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Volume 7
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Climate, Volume 7, Issue 1 (January 2019) – 17 articles

Cover Story (view full-size image): The extent and intensity of drought have important impacts on natural and human systems in water-dependent regions. Long-term (1801–2014) annual Palmer Drought Severity Index (PDSI) data indicate that the recent occurrence of dry years in California is not unprecedented. The variability associated with large-scale ocean and atmospheric patterns (like the Pacific Decadal Oscillation and the El Niño Southern Oscillation) is mirrored in the drought persistence cycles observed in the PDSI time series. The 40-year (2015–2054) yearly forecast (ensemble modelling with exponential smoothing) indicates a weak intensification of drought in the near future, followed by a stable period. California might have reached its equilibrium at the end of a long-memory process, which is an exception in Southwestern U.S. View this paper.
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16 pages, 5586 KiB  
Article
Effect of Extreme Climate on Topology of Railway Prestressed Concrete Sleepers
by Dan Li and Sakdirat Kaewunruen
Climate 2019, 7(1), 17; https://doi.org/10.3390/cli7010017 - 20 Jan 2019
Cited by 16 | Viewed by 6100
Abstract
Railway networks are exposed to various environmental conditions. It is thus critical that infrastructure components can tolerate such effects by design. Railway sleepers are a critical safety component in ballasted track systems. Prestressed concrete is currently the most common material for railway sleepers [...] Read more.
Railway networks are exposed to various environmental conditions. It is thus critical that infrastructure components can tolerate such effects by design. Railway sleepers are a critical safety component in ballasted track systems. Prestressed concrete is currently the most common material for railway sleepers due to its superior advantages in structural performance, low maintenance, sustainability, and construction. In practice, many prestressed concrete sleepers are installed in harsh environments that are subject to various changes in climate. Environmental conditions are, therefore, one of the most critical phenomena affecting the time-dependent behaviour of prestressed concrete sleepers. Hence, the impact of climate changes on the serviceability of railway infrastructure needs to be thoroughly investigated. Temperature and relative humidity are crucial aspects that have not been sufficiently studied so far with reference to prestressed concrete sleepers embedded in track systems. This study aims to investigate the effects of extreme climatic conditions on the performance and time-dependent behaviour of prestressed concrete sleepers using contemporary design approaches. The issue concerning the effects of climate uncertainties on creep and shrinkage is rigorously investigated on the basis of both environmental temperature and relative humidity. The outcome indicates that environmental conditions play a vital role in the time-dependent behaviour of prestressed concrete sleepers. The insights will be essential for assessing the long-term serviceability of prestressed concrete sleepers that have been installed in railway lines and are subjected to extreme environmental conditions. Full article
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17 pages, 2711 KiB  
Article
Temporal and Spatial Variability in Surface Air Temperature and Diurnal Temperature Range in Spain over the Period 1950–2011
by Julia Bilbao, Roberto Román and Argimiro De Miguel
Climate 2019, 7(1), 16; https://doi.org/10.3390/cli7010016 - 19 Jan 2019
Cited by 22 | Viewed by 6226
Abstract
Maximum (Tmax), minimum (Tmin), mean (Tmean) air temperature and diurnal temperature range (DTR) trends on a seasonal and annual time scale are evaluated from data recorded at nine Spanish weather stations during the period 1950–2011. Temporal and [...] Read more.
Maximum (Tmax), minimum (Tmin), mean (Tmean) air temperature and diurnal temperature range (DTR) trends on a seasonal and annual time scale are evaluated from data recorded at nine Spanish weather stations during the period 1950–2011. Temporal and spatial variability in temperatures and in the diurnal temperature range (DTR) are presented. The non-parametric Theil-Sen approach and the Mann-Kendall test are used to evaluate anomaly temperature trends and their statistical significance, respectively. An air temperature reduction in Spain between 1950 and 1980 emerges and significant warming is observed between 1980 and 2011. On a seasonal scale, the weakest trends (mostly insignificant at the 5% confidence level) are noted during autumn, while the strongest warming rates were found during summer and spring. The rate of change between 1950 and 2011 in Tmax, Tmin and Tmean was 1.6 °C, 1.1 °C and 1.3 °C, respectively. DTR trends showed a decrease on the Mediterranean coast and a small change in northern, Atlantic and rural areas. The spatial distribution of annual and seasonal trends was plotted as isoline maps and strong trend gradients from the south to the north of the country are observed. DTR values were negatively correlated with relative humidity and precipitation and positively correlated with sunshine hours. Full article
(This article belongs to the Special Issue Climate and Climate Niche Models)
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6 pages, 363 KiB  
Editorial
Introducing Urban Overheating—Progress on Mitigation Science and Engineering Applications
by Michele Zinzi and Matheos Santamouris
Climate 2019, 7(1), 15; https://doi.org/10.3390/cli7010015 - 19 Jan 2019
Cited by 7 | Viewed by 3954
Abstract
Buildings and construction is the most important economic sector in the world after agriculture [...] Full article
(This article belongs to the Special Issue Urban Overheating - Progress on Mitigation Science and Engineering Applications)
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15 pages, 582 KiB  
Article
Cardamom Casualties: Extreme Weather Events and Ethnic Minority Livelihood Vulnerability in the Sino-Vietnamese Borderlands
by Jean-François Rousseau, Sarah Turner and Yiqiang Xu
Climate 2019, 7(1), 14; https://doi.org/10.3390/cli7010014 - 18 Jan 2019
Cited by 9 | Viewed by 4803
Abstract
In the wake of important economic reforms and an ongoing agrarian transition, non-timber forest products, most notably black cardamom, have emerged as significant trade options for ethnic minority farmers in the mountainous Sino-Vietnamese borderlands. Yet, after a series of harsh winters had already [...] Read more.
