducing decision time horizons. Both of these adaptation strategies provide an advantage in the circumstances where also political decisions and societal changes have a great effect on decision making.

Description: A detailed statistical analysis was performed at the Neuquén river basin using precipitation data for 1980–2007. The hydrological year begins in March with a maximum in June associated with rainfall and another relative maximum in October derived from snow-break. General features of the rainy season and the excess or deficits thereof are analyzed using standardized precipitation index (SPI) for a six-month period in the basin. The SPI has a significant cycle of 14.3 years; the most severe excess (SPI greater than 2) has a return period of 25 years, while the most severe droughts (SPI less than −2) have a return period of 10 years. The SPI corresponding to the rainy season (April–September) (SPI9) has no significant trend and is used to classify wet/dry years. In order to establish the previous circulation patterns associated with interannual SPI9 variability, the composite fields of wet and dry years are compared. There is a tendency for wet (dry) periods to take place during El Niño (La Niña) years, when there are positive anomalies of precipitable water over the basin, when the zonal flow over the Pacific Ocean is weakened (intensified) and/or when there are negative pressure anomalies in the southern part of the country and Antarctic sea. Some prediction schemes using multiple linear regressions were performed. One of the models derived using the forward stepwise method explained 42% of the SPI9 variance and retained two predictors related to circulation over the Pacific Ocean: one of them shows the relevance of the intensity of zonal flow in mid-latitudes, and the other is because of the influence of low pressure near the Neuquén River basin. The cross-validation used to prove model efficiency showed a correlation of 0.41 between observed and estimated SPI9; there was a probability of detection of wet (dry) years of 80% (65%) and a false alarm relation of 25% in both cases.

Description: The Abdus Salam International Center for Theoretical Physics (ICTP) version 4.4 Regional Climate Model (RegCM4) is used to investigate the rainfall response to cooler/warmer sea surface temperature anomaly (SSTA) forcing in the Indian and Atlantic Oceans. The effect of SSTA forcing in a specific ocean basin is identified by ensemble, averaging 10 individual simulations in which a constant or linearly zonally varying SSTA is prescribed in individual basins while specifying the 1971–2000 monthly varying climatological sea surface temperature (SST) across the remaining model domain. The nonlinear rainfall response to SSTA amplitude also is investigated by separately specifying +1K, +2K, and +4K SSTA forcing in the Atlantic and Indian Oceans. The simulation results show that warm SSTs over the entire Indian Ocean produce drier conditions across the larger Blue Nile catchment, whereas warming ≥ +2K generates large positive rainfall anomalies exceeding 10 mm·day−1 over drought prone regions of Northeastern Ethiopia. However, the June–September rainy season tends to be wetter (drier) when the SST warming (cooling) is limited to either the Northern or Southern Indian Ocean. Wet rainy seasons generally are characterized by deepening of the monsoon trough, east of 40°E, intensification of the Mascarene high, strengthening of the Somali low level jet and the tropical easterly jet, enhanced zonal and meridional vertically integrated moisture fluxes, and steeply vertically decreasing moist static energy. The opposite conditions hold for dry monsoon seasons.

Description: A new dynamical downscaling methodology to analyze the impact of global climate change on the local climate of cities worldwide is presented. The urban boundary layer climate model UrbClim is coupled to 11 global climate models contained in the Coupled Model Intercomparison Project 5 archive, conducting 20-year simulations for present (1986–2005) and future (2081–2100) climate conditions, considering the Representative Concentration Pathway 8.5 climate scenario. The evolution of the urban heat island of eight different cities, located on three continents, is quantified and assessed, with an unprecedented horizontal resolution of a few hundred meters. For all cities, urban and rural air temperatures are found to increase strongly, up to 7 °C. However, the urban heat island intensity in most cases increases only slightly, often even below the range of uncertainty. A potential explanation, focusing on the role of increased incoming longwave radiation, is put forth. Finally, an alternative method for generating urban climate projections is proposed, combining the ensemble temperature change statistics and the results of the present-day urban climate.

Description: Extreme rainfall events are meteorological hazards that cause great damage and many casualties in the world. This paper examines the trends in extreme rainfall from 10 sub-daily time series and 44 daily time series in Côte d’Ivoire. Rainfall data were converted into indices. In total, six (6) indices were used for daily extreme rainfall and one (1) index for sub-daily extreme rainfall (15 to 240 min). Two statistical tests for trend detection were used to evaluate the possible trend in these precipitation data. The first is a Mann-Kendall non-parametric trend test, used to evaluate the existence of monotonic trends. The second is a linear regression method, based on a parametric approach to trend detection. Results show that very few statistically significant decreasing trends can be detected at the sub-daily and daily timescales. Some decreasing trends in extreme rainfall events were localized in the south and southeast. These results could enhance the implementation of adaptation systems to flood risk.

Description: Carbon neutrality represents one climate strategy adopted by many cities, including the city of Helsinki and the Helsinki metropolitan area in Finland. This study examines initiatives adopted by the Helsinki metropolitan area aimed at reducing energy-related carbon emissions and achieving carbon neutrality through future actions. Various sectorial energy consumption rates per year and carbon emissions from various sectors within the city of Helsinki and the metropolitan area were extracted from an online database and re-calculated (in GWh, MWh/inhabitant and MtCO2e, KtCO2e/inhabitant). We employed a backcasting scenario method to explore the various carbon reduction measures in the Helsinki metropolitan area. About 96% of the emissions produced in the Helsinki metropolitan area are energy-based. District heating represents the primary source of emissions, followed by transportation and electricity consumption, respectively. We also found that accomplishing the carbon reduction strategies of the Helsinki metropolitan area by 2050 remains challenging. Technological advancement for clean and renewable energy sources, smart policies and raising awareness resulting in behavioral changes greatly affect carbon reduction actions. Thus, strong political commitments are also required to formulate and implement stringent climate actions.

Description: Climate change will have large impacts on water resources and its predictions are fraught with uncertainties in West Africa. With the current global drive for renewable energy due to climate change, there is a need for understanding the effects of hydro-climatic changes on water resources and hydropower generation. A hydrological model was used to model runoff inflow into the largest hydroelectric dam (Kainji) in the Niger Basin (West Africa) under present and future conditions. Inflow to the reservoir was simulated using hydro-climatic data from a set of dynamically downscaled 8 global climate models (GCM) with two emission scenarios from the CORDEX-Africa regional downscaling experiment, driven with CMIP5 data. Observed records of the Kainji Lake were used to develop a hydroelectricity production model to simulate future energy production for the reservoir. Results indicate an increase in inflow into the reservoir and concurrent increases in hydropower production for the majority of the GCM data under the two scenarios. This analysis helps planning hydropower schemes for sustainable hydropower production.

Description: In recent years, biofuels have emerged as a suitable alternative to hydrocarbon fuel due to their foreseen potential of being a future energy resource. Biofuel development initiatives have been successfully implemented in countries like Brazil, United States of America, European Union, Canada, Australia, and Japan. However, such programmes have been stagnant in Africa due to various constraints, such as financial barriers, technical expertise, land availability, and government policies. Nonetheless, some countries within the continent have realized the potential of biofuels and have started to introduce similar programmes and initiatives for their development. These include the bioethanol production initiatives and the plantation of jatropha oil seeds in most Sub-Saharan African countries for biodiesel production. Therefore, this paper examines the biofuel development initiatives that have been implemented in several countries across Sub-Saharan Africa over the past few years. It also discusses the opportunities and challenges of having biofuel industries in the continent. Finally, it proposes some recommendations that could be applied to accelerate their development in these Sub-Saharan African countries.

Description: Global climate change has local implications. Focusing on datasets from the topographically-challenging Karnali river basin in Western Nepal, this research provides an overview of hydro-climatic parameters that have been observed during 1981–2012. The spatial and temporal variability of temperature and precipitation were analyzed in the basin considering the seven available climate stations and 20 precipitation stations distributed in the basin. The non-parametric Mann–Kendall test and Sen’s method were used to study the trends in climate data. Results show that the average precipitation in the basin is heterogeneous, and more of the stations trend are decreasing. The precipitation shows decreasing trend by 4.91 mm/year, i.e., around 10% on average. Though the increasing trends were observed in both minimum and maximum temperature, maximum temperature trend is higher than the minimum temperature and the maximum temperature trend during the pre-monsoon season is significantly higher (0.08 °C/year). River discharge and precipitation observations were analyzed to understand the rainfall-runoff relationship. The peak discharge (August) is found to be a month late than the peak precipitation (July) over the basin. Although the annual precipitation in most of the stations shows a decreasing trend, there is constant river discharge during the period 1981–2010.

Description: The aim of the presented study is to assess the impacts of climate change on hydropower production of the Toce Alpine river basin in Italy. For the meteorological forcing of future scenarios, time series were generated by applying a quantile-based error-correction approach to downscale simulations from two regional climate models to point scale. Beside a general temperature increase, climate models simulate an increase of mean annual precipitation distributed over spring, autumn and winter, and a significant decrease in summer. A model of the hydropower system was driven by discharge time series for future scenarios, simulated with a spatially distributed hydrological model, with the simulation goal of defining the reservoirs management rule that maximizes the economic value of the hydropower production. The assessment of hydropower production for future climate till 2050 respect to current climate (2001–2010) showed an increase of production in autumn, winter and spring, and a reduction in June and July. Significant change in the reservoir management policy is expected due to anticipation of the date when the maximum volume of stored water has to be reached and an increase of the reservoir drawdown during August and September to prepare storage capacity for autumn inflows.

Description: Climate change would significantly affect the temporal pattern and amount of annual precipitation at the regional level, which in turn would affect the regional water resources and future water availability. The Peace Region is a critical region for northern British Columbia’s social, environmental, and economic development, due to its potential in various land use activities. This study investigated the impacts of future climate change induced precipitation on water resources under the A2 and B1 greenhouse gas emission scenarios for 2020–2040 in a study area along the main river of the Kiskatinaw River watershed in the Peace Region as a case study using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) modeling system. The simulation results showed that climate change induced precipitation changes significantly affect monthly, seasonal and annual stream flows. With respect to the mean annual stream flow of the reference period (2000–2011), the mean annual stream flow from 2020 to 2040 under the A2 and B1 scenarios is expected to increase by 15.5% and 12.1%, respectively, due to the increased precipitation (on average 5.5% in the A2 and 3.5% in the B1 scenarios) and temperature (on average 0.76 °C in the A2 and 0.57 °C in the B1 scenarios) predicted, with respect to that under the reference period. From the seasonal point of view, the mean seasonal stream flow during winter, spring, summer and fall from 2020 to 2040 under the A2 scenario is expected to increase by 10%, 16%, 11%, and 11%, respectively. On the other hand, under the B1 scenario these numbers are 6%, 15%, 6%, and 8%, respectively. Increased precipitation also resulted in increased groundwater discharge and surface runoff. The obtained results from this study will provide valuable information for the study area in the long-term period for seasonal and annual water extractions from the river and allocation to the stakeholders for future water supply, and help develop a regional water resources management plan for climate change induced precipitation changes.

Description: The Caucasus Region has been affected by an increasing number of heat waves during the last decades, which have had serious impacts on human health, agriculture and natural ecosystems. A dataset of 22 homogenized, daily maximum (Tmax) and minimum (Tmin) air temperature series is developed to quantify climatology and summer heat wave changes for Georgia and Tbilisi station between 1961 and 2010 using the extreme heat factor (EHF) as heat wave index. The EHF is studied with respect to eight heat wave aspects: event number, duration, participating heat wave days, peak and mean magnitude, number of heat wave days, severe and extreme heat wave days. A severity threshold for each station was determined by the climatological distribution of heat wave intensity. Moreover, heat wave series of two indices focusing on the 90th percentile of daily minimum temperature (CTN90p) and the 90th percentile of daily maximum temperature (CTX90p) were compared. The spatial distribution of heat wave characteristics over Georgia showed a concentration of high heat wave amplitudes and mean magnitudes in the Southwest. The longest and most frequently occurring heat wave events were observed in the Southeast of Georgia. Most severe heat wave events were found in both regions. Regarding the monthly distribution of heat waves, the largest proportion of severe events and highest intensities are measured during May. Trends for all Georgia-averaged heat wave aspects demonstrate significant increases in the number, intensity and duration of low- and high-intensity heat waves. However, for the heat wave mean magnitude no change was observed. Heat wave trend magnitudes for Tbilisi mainly exceed the Georgia-averages and its surrounding stations, implying urban heat island (UHI) effects and synergistic interactions between heat waves and UHIs. Comparing heat wave aspects for CTN90p and CTX90p, all trend magnitudes for CTN90p were larger, while the correlation between the annual time-series was very high among all heat wave indices analyzed. This finding reflects the importance of integrating the most suitable heat wave index into a sector-specific impact analysis.

