Climate, Volume 4, Issue 4 (December 2016) – 18 articles

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

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

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

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

Severe convective phenomena cause significant loss in the economy and, primarily, casualties. Therefore, it is essential to forecast such extreme events to avoid or minimize the negative consequences. Wind shear provides an updraft-downdraft separation in the convective cell, which extends the cell lifetime. Wind shears between a few different air layers have been examined in all damaging convective cases in Poland, taken from the European Severe Weather Database between 2011 and 2015, in order to find their values and patterns according to the intensity of this phenomenon. Each severe weather report was assigned wind shear values from the nearest sounding station, and subsequently the presented summary was made. It was found that wind shear values differ between the given phenomena and their intensity. This regularity is particularly visible in shears containing 0 km wind. The highest shears occur within wind reports. Lower values are associated with hail reports. An important difference between weak and F1+ tornadoes was found in most of the wind shears. Severe phenomena probability within 0–6 km and 0–1 km shears show different patterns according to the phenomena and their intensity. This finding has its application in severe weather forecasting. Full article

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth’s surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1–2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called R_value metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the R_value technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the R_value technique. Results indicate an average increasing R_value of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E’s day- and night-time observations. Full article

The effects of temperature and rainfall changes on hydropower generation in Ghana from 1960–2011 were examined to understand country-wide trends of climate variability. Moreover, the discharge and the water level trends for the Akosombo reservoir from 1965–2014 were examined using the Mann-Kendall test statistic to assess localised changes. The annual temperature trend was positive while rainfall showed both negative and positive trends in different parts of the country. However, these trends were not statistically significant in the study regions in 1960 to 2011. Rainfall was not evenly distributed throughout the years, with the highest rainfall recorded between 1960 and 1970 and the lowest rainfalls between 2000 and 2011. The Mann-Kendall test shows an upward trend for the discharge of the Akosombo reservoir and a downward trend for the water level. However, the discharge irregularities of the reservoir do not necessarily affect the energy generated from the Akosombo plant, but rather the regular low flow of water into the reservoir affected power generation. This is the major concern for the operations of the Akosombo hydropower plant for energy generation in Ghana. Full article

Cloud fraction (CF) plays a crucial role in the Earth’s radiative energy budget and thus in the climate. Reliable long-term measurements of CF are rare. The ground-based TROpospheric WAter RAdiometer (TROWARA) at Bern, Switzerland continuously measures integrated liquid water and infrared brightness temperature with a time resolution of 6–11 s since 2004. The view direction of TROWARA is constant (zenith angle 50 ${}^{\circ }$ ), and all radiometer channels see the same volume of the atmosphere. TROWARA is sensitive to liquid water clouds while the microwave signal of ice clouds is negligible. By means of the measurement data we derived CF of thin liquid water clouds (1); thick supercooled liquid water clouds (2); thick warm liquid water clouds (3) and all liquid water clouds (4). The article presents the time series and seasonal climatologies of these four classes of CF. CF of thick supercooled liquid water clouds is larger than 15% from November to March. A significant negative trend of $-0.29\%\pm 0.10$ %/yr is found for CF of thin liquid water clouds. No trends are found for the other classes (2, 3, 4) since their strong natural variability impedes a significant trend. However, CF of warm liquid water clouds increased by about $+0.51\%\pm 0.27$ %/yr from 2004 to 2015. Finally, we performed a Mann-Kendall analysis of seasonal trends which gave several significant trends in the classes 1, 2 and 3. Full article