Climate — Open Access Climate Science Journal

Social learning, a key factor in fostering behavioural change and improving decision making, is considered necessary for achieving substantial CO2 emission reductions. However, no empirical evidence exists on how it contributes to mitigation of transport CO2 emissions, or the extent of its influence on decision making. This paper presents evidence addressing these knowledge gaps. Social learning-oriented workshops were conducted to gather the views and preferences of participants from the general public in Bahrain on selected transport CO2 mitigation measures. Social preferences were inputted into a deliberative decision-making model and then compared to a previously prepared participative model. An analysis of the results revealed that social learning could contribute to changes in views, preferences and acceptance regarding mitigation measures, and these changes were statistically significant at an alpha level of 0.1. Thus, while social learning evidently plays an important role in the decision-making process, the impacts of using other participatory techniques should also be explored. Full article

California experienced an extraordinary drought from 2012–2015 (which continues into 2016). This study, from an operational perspective, reviewed the development of this drought in a hydroclimatic framework and examined its characteristics at different temporal and spatial scales. Observed and reconstructed operational hydrologic indices and variables widely used in water resources planning and management at statewide and (hydrologic) regional scales were employed for this purpose. Parsimonious metrics typically applied in drought assessment and management practices including the drought monitor category, percent of average, and rank were utilized to facilitate the analysis. The results indicated that the drought was characterized by record low snowpack (statewide four-year accumulated deficit: 280%-of-average), exceptionally low April-July runoff (220%-of-average deficit), and significantly below average reservoir storage (93%-of-average deficit). During the period from 2012–2015, in general, water year 2015 stood out as the driest single year; 2014–2015 was the driest two-year period; and 2013–2015 tended to be the driest three-year period. Contrary to prior studies stating that the 2012–2015 drought was unprecedented, this study illustrated that based on eight out of 28 variables, the 2012–2015 drought was not without precedent in the record period. Spatially, on average, the South Coast Region, the Central Coast Region, the Tulare Region, and the San Joaquin Region generally had the most severe drought conditions. Overall, these findings are highly meaningful for water managers in terms of making better informed adaptive management plans. Full article

As a mountainous country, Nepal is most susceptible to precipitation extremes and related hazards, including severe floods, landslides and droughts that cause huge losses of life and property, impact the Himalayan environment, and hinder the socioeconomic development of the country. Given that the countrywide assessment of such extremes is still lacking, we present a comprehensive picture of prevailing precipitation extremes observed across Nepal. First, we present the spatial distribution of daily extreme precipitation indices as defined by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) from 210 stations over the period of 1981–2010. Then, we analyze the temporal changes in the computed extremes from 76 stations, featuring long-term continuous records for the period of 1970–2012, by applying a non-parametric Mann−Kendall test to identify the existence of a trend and Sen’s slope method to calculate the true magnitude of this trend. Further, the local trends in precipitation extremes have been tested for their field significance over the distinct physio-geographical regions of Nepal, such as the lowlands, middle mountains and hills and high mountains in the west (WL, WM and WH, respectively), and likewise, in central (CL, CM and CH) and eastern (EL, EM and EH) Nepal. Our results suggest that the spatial patterns of high-intensity precipitation extremes are quite different to that of annual or monsoonal precipitation. Lowlands (Terai and Siwaliks) that feature relatively low precipitation and less wet days (rainy days) are exposed to high-intensity precipitation extremes. Our trend analysis suggests that the pre-monsoonal precipitation is significantly increasing over the lowlands and CH, while monsoonal precipitation is increasing in WM and CH and decreasing in CM, CL and EL. On the other hand, post-monsoonal precipitation is significantly decreasing across all of Nepal while winter precipitation is decreasing only over the WM region. Both high-intensity precipitation extremes and annual precipitation trends feature east−west contrast, suggesting significant increase over the WM and CH region but decrease over the EM and CM regions. Further, a significant positive trend in the number of consecutive dry days but significant negative trend in the number of wet (rainy) days are observed over the whole of Nepal, implying the prolongation of the dry spell across the country. Overall, the intensification of different precipitation indices over distinct parts of the country indicates region-specific risks of floods, landslides and droughts. The presented findings, in combination with population and environmental pressures, can support in devising the adequate region-specific adaptation strategies for different sectors and in improving the livelihood of the rural communities in Nepal. Full article