Description: Ensembles of general circulation model (GCM) integrations yield predictions for meteorological conditions in future months. Such predictions have implicit uncertainty resulting from model structure, parameter uncertainty, and fundamental randomness in the physical system. In this work, we build probabilistic models for long-term forecasts that include the GCM ensemble values as inputs but incorporate statistical correction of GCM biases and different treatments of uncertainty. Specifically, we present, and evaluate against observations, several versions of a probabilistic forecast for gridded air temperature 1 month ahead based on ensemble members of the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2). We compare the forecast performance against a baseline climatology based probabilistic forecast, using average information gain as a skill metric. We find that the error in the CFSv2 output is better represented by the climatological variance than by the distribution of ensemble members because the GCM ensemble sometimes suffers from unrealistically little dispersion. Lack of ensemble spread leads a probabilistic forecast whose variance is based on the ensemble dispersion alone to underperform relative to a baseline probabilistic forecast based only on climatology, even when the ensemble mean is corrected for bias. We also show that a combined regression based model that includes climatology, temperature from recent months, trend, and the GCM ensemble mean yields a probabilistic forecast that outperforms approaches using only past observations or GCM outputs. Improvements in predictive skill from the combined probabilistic forecast vary spatially, with larger gains seen in traditionally hard to predict regions such as the Arctic.

Description: The study examined the spatiotemporal distribution of drought in the Maasai rangelands of Kenya. The implications of this distribution, in concert with the documented existing and/or projected social and biophysical factors, on critical rangeland resources in Maasai-pastoralism are discussed using an integrated approach. Participatory interviews with the Maasai, retrieval from archives, and acquisition from instrument measurements provided data for the study. Empirical evidence of the current study reveals that drought occurrences in this rangeland have been recurrent, widespread, cyclic, sometimes temporally clustered, and have manifested with varying intensities across spatial, temporal, and, occasionally, social scales; and they have more intensity in lower than higher agroecological areas. An estimated 86% of drought occurrences in this rangeland, over the last three decades alone, were of major drought category. The 2000s, with four major drought events including two extreme droughts, are an important drought period. A strong consensus exists among the Maasai regarding observed drought events. In Maasai-pastoralism, the phenomenon called drought, pastoralist drought, is simultaneously multivariate and multiscalar: its perception comprises the simultaneous manifestation of cross-scale meteorological, socioeconomic, and environmental factors and processes, and their various combinations. The inherent simultaneous multivariate and scalar nature of the pastoralist drought distinguishes it from the conventional drought types, particularly the meteorological drought that predominantly guides drought and resource management in the rangelands of Kenya. In Maasai-pastoralism, the scarcely used (33%) meteorological drought is construed as rainfall delay/failure across spatial and/or temporal scale, and never its reduced amount. Collectively, the current findings reveal that knowledge about drought affects the way the manifestation of this climatic hazard is perceived, communicated, and characterized; hence, ceteris paribus, alongside its spatiotemporal distribution, shapes the nature of the adaptive capacity of and resource management in Maasai-pastoralism. Studies that anticipate enhancing the drought-adaptive capacity of the Maasai should account for cross-scale social and biophysical factors, their processes, and interactions; they must engage the affected inhabitants, and utilize and integrate multiple data sources and approaches. These necessities become more crucial for informing adaptation under the present spatiotemporal distribution of drought as well as in relation to the projected increase in occurrence and intensity of this climatic hazard as the climate continues to change, and as pressures from socioeconomic globalization persistently proliferate into the Maasai’s social and biophysical landscapes.

Description: Previous work suggests that changes in seasonality could lead to a 70% reduction in the extent of the Amazon rainforest. The primary cause of the dieback of the rainforest is a lengthening of the dry season due to a weakening of the large-scale tropical circulation. Here we examine these changes in the seasonal cycle. Under present day conditions the Amazon climate is characterized by a zonal separation of the dominance of the annual and semi-annual seasonal cycles. This behavior is strongly modified under greenhouse warming conditions, with the annual cycle becoming dominant throughout the Amazon basin, increasing differences between the dry and wet seasons. In particular, there are substantial changes in the annual cycle of temperature due to the increase in the temperature of the warmest month, but the lengthening of the dry season is believed to be particularly important for vegetation-climate feedbacks. Harmonic analysis performed to regional climate model simulations yields results that differ from the global climate model that it is forced from, with the regional model being more sensitive to changes in the seasonal cycle.

Description: There are strong relationships between climate and ecosystems. With the prospect of anthropogenic forcing accelerating climate change, there is a need to understand how terrestrial vegetation responds to this change as it influences the carbon balance. Previous studies have primarily addressed this question using empirically based models relating the observed pattern of vegetation and climate, together with scenarios of potential future climate change, to predict how vegetation may redistribute. Unlike previous studies, here we use an advanced mechanistic, individually based, ecosystem model to predict the terrestrial vegetation response from future climate change. The use of such a model opens up opportunities to test with remote sensing data, and the possibility of simulating the transient response to climate change over large domains. The model was first run with a current climatology at half-degree resolution and compared to remote sensing data on dominant plant functional types for northern North America for validation. Future climate data were then used as inputs to predict the equilibrium response of vegetation in terms of dominant plant functional type and carbon redistribution. At the domain scale, total forest cover changed by ~2% and total carbon storage increased by ~8% in response to climate change. These domain level changes were the result of much larger gross changes within the domain. Evergreen forest cover decreased 48% and deciduous forest cover increased 77%. The dominant plant functional type changed on 58% of the sites, while total carbon in deciduous vegetation increased 107% and evergreen vegetation decreased 31%. The percent of terrestrial carbon from deciduous and evergreen plant functional types changed from 27%/73% under current climate conditions, to 54%/46% under future climate conditions. These large predicted changes in vegetation and carbon in response to future climate change are comparable to previous empirically based estimates, and motivate the need for future development with this mechanistic model to estimate the transient response to future climate changes.

Description: This paper advances the current debates on famine and famine history, with a focus on the first half of the 18th century in Ireland. Ireland was often hit by severe famines and two of them, specifically the famines of 1728–1729 and 1740–1741, are at the center of this article. The analysis of those famines will show the relevance of weather extremes as one driver in the functional chain of famines. Analyzing the linkage between weather extremes and social, political and economic vulnerabilities of the society further enhances the debate on past famines. Additionally, this paper focuses on the migration flows in the context of both Irish famines. These migration flows lay the foundation for the migration patterns during the “Great Irish Famine” of 1845–1852.

Description: High daily temperatures in the Mediterranean and Europe have been documented in observation and modeling studies. Long-term temperature data, from 1988 to 2017, from a suburban station and an urban station in Nicosia, Cyprus have been analyzed, and the diurnal temperature range (DTR) trend was investigated. The seasonal Mann–Kendall test revealed a decreasing DTR trend of −0.24 °C/decade at the urban station and −0.36 °C/decade at the suburban station, which were attributed to an increase in the daily minimum temperature. Variations in precipitation, longwave radiation, ultraviolet-A (UVA), ultraviolet-B (UVB), cloud cover, water vapor, and urbanization were used to assess their possible relationship with regional DTR. The clustering of daytime and night-time data showed a strong relationship between the DTR and observed cloud cover, net longwave radiation, and precipitation. Clouds associated with smaller shortwave and net longwave radiation reduce the DTR by decreasing the surface solar radiation, while atmospheric absolute humidity denotes an increased daytime surface evaporative cooling and higher absorption of the short and longwave radiation. The intra-cluster variation could be reduced, and the inter-cluster variance increased by the addition of other meteorological parameters and anthropogenic sources that affect DTR in order to develop a quantitative basis for assessing DTR variations.

Description: Flows originating from alpine dominated cold region watersheds typically experience extended winter low flows followed by spring snowmelt and summer rainfall driven high flows. In a warmer climate, there will be a temperature-induced shift in precipitation from snowfall towards rain along with changes in precipitation intensity and snowmelt timing, resulting in alterations in the frequency and magnitude of peak flow events. This study examines the potential future changes in the frequency and severity of peak flow events in the Athabasca River watershed in Alberta, Canada. The analysis is based on simulated flow data by the variable infiltration capacity (VIC) hydrologic model driven by statistically downscaled climate change scenarios from the latest coupled model inter-comparison project (CMIP5). The hydrological model projections show an overall increase in mean annual streamflow in the watershed and a corresponding shift in the freshet timing to an earlier period. The river flow is projected to experience increases during the winter and spring seasons and decreases during the summer and early fall seasons, with an overall projected increase in peak flow, especially for low frequency events. Both stationary and non-stationary methods of peak flow analysis, performed at multiple points along the Athabasca River, show that projected changes in the 100-year peak flow event for the high emissions scenario by the 2080s range between 4% and 33% depending on the driving climate models and the statistical method of analysis. A closer examination of the results also reveals that the sensitivity of projected changes in peak flows to the statistical method of frequency analysis is relatively small compared to that resulting from inter-climate model variability.

Description: Bangladesh remains one of the most vulnerable countries in the world to the effects of climate change. Given the reliance of a large segment of the population on the agricultural sector for both their livelihoods as well as national food security, climate change adaptation in the agricultural sector is crucial for continued national food security and economic growth. Using household data from lowland rice farmers of selected haor areas in Sylhet, the current work presents an analysis of the determinants behind the implementation of different climate change adaptation strategies by lowland rice farmers. The first objective of this study was to explore the extent of awareness of climate change within this population as well as the type of opinions held by lowland rice farmers with respect to climate change. To serve this purpose, a severity index (SI) was developed and subsequently employed to evaluate the perceptions and attitudes of 378 farmers with respect to climate change vulnerability. Respondents were interviewed with respect to climate change related circumstances they faced in their daily lives. Attained SI index values ranged from 69.18% to 93.52%. The SI for the perception “Climate change affects rice production” was measured as 93.52%. Using data collected from the same 378 farmers, a logistic regression was carried out to investigate the impact of socio-economic and institutional factors on adaptation. The results show that credit from non-government organizations is highly statistically significant for adaptation, and that rural market structure also has a positive effect on adaptation. Among the studied factors, credit from non-governmental organizations (NGOs) was found to be the most important factor for adaptation. The results of this work further indicate that marginal farmers would benefit from government (GoB) funded seasonal training activities that cover pertinent information regarding adaptation after flash floods. Additionally, the authors of this piece recommend timely issuance of government-assisted credit during early flash floods to afflicted farmers, as such an initiative can aid farmers in adapting different strategies to mitigate losses and enhance their productivity as well as livelihood.

Description: Drought and extreme temperatures forecasting is important for water management and the prevention of health risks, especially in a period of observed climatic change. A large precipitation deficit together with increased evapotranspiration rates in the preceding days contribute to exceptionally high temperature anomalies in the summer above the average local maximum temperature for each month. Using a retrospective approach, this study investigated droughts and extreme temperatures in the greater area of Nicosia, Cyprus and suggests a different approach in determining the lag period of summer temperature anomalies and precipitation. In addition, dry conditions defined with the use of the Standardized Precipitation-Evapotranspiration Index (SPEI) were associated with positive temperature anomalies at a percentage up to 33.7%. The compound effect of precipitation levels and evapotranspiration rates of the preceding days for the period 1988–2017 to summer temperature anomalies was demonstrated with significantly statistical R squared values up to 0.57. Furthermore, the cooling effect of precipitation was higher and prolonged longer in rural and suburban than urban areas, a fact that is directly related to the evaporation potential of the area in concern. Our work demonstrates the compound effect of precipitation levels and evapotranspiration rates of the preceding days to summer temperature anomalies.

Description: The potential costs of road traffic accidents (RTAs) to society are immense. Yet, no study has attempted to examine the impact of climate change on RTAs in Saudi Arabia, though RTA-leading deaths are very high, and the occurrence of climatic events is very frequent. Therefore, this study aims to assess the impact of climate change on RTAs in Saudi Arabia and to recommend some climate change mitigation and adaptation policies to make roads safe for all. This study employed annual data from 13 regions of Saudi Arabia, from 2003 to 2013. The data were analyzed on the basis of panel regression models—fixed effect, random effect, and the pooled ordinary least square. The findings show that temperature, rainfall, sandstorms, and number of vehicles were statistically and significantly responsible for RTAs in Saudi Arabia in the study period. This study also found that RTAs both inside and outside cities significantly caused injuries, but only RTAs inside cities significantly caused death. Furthermore, the death from RTAs injuries was found to be statistically significant only for motor vehicle accidents. The findings will assist policymakers in taking the right courses of action to mitigate the negative impacts of climate change through understanding climate influence on RTAs.

Description: The future climate is projected to change rapidly with potentially severe consequences for global food security. This study aims to improve the understanding of future changes in the suitability of crop growth conditions. It proposes a definition of crop realization, of the climate departure from recent historical variability, or crop–climate departure. Four statistically downscaled and bias-corrected Global Climate Models (GCMs): CCCMA, CNRM5, NOAA-GFDL, and MIROC5 performed simulations for the period 1960–2100 under the Representative Concentration Pathway RCP8.5 scenario to compute 20 year moving averages at 5-year increments. These were used to drive a crop suitability model, Ecocrop, for eight different crops across the three Food and Agriculture Organizations (FAO) AgroEcological Zones (AEZs) of West Africa (Guinea, Sahel, and Savanna). Simulations using historical climate data found that all crops except maize had a suitability index value (SIV) ≥0.50 outside the Sahel region, equivalent to conditions being suitable or strongly suitable. Simulations of future climate reveal that warming is projected to constrain crop growth suitability for cassava and pineapple in the Guinea zone. A potential for the northward expansion of maize is projected by the end of the century, suggesting a future opportunity for its growth in the southern Sahel zone. Crop growth conditions for mango and pearl millet remain suitable across all three AEZs. In general, crops in the Savanna AEZ are the most sensitive to the projected changes in climate. The changes in the crop–climate relationship suggests a future constraint in crop suitability, which could be detrimental to future food security in West Africa. Further studies to explore associated short- and long-term adaptation options are recommended.