In the wake of important economic reforms and an ongoing agrarian transition, non-timber forest products, most notably black cardamom, have emerged as significant trade options for ethnic minority farmers in the mountainous Sino-Vietnamese borderlands. Yet, after a series of harsh winters had already crippled cardamom harvests in the 2000s, extreme weather in 2016 decimated the cardamom plantations of hundreds of farming households. Drawing from sustainable livelihoods, livelihood diversification, and vulnerability literatures, we investigate the multiple factors shaping how these harvest failures have affected ethnic minority cultivator livelihoods. Focusing on four case study villages, two in Yunnan, and two in northern Vietnam, we analyse the coping and adaptation strategies Hmong, Yao, Hani, and Yi minority farmers have adopted. We find that farmers’ decisions and strategies have been rooted in a complex ensemble of factors including their degree of market access, other livelihood opportunities available to them, cultural traditions and expectations, and state development strategies. Moreover, we find that in recent years the Chinese and Vietnamese states have stood-by as affected cultivators have struggled to reorganize their livelihoods, suggesting that the impacts of extreme weather events might even serve state projects to further agrarian transitions in these borderlands. Full article
(This article belongs to the Special Issue Social-Ecological Systems, Climate and Global Change Impacts)
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14 pages, 873 KiB  
Article
Can Protection Motivation Theory Explain Farmers’ Adaptation to Climate Change Decision Making in The Gambia?
by Abdoul Rasmane Bagagnan, Issa Ouedraogo, William M. Fonta, Musa Sowe and Anne Wallis
Climate 2019, 7(1), 13; https://doi.org/10.3390/cli7010013 - 14 Jan 2019
Cited by 32 | Viewed by 6770
Abstract
In The Gambia, climate change has affected, and continues to affect, the agriculture sector. Thus, there is a need to develop and understand effective agricultural adaptation policies. The present study used protection motivation theory to describe farmers’ adoption of climate change adaptation measures [...] Read more.
In The Gambia, climate change has affected, and continues to affect, the agriculture sector. Thus, there is a need to develop and understand effective agricultural adaptation policies. The present study used protection motivation theory to describe farmers’ adoption of climate change adaptation measures in the Central River Region of The Gambia. Primary data were collected in eight communities of the region. A transect walk was conducted, followed by a survey of farmers (n = 283). Perception data collected referred back to the past 20 years, with stated implementation addressing current adaptation practices. Results showed that the perception variables, namely, severity, ability to withstand, and internal barriers, were significantly correlated with protection motivation, while protection motivation and stated implementation for water conservation technique were strongly correlated. Structural equation modeling confirmed the mediation role of protection motivation between farmers’ “stated implementation” of adaptation measures and their perception of climate variability. A decrease in soil water storage capacity, degradation of the quality of soil surface structure, and a decrease of the length of the growing season are all factors that motivate farmers to implement an adaptation measure. The cost of the implementation and farmers’ vulnerability are factors that prevent implantation of adaptation measures. This study suggested that farmers’ resilience should be improved and adaptation measures should be subsidized in order to make them more accessible to farmers. Full article
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18 pages, 1547 KiB  
Article
Dust Devils: Structural Features, Dynamics and Climate Impact
by Oleg Onishchenko, Viktor Fedun, Wendell Horton, Oleg Pokhotelov and Gary Verth
Climate 2019, 7(1), 12; https://doi.org/10.3390/cli7010012 - 11 Jan 2019
Cited by 10 | Viewed by 7596
Abstract
According to modern concepts, the main natural sources of dust in the atmosphere are dust storms and associated dust devils—rotating columns of rising dust. The impact of dust and aerosols on climate change in the past, present and future is one of the [...] Read more.