Error characterization is vital for the advancement of precipitation algorithms, the evaluation of numerical model outputs, and their integration in various hydro-meteorological applications. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) has been a benchmark for successive Global Precipitation Measurement (GPM) based products. This has given way to the evolution of many multi-satellite precipitation products. This study evaluates the performance of the newly released multi-satellite Multi-Source Weighted-Ensemble Precipitation (MSWEP) product, whose temporal variability was determined based on several data products including TMPA 3B42 RT. The evaluation was conducted over India with respect to the IMD-gauge-based rainfall for pre-monsoon, monsoon, and post monsoon seasons at daily scale for a 35-year (1979–2013) period. The rainfall climatology is examined over India and over four geographical extents within India known to be subject to uniform rainfall. The performance evaluation of rainfall time series was carried out. In addition to this, the performance of the product over different rainfall classes was evaluated along with the contribution of each class to the total rainfall. Further, seasonal evaluation of the MSWEP products was based on the categorical and volumetric indices from the contingency table. Upon evaluation it was observed that the MSWEP products show large errors in detecting the higher quantiles of rainfall (>75th and > 95th quantiles). The MSWEP precipitation product available at a 0.25° × 0.25° spatial resolution and daily temporal resolution matched well with the daily IMD rainfall over India. Overall results suggest that a suitable region and season-dependent bias correction is essential before its integration in hydrological applications. While the MSWEP was observed to perform well for daily rainfall, it suffered from poor detection capabilities for higher quantiles, making it unsuitable for the study of extremes. Full article

In arid and semi-arid areas, rainfall is often characterized by a strong spatial and temporal variability. These environmental factors, combined with the sparsity of the measurement networks in developing countries, constitute real constraints for water resources management. In recent years, several spatial rainfall measurement sources have become available, such as TRMM data (Tropical Rainfall Measurement Mission). In this study, the TRMM 3B42 Version 7 product was evaluated using rain gauges measurements from 19 stations in the Oum-Er-Bia (OER) basin located in the center of Morocco. The relevance of the TRMM product was tested by direct comparison with observations at different time scales (daily, monthly, and annual) between 1998 and 2010. Results show that the satellite product provides poor estimations of rainfall at the daily time scale giving an average Pearson correlation coefficient (r) of 0.2 and average Root Mean Square Error (RMSE) of 10 mm. However, the accuracy of TRMM rainfall is improved when temporally averaged to monthly time scale (r of 0.8 and RMSE of 28 mm) or annual time scale (r of 0.71 and RMSE of 157 mm). Moreover, improved correlation with observed data was obtained for data spatially averaged at the watershed scale. Therefore, at the monthly and annual time scales, TRMM data can be a useful source of rainfall data for water resources monitoring and management in ungauged basins in semi-arid regions. Full article

It is already documented that climate change will lead to an intensification of the global water cycle with a consequent increase in flood hazards. Bangladesh is also facing an increasing trend of flood disasters. Among the various risks and disasters in Bangladesh, flood is the most common and frequent. Floods make people vulnerable, as they take away their livelihoods at the first instance and leave them with little resources to overcome from the situation. Because of floods, rural poor communities face job loss, and two-thirds of their income is reduced, which limits their capabilities of preparedness, response, and recovery to subsequent floods. People cope with the situation by bearing substantial debts and a loss of productive assets. With an empirical field study in one of the most flood-prone upazilas (sub-districts) of Bangladesh, namely Goalanda Upazilla of the Rajbari district, this study intends to draw a “flood impact tree” of the study area. It also examines the impacts of flood on the livelihood of the rural poor and explores their coping strategies. This paper aims to facilitate an understanding of the impact of floods on their livelihood, especially on the income and occupations of the rural poor. At the same time, it aims to learn from their coping mechanisms. Full article