Description: Urban territorial expansion generated in the last decades has brought a series of consequences, such as the variation between urban and suburban weather conditions affecting indoor temperature and increasing electricity consumption derived from the use of cooling systems. Current approaches of simulation models in residential buildings use indoor environmental data for carrying out validations to propose hygrothermal comfort alternatives for the mitigation of the effects of the external environmental conditions on the interior spaces of dwellings. In this work, an hourly evaluation of both indoor and outdoor environmental parameters of two case studies in a tropical climate was carried out, by means of a whole-building simulation approach tool during a week representative of the warmest period of the year. The integration of the collected environmental data in the theoretical model allowed us to reduce the error range of the estimated indoor temperature with results in normalized mean bias error between 7.10% and −0.74% and in coefficient of variation of the root mean square error between 16.72% and 2.62%, in the different indoor zones of the case studies. At the same time, the energy assessment showed a difference of 33% in Case 1 and −217% in Case 2 for final electricity consumption.

Description: Mitigating climate change to limit the global temperature increase (relative to pre-industrial temperatures) to 2 °C is receiving considerable attention around the world. Here, historical and future carbon dioxide equivalent (CO2e) emissions from municipal solid waste (MSW) in Bahrain were calculated using the revised Intergovernmental Panel on Climate Change (IPCC) 1996 and IPCC 2006 methods. The extent to which waste-to-energy (WtE) technologies can contribute to climate change mitigation was assessed by performing a multicriteria analysis. The results indicated that CO2e emissions from MSW in Bahrain have been increasing since the Askar landfill was constructed in 1986. Emission recalculations indicated that CO2e emissions from MSW contribute 6.2% of total emissions in Bahrain rather than the 11.6% reported in the second national communication. Methane emissions from MSW in 2030 are predicted to be 22–63 Gg. The WtE technologies anaerobic digestion and landfill gas recovery gave the best and gasification the worst multicriteria analysis model results. A database of WtE plants around the world should be compiled to allow decisions around the world to be based on best practices. The potential for maximizing energy recovery and decreasing costs needs to be investigated to allow WtE plants to compete better with renewable and nonrenewable energy sources.

Description: European climate change objectives aim to reduce CO2 emissions, promote the spread of renewable energy sources (RES), and stimulate energy efficiency (EE). The situation of local and regional governance is crucial in the implementation of community objectives. A multi-year research project was implemented in East Hungary by the University of Debrecen and Eszterházy University. It focuses on the relevance of local communities in the formation of adequate responses to the fore-mentioned challenges. A broad range of primary data collections (questionnaires and interviews) were implemented in two rural counties of the country. The first objective was to elicit existing plans concerning RES and EE at the municipality level and to measure the rate of public participation in the elaboration of them. Secondly, the scopes of the implemented projects were examined in the target area. According to the results, local leaders seem to be committed to environmental issues, but communities rarely possess energy/climate-change plans and projects. The main motivators of project implementation are financial. Because of poor financial conditions, only EU co-financed projects are realized. As subsidies come through the national government, political factors are crucial. From a governance point of view, national and county levels are decisive, and local specialties are not taken into consideration.

Description: To satisfy Jordan’s growing demand for electricity and to diversify its energy mix, the Jordanian government is considering a number of electricity-generation technologies that would allow for locally available resources to be used alongside imported energy. Energy policy in Jordan aims to address both climate change mitigation and energy security by increasing the share of low-carbon technologies and domestically available resources in the Jordanian electricity mix. Existing technological alternatives include the scaling up of renewable energy sources, such as solar and wind; the deployment of nuclear energy; and shale oil exploration. However, the views, perceptions, and opinions regarding these technologies—their benefits, risks, and costs—vary significantly among different social groups both inside and outside the country. Considering the large-scale policy intervention that would be needed to deploy these technologies, a compromise solution must be reached. This paper is based on the results of a four-year research project that included extensive stakeholder processes in Jordan, involving several social groups and the application of various methods of participatory governance research, such as multi-criteria decision-making. The results show the variety of opinions expressed and provide insights into each type of electricity-generation technology and its relevance for each stakeholder group. There is a strong prevalence of economic rationality in the results, given that electricity-system costs are prioritized by almost all stakeholder groups.

Description: This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985–2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data’s ability in reproducing the climatology of the catchment was evaluated. The extreme rainfall and temperature indices were computed using a RClimdex package by considering seventeen (17) climate change indices from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Trend detection and quantification in the rainfall (frequency and intensity) and temperature extreme indices were analyzed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator. The results show a very high seasonal correlation coefficient (r = 0.99), Nash–Sutcliff efficiency (0.98) and percentage bias (4.4% and −8.1%) between the stations and the gridded data. An investigation of dry and wet years using Standardized Anomaly Index shows 45.5% frequency of drier than normal periods compared to 54.5% wetter than normal periods in the catchment with 1999 and 2003 been extremely wet years while the year 1990 and 2013 were extremely dry. The intensity and magnitude of extreme rainfall indices show a decreasing trend for more than 78% of the rainfall locations while positive trends were observed in the frequency of extreme rainfall indices (R10mm, R20mm, and CDD) with the exception of consecutive wet days (CWD) that shows a decreasing trend. A general warming trend over the catchment was observed through the increase in the annual number of warm days (TX90p), warm nights (TN90p) and warm spells (WSDI). The spatial distribution analysis shows a high frequency and intensity of extremes rainfall indices in the south of the catchment compared to the middle and northern of part of the catchment, while temperature extremes were uniformly distributed over the catchment.

Description: The agricultural industry employs a large workforce in Ghana and remains the primary source of food security and income. The consequences of extreme weather in this sector can be catastrophic. A consistent picture of meteorological risk and adaptation patterns can lead to useful information, which can help local farmers make informed decisions to advance their livelihoods. We modelled historical data using extreme value theory and structural equation modelling. Subsequently, we studied extreme weather variability and its relationship to composite indicators of agricultural production and the long-term trend of weather risk. Minimum and maximum annual temperatures have negligible heterogeneity in their trends, while the annual maximum rainfall is homogenous in trend. Severe rainfall affects cereals and cocoa production, resulting in reduced yields. Cereals and cocoa grow well when there is even distribution of rainfall. The return levels for the next 20–100 years are gradually increasing with the long-term prediction of extreme weather. Also, heavy rains affect cereals and cocoa production negatively. All indicators of agriculture had a positive relationship with maximum extreme weather.

Description: Provision of data and information for disaster risk reduction is increasingly important to enable resilience. However, the focus of provision in many African countries is limited to national scale risk assessment and meteorological data. The research aimed to consider the perspectives on availability and access to information of different local urban actors that require reliable and specific information to make informed decisions. The research used workshop discussions and questionnaires to collect views from stakeholders in flood risk management in Nigerian cities about their current access to information and requirements. The results confirmed that stakeholders and communities agree in recognising the importance of climate information. Findings identified issues surrounding communication between agencies, government and technical experts. The role of the media and business in filling the vacuum left by state provision of information was further highlighted, demonstrating the potential for Private Public Partnerships in supporting adaptation and response to flooding. However, significant differences in access between sub-groups were also revealed such that some marginalised groups may be excluded from information. It follows that climate services, data and information provision need to be collaboratively designed in order to be more inclusive, meet user requirements and build community capacity.

Description: This study focusses on identifying a set of representative climate model projections for the Upper Indus Basin (UIB). Although a large number of General Circulation Models (GCM) predictor sets are available nowadays in the CMIP5 archive, the issue of their reliability for specific regions must still be confronted. This situation makes it imperative to sort out the most appropriate single or small-ensemble set of GCMs for the assessment of climate change impacts in a region. Here a set of different approaches is adopted and applied for the step-wise shortlisting and selection of appropriate climate models for the UIB under two RCPs: RCP 4.5 and RCP 8.5, based on: (a) range of projected mean changes, (b) range of projected extreme changes, and (c) skill in reproducing the past climate. Furthermore, because of higher uncertainties in climate projection for high mountainous regions like the UIB, a wider range of future GCM climate projections is considered by using all possible extreme future scenarios (wet-warm, wet-cold, dry-warm, dry-cold). Based on this two-fold procedure, a limited number of climate models is pre-selected, from of which the final selection is done by assigning ranks to the weighted score for each of the mentioned selection criteria. The dynamically downscaled climate projections from the Coordinated Regional Downscaling Experiment (CORDEX) available for the top-ranked GCMs are further statistically downscaled (bias-corrected) over the UIB. The downscaled projections up to the year 2100 indicate temperature increases ranging between 2.3 °C and 9.0 °C and precipitation changes that range from a slight annual increase of 2.2% under the drier scenarios to as high as 15.9% in the wet scenarios. Moreover, for all scenarios, future precipitation will be more extreme, as the probability of wet days will decrease, while, at the same time, precipitation intensities will increase. The spatial distribution of the downscaled predictors across the UIB also shows similar patterns for all scenarios, with a distinct precipitation decrease over the south-eastern parts of the basin, but an increase in the northeastern parts. These two features are particularly intense for the “Dry-Warm” and the “Median” scenarios over the late 21st century.

Description: This bibliometric analysis deals with research on the decline and fall of the Western Roman Empire in connection with climate change. Based on the Web of Science (WoS) database, we applied a combination of three different search queries for retrieving the relevant literature: (1) on the decline and fall of the Roman Empire in general, (2) more specifically on the downfall in connection with a changing climate, and (3) on paleoclimatic research in combination with the time period of the Roman Empire and Late Antiquity. Additionally, we considered all references cited by an ensemble of selected key papers and all citing papers of these key papers, whereby we retrieved additional publications (in particular, books and book chapters). We merged the literature retrieved, receiving a final publication set of 85 publications. We analyzed this publication set by applying a toolset of bibliometric methods and visualization programs. A co-authorship map of all authors, a keyword map for a rough content analysis, and a citation network based on the publication set of 85 papers are presented. We also considered news mentions in this study to identify papers with impacts beyond science. According to the literature retrieved, a multitude of paleoclimatic data from various geographical sites for the time of late antiquity indicate a climatic shift away from the stability of previous centuries. Recently, some scholars have argued that drought in Central Asia and the onset of a cooler climate in North-West Eurasia may have put Germanic tribes, Goths, and Huns on the move into the Roman Empire, provoking the Migration Period and eventually leading to the downfall of the Western Roman Empire. However, climate is only one variable at play; a combination of many factors interacting with each other is a possible explanation for the pattern of long-lasting decline and final collapse. Currently, the number of records from different locations, the toolbox of suitable analytic methods, and the precision of dating are evolving rapidly, contributing to an answer for one of the most classic of all historical questions. However, these studies still lack the inevitable collaboration of the major disciplines involved: archeology, history, and climatology. The articles of the publication set analyzed mainly result from research in the geosciences.

Description: The effects of neighborhood-scale land use and land cover (LULC) properties on observed air temperatures are investigated in two regions within Los Angeles County: Central Los Angeles and the San Fernando Valley (SFV). LULC properties of particular interest in this study are albedo and tree fraction. High spatial density meteorological observations are obtained from 76 personal weather-stations. Observed air temperatures were then related to the spatial mean of each LULC parameter within a 500 m radius “neighborhood” of each weather station, using robust regression for each hour of July 2015. For the neighborhoods under investigation, increases in roof albedo are associated with decreases in air temperature, with the strongest sensitivities occurring in the afternoon. Air temperatures at 14:00–15:00 local daylight time are reduced by 0.31 °C and 0.49 °C per 1 MW increase in daily average solar power reflected from roofs per neighborhood in SFV and Central Los Angeles, respectively. Per 0.10 increase in neighborhood average albedo, daily average air temperatures were reduced by 0.25 °C and 1.84 °C. While roof albedo effects on air temperature seem to exceed tree fraction effects during the day in these two regions, increases in tree fraction are associated with reduced air temperatures at night.

Description: An objective definition of climatologically homogeneous areas in the southern Balkans is attempted with the use of daily 0.25° × 0.25° ERA5 meteorological data of air temperature, dew point, zonal and meridional wind components, Convective Available Potential Energy, Convective Inhibition, and total cloud cover. The classification of the various grid points into climatologically homogeneous areas is carried out by applying Principal Component Analysis and K-means Cluster Analysis on the mean spatial anomaly patterns of the above parameters for the 10-year period of 2008 to 2017. According to the results, 12 climatologically homogenous areas are found. From these areas, eight are mainly over the sea and four are mainly over the land. The mean intra-annual variations of the spatial anomalies of the above parameters reveal the main climatic characteristics of these areas for the above period. These characteristics refer, for example, to how much warmer or cloudy the climate of a specific area is in a specific season relatively to the rest of the geographical domain. The continentality, the latitude, the altitude, the orientation, and the seasonal variability of the thermal and dynamic factors affecting the Mediterranean region are responsible for the climate characteristics of the 12 areas and the differences among them.

Description: The purpose of this study was to better understand the relationships between diurnal variations of air temperature measured hourly at the soil surface, compared with the thermal infra-red (TIR) emission properties of soil surfaces located in the Lower Colorado Desert of California, eastern Riverside County. Fifty air temperature loggers were deployed in January of 2017 on wooden stakes that were driven into the sandy or rocky desert soils at both Ford Dry Lake and the southern McCoy Mountains wash. The land surface temperature (LST) derived from Landsat satellite images was compared to measured air temperatures at 1 m and at the soil surface on 14 separate dates, until mid-September, 2017. Results showed that it is feasible to derive estimated temperatures at the soil surface from hourly air temperatures, recorded at 1 m above the surface (ambient). The study further correlated Landsat LST closely with site measurements of air and surface temperatures in these solar energy development zones of southern California, allowing inter-conversion with ground-based measurements for use in ecosystem change and animal population biology studies.

