Open AccessArticle
Understanding Farmers’ Perceptions and Adaptations to Precipitation and Temperature Variability: Evidence from Northern Iran
Climate 2016, 4(4), 58; doi:10.3390/cli4040058 -
Abstract
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
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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
Open AccessArticle
Predictability of Seasonal Streamflow in a Changing Climate in the Sierra Nevada
Climate 2016, 4(4), 57; doi:10.3390/cli4040057 -
Abstract
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
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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
Open AccessArticle
Climate Change Impacts on the Hydrological Processes of a Small Agricultural Watershed
Climate 2016, 4(4), 56; doi:10.3390/cli4040056 -
Abstract
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
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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
Open AccessArticle
Vulnerabilities and Adapting Irrigated and Rainfed Cotton to Climate Change in the Lower Mississippi Delta Region
Climate 2016, 4(4), 55; doi:10.3390/cli4040055 -
Abstract
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
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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
Open AccessArticle
Simulated Regional Yields of Spring Barley in the United Kingdom under Projected Climate Change
Climate 2016, 4(4), 54; doi:10.3390/cli4040054 -
Abstract
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
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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
Open AccessArticle
Forecasted Changes in West Africa Photovoltaic Energy Output by 2045
Climate 2016, 4(4), 53; doi:10.3390/cli4040053 -
Abstract
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
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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
Open AccessArticle
Analysis of VIA and EbA in a River Bank Erosion Prone Area of Bangladesh Applying DPSIR Framework
Climate 2016, 4(4), 52; doi:10.3390/cli4040052 -
Abstract
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
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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
Open AccessCommunication
Wind Shear and the Strength of Severe Convective Phenomena—Preliminary Results from Poland in 2011–2015
Climate 2016, 4(4), 51; doi:10.3390/cli4040051 -
Abstract
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.
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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
Open AccessArticle
A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input
Climate 2016, 4(4), 50; doi:10.3390/cli4040050 -
Abstract
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
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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 Rvalue 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 Rvalue 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 Rvalue technique. Results indicate an average increasing Rvalue 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
Open AccessArticle
Multiyear Rainfall and Temperature Trends in the Volta River Basin and their Potential Impact on Hydropower Generation in Ghana
Climate 2016, 4(4), 49; doi:10.3390/cli4040049 -
Abstract
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
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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
Open AccessArticle
Cloud Fraction of Liquid Water Clouds above Switzerland over the Last 12 Years
Climate 2016, 4(4), 48; doi:10.3390/cli4040048 -
Abstract
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
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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), 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%±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%±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
Open AccessReview
The Vulnerability of Rice Value Chains in Sub-Saharan Africa: A Review
Climate 2016, 4(3), 47; doi:10.3390/cli4030047 -
Abstract
Rice is one of the most important food crops in sub-Saharan Africa. Climate change, variability, and economic globalization threatens to disrupt rice value chains across the subcontinent, undermining their important role in economic development, food security, and poverty reduction. This paper maps existing
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Rice is one of the most important food crops in sub-Saharan Africa. Climate change, variability, and economic globalization threatens to disrupt rice value chains across the subcontinent, undermining their important role in economic development, food security, and poverty reduction. This paper maps existing research on the vulnerability of rice value chains, synthesizes the evidence and the risks posed by climate change and economic globalization, and discusses agriculture and rural development policies and their relevance for the vulnerability of rice value chains in sub-Saharan Africa. Important avenues for future research are identified. These include the impacts of multiple, simultaneous pressures on rice value chains, the effects of climate change and variability on parts of the value chain other than production, and the forms and extent to which different development policies hinder or enhance the resilience of rice value chains in the face of climatic and other pressures. Full article
Open AccessArticle
A 133-Year Record of Climate Change and Variability from Sheffield, England
Climate 2016, 4(3), 46; doi:10.3390/cli4030046 -
Abstract