Warming of the climate system is unequivocal, and many of the observed changes are unprecedented over the past five decades. Globally, the atmosphere and the ocean are becoming increasingly warmer, the amount of ice on the earth is decreasing over the oceans, and the sea level has risen. According to the Intergovernmental Panel on Climate Change, the average increase in global temperature (combined land and surface) between the 1850–1900 period and the 2003–2012 period was 0.78 °C (0.72 to 0.85). But should we prepare for such a relatively small change? The importance is not the means of the warming but the considerable likelihood of climate change that could trigger extreme natural hazards. The impact and the risk of climate change associated with railway infrastructure have not been fully addressed in the literature due to the differences in local environmental parameters. On the other hand, the current railway network in Malaysia, over the last decade, has been significantly affected by severe weather conditions such as rainfall, lightning, wind and very high temperatures. Our research findings based on a critical literature review and expert interviews point out the extremes that can lead to asset system failure, degraded operation and ultimately, delays in train services. During flooding, the embankment of the track can be swept away and bridge can be demolished, while during drought, the embankment of the track can suffer from soil desiccation and embankment deterioration; high temperature increases the risk of track buckling and high winds can result in vegetation or foreign object incursion onto the infrastructure as well as exert an additional quasi-static burden. This review is of significant importance for planning and design of the newly proposed high speed rail link between Malaysia and Singapore. Full article

This study identifies the impact of climate change and adaptation practices on agriculture in the Rautahat district of central Nepal by analyzing the atmospheric temperature, rainfall pattern, soil moisture, and direct field survey. The impact and status of crop production systems are emphasized. Primary data on crop production system were collected through household surveys and adaptation practices in crop production were collected through focus group discussions, key informants’ interviews, and direct observations. Time series data on key climatic variables and productivity of major crops were collected from the government sources. Mann–Kendall trend analysis and Sen’s Slope methods were used for the analysis and quantification of temperature and rainfall trends. Spearman’s rank correlation analysis was performed to find the relation of seasonal rainfall with the crop yields. The study showed that the annual average rainfall was decreasing at the rate of 10.21 mm/year and the annual mean temperature had increased at a rate of 0.02 °C/year over the last 30 years, but their variations were found to be statistically insignificant. Seasonal rainfall also increased, except for the post-monsoon rain. Estimation of Soil Moisture Index through remote sensing technique indicates that it has been reduced considerably over the past 15 years at the beginning of the monsoon. It was observed that farmers have been using different adaptation measures like the use of high-yielding varieties of crops, enhanced irrigation system, switching to hybrid seed, and increased access to pesticides. As a result, the yields of major crops including rice, maize, wheat, sugarcane, potatoes, and pulses all showed increasing trends during 1999 to 2014. However, the total costs of production of all crops have increased many fold as a consequence of the cost associated with the arrangements for such adaptation measures and shifts towards market-based commodities. Full article

Background: This study investigates the connection between annual global solar radiation and ground albedo solar radiation due to desertification in line with previous research on the correlation between climatic changes and desertification. Methods: A simulation study was performed using an algorithm formulated by the authors and the typical albedo coefficient values of forested ground, green grass and desert sand. Results: It is shown that changing the albedo coefficients from values corresponding to forested ground or green grass to values corresponding to the desert sand causes a significant increase in the annual global solar radiation acquired at different latitudes, leading one to hypothesize a mechanism of reduction of convective overturning and precipitation decreases due to desertification. Conclusion: In this scenario, modifications of local and global climate can be connected to changes of ground solar albedo induced by desertification. Full article

While agricultural practices are widely reported to contribute to anthropogenic greenhouse gas (GHG) emissions, there are only limited measurements available for emission rates in the monsoon climate of the African continent. We conducted a scoping study to measure nitrous oxide (N₂O-N) and methane (CH₄) emission rates from 24 plots constructed on smallholder agricultural farms along the slope catena of three transects in the sub-humid Anjeni watershed in the Ethiopian highlands. Greenhouse gas flux samples were collected in 2013, before, towards the end, and after the rainy monsoon phase. At each location, three plots were installed in groups: two plots grown with barley (one enriched with charcoal and the other without soil amendment) and lupine was grown on the third plot without any soil amendment. Preliminary study results showed that nitrous oxide emission rates varied from −275 to 522 μg·m⁻²·h⁻¹ and methane emissions ranged from −206 to 264 μg·m⁻²·h⁻¹ with overall means of 51 and 5 μg·m⁻²·h⁻¹ for N₂O-N and CH₄, respectively. Compared with the control, charcoal and lupine plots had elevated nitrous oxide emissions. Plots amended with charcoal showed on average greater methane uptake than was emitted. While this study provides insights regarding nitrous oxide and methane emission levels from smallholder farms, studies of longer durations are needed to verify the results. Full article