Description: Earth’s global surface temperature shows variability on an extended range of temporal scales and satisfies an emergent scaling symmetry. Recent studies indicate that scale invariance is not only a feature of the observed temperature fluctuations, but an inherent property of the temperature response to radiative forcing, and a principle that links the fast and slow climate responses. It provides a bridge between the decadal- and centennial-scale fluctuations in the instrumental temperature record, and the millennial-scale equilibration following perturbations in the radiative balance. In particular, the emergent scale invariance makes it possible to infer equilibrium climate sensitivity (ECS) from the observed relation between radiative forcing and global temperature in the instrumental era. This is verified in ensembles of Earth system models (ESMs), where the inferred values of ECS correlate strongly to estimates from idealized model runs. For the range of forcing data explored in this paper, the method gives best estimates of ECS between 1.8 and 3.7 K, but statistical uncertainties in the best estimates themselves will provide a wider likely range of the ECS.

Description: Probabilistic models are useful tools in understanding rainfall characteristics, generating synthetic data and predicting future events. This study describes the results from an analysis on comparing the probabilistic nature of daily, monthly and seasonal rainfall totals using data from 1327 rainfall stations across Australia. The main objective of this research is to develop a relationship between parameters obtained from models fitted to daily, monthly and seasonal rainfall totals. The study also examined the possibility of estimating the parameters for daily data using fitted parameters to monthly rainfall. Three distributions within the Exponential Dispersion Model (EDM) family (Normal, Gamma and Poisson-Gamma) were found to be optimal for modelling the daily, monthly and seasonal rainfall total. Within the EDM family, Poisson-Gamma distributions were found optimal in most cases, whereas the normal distribution was rarely optimal except for the stations from the wet region. Results showed large differences between regional and seasonal ϕ-index values (dispersion parameter), indicating the necessity of fitting separate models for each season. However, strong correlations were found between the parameters of combined data and those derived from individual seasons (0.70–0.81). This indicates the possibility of estimating parameters of individual season from the parameters of combined data. Such relationship has also been noticed for the parameters obtained through monthly and daily models. Findings of this research could be useful in understanding the probabilistic features of daily, monthly and seasonal rainfall and generating daily rainfall from monthly data for rainfall stations elsewhere.

Description: The emergence of urban heat as a climate-induced health stressor is receiving increasing attention among researchers, practitioners, and climate educators. However, the measurement of urban heat poses several challenges with current methods leveraging either ground based, in situ observations, or satellite-derived surface temperatures estimated from land use emissivity. While both techniques contain inherent advantages and biases to predicting temperatures, their integration may offer an opportunity to improve the spatial resolution and global application of urban heat measurements. Using a combination of ground-based measurements, machine learning techniques, and spatial analysis, we addressed three research questions: (1) How much do ambient temperatures vary across time and space in a metropolitan region? (2) To what extent can the integration of ground-based measurements and satellite imagery help to predict temperatures? (3) What landscape features consistently amplify and temper heat? We applied our analysis to the cities of Baltimore, Maryland, and Richmond, Virginia, and the District of Columbia using geocomputational machine learning processes on data collected on days when maximum air temperatures were above the 90th percentile of historic averages. Our results suggest that the urban microclimate was highly variable across all of the cities—with differences of up to 10 °C between coolest and warmest locations at the same time—and that these air temperatures were primarily dependent on underlying landscape features. Additionally, we found that integrating satellite data with ground-based measures provided highly accurate and precise descriptions of temperatures in all three study regions. These results suggest that accurately identifying areas of extreme urban heat hazards for any region is possible through integrating ground-based temperature and satellite data.

Description: Nepal has experienced recent changes in two crucial climatic variables: temperature and precipitation. Therefore, climate-induced water security concerns have now become more pronounced in Nepal as changes in temperature and precipitation have already altered some hydrological processes such as the river runoff in some river systems. However, the linkage between precipitation patterns and streamflow characteristics are poorly understood, especially in small rivers. We analysed the temporal trends of temperature, precipitation, and extreme indices of wet and dry spells in the Rosi watershed in Central Nepal, and observed the temporal patterns of the streamflow of the Rosi river. We also examined the linkages between the average and extreme climate indices and streamflow. We found that the area has warmed up by an average of 0.03 °C/year, and has seen a significant decline in precipitation. The dry spell as represented by the maximum length of the dry spell (CDD) and the magnitude of dryness (AII) has become more pronounced, while the wet spell as represented by the number of heavy rainfall days (R5D) and the precipitation intensity on wet days (SDII) has diminished significantly. Our analysis shows that recent changes in precipitation patterns have affected the streamflow of the Rosi river, as manifested in the observed decline in annual and seasonal streamflows. The decrease in the availability of water in the river is likely to have severe consequences for water security in the area.

Description: This work focuses on trend analysis of rainfall, evaporation, temperature, relative humidity, wind speed, and sunshine duration over the Ouémé Delta in Bénin. Eight temperature based indices and fifteen rainfall based indices are computed from 1960 to 2016. Moreover, maximum 1, 2, 3, 5, and 10 days precipitation indices were computed at the monthly scale. Trends are detected at 0.05 confidence level, using a combination of Mann-Kendall and prewhitened Mann-Kendall test. Partial correlation and stepwise regression are used to detect the set of meteorological variables that influence pan evaporation in Ouémé Delta. Results showed intensification of heavy rainfall over Ouémé Delta. Moreover, a significant increasing trend is detected in temperature. As consequence, diurnal temperature significantly decreases as proof of the global warming. Average pan evaporation showed a significant slither increasing trend over the area. Change in pan evaporation can be explained by wind speed and sunshine duration that hold almost 50% of pan evaporation variance. As future temperature is going to be increasing, pan evaporation may increase considerably. So, adaptation measures have to be reinforced in the Ouémé Delta area where farmer are used to rainfed agriculture for food security. Moreover, Ouémé Delta plan have to be developed for it resources sustainability.

Description: Climate change is an unprecedented risk that humans have not previously experienced. It is accepted that people are generally worried about global warming. However, it is also a fact that there is a small but increasing number of climate change skeptics. These skeptics do not believe that there is any risk, nor are they concerned with other worrisome facts related to climate change. Skeptics regard the present scientific findings supporting climate change as false artefacts. Our study aimed to explore the factors that influence climate skepticism. In this work, to make a regression model, we established environmental skepticism as a dependent variable and included sociodemographic factors, values, and perception factors as the three independent variables. Also, to examine their roles indirectly, we regarded values as moderators. The results show that, in terms of values, ideology, environmentalism, religiosity, two kinds of cultural biases, and science and technology (S&T) optimism influence skepticism at the individual level, whereas, in terms of perception factors, perceived risk, perceived benefit, and negative affect have an impact. Also, values such as ideology, religiosity, environmentalism, and cultural biases play a moderating role that facilitates, buffers, or changes the effect of psychometric variables on an individual’s skepticism.

Description: Severity of drought in California (U.S.) varies from year-to-year and is highly influenced by precipitation in winter months, causing billion-dollar events in single drought years. Improved understanding of the variability of drought on decadal and longer timescales is essential to support regional water resources planning and management. This paper presents a soft-computing approach to forecast the Palmer Drought Severity Index (PDSI) in California. A time-series of yearly data covering more than two centuries (1801–2014) was used for the design of ensemble projections to understand and quantify the uncertainty associated with interannual-to-interdecadal predictability. With a predictable structure elaborated by exponential smoothing, the projections indicate for the horizon 2015–2054 a weak increase of drought, followed by almost the same pace as in previous decades, presenting remarkable wavelike variations with durations of more than one year. Results were compared with a linear transfer function model approach where Pacific Decadal Oscillation and El Niño Southern Oscillation indices were both used as input time series. The forecasted pattern shows that variations attributed to such internal climate modes may not provide more reliable predictions than the one provided by purely internal variability of drought persistence cycles, as present in the PDSI time series.

Description: The study of climate, in such a diverse climatic region as the Caucasus, is necessary in order to evaluate the influence of local factors on the formation of temperature and precipitation regimes in its various climatic zones. This study is based on the instrumental data (temperatures and precipitation) from 20 weather stations, located on the territory of the Caucasian region during 1961–2011. Mathematical statistics, trend analysis, and rescaled range Methods were used. It was found that the warming trend prevailed in all climatic zones, it intensified since the beginning of global warming (since 1976), while the changes in precipitation were not so unidirectional. The maximum warming was observed in the summer (on average by 0.3 °C/10 years) in all climatic zones. Persistence trends were investigated using the Hurst exponent H (range of variation 0–1), which showed a higher trend persistence of annual mean temperature changes (H = 0.8) compared to annual sum precipitations (H = 0.64). Spatial-correlation analysis performed for precipitations and temperatures showed a rapid decrease in the correlation between precipitations at various weather stations from R = 1 to R = 0.5, on a distance scale from 0 to 200 km. In contrast to precipitation, a high correlation (R = 1.0–0.7) was observed between regional weather stations temperatures at a distance scale from 0 to 1000 km, which indicates synchronous temperature changes in all climatic zones (unlike precipitation).

Description: Urban climatology is a complex field owed to the intersecting parameters. In city planning, neighborhood fabric and vegetation plays a great role in modifying arid microclimates. This work presents an approach to enable urban designers to find the optimum land use parameters to achieve pedestrian thermal comfort. In this study, a model was developed based on ENVI-met simulations of two urban and suburban sites in Cairo, Egypt. Initial design parameters were; compactness degree, grass coverage, leaf area density, trees ground coverage, and asphalt and buildings areas. After regression analysis, the step-wise algorithm succeeded in creating the best fit of 94% R2 and 92% adjusted R2. The suggested Urban Design Comfort Model (UDCM) was examined using MATLAB to find the optimum design parameters. Optimum values were applied to generate primitive urban configurations using Grasshopper. The primitives were simulated again in ENVI-met to validate UDCM. The resulted value of Physiological Equivalent Temperature, PET at peak time was reduced from the initial result of ENVI-met (42.3 °C) in both sites to reach (38.7 °C) then (36.8 °C) after refinement with extra foliage. This approach, as a tool for urban designers, not only facilitates and speeds up urban form design process on a passive basis, but also provides deep insights on the development of UDCM considering all different city transects rather than two.

Description: Multiple factors constrain smallholder agriculture and farmers’ adaptive capacities under changing climates, including access to information to support context appropriate farm decision-making. Current approaches to geographic information dissemination to smallholders, such as the rural extension model, are limited, yet advancements in internet and communication technologies (ICTs) could help augment these processes through the provision of agricultural geographic information (AGI) directly to farmers. We analysed recent ICT initiatives for communicating climate and agriculture-related information to smallholders for improved livelihoods and climate change adaptation. Through the critical analysis of initiatives, we identified opportunities for the success of future AGI developments. We systematically examined 27 AGI initiatives reported in academic and grey literature (e.g., organisational databases). Important factors identified for the success of initiatives include affordability, language(s), community partnerships, user collaboration, high quality and locally-relevant information through low-tech platforms, organisational trust, clear business models, and adaptability. We propose initiatives should be better-targeted to deliver AGI to regions in most need of climate adaptation assistance, including SE Asia, the Pacific, and the Caribbean. Further assessment of the most effective technological approaches is needed. Initiatives should be independently assessed for evaluation of their uptake and success, and local communities should be better-incorporated into the development of AGI initiatives.

Description: A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with available station observations and analyzed for basinwide precipitation trends. Compared to observations, some data sets tended to greatly underestimate precipitation, while others overestimate it. Additionally, the discrepancies between data set and station precipitation showed significant time trends in many cases, suggesting that the precipitation trends of those data sets were not consistent with station data. Among the data sets considered, the station-based Global Precipitation Climatology Centre (GPCC) gridded data set showed good agreement with observations in terms of mean amount, trend, and spatial and temporal pattern. GPCC had average precipitation of about 500 mm per year over the basin and an increase in mean precipitation of about 15% between 1891 and 2016. For the more recent past, since 1958 or 1979, no significant precipitation trend was seen. Among the remote sensing based data sets, the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) compared best to station observations and, though available for a shorter time period than station-based data sets such as GPCC, may be especially valuable for parts of the basin without station data. The reanalyses tended to have substantial biases in precipitation mean amount or trend relative to the station data. This assessment of precipitation data set quality and precipitation trends over the Indus basin may be helpful for water planning and management.

Description: We examined the effects of elevated CO2 and elevated O3 concentrations on net CO2 assimilation and growth of Fagus crenata in a screen-aided free-air concentration-enrichment (FACE) system. Seedlings were exposed to ambient air (control), elevated CO2 (550 µmol mol−1 CO2, +CO2), elevated O3 (double the control, +O3), and the combination of elevated CO2 and O3 (+CO2+O3) for two growing seasons. The responses in light-saturated net CO2 assimilation rates per leaf area (Agrowth-CO2) at each ambient CO2 concentration to the elevated CO2 and/or O3 treatments varied widely with leaf age. In older leaves, Agrowth-CO2 was lower in the presence of +O3 than in untreated controls, but +CO2+O3 treatment had no effect on Agrowth-CO2 compared with the +CO2 treatment. Total plant biomass increased under conditions of elevated CO2 and was largest in the +CO2+O3 treatment. Biomass allocation to roots decreased with elevated CO2 and with elevated O3. Elongation of second-flush shoots also increased in the presence of elevated CO2 and was largest in the +CO2+O3 treatment. Collectively, these results suggest that conditions of elevated CO2 and O3 contribute to enhanced plant growth; reflecting changes in biomass allocation and mitigation of the negative impacts of O3 on net CO2 assimilation.