A 133-year length (1883–2015) daily climate record from Sheffield, England (53.38°N, 1.49°W) is analysed. Across the entire length of the record, there are significant warming trends annually and for all seasons, whereas precipitation shows a significant annual increase but the seasonal trends, whilst
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A 133-year length (1883–2015) daily climate record from Sheffield, England (53.38°N, 1.49°W) is analysed. Across the entire length of the record, there are significant warming trends annually and for all seasons, whereas precipitation shows a significant annual increase but the seasonal trends, whilst all positive, are not significant. Trends in extreme indices mirror the mean long-term warming and wetting signal. Record hot and cold daily temperatures and precipitation amounts are associated with summer anticyclonic conditions, an anomalous easterly winter jet stream and summer cyclonic activity, respectively. Whilst there are large uncertainties surrounding the calculation of return periods for the daily maximum, minimum and precipitation records from a single record, our best estimates suggest that in the current climate (2015), the existing records have return periods of 38, 529 and 252 years, respectively. The influence of several climate indices on mean and extreme indices are considered on seasonal scales, with the North Atlantic Oscillation displaying the strongest relationship. Future mean maximum temperature and precipitation alongside extreme indices representing the warmest and wettest day of the year are analysed from two downscaled climate model output archives under analysis periods of a 1.5 and 2 degree warmer world and the 2080–2099 end of 21st century period. For this mid-latitude location, there is minimal difference in model projections between a 1.5 and 2 degree world, but a significant difference between the 1.5/2 degree world and the end of century 2080–2099 period under the most severe climate warming scenarios. Full article
Open AccessArticle
Trend and Homogeneity Analysis of Precipitation in Iran
Climate 2016, 4(3), 44; doi:10.3390/cli4030044 -
Abstract
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
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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. Full article
Open AccessArticle
Life Cycle Characteristics of Warm-Season Severe Thunderstorms in Central United States from 2010 to 2014
Climate 2016, 4(3), 45; doi:10.3390/cli4030045 -
Abstract
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
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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. Full article
Open AccessArticle
Polar Cyclone Identification from 4D Climate Data in a Knowledge-Driven Visualization System
Climate 2016, 4(3), 43; doi:10.3390/cli4030043 -
Abstract
Arctic cyclone activity has a significant association with Arctic warming and Arctic ice decline. Cyclones in the North Pole are more complex and less developed than those in tropical regions. Identifying polar cyclones proves to be a task of greater complexity. To tackle
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Arctic cyclone activity has a significant association with Arctic warming and Arctic ice decline. Cyclones in the North Pole are more complex and less developed than those in tropical regions. Identifying polar cyclones proves to be a task of greater complexity. To tackle this challenge, a new method which utilizes pressure level data and velocity field is proposed to improve the identification accuracy. In addition, the dynamic, simulative cyclone visualized with a 4D (four-dimensional) wind field further validated the identification result. A knowledge-driven system is eventually constructed for visualizing and analyzing an atmospheric phenomenon (cyclone) in the North Pole. The cyclone is simulated with WebGL on in a web environment using particle tracing. To achieve interactive frame rates, the graphics processing unit (GPU) is used to accelerate the process of particle advection. It is concluded with the experimental results that: (1) the cyclone identification accuracy of the proposed method is 95.6% when compared with the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data; (2) the integrated knowledge-driven visualization system allows for streaming and rendering of millions of particles with an interactive frame rate to support knowledge discovery in the complex climate system of the Arctic region. Full article
Open AccessArticle
Diurnal and Seasonal Variation of Surface Urban Cool and Heat Islands in the Semi-Arid City of Erbil, Iraq
Climate 2016, 4(3), 42; doi:10.3390/cli4030042 -
Abstract
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
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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. Full article
Open AccessArticle
Future Water Availability from Hindukush-Karakoram-Himalaya upper Indus Basin under Conflicting Climate Change Scenarios
Climate 2016, 4(3), 40; doi:10.3390/cli4030040 -
Abstract
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
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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. Full article
Open AccessArticle
Statistical-Synoptic Analysis of the Atmosphere Thickness Pattern of Iran’s Pervasive Frosts
Climate 2016, 4(3), 41; doi:10.3390/cli4030041 -
Abstract
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,
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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. Full article
Open AccessReview
Hydrological Climate Change Impact Assessment at Small and Large Scales: Key Messages from Recent Progress in Sweden
Climate 2016, 4(3), 39; doi:10.3390/cli4030039 -
Abstract
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
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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. Full article