In recent years, SUHIs (surface urban heat islands) have been greatly emphasized in urban climate studies, since it is one of the climate phenomena most influenced by human action. In this study, temporal and spatial variations of SUHIs in the cities of Ceres and Rialma (Brazil) were investigated; satellite Landsat 8 TIRS/OLI images from 2013 to 2016 were used for this purpose. The results showed that in all seasons, two relationships were observed, one positive and one negative. An $NDVI$ (Normalized Difference Vegetation Index) of 0.2 is the divider of this relationship: up to this value, the relationship is positive, that is, the higher the $NDVI$ value, the higher the surface temperature, while the relationship is negative at an $NDVI$ greater than 0.2. There was high seasonal variation in the SUHIs, with the highest intensities recorded in the spring and summer (±12 °C), and the lowest in the winter. These temporal variations were attributed to the annual cycle of precipitation, which directly involves the robustness of the Cerrado vegetation. SUHIs occupied, on average, an area three times larger than the area of SUCIs (surface urban cool islands). The highest values of SUCIs were observed in water bodies and in valley bottoms. Overall, SUHIs showed high intensities; however, a more intense core area, such as in large cities, was not observed. Full article

This paper aims at enhancing the previously formulated culture-theoretical explanation of risk-related perception and action with ecological and institutional connectedness. This is needed for global comparison of adaptation cultures as well as transferability of local knowledge. Differences in climate-related patterns of knowledge will therefore be explained by common patterns of socially shared knowledge in relation to ecological and institutional transformation. This will be done by combining a cultural-knowledge approach with different social-ecological and institutional contexts. Changes in knowledge development as well as in adaptation practices will be described by state-and-transition. The proposed approach combines the culture-theoretical explanation of Values-Beliefs-Identities (VBI) and socio-ecological as well as institutional approach of the state-and-transition model. Full article

Precipitation and temperature variability present significant agricultural risks worldwide. Northern Iran’s agriculture mainly depends on paddy fields, which are directly affected by precipitation and temperature variability. The main aim of this study is to explore farmers’ attitudes towards precipitation and temperature variability and their adaptation strategies in paddy fields in a typical agricultural province in northern Iran. Primary survey data were collected from a sample of 382 paddy farmers of Rasht County in Guilan Province. Data have been analyzed using both summary statistics and bivariate analysis (Pearson, Spearman, and Eta correlation coefficients). Empirical findings reveal that most paddy farmers had experienced precipitation and temperature variability and were taking measures to reduce its negative impacts on their crops. Results also indicate that farm size and household income influence farmers’ perception to precipitation and temperature variability, while availability of water resources also influence farmers’ adaptation decisions. Full article

The goal of this work is to assess climate change and its impact on the predictability of seasonal (i.e., April–July) streamflow in major water supply watersheds in the Sierra Nevada. The specific objective is threefold: (1) to examine the hydroclimatic impact of climate change on precipitation and temperature at the watershed scale, as well as the variability and trends in the predictand (i.e., April–July streamflow runoff) and its operational predictors (including 1 April snow water equivalent, October–March precipitation and runoff, and April–June precipitation) in a changing climate; (2) to detect potential changes in the predictability of April–July streamflow runoff in response to climate change; and (3) to assess the relationship between April–July streamflow runoff and potential new predictors and the corresponding trend. Historical records (water year 1930–2015) of annual peak snow water equivalent, monthly full natural flow, monthly temperature and precipitation data from 12 major watersheds in the west side of the Sierra Nevada in California (which are of great water supply interest) are analyzed. The Mann-Kendall Trend-Free Pre-Whitening procedure is applied in trend analysis. The results indicate that no significant changes in both the predictand and predictors are detected. However, their variabilities tend to be increasing in general. Additionally, the predictability of the April–July runoff contributed from each predictor is generally increasing. The study further shows that standardized precipitation, runoff, and snow indices have higher predictability than their raw data counterparts. These findings are meaningful from both theoretical and practical perspectives, in terms of guiding the development of new forecasting models and enhancing the current operational forecasting model, respectively, for improved seasonal streamflow forecasting. Full article