According to modern concepts, the main natural sources of dust in the atmosphere are dust storms and associated dust devils—rotating columns of rising dust. The impact of dust and aerosols on climate change in the past, present and future is one of the poorly understood and, at the same time, one of the fundamental elements needed for weather and climate forecasting. The purpose of this review is to describe and summarise the results of the study of dust devils in the Earth’s atmosphere. Special attention is given to the description of the 3D structures, the external flows and atmospheric gradients of temperature that lead to the generation and maintenance of the dust devils. Full article
(This article belongs to the Special Issue Impact of Atmospheric Chemistry on Local Weather and Local Climate)
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15 pages, 3401 KiB  
Article
Analysis of Climate Change in the Caucasus Region: End of the 20th–Beginning of the 21st Century
by Alla A. Tashilova, Boris A. Ashabokov, Lara A. Kesheva and Nataliya V. Teunova
Climate 2019, 7(1), 11; https://doi.org/10.3390/cli7010011 - 10 Jan 2019
Cited by 18 | Viewed by 7551
Abstract
The study of climate, in such a diverse climatic region as the Caucasus, is necessary in order to evaluate the influence of local factors on the formation of temperature and precipitation regimes in its various climatic zones. This study is based on the [...] Read more.
The study of climate, in such a diverse climatic region as the Caucasus, is necessary in order to evaluate the influence of local factors on the formation of temperature and precipitation regimes in its various climatic zones. This study is based on the instrumental data (temperatures and precipitation) from 20 weather stations, located on the territory of the Caucasian region during 1961–2011. Mathematical statistics, trend analysis, and rescaled range Methods were used. It was found that the warming trend prevailed in all climatic zones, it intensified since the beginning of global warming (since 1976), while the changes in precipitation were not so unidirectional. The maximum warming was observed in the summer (on average by 0.3 °C/10 years) in all climatic zones. Persistence trends were investigated using the Hurst exponent H (range of variation 0–1), which showed a higher trend persistence of annual mean temperature changes (H = 0.8) compared to annual sum precipitations (H = 0.64). Spatial-correlation analysis performed for precipitations and temperatures showed a rapid decrease in the correlation between precipitations at various weather stations from R = 1 to R = 0.5, on a distance scale from 0 to 200 km. In contrast to precipitation, a high correlation (R = 1.0–0.7) was observed between regional weather stations temperatures at a distance scale from 0 to 1000 km, which indicates synchronous temperature changes in all climatic zones (unlike precipitation). Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
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5 pages, 195 KiB  
Editorial
Acknowledgement to Reviewers of Climate in 2018
by Climate Editorial Office
Climate 2019, 7(1), 10; https://doi.org/10.3390/cli7010010 - 8 Jan 2019
Cited by 1 | Viewed by 2731
Abstract
Rigorous peer-review is the corner-stone of high-quality academic publishing [...] Full article
15 pages, 5562 KiB  
Article
Assessing Heat Waves over Greece Using the Excess Heat Factor (EHF)
by Konstantia Tolika
Climate 2019, 7(1), 9; https://doi.org/10.3390/cli7010009 - 7 Jan 2019
Cited by 18 | Viewed by 5298
Abstract
Heat waves are considered one of the most noteworthy extreme events all over the world due to their crucial impacts on both society and the environment. For the present article, a relatively new heat wave index, which was primarily introduced for the study [...] Read more.
Heat waves are considered one of the most noteworthy extreme events all over the world due to their crucial impacts on both society and the environment. For the present article, a relatively new heat wave index, which was primarily introduced for the study of extreme warming conditions over Australia (Excess Heat Factor (EHF, hereafter)), was applied over Greece (eastern Mediterranean) for a 55-year period in order to examine its applicability to a region with different climatic characteristics (compared to Australia) and its ability to define previous exceptional heat waves. The computation of the EHF index for the period 1958–2012 demonstrated that, during the warm period of the year (June, July, August, and September (JJAS)), Greece experiences approximately 20 days per year with positive anomalous conditions (EHF > 0) with positive statistically significant trends for all stations under study. Moreover, an average of 128 spells with a duration of 3 to 10 consecutive days with positive EHF values were found during the examined 55-year period. As the duration of the spell was extended, their frequency lessened. Finally, it was found that the EHF index not only detected, identified, and described efficiently the characteristics of the heat waves, but it also provided additional useful information regarding the impact of these abnormal warming conditions on the human ability to adapt to them. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
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17 pages, 2912 KiB  
Article
Statistical Analysis of Recent and Future Rainfall and Temperature Variability in the Mono River Watershed (Benin, Togo)
by Lawin Agnidé Emmanuel, Nina Rholan Hounguè, Chabi Angelbert Biaou and Djigbo Félicien Badou
Climate 2019, 7(1), 8; https://doi.org/10.3390/cli7010008 - 6 Jan 2019
Cited by 31 | Viewed by 6505
Abstract
This paper assessed the current and mid-century trends in rainfall and temperature over the Mono River watershed. It considered observation data for the period 1981–2010 and projection data from the regional climate model (RCM), REMO, for the period 2018–2050 under emission scenarios RCP4.5 [...] Read more.