Description: The urban heat island (UHI) phenomenon is an important research topic in the scholarly community. There are only few research studies related to the UHI in the Seoul metropolitan area (SMA). Therefore, this study examined the impact of urbanization on the formation of UHI in the SMA as a geospatial study by using Landsat data from 1996, 2006, and 2017. For this purpose, we analyzed the relative variation of land surface temperature (LST) with changes of land use/land cover (LULC) rather than absolute values of LST using gradient, intensity, and directional analyses. It was observed that the impervious surface (IS) has expanded, and the UHI effect was more penetrating in the study area, with considerable loss of other LULC including green surfaces along with the rapid urbanization of the study area. In this study, we divided the IS into persistent IS (PIS) and newly added IS (NAIS). The spatial distribution of the IS, forest surface (FS), PIS, and NAIS was observed based on gradient zones (GZs). The results show that GZ1 recorded a difference of 6.0 °C when compared with the GZ109 in 2017. The results also show that the city center was warmer than the surrounding areas during the period of study. Results reveal that the mean LST has a strong significant positive relationship with a fraction of IS and PIS in 2006 and 2017. On other hand, the mean LST has a strong negative relationship with a fraction of FS and NAIS in the same time points. Relatively low temperatures were recorded in FS and NAIS in both time points. Further, it was proved that the local climate of the SMA and its surroundings had been affected by the UHI effect. Therefore, urban planners of the SMA should seriously consider the issue and plan to mitigate the effect by improving the green surfaces of the city. More greening-oriented concepts are recommended in both horizontal and vertical directions of the SMA, that can be used to control the negative impact associated with UHI. The overall outputs of the study could be used as a proxy indicator for the sustainability of the SMA and its surroundings.

Description: Climate change has been one of the most debated topics in the past few decades, but a number of challenges have hindered the development of robust policies and strategies by nations. At the same time, social media platforms—such as Instagram, Twitter, and Facebook—have given the opportunity for the general public to share opinions and engage with the issue of climate change like never before. This phenomenon is considered to be a new form of soft power which can provide input into the discussion and possibly affect the current international political mechanisms. The present paper aims to (1) define the forms and characteristics of social media as a soft power method, (2) analyze its influence on the awareness of societies, and (3) assess if increased public awareness could influence the official political and policy processes. In order to assess if social media has influence on people’s relative awareness, we have focused on analyzing the links between a few highly visible climate change related events and the trends in people’s searches on the Internet in connection to those events. The study finds that even though it is difficult to assess the effects of social media as a soft power tool with certainty, there are visible links between social media and changing public perceptions, with the possibility of public opinion influencing political decision-making.

Description: Green infrastructure (GI) has increasingly gained popularity for achieving adaptation and mitigation goals associated with climate change and extreme weather events. To continue implementing GI, financial tools are needed for upfront project capital or development costs and later for maintenance. This study’s purpose is to evaluate financing tools used in a selected GI dataset and to assess how those tools are linked to various GI technologies and other GI project characteristics like cost and size. The dataset includes over 400 GI U.S. projects, comprising a convenience sample, from the American Society of Landscape Architects (ASLA). GI project characteristics were organized to answer a number of research questions using descriptive statistics. Results indicated that the number of projects and overall cost shares were mostly located in a few states. Grants were the most common financial tool with about two-thirds of the projects reporting information on financial tools receiving grant funding. Most projects reported financing from only one tool with a maximum of three tools. Projects primarily included multiple GI technologies averaging three and a maximum of nine. The most common GI technologies were bioswales, retention, rain gardens, and porous pavements. These findings are useful for decision-makers evaluating funding support for GI.

Description: Most weather and climate models simulate circulations by numerically approximating a complex system of partial differential equations that describe fluid flow. These models also typically use one of a few standard methods to parameterize the effects of smaller-scale circulations such as convective plumes. This paper discusses the continued development of a radically different modeling approach. Rather than solving partial differential equations, the author’s Lagrangian models predict the motions of individual fluid parcels using ordinary differential equations. They also use a unique convective parameterization, in which the vertical positions of fluid parcels are rearranged to remove convective instability. Previously, a global atmospheric model and basin-scale ocean models were developed with this approach. In the present study, components of these models are combined to create a new global Lagrangian ocean model (GLOM), which will soon be coupled to a Lagrangian atmospheric model. The first simulations conducted with the GLOM examine the contribution of interior tracer mixing to ocean circulation, stratification, and water mass distributions, and they highlight several special model capabilities: (1) simulating ocean circulations without numerical diffusion of tracers; (2) modeling deep convective transports at low resolution; and (3) identifying the formation location of ocean water masses and water pathways.

Description: A previous test of global warming theory, on a local level, for Texas revealed inverse correlations between air temperature and death rates. The present study expands the test field to the continental U.S. Using an ecological design, mean daily maximum air temperature (“temperature”) in the 48 contiguous states plus the District of Columbia by year from 1968–2013 was compared to age-adjusted all-cause mortality (“deaths”) in these same jurisdictions for the same years using Pearson correlation (n = 46 years). The comparison was made for three race categories, white, black, and all races, where each category included all ages and both genders. There was 5.0 degree F range for the years studied (62.7–67.7 degrees F). Correlations were moderate strength, inverse, and statistically significant, as follows. Whites: r = −0.576, p 〈 0.0001; Blacks: r = −0.556, p = 0.0001; and all races: r = −0.577, p 〈 0.0001. These correlations are consistent with the Texas study, both of which indicated that warmer years tended to correlate with decreased death rates. A limitation to this research is its (ecological) design, but is an initial step towards further investigation.

Description: Changes in rainfall regime during the last five decades over the West African Sahel have significantly modified the hydrological regime of many rivers with a significant impact on water resources. In this study, the main hydrological processes on the Nakanbe watershed in Burkina Faso are described with two hydrological models: GR2M (lumped and monthly model) and ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) (distributed and half hourly model). Both models were calibrated on the watershed from observed runoff data at Wayen outlet (area of 22,000 km2) for the 1978–1999 period. The mean annual hydrological balance components on the watershed over this period are composed of about 4% of runoff, 10% of groundwater recharge and 86% of actual evapotranspiration for both models. An assessment of the hydrological impacts of the changes in rainfall regime simulated by five regional climate models shows some discrepancies. The hydrological simulations show that the hydrological impacts on the water balance of the watershed come mainly from the changes in rainfall field with regard to the frequency and the intensity of rain events. Compared to the decrease in frequency, it appears that the decrease in the intensity of rain events is much more prejudicial to runoff and groundwater recharge.

Description: The present study surveys the opinion of the residents of the Athens area in Greece on a wide range of issues related to climate change, such as their environmental consciousness and awareness and their willingness to take action against climate change. This study is performed at a time of a severe economic crisis in Greece. Based on a questionnaire, this study examines the general trends reported on various environmental issues, more particularly concerning climate change. The main results are that Greek citizens are aware of the problems of environmental and of climate change and also believe that the environmental quality of Greece is quite poor. They believe they are fairly well informed about climate change. However, the current economic crisis in Greece has reversed the progress made in the past concerning the awareness of climate change. Also, the citizens have very low confidence in the public authorities and the big enterprises to deal with climate change, while they have high level of trust in scientific and environmental organizations. They agree with public actions, but are against individual actions to protect the environment as they consider the main stakeholders (state, industry) to be mainly responsible for environmental degradation.

Description: Aerosol particles can affect cloud microphysical properties by serving as ice nuclei (IN). Large uncertainties exist in the ice nucleation parameterizations (INPs) used in current climate models. In this Part II paper, to examine the sensitivity of the model predictions to different heterogeneous INPs, WRF-CAM5 simulation using the INP of Niemand et al. (N12) [1] is conducted over East Asia for two full years, 2006 and 2011, and compared with simulation using the INP of Meyers et al. (M92) [2], which is the original INP used in CAM5. M92 calculates the nucleated ice particle concentration as a function of ice supersaturation, while N12 represents the nucleated ice particle concentration as a function of temperature and the number concentrations and surface areas of dust particles. Compared to M92, the WRF-CAM5 simulation with N12 produces significantly higher nucleated ice crystal number concentrations (ICNCs) in the northern domain where dust sources are located, leading to significantly higher cloud ice number and mass concentrations and ice water path, but the opposite is true in the southern domain where temperatures and moistures play a more important role in ice formation. Overall, the simulation with N12 gives lower downward shortwave radiation but higher downward longwave radiation, cloud liquid water path, cloud droplet number concentrations, and cloud optical depth. The increase in cloud optical depth and the decrease in downward solar flux result in a stronger shortwave and longwave cloud forcing, and decreases temperature at 2-m and precipitation. Changes in temperature and radiation lower surface concentrations of OH, O3, SO42−, and PM2.5, but increase surface concentrations of CO, NO2, and SO2 over most of the domain. By acting as cloud condensation nuclei (CCN) and IN, dust particles have different impacts on cloud water and ice number concentrations, radiation, and temperature at 2-m and precipitation depending on whether the dominant role of dust is CCN or IN. These results indicate the importance of the heterogeneous ice nucleation treatments and dust emissions in accurately simulating regional climate and air quality.

Description: The purpose of this review is to describe the global scope of the multidecadal climate oscillations that go back at least, through several hundred years. Literature, historic data, satellite data and global circulation model output have been used to provide evidence for the zonal and meridional jet stream patterns. These patterns were predominantly zonal from the 1970s to 1990s and switched since the 1990s to a meridional wind phase, with weakening jet streams forming Rossby waves in the northern and southern hemispheres. A weakened northern jet stream has allowed northerly winds to flow down over the continents in the northern hemisphere during the winter period, causing some harsh winters and slowing anthropogenic climate warming regionally. Wind oscillations impact ocean gyre circulation affecting upwelling strength and pelagic fish abundance with synchronous behavior in sub Arctic gyres during phases of the oscillation and asynchronous behavior in subtropical gyres between the Atlantic and Pacific oceans.

Description: The long-term harsh climate conditions in 2015 distorted already from June up to November in all study trees of Tsuga and Taxus the intracellular organization of the needles. Intimately involved in these repressive processes were the flavanols, a small subgroup of the flavonoids. They were not only deposited in vacuoles of conifer needles but also in the nuclei and chromosomes. Among the many flavonoids the small group of catechin derivatives and polymers named flavanols can exclusively be stained blue with DMACA (dimethylaminocinnamaldehyde). From mid-July onward, the vacuolar flavanols of the epidermal cell layers were gradually diminished as evidenced by decreasing blue staining of nuclei and vacuoles. Subsequently, in August also the large spongy mesophyll cells showed the flavanols decreasing progressively. Apparently, the antioxidant flavanols operate as oxygen radical scavengers. (ROS) were used up during the harsh environmental stress conditions. Both, Tsuga and Taxus reacted in this way. However, it is quite surprising that in all study trees the palisade cells did not contain such vacuolar flavanols. Only these cells were in June the first to show a loss of chlorophyll from chloroplasts as well as an efflux of flavanols from the nuclei. Conversely, from September onward another group of phenols, the yellow-staining flavanols were newly formed in the palisade cells and later on also in the mesophyll cells. Obviously, they were assembled finally to stabilize finally the fragile cell sites. Summing up, the present study shows by cytological studies that the climatic conditions in 2015 produced the worst disturbance of subcellular structures observed since 2000 when our studies on nuclear phenols in needles of conifers were initiated.

Description: Hydrological climate change impact assessment is generally performed by following a sequence of steps from global and regional climate modelling, through data tailoring (bias-adjustment and downscaling) and hydrological modelling, to analysis and impact assessment. This “climate-hydrology-assessment chain” has been developed with a primary focus on applicability to a medium-sized rural basin, which has been and still is the main type of domain investigated in this context. However, impact assessment is to an increasing degree being performed at scales smaller or larger than the medium-sized rural basin. Small-scale assessment includes e.g., impacts on solute transport and urban hydrology and large-scale assessment includes e.g., climate teleconnections and continental modelling. In both cases, additional complexity is introduced in the process and additional demands are placed on all components involved, i.e., climate and hydrology models, tailoring methods, assessment principles, and tools. In this paper we provide an overview of recent progress with respect to small- and large-scale hydrological climate change impact assessment. In addition, we wish to highlight some key issues that emerged as a consequence of the scale and that need further attention from now on. While we mainly use examples from work performed in Europe for illustration, the progress generally reflects the overall state of the art and the issues considered are of a generic character.