Weather extremes and climate variability directly impact the hydrological cycle influencing agricultural productivity. The issues related to climate change are of prime concern for every nation as its implications are posing negative impacts on society. In this study, we used three climate change scenarios to simulate the impact on local hydrology of a small agricultural watershed. The three emission scenarios from the Special Report on Emission Scenarios, of the Intergovernmental Panel on Climate Change (IPCC) 2007 analyzed in this study were A2 (high emission), A1B (medium emission), and B1 (low emission). A process based hydrologic model SWAT (Soil and Water Assessment Tool) was calibrated and validated for the Skunk Creek Watershed located in eastern South Dakota. The model performance coefficients revealed a strong correlation between simulated and observed stream flow at both monthly and daily time step. The Nash Sutcliffe Efficiency for monthly model performace was 0.87 for the calibration period and 0.76 for validation period. The future climate scenarios were built for the mid-21st century time period ranging from 2046 to 2065. The future climate data analysis showed an increase in temperatures between 2.2 °C to 3.3 °C and a decrease in precipitation from 1.8% to 4.5% expected under three different climate change scenarios. A sharp decline in stream flow (95.92%–96.32%), run-off (83.46%–87.00%), total water yield (90.67%–91.60%), soil water storage (89.99%–92.47%), and seasonal snow melt (37.64%–43.06%) are predicted to occur by the mid-21st century. In addition, an increase in evapotranspirative losses (2%–3%) is expected to occur within the watershed when compared with the baseline period. Overall, these results indicate that the watershed is highly susceptible to hydrological and agricultural drought due to limited water availability. These results are limited to the available climate projections, and future refinement in projected climatic change data, at a finer regional scale would provide greater clarity. Nevertheless, models like SWAT are excellent means to test best management practices to mitigate the projected dry conditions in small agricultural waterhseds. Full article

Anthropogenic activities continue to emit potential greenhouse gases (GHG) into the atmosphere leading to a warmer climate over the earth. Predicting the impacts of climate change (CC) on food and fiber production systems in the future is essential for devising adaptations to sustain production and environmental quality. We used the CSM-CROPGRO-cotton v4.6 module within the RZWQM2 model for predicting the possible impacts of CC on cotton (Gossypium hirsutum) production systems in the lower Mississippi Delta (MS Delta) region of the USA. The CC scenarios were based on an ensemble of climate projections of multiple GCMs (Global Climate Models/General Circulation Models) for climate change under the CMIP5 (Climate Model Inter-comparison and Improvement Program 5) program, that were bias-corrected and spatially downscaled (BCSD) at Stoneville location in the MS Delta for the years 2050 and 2080. Four Representative Concentration Pathways (RCP) drove these CC projections: 2.6, 4.5, 6.0, and 8.5 (these numbers refer to radiative forcing levels in the atmosphere of 2.6, 4.5, 6.0, and 8.5 W·m⁻²), representing the increasing levels of the greenhouse gas (GHG) emission scenarios for the future, as used in the Intergovernmental Panel on Climate Change-Fifth Assessment Report (IPCC-AR5). The cotton model within RZWQM2, calibrated and validated for simulating cotton production at Stoneville, was used for simulating production under these CC scenarios. Under irrigated conditions, cotton yields increased significantly under the CC scenarios driven by the low to moderate emission levels of RCP 2.6, 4.5, and 6.0 in years 2050 and 2080, but under the highest emission scenario of RCP 8.5, the cotton yield increased in 2050 but declined significantly in year 2080. Under rainfed conditions, the yield declined in both 2050 and 2080 under all four RCP scenarios; however, the yield still increased when enough rainfall was received to meet the water requirements of the crop (in about 25% of the cases). As an adaptation measure, planting cotton six weeks earlier than the normal (historical average) planting date, in general, was found to boost irrigated cotton yields and compensate for the lost yields in all the CC scenarios. This early planting strategy only partially compensated for the rainfed cotton yield losses under all the CC scenarios, however, supplemental irrigations up to 10 cm compensated for all the yield losses. Full article

This paper assessed the effect of projected climate change on the grain yield of barley in fourteen administrative regions in the United Kingdom (UK). Climate data for the 2030s, 2040s and 2050s for the high emission scenario (HES), medium emissions scenario (MES) and low emissions scenario (LES) were obtained from the UK Climate Projections 2009 (UKCP09) using the Weather Generator. Simulations were performed using the AquaCrop model and statistics of simulated future yields and baseline yields were compared. The results show that climate change could be beneficial to UK barley production. For all emissions scenarios and regions, differences between the simulated average future yields (2030s–2050s) and the observed yields in the baseline period (1961–1990) ranged from 1.4 to 4 tons·ha⁻¹. The largest increase in yields and yield variability occurred under the HES in the 2050s. Absolute increases in yields over baseline yields were substantially greater in the western half of the UK than in the eastern regions but marginally from south to north. These increases notwithstanding, yield reductions were observed for some individual years due to saturated soil conditions (most common in Wales, Northern Ireland and South-West Scotland). These suggest risks of yield penalties in any growing season in the future, a situation that should be considered for planning adaptation and risk management. Full article

The impacts of climate change on photovoltaic (PV) output in the fifteen countries of the Economic Community of West African States (ECOWAS) was analyzed in this paper. Using a set of eight climate models, the trends of solar radiation and temperature between 2006–2100 were examined. Assuming a lifetime of 40 years, the future changes of photovoltaic energy output for the tilted plane receptor compared to 2006–2015 were computed for the whole region. The results show that the trends of solar irradiation are negative except for the Irish Centre for High-End Computing model which predicts a positive trend with a maximum value of 0.17 W/m²/year for Cape Verde and the minimum of −0.06 W/m²/year for Liberia. The minimum of the negative trend is −0.18 W/m²/year predicted by the Model for Interdisciplinary Research on Climate (MIROC), developed at the University of Tokyo Center for Climate System Research for Cape Verde. Furthermore, temperature trends are positive with a maximum of 0.08 K/year predicted by MIROC for Niger and minimum of 0.03 K/year predicted by Nature Conservancy of Canada (NCC), Max Planck Institute (MPI) for Climate Meteorology at Hamburg, French National Meteorological Research Center (CNRM) and Canadian Centre for Climate Modelling and Analysis (CCCMA) for Cape Verde. Photovolataic energy output changes show increasing trends in Sierra Leone with 0.013%/year as the maximum. Climate change will lead to a decreasing trend of PV output in the rest of the countries with a minimum of 0.032%/year in Niger. Full article

This study aims to set up a comprehensive approach to the Vulnerability and Impact Assessment (VIA) of river erosion and to suggest Ecosystem-based Adaptation (EbA) practices. Based on the analysis of vulnerability using the Driver-Pressure-State-Impact-Response (DPSIR) framework, this paper discusses some of the significant climatic (rainfall pattern, temperature, seasonal drift, cold wave and heat wave) and non-climatic (river erosion, repetitive death of field crops and agrochemicals) forces in the Kazipur Upazila (Sirajganj District)—a river erosion-prone area of Bangladesh. Both primary (Key Informants Interview, Household Survey, and Focus Group Discussion) and secondary (climatic, literature review) data have been used in revealing the scenario of climatic stress. The analysis revealed a slightly increasing trend of mean annual temperature, and a decreasing trend of total annual rainfall from 1981 to 2015, which have been supported by people’s perception. This study found that river erosion, the increase of temperature and the late arrival of monsoon rain, excessive monsoon rainfall, high use of agrochemicals, and flow alterations are major drivers in the riverine ecosystem. These drivers are creating pressures on agricultural land, soil fertility, water availability and livelihood patterns of affected communities. Hence, floating bed cultivation, integrated pest management, use of cover crops, reforestation, the introduction of an agro-weather forecasting system, and a new variety of flood tolerant species have been suggested as potential EbA to cope with river bank erosion and to increase the capacity of the affected ecosystem. Full article