Description: Natural resource professionals, ranging from forest managers and educators to floodplain managers, play a critical role in implementing and conducting outreach with regards to climate mitigation and adaptation appropriate to local and regional scales. Natural resource professionals can also pave the way by adopting actions that serve as demonstrations of efforts to mitigate greenhouse gas emissions or adapt natural systems for the future. A web survey of 1488 natural resource professionals across New York State (NYS) was conducted to assess their attitudes toward climate change, views toward climate change mitigation and adaptation priorities, actions taken to address climate change, and barriers faced as they relate to their professional responsibilities. The majority of natural resource professionals believe that climate change is happening, but there was slightly less agreement about human causes of climate change. Most natural resource professionals (69%) see evidence of how climate change is impacting natural resources in NYS, but few (17%) believed that there was sufficient information about how to address climate impacts at the local level. Nearly 60% of natural resources professionals undertook climate mitigation or adaptation actions in their work. Prominent influencing factors for action were proactive leadership and local impacts. Barriers to taking action on climate change were a lack of human and financial resources, the nature of costs relative to benefits, and lack of perceived threat. As managers and educators responsible for local water, land, and wildlife resources, natural resource professionals witness changes resulting from climate change first-hand. This paper will be useful to decision-makers at state and federal government levels regarding policies, incentives, and guidance that can be created with the goal of promoting a sound natural resource strategy in support of climate change readiness.

Description: Future of the crucial Himalayan water supplies has generally been assessed under the anthropogenic warming, typically consistent amid observations and climate model projections. However, conflicting mid-to-late melt-season cooling within the upper Indus basin (UIB) suggests that the future of its melt-dominated hydrological regime and the subsequent water availability under changing climate has yet been understood only indistinctly. Here, the future water availability from the UIB is presented under both observed and projected—though likely but contrasting—climate change scenarios. Continuation of prevailing climatic changes suggests decreased and delayed glacier melt but increased and early snowmelt, leading to reduction in the overall water availability and profound changes in the overall seasonality of the hydrological regime. Hence, initial increases in the water availability due to enhanced glacier melt under typically projected warmer climates, and then abrupt decrease upon vanishing of the glaciers, as reported earlier, is only true given the UIB starts following uniformly the global warming signal. Such discordant future water availability findings caution the impact assessment communities to consider the relevance of likely (near-future) climate change scenarios—consistent to prevalent climatic change patterns—in order to adequately support the water resource planning in Pakistan.

Description: This work operationalizes the determinants of climate change risk, exposure and vulnerability, through the perceptions held by Native hunters, fishers, and gatherers in Savoonga and Shaktoolik, Alaska. Informed by their skill, experience, and the traditional knowledge of their elders, hunters, fishers, and gatherers in these communities are astute observers of their environment and environmental change. A questionnaire is used to sort and rank their perceptions of the most obvious and disruptive elements of climate change as representations of exposure and vulnerability, respectively. Results represent the relative strength and significance of those perceptions of environmental change. In addition to other changes, storms are among the most obvious and disruptive impacts of climate change to respondents in both communities, while changes to sea ice tend to be more disruptive in Savoonga, a more ice-obligate culture, than Shaktoolik. Changes on the tundra are more obvious in Shaktoolik, but is the least disruptive category of change in both villages. Changes along the coast were both obvious and disruptive, albeit more so in Shaktoolik than Savoonga. The findings suggest that traditional ecological knowledge is a valuable source of information to access perceptions of risk, and develop climate risk management and adaptation plans. The questionnaire design and statistical methodology may be of interest to those working on community-based adaptation and risk assessment projects in high-risk, poor, and marginalized Native communities with small populations.

Description: Rice production underpins the national economy and the most rural livelihoods in Cambodia, but it is negatively impacted by repeated droughts. The research reported on in this paper focuses on relationships between drought occurrences in Cambodia’s most drought-prone province (Kampong Speu) and (i) damage to the annual rice harvest between 1994 and 2011, and (ii) the Niño 3.4 index. Droughts were identified using the Standardised Precipitation Index (SPI). In seven of the years between 1994 and 2006 droughts damaged >1000 ha of rice in the Kampong Speu province. Furthermore, in 11 years >200 ha of rice were damaged. A critical success index of 0.66 obtained for an analysis of SPI-defined drought and area rice damage in the province indicates a strong statistical relationship. A statistically significant correlation (r = −0.455) was achieved between Niño 3.4 and 12-month SPI values lagged by three months, this indicates the importance of ENSO linkages in explaining drought in this region. Late season droughts lead to greater rice damage than early- and mid-season droughts.

Description: Climate change impacts on water resources have jeopardized human security in the Sahel countries for many decades, especially in achieving food security. Many strategies and policies have been made to address such impacts. However, there are still difficulties to measure progress and the effectiveness of these policies and strategies with regard to climate risks. The lack of practical and consensual monitoring tool is one of the factors that can explain gaps in policies and initiatives to overcome these impacts. To move towards filling this gap, using ClimProspect model and a participatory approach, and based on in-depth vulnerability analysis, this paper makes available some innovative integrated and coherent resilience indicators and a new index for Burkina Faso’s water resources. Taking into account both climate and disaster risks, the indicators and index developed are related to warning, responses, recovery and long term resilience. The indicators-based index applied to three sites shows that agriculture water is less resilient to a changing climate with a score varying from 22.66% to 24%. These tools can help in formulating, implementation and reviewing water policy to secure water resources under the stress of climate change. The approach and findings bring together, on one hand, social and ecological resilience to climate risks, and sciences and policy on the other.

Description: This study aims to calibrate and validate the generic crop model (CROPGRO-Soybean) and estimate the soybean yield, considering simulations with different sowing times for the current period (1990–2013) and future climate scenario (2014–2030). The database used came from observed data, nine climate models of CORDEX (Coordinated Regional climate Downscaling Experiment)-Africa framework and MERRA (Modern Era Retrospective-Analysis for Research and Applications) reanalysis. The calibration and validation data for the model were acquired in field experiments, carried out in the 2009/2010 and 2010/2011 growing seasons in the experimental area of the International Institute of Tropical Agriculture (IITA) in Angónia, Mozambique. The yield of two soybean cultivars: Tgx 1740-2F and Tgx 1908-8F was evaluated in the experiments and modeled for two distinct CO2 concentrations. Our model simulation results indicate that the fertilization effect leads to yield gains for both cultivars, ranging from 11.4% (Tgx 1908-8F) to 15% (Tgx 1740-2Fm) when compared to the performance of those cultivars under current CO2 atmospheric concentration. Moreover, our results show that MERRA, the RegCM4 (Regional Climatic Model version 4) and CNRM-CM5 (Centre National de Recherches Météorologiques – Climatic Model version 5) models provided more accurate estimates of yield, while others models underestimate yield as compared to observations, a fact that was demonstrated to be related to the model’s capability of reproducing the precipitation and the surface radiation amount.

Description: Recent evidence suggests that urban forms and materials can help to mediate temporal variation of microclimates and that landscape modifications can potentially reduce temperatures and increase accessibility to outdoor environments. To understand the relationship between urban form and temperature moderation, we examined the spatial and temporal variation of air temperature throughout one desert city—Doha, Qatar—by conducting vehicle traverses using highly resolved temperature and GPS data logs to determine spatial differences in summertime air temperatures. To help explain near-surface air temperatures using land cover variables, we employed three statistical approaches: Ordinary Least Squares (OLS), Regression Tree Analysis (RTA), and Random Forest (RF). We validated the predictions of the statistical models by computing the Root Mean Square Error (RMSE) and discovered that temporal variations in urban heat are mediated by different factors throughout the day. The average RMSE for OLS, RTA and RF is 1.25, 0.96, and 0.65 (in Celsius), respectively, suggesting that the RF is the best model for predicting near-surface air temperatures at this study site. We conclude by recommending the features of the landscape that have the greatest potential for reducing extreme heat in arid climates.

Description: The main objective of this study is to examine trend and homogeneity through the analysis of rainfall variability patterns in Iran. The study presents a review on the application of homogeneity and seasonal time series analysis methods for forecasting rainfall variations. Trend and homogeneity methods are applied in the time series analysis from collecting rainfall data to evaluating results in climate studies. For the homogeneity analysis of monthly, seasonal and annual rainfall, homogeneity tests were used in 140 stations in the 1975–2014 period. The homogeneity of the monthly and annual rainfall at each station was studied using the autocorrelation (ACF), and the von Neumann (VN) tests at a significance level of 0.05. In addition, the nature of the monthly and seasonal rainfall series in Iran was studied using the Kruskal-Wallis (KW) test, the Thumb test (TT), and the least squares regression (LSR) test at a significance level of 0.05. The present results indicate that the seasonal patterns of rainfall exhibit considerable diversity across Iran. Rainfall seasonality is generally less spatially coherent than temporal patterns in Iran. The seasonal variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The present study comparisons among variations of patterns with the seasonal rainfall series reveal that the variability of rainfall can be predicted by the non-trended and trended patterns.

Description: The influence of land surface temperature (LST) makes the near-surface layer of the troposphere a key driver of urban climate. This paper assesses the temporal formation of the daytime Surface Urban Cool Island (SUCI) and night-time Surface Urban Heat Island (SUHI) effect in Erbil, Iraq, situated in a semi-arid climate region. LST retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra and MODIS Normalized Difference Vegetation Index (NDVI) from January 2003 to December 2014 are analysed. The relationships of LST with NDVI and the Normalized Multi-band Drought Index (NMDI) are investigated in order to assess the influence of vegetation and moisture on the observed patterns of LST and the SUCI/SUHI. The results indicate that during the daytime, in summer, autumn and winter, densely built-up areas had lower LST acting as a SUCI compared to the non-urbanised area around the city. In contrast, at night-time, Erbil experienced higher LST and demonstrated a significant SUHI effect. The relationship between LST and NDVI is affected by seasonality and is strongly inverted during spring (r2 = 0.73; p 〈 0.01). Contrary to previous studies of semi-arid cities, a SUCI was detected, not only in the morning, but also during the afternoon.

Description: Weather monitoring systems, such as Doppler radars, collect a high volume of measurements with fine spatial and temporal resolutions that provide opportunities to study many convective weather events. This study examines the spatial and temporal characteristics of severe thunderstorm life cycles in central United States mainly covering Kansas, Oklahoma, and northern Texas during the warm seasons from 2010 to 2014. Thunderstorms are identified using radar reflectivity and cloud-to-ground lightning data and are tracked using a directed graph model that can represent the whole life cycle of a thunderstorm. Thunderstorms were stored in a GIS database with a number of additional thunderstorm attributes. Spatial and temporal characteristics of the thunderstorms were analyzed, including the yearly total number of thunderstorms, their monthly distribution, durations, initiation time, termination time, movement speed and direction, and the spatial distributions of thunderstorm tracks, initiations, and terminations. Results revealed that thunderstorms were most frequent across the eastern part of the study area, especially at the borders between Kansas, Missouri, Oklahoma, and Arkansas. Finally, thunderstorm occurrence is linked to land cover, including a comparison of thunderstorms between urban and surrounding rural areas. Results demonstrated that thunderstorms would favor forests and urban areas. This study demonstrates that advanced GIS representations and analyses for spatiotemporal events provide effective research tools to meteorological studies.

Description: The present study aimed at analyzing the synoptic pattern of atmospheric thickness of winter pervasive frosts in Iran. To this end, the data related to the daily minimum temperature of a 50-year period (1961–2010) were gathered from 451 synoptic and climatology stations. Then, the instances in which the temperature was below 0 °C for at least two consecutive days and this phenomenon covered at least 50% of the entirety of Iran were selected. Subsequently, the atmosphere thickness pattern was extracted for these days, with the representative day being identified and analyzed through cluster analysis. The results showed that the Siberian high pressure plays a significant role in the occurrence of pervasive frosts in Iran. In some other cases, the northeast–southwest direction of this pattern leads to its combination with the East Europe high pressure, causing widespread frosts in Iran. Furthermore, the interaction between counter clockwise currents in this system and the clockwise currents in the Azores high pressure tongue directs cold weather from northern parts of Europe toward Iran. The formation of blocking systems leads to the stagnation of cold weather over Iran, a phenomenon that results in significant reduction of temperature and severe frosts in these areas. In addition, the omega pattern (the fifth pattern) and Deep Eastern European trough and polar low pressure pattern (the fourth pattern) were the most dominant and severe frost patterns in Iran respectively.

Description: This paper examines the onset and cessation dates of the rainy season over Ghana using rain gauge data from the Ghana Meteorological Agency (GMet) over the period of 1970–2012. The onset and cessation dates were determined from cumulative curves using the number of rainy days and rainfall amount. In addition, the inter-annual variability of the onset and cessation dates for each climatic zone was assessed using wavelet analysis. A clear distinction between the rainfall characteristics and the length of the rainy season in the various climatic zones is discussed. The forest and coastal zones in the south had their rainfall onset from the second and third dekads of March. The onset dates of the transition zone were from the second dekad of March to the third dekad of April. Late onset, which starts from the second dekad of April to the first dekad of May, was associated with the savannah zone. The rainfall cessation dates in the forest zone were in the third dekad of October to the first dekad of November, and the length of the rainy season was within 225–240 days. The cessation dates of the coastal zone were within the second and third dekad of October, and the length of rainy season was within 210–220 days. Furthermore, the transition zone had cessation dates in the second to third dekad of October, and the length of the rainy season was within 170–225 days. Lastly, the savannah zone had cessation dates within the third dekad of September to the first dekad of October, and the length of rainy season was within 140–180 days. The bias in the rainfall onset, cessation and length of the rainy season was less than 10 days across the entire country, and the root mean square error (RMSE) was in the range of 5–25 days. These findings demonstrate that the onset derived from the cumulative rainfall amount and the rainy days are in consistent agreement. The wavelet power spectrum and its significant peaks showed evidence of variability in the rainfall onset and cessation dates across the country. The coastal and forest zones showed 2–8- and 2–4-year band variability in the onsets and cessations, whereas the onset and cessation variability of the transition and savannah zones were within 2–4 and 4–8 years. This result has adverse effects on rain-fed agricultural practices, disease control, water resource management, socio-economic activities and food security in Ghana.

Description: This study analyzed the trends of extreme daily rainfall indices over the Indochina Peninsula from 1960 to 2007. The trends were obtained from high-resolution gridded daily rainfall data compiled by APHRODITE with coordinates of 4°N–25°N and 90E°–112°E. The indices were selected from the list of climate change indices recommended by ETCCDI, which is a joint group of WMO CCl, CLIVAR and JCOMM. The indices are based on the number of heavy rainfall days (≥10 mm), number of very heavy rainfall days (≥20 mm), number of extremely heavy rainfall days (≥25 mm), consecutive dry days (〈1 mm), consecutive wet days (≥1 mm), daily maximum rainfall, five-day maximum rainfall, annual wet-day rainfall total, Simple Daily Intensity Index, very wet days, and extremely wet days. The indices were simulated by calculating different extreme characteristics according to wet and dry conditions, frequency, and intensity. Linear trends were calculated by using a least squares fit and significant or non-significant trends were identified using the Mann–Kendall test. The results of this study revealed contrasting trends in extreme rainfall in eastern and western Indochina Peninsula. The changes in extreme rainfall events in the east primarily indicate positive trends in the number of heavy rainfall days, very heavy rainfall days, extremely heavy rainfall days, consecutive wet days and annual wet-day rainfall total, with significant trends at times. These events correlated with the northeastern monsoon that influences the Indochina Peninsula from October to February annually. The results in the west primarily indicate negative trends in consecutive wet days, where significant trends were correlated with decreasing number of annual wet-day rainfall total, heavy rainfall days, very heavy rainfall days, and extremely heavy rainfall days. Daily maximum rainfall, five-day maximum rainfall, very wet days, and extremely wet days show random positive (negative) significant (non-significant) trends, while the simple daily intensity index shows positive trends that dominate the southern part of the Indochina Peninsula, with some grids show significant trends.

Description: Changes in annual rainfall in five sub-regions of the Argentine Pampa Region (Rolling, Central, Mesopotamian, Flooding and Southern) were examined for the period 1941 to 2010 using data from representative locations in each sub-region. Dubious series were adjusted by means of a homogeneity test and changes in mean value were evaluated using a hydrometeorological time series segmentation method. In addition, an association was sought between shifts in mean annual rainfall and changes in large-scale atmospheric pressure systems, as measured by the Atlantic Multidecadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO) and the Southern Oscillation Index (SOI). The results indicate that the Western Pampas (Central and Southern) are more vulnerable to abrupt changes in average annual rainfall than the Eastern Pampas (Mesopotamian, Rolling and Flooding). Their vulnerability is further increased by their having the lowest average rainfall. The AMO showed significant negative correlations with all sub-regions, while the PDO and SOI showed significant positive and negative correlations respectively with the Central, Flooding and Southern Pampa. The fact that the PDO and AMO are going through the phases of their cycles that tend to reduce rainfall in much of the Pampas helps explain the lower rainfall recorded in the Western Pampas sub-regions in recent years. This has had a significant impact on agriculture and the environment.

Description: Predicting the future climate and its impacts on the global environment is model based, presenting a level of uncertainty. Alternative robust approaches of analyzing high volume climate data to reveal underlying regional and local trends are increasingly incorporating satellite data. This study uses a centered log-ratio (clr) transformation approach and robust principal component analysis (PCA), on a long-term Normalized Difference Vegetation Index (NDVI) dataset to test its applicability in analyzing large multi-temporal data, and potential to recognize important trends and patterns in regional climate. Twenty five years of NDVI data derived by Global Inventory Modeling and Mapping Studies (GIMMS) from 1982 to 2006 were extracted for 88 subwatersheds in central Kenya and statistically analyzed. Untransformed (raw) and clr transformed NDVI data were evaluated using robust PCA. The robust PCA compositional biplots of the clr transformed long-term NDVI data demonstrated the finest spatial-temporal display of observations identifying climate related events that impacted vegetation activity and observed variations in greenness. The responses were interpreted as normal conditions, El Niño Southern Oscillation (ENSO) events of El Niño and La Niña, and drought events known to influence the moisture level and precipitation patterns (high, low, normal) and therefore the level of vegetation greenness (NDVI value). More drought events (4) were observed between 1990 and 2006, a finding corroborated by several authors and linked to increasing climate variability. Results are remarkable, emphasizing the need for appropriate data transformation prior to PCA, dealing with huge complex datasets, to enhance pattern recognition and meaningful interpretation of results. Through improved analysis of past data, uncertainty is decreased in modeling future trends.

Description: Economic evidence is a key component of public policy responses to complex societal and health problems, including climate change. Activities to protect human health from climate change should routinely be evaluated not only in terms of their effectiveness or unintended consequences, but also in terms of the health damage cost of inaction, the cost of health adaptation, and the monetized benefits of different alternatives. In this paper we reviewed the economic evidence on the health impacts of climate change and health-relevant adaptation within the 53 Member States of the World Health Organization (WHO) European Region, including grey literature and conventional scientific literature. We found that the evidence base on the health economics of climate change is scarce, incomplete and inconsistent. Despite these shortcomings, the existing evidence clearly indicates that adaptation to avert the health impacts of climate change could provide substantial economic benefits, particularly in the poorer areas of the Region.

Description: This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km2) in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH) of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced) is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960–1971 is selected for calibration while the period 1972–1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT) from the European program ENSEMBLES, forced by two global climate models (GCM): ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature) are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to reproduce the occurrence of dry days but still underestimates them. From the statistical distribution point of view, corrected SMH precipitation data introduced into the MBBH model were not able to reproduce extreme runoff values generated by observed precipitation data during validation (larger than 80 mm/month). This may be due to the SMH weakness in reproducing moderate and high rainfall levels even after bias correction. This approach may be considered as a way to use regional climate models (RCM) model outputs for studying hydrological impacts.

Description: A new method of regime shift detection in the correlation coefficient is proposed. The method is designed to find multiple change-points with unknown locations in time series. It signals a possible regime shift in real time and allows for its monitoring. The method is tested on randomly generated time series with predefined change-points. It is applied to examine structural changes in the Bering Sea climate. A major shift is found in 1967, which coincides with a transition from a zonal type of atmospheric circulation to a meridional one. The roles of the Siberian and Alaskan centers of action on winter temperatures in the eastern Bering Sea have been investigated.

Description: Given the climatic changes around the world and the growing outdoor sports participation, existing guidelines and recommendations for exercising in naturally challenging environments such as heat, cold or altitude, exhibit potential shortcomings. Continuous efforts from sport sciences and exercise physiology communities aim at minimizing the risks of environmental-related illnesses during outdoor sports practices. Despite this, the use of simple weather indices does not permit an accurate estimation of the likelihood of facing thermal illnesses. This provides a critical foundation to modify available human comfort modeling and to integrate bio-meteorological data in order to improve the current guidelines. Although it requires further refinement, there is no doubt that standardizing the recently developed Universal Thermal Climate Index approach and its application in the field of sport sciences and exercise physiology may help to improve the appropriateness of the current guidelines for outdoor, recreational and competitive sports participation. This review first summarizes the main environmental-related risk factors that are susceptible to increase with recent climate changes when exercising outside and offers recommendations to combat them appropriately. Secondly, we briefly address the recent development of thermal stress models to assess the thermal comfort and physiological responses when practicing outdoor activities in challenging environments.

Description: Satellite-based precipitation products have been shown to represent precipitation well over Nepal at monthly resolution, compared to ground-based stations. Here, we extend our analysis to the daily and subdaily timescales, which are relevant for mapping the hazards caused by storms as well as drought. We compared the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42RT product with individual stations and with the gridded APHRODITE product to evaluate its ability to retrieve different precipitation intensities. We find that 3B42RT, which is freely available in near real time, has reasonable correspondence with ground-based precipitation products on a daily timescale; rank correlation coefficients approach 0.6, almost as high as the retrospectively calibrated TMPA 3B42 product. We also find that higher-quality ground and satellite precipitation observations improve the correspondence between the two on the daily timescale, suggesting opportunities for improvement in satellite-based monitoring technology. Correlation of 3B42RT and 3B42 with station observations is lower on subdaily timescales, although the mean diurnal cycle of precipitation is roughly correct. We develop a probabilistic precipitation monitoring methodology that uses previous observations (climatology) as well as 3B42RT as input to generate daily precipitation accumulation probability distributions at each 0.25° x 0.25° grid cell in Nepal and surrounding areas. We quantify the information gain associated with using 3B42RT in the probabilistic model instead of relying only on climatology and show that the quantitative precipitation estimates produced by this model are well calibrated compared to APHRODITE.

Description: The increasing rate of heat in the climate in urban areas has become one of the striking problems in many developing countries. This study examined the relationships between the monthly temperature, rainfall and incidence of heat-rash between 2003 and 2012 in order to determine the impact of climate on occurrence of heat-rash in Akure, Ondo state, Nigeria. Data were obtained from Ondo State Specialist Hospital and Ondo State Meteorological Center. A line graph analysis was employed to identify the trend of the temperature, rainfall and incidence of this weather-based disease. Correlation analysis determined the relationship existing between the monthly temperature and the heat-rash. Tables and graphs were generally used for data presentation. The result shows that; the monthly temperature is low between the month of May and October when the minimum and maximum temperature is at 20.6 °C and 34.1 °C respectively; high temperature was recorded during the month of January, February, March and slightly different in April, November and December ranging from 24.6 °C to 35.1 °C.; the monthly temperature descends sharply during the month of March and remains low in April, May, June and July that characterized with high peak of rainfall; heat-rash has significant increase in 2003 (September), 2004 (September), 2007 (December), 2011 (November) and 2012 (October). The study recommends that people in this area and other related environments should engage in sensitizing the public on awareness of temperature—rash relationship and put up a measure of avoiding the heat effect during the periods of high temperature.

Description: The editors of Climate would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2015. [...]

Description: This study investigates the effects of El Niño/Southern Oscillation (ENSO) on temperature and rainfall in Nigeria. The persistent rise in population with more demands for rainfall and water supply in Nigeria requires a better understanding of the impacts of ENSO (La Niña, El Niño) induced changes on the precipitation patterns under future climate conditions. Thus, we compared the sea surface temperature (SST) from the ENSO regions of the Tropical Pacific Ocean (Niño 3 (150°W–90°W, 5°S–5°N) and Niño 4 (160°E–150°W, 5°S–5°N)) with the observed temperature from Nigeria and the temperature is further compared with the associated rainfall. The results show that an increase or decrease in the Niño 3 and Niño 4 SST is accompanied by a corresponding change in the temperature over Nigeria; however, there is better agreement with the Niño 3 SST compared to the Niño 4 SST. The investigation suggests that a slight northward (southward) shift in the mean position of Intertropical Convergence Zone (ITCZ) during a La Niña (El Niño) event is followed by a reduction (increase) in the average temperature within Nigeria while the mean precipitation rises (reduces) over the country. These results could aid weather prediction which might improve the economy as well as save lives and property during climate-related hazards like drought, forest fires and floods.

Description: Recently, considerable focus, e.g., in the fifth IPCC (Intergovernmental Panel on Climate Change) Assessment Report (2014) has been trained on why adaptation and mitigation have not been developed more than at present, with relatively few local government actions taken compared with, for example, more discursive policy agreement on the importance of the issue of climate change. Going beyond a focus on general limits and barriers, this comment suggests that one important issue is that climate change has not yet been sufficiently integrated into the state regulative structure of legislation and policy-making. A comparison between three cases suggests that local developments that are not supported in particular by binding regulation are unlikely to achieve the same general level of implementation as issues for which such regulative demands (and thereby also requirements for prioritization) exist. This constitutes an important consideration for the development of adaptation and mitigation as policy areas, including on the local level.

Description: Climate changes imposed differential impacts on Bangladesh in the form of sea level rise, extreme events, and variability, which has enormous economic, environmental and social cost. Such impacts are assorted across the ecosystems of the Southwest, Northwest and Central region of the country. Among the different sectors, agriculture is comparatively more vulnerable to climate change impacts. In order to reduce the climate change induced loss and damage, a series of adaptation options have been being practiced by the people at the local level for many years, but the effectiveness, profitability, and sustainability of such adaptation options are still not too well investigated or understood. From this backdrop, the study intends to identify, prioritize and evaluate the adaptation options in the agriculture of different ecosystems of Bangladesh. It is found that the economic gain of adopting rice prawn farming, replantation of rice, and saline tolerant and short duration rice varieties are much higher than the other adaption options. Through investing $10 in such adaptation options, $22, $4, $2 and $2 net return will be provided, respectively. Unavailability and less affordability are impeding the promotion of some effective adaption options, which require more attention from policy makers, while further research, demonstration and capacity building of the farmers will reduce vulnerability and build resilience.

Description: Typically, a climate change risk assessment focuses on individual sectors or hazards. However, interdependencies between climate risks manifest themselves via functional, physical, geographical, economic, policy and social mechanisms. These can occur over a range of spatial or temporal scales and with different strengths of coupling. Three case studies are used to demonstrate how interdependencies can significantly alter the nature and magnitude of risk, and, consequently, investment priorities for adaptation. The three examples explore interdependencies that arise from (1) climate loading dependence; (2) mediation of two climate impacts by physical processes operating over large spatial extents; and, (3) multiple risks that are influenced by shared climatic and socio-economic drivers. Drawing upon learning from these case studies, and other work, a framework for the analysis and consideration of interdependencies in climate change risk assessment has been developed. This is an iterative learning loop that involves defining the system, scoping interaction mechanisms, applying appropriate modelling tools, identifying vulnerabilities and opportunities, and assessing the performance of adaptation interventions.

Description: In response to climate change at different spatial scales, adaptation has become one of the focal points of current research and policy developments. In the context of coastal Cambodia, there is little research on local level adaptation to climate change. Using ordinal logistic and logistic regression analyses, this study examines the relationship between perceived self-efficacy and anticipatory and reactive adaptation to climate change among 1823 households in coastal communities in Cambodia. Findings indicate that individuals who reported higher categories of self-efficacy were more likely to report both anticipatory (OR = 1.74, p 〈 0.001) and reactive adaptation (OR = 3.61, p 〈 0.001) measures. Similary, tndividuals who had higher education had higher odds of reporting anticipatory adaptation (OR = 1.71, p 〈 0.001) and reactive adaptation (OR = 1.63, p 〈 0.05) when compared with those without formal education. Participants who have been living in their current residence for six years or more were more likely to report anticipatory adaptation (OR = 1.09, p 〈 0.05) and reactive adapation (OR = 1.22, p 〈 0.001) compared with those who had lived there for a shorter duration of time. Region of residence was positively associated with both anticipatory and reactive adaptation. In this context, it is important to note that individuals in the most agriculture-dependent and climate sensitive province reported the least anticipatory and reactive adaptation measures. Policy makers should target empowerment of the most vulnerable population to facilitate better adaptation behavior, and mainstreaming of knowledge on climate change adaptation through both formal and informal education at the community level.

Description: The Intergovernmental Panel on Climate Change (IPCC), 2014, suggests that an important increase in frequency and magnitude of hazardous processes related to climate change is to be expected at the global scale. Consequently, it is necessary to improve the level of preparedness and the level of public awareness, to fill institutional gaps, and to improve territorial planning in order to reduce the potentially disastrous impact of natural hazards related to climate change. This paper mainly presents a new framework for risk assessment and mapping which enables countries with limited data sources to assess their risk to climate change related hazards at the local level, in order to reduce potential costs, to develop risk reduction strategies, to harmonize their preparedness efforts with neighboring countries and to deal with trans-boundary risk. The methodology is based on the European Commission’s “Risk Assessment and Mapping Guidelines for Disaster Management” (2010) and considers local restrictions, such as a lack of documentation of historic disastrous events, spatial and other relevant data, offering alternative options for risk assessment, and the production of risk maps. The methodology is based on event tree analysis. It was developed within the European project SEERISK and adapted for a number of climate change-related hazards including floods, heat waves, wildfires, and storms. Additionally, the framework offers the possibility for risk assessment under different future scenarios. The implications for climate change adaptation policy are discussed.

Description: In this study, past (1970-2005) as well as future long term (2011-2099) trends in various extreme events of temperature and precipitation have been investigated over selected hydro-meteorological stations in the Sutlej river basin. The ensembles of two Coupled Model Intercomparison Project (CMIP3) models: third generation Canadian Coupled Global Climate Model and Hadley Centre Coupled Model have been used for simulation of future daily time series of temperature (maximum and minimum) and precipitation under A2 emission scenario. Large scale atmospheric variables of both models and National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis data sets have been downscaled using statistical downscaling technique at individual stations. A total number of 25 extreme indices of temperature (14) and precipitation (11) as specified by the Expert Team of the World Meteorological Organization and Climate Variability and Predictability are derived for the past and future periods. Trends in extreme indices are detected over time using the modified Mann-Kendall test method. The stations which have shown either decrease or no change in hot extreme events (i.e., maximum TMax, warm days, warm nights, maximum TMin, tropical nights, summer days and warm spell duration indicators) for 1970–2005 and increase in cold extreme events (cool days, cool nights, frost days and cold spell duration indicators) are predicted to increase and decrease respectively in the future. In addition, an increase in frequency and intensity of extreme precipitation events is also predicted.

Description: The annual cycle of Indian monsoon rainfall plays a critical role in the agricultural as well as the industrial sector. Thus, it is necessary to evaluate the behaviour of the monsoon annual cycle in a warming climate. There are several studies on the variability and uncertainty of the Indian monsoon. This study, examines the impact of climate change on the annual cycle of monsoon rainfall in India from 1871–2100 by applying 20 model simulations designed by the World Climate Research Programme (WCRP) coupled with the model inter-comparison Project 5 (CMIP5). It is found that the models MPI-ESM-LR, INM-CM4 and MRI-CGCM3 best capture the spatial patterns of the monsoon rainfall peak month (MRPM) of the winter monsoon compared to observations, whereas HadGEM2-AO and MIROC-ESM-CHEM best capture the MRPM of the summer monsoon. The MIROC, MIROC-ESM, and MIROC-ESM-CHEM models best capture the average rainfall intensity as well as the MRPM of all-India rainfall. This paper examines the future spatial distribution of the MRPM for meteorological sub-divisions of India, that can have crucial implications for water resources and management. Although the future projections as per the CMIP5 models indicate no changes in the MRPM of the all-India rainfall, a reduction in average intensity can be expected. The projections indicate a shift in the MRPM in some meteorological sub-divisions, particularly with regard to the summer monsoon but no significant change has been projected for the winter monsoon. For example, the summer monsoon MRPM is projected to move from July to August in northern and central India.

Description: Forest-dependent indigenous communities rely on natural resources for their livelihoods, but those are currently under threat due to many factors, including the adverse impact of climate change. The present study looks into climate change-related perception and adaptation strategies of three forest-dependent indigenous communities, namely, Khasia, Tripura and Garo in the Lawachara National Park of Northeastern Bangladesh. Household surveys, focus group discussions, key informant interviews, and observation methods were used to unveil the climatic events, impacts and related adaptations. The events include the change in temperature and rainfall patterns, landslide, soil erosion and flash flood, heavy cold and fog, and natural calamities. Moreover, livelihood problems emanating from these events are the drying up of streams and wells, irregular rainfall, increased dieback and mortality of seedlings, pests, diseases, and the attack of crops by wild animals. Likewise, the reduction of soil moisture content, growing season and crop productivity, landslides, damage of roads and culverts, and increased human diseases are common. This study recognized 29 adaptation strategies and divided them into six management categories, drawing on their local knowledge of the natural resources and other technologies. The study reveals that, although adaptation strategies through land use and land cover changes are not enough to sustain their livelihoods, the tactics help them to reduce the risk of, and increase food security and community resilience against, climate change.

Description: Several studies have concluded that mountainous countries such as Nepal are more vulnerable to climate change; thus, a changing climate should have a significant impact on crop yields. This work aims to explore the impact of climate change on major crop yields in the mountainous parts of Nepal and to determine their relationships based on a regression model between historical climatic data and yield data for food crops. The study starts with an analysis of the last 30 years of climatic data from Lamjung district. Mann-Kendall and Sen’s Slope methods have been used for the trend analysis and quantification. The results showed an increase in temperature of approximately 0.02 °C to 0.07 °C per year in different seasons and a mixed trend in precipitation. Although there was no significant impact of the climate variables on the yields of all crops, the regression analysis revealed negative relationships between maize yield and summer precipitation and between wheat yield and winter minimum temperature, and a positive relationship between millet yield and summer maximum temperature.

Description: Variation in quantities such as precipitation and temperature is often assessed by detecting and characterizing trends in available meteorological data. The objective of this study was to determine the long-term trends in annual precipitation and mean annual air temperature for the state of Kentucky. Non-parametric statistical tests were applied to homogenized and (as needed) pre-whitened annual series of precipitation and mean air temperature during 1950–2010. Significant trends in annual precipitation were detected (both positive, averaging 4.1 mm/year) for only two of the 60 precipitation-homogenous weather stations (Calloway and Carlisle counties in rural western Kentucky). Only three of the 42 temperature-homogenous stations demonstrated trends (all positive, averaging 0.01 °C/year) in mean annual temperature: Calloway County, Allen County in southern-central Kentucky, and urbanized Jefferson County in northern-central Kentucky. In view of the locations of the stations demonstrating positive trends, similar work in adjacent states will be required to better understand the processes responsible for those trends and to properly place them in their larger context, if any.

Description: This study presents the results of an impact analysis of climate change on salinization and the long-term availability of drinking water resources along the river Lek, a tidal branch of the Rhine delta, and a potential mitigation measure. To this end, a one-dimensional modelling approach was used that enabled studying 50 years of variation in discharge and tide in current and future climate. It was found that all locations are increasingly vulnerable to salt intrusion caused by the combination of sea level rise and decreasing river discharges. This affects both the yearly average chloride concentration and long duration exceedances of the threshold value of 150 mg/L. It was also found that diverting a higher fresh water discharge to the Lek of several tens of cubic meters per second reduces the risk of salinization at the upstream inlet locations. However, the increased influence of seawater intrusion on the drinking water inlets cannot be fully compensated for by this measure. The potential gain of the extra water for the drinking water inlets along the Lek has to be balanced against the impact of this measure on water levels and stream flows in other parts of the river system.

Description: The South Atlantic Ocean is currently undergoing significant alterations due to climate change. This region is important to the global carbon cycle, but marine carbon data are scarce in this basin. Additionally, this region is influenced by Agulhas eddies. However, their effects on ocean biogeochemistry are not yet fully understood. Thus, we aimed to model the carbonate parameters in this region and investigate the anthropogenic carbon (Cant) content in 13 eddies shed by the Agulhas retroflection. We used in situ data from the CLIVAR/WOCE/A10 section to elaborate total dissolved inorganic carbon (CT) and total alkalinity (AT) models and reconstruct those parameters using in situ data from two other Brazilian initiatives. Furthermore, we applied the Tracer combining Oxygen, inorganic Carbon, and total Alkalinity (TrOCA) method to calculate the Cant, focusing on the 13 identified Agulhas eddies. The CT and AT models presented root mean square errors less than 1.66 and 2.19 μmol kg−1, indicating Global Ocean Acidification Observing Network climate precision. The Cant content in the Agulhas eddies was 23% higher than that at the same depths of the surrounding waters. We observed that Agulhas eddies can play a role in the faster acidification of the South Atlantic Central Water.

Description: Public perception of climate change is an important element that affects attitudes towards adaptation and mitigation. Understanding the general public’s perception of the issue can assist decision-makers, though the climate change perception is affected by multiple factors. This study examines the main sociodemographic factors, including gender, and the role of previous personal experience with extreme weather events on climate change perception and engagement in individual adaptation and mitigation actions among the general population in the Czech Republic. Based on statistical analysis, gender, age and previous experience with extreme weather events have been found to play a significant role in the climate change beliefs of individuals and in the perception of the cause of the changing climate. The analysis revealed that respondents with previous experience with extreme weather events were significantly more likely to implement adaptation and mitigation actions than respondents with no experience. The survey represents insights into climate change perception and beliefs of the general public at the national level.

Description: Globally, areas of high-quality wildlife habitat of significant environmental value are at risk of permanent damage from climate change. These areas represent social-ecological systems that will require increasing management intervention to maintain their biological and socio-cultural values. Managers of protected areas have begun to recognize the inevitability of ecosystem change and the need to embrace dynamic approaches to intervention. However, significant uncertainty remains about the onset and severity of some impacts, which makes planning difficult. For Indigenous communities, there are intrinsic links between cultural heritage and the conservation of place and biodiversity that need to be better integrated in protected area planning and management. In New South Wales, Australia, management of public conservation reserves and national parks is the responsibility of a State government agency, the National Parks and Wildlife Service (NPWS). This paper describes the outcomes of a participatory planning process with NPWS staff to, firstly, identify the options available, the available ‘tool kit’, to manage biodiversity and cultural heritage in protected areas; secondly, explore how the selection of management actions from the ‘tool kit’ is associated with the level of climate risk to biodiversity or cultural heritage assets; and thirdly, to understand how the form of individual management actions might adapt to changes in climate risk. Combining these three elements into a series of risk-based, adaptive pathways for conservation of biodiversity and cultural heritage is a novel approach that is currently supporting place-based planning for public conservation areas. Incorporation of the trade-offs and synergies in seeking to effectively manage these discrete but related types of values and the implications for conservation practice are discussed.

Description: Species distribution models have many applications in conservation and ecology, and climate data are frequently a key driver of these models. Often, correlative modeling approaches are developed with readily available climate data; however, the impacts of the choice of climate normals is rarely considered. Here, we produced species distribution models for five disparate species using four different modeling algorithms and compared results between two different, but overlapping, climate normals time periods. Although the correlation structure among climate predictors did not change between the time periods, model results were sensitive to both baseline climate period and model method, even with model parameters specifically tuned to a species. Each species and each model type had at least one difference in variable retention or relative ranking with the change in climate time period. Pairwise comparisons of spatial predictions were also different, ranging from a low of 1.6% for climate period differences to a high of 25% for algorithm differences. While uncertainty from model algorithm selection is recognized as an important source of uncertainty, the impact of climate period is not commonly assessed. These uncertainties may affect conservation decisions, especially when projecting to future climates, and should be evaluated during model development.