This paper assessed the current and mid-century trends in rainfall and temperature over the Mono River watershed. It considered observation data for the period 1981–2010 and projection data from the regional climate model (RCM), REMO, for the period 2018–2050 under emission scenarios RCP4.5 and RCP8.5. Rainfall data were interpolated using ordinary kriging. Mann-Kendall, Pettitt and Standardized Normal Homogeneity (SNH) tests were used for trends and break-points detection. Rainfall interannual variability analysis was based on standardized precipitation index (SPI), whereas anomalies indices were considered for temperature. Results revealed that on an annual scale and all over the watershed, temperature and rainfall showed an increasing trend during the observation period. By 2050, both scenarios projected an increase in temperature compared to the baseline period 1981–2010, whereas annual rainfall will be characterized by high variabilities. Rainfall seasonal cycle is expected to change in the watershed: In the south, the second rainfall peak, which usually occurs in September, will be extended to October with a higher value. In the central and northern parts, rainfall regime is projected to be characterized by late onsets, a peak in September and lower precipitation until June and higher thereafter. The highest increase and decrease in monthly precipitation are expected in the northern part of the watershed. Therefore, identifying relevant adaptation strategies is recommended. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
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23 pages, 1393 KiB  
Article
Determinants of Farmers’ Decisions on Risk Coping Strategies in Rural West Java
by Dadang Jainal Mutaqin
Climate 2019, 7(1), 7; https://doi.org/10.3390/cli7010007 - 5 Jan 2019
Cited by 8 | Viewed by 6272
Abstract
The impact of natural hazards on agriculture in Indonesia is becoming increasingly severe. Therefore, improving farmers’ capacity to undertake risk coping strategies is essential to maintaining their prosperity. The objective of this study was to investigate the determinants of farmers’ decisions on ex [...] Read more.
The impact of natural hazards on agriculture in Indonesia is becoming increasingly severe. Therefore, improving farmers’ capacity to undertake risk coping strategies is essential to maintaining their prosperity. The objective of this study was to investigate the determinants of farmers’ decisions on ex ante and ex post coping strategies in rural West Java, Indonesia. The study was based on a field survey of 180 farmers conducted in the Garut district from July to October 2017. The study used the protection motivation theory framework and applied three econometric models: binomial logit model, zero truncated Poisson regression model, and multinomial logit model. Most farmers (74.4%) adopted ex ante coping strategies. They were characterized as having higher risk aversion per capita expenditure and disaster experience, but lower discount rates and percentage of damage and locations in downstream and midstream areas. Coping appraisal perceptions were found to be important factors in the risk coping analysis. Four determinants of the decision on the number of ex ante coping strategies adopted were: per capita expenditure, land size, disaster experience, and access to financial institutions. The most common ex post coping strategy adopted by farmers was the middle-stress type. Full article
(This article belongs to the Special Issue Social-Ecological Systems, Climate and Global Change Impacts)
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17 pages, 8150 KiB  
Article
Decadal Oscillation in the Predictability of Palmer Drought Severity Index in California
by Nazzareno Diodato, Lelys Bravo De Guenni, Mariangel Garcia and Gianni Bellocchi
Climate 2019, 7(1), 6; https://doi.org/10.3390/cli7010006 - 3 Jan 2019
Cited by 10 | Viewed by 5258
Abstract
Severity of drought in California (U.S.) varies from year-to-year and is highly influenced by precipitation in winter months, causing billion-dollar events in single drought years. Improved understanding of the variability of drought on decadal and longer timescales is essential to support regional water [...] Read more.
Severity of drought in California (U.S.) varies from year-to-year and is highly influenced by precipitation in winter months, causing billion-dollar events in single drought years. Improved understanding of the variability of drought on decadal and longer timescales is essential to support regional water resources planning and management. This paper presents a soft-computing approach to forecast the Palmer Drought Severity Index (PDSI) in California. A time-series of yearly data covering more than two centuries (1801–2014) was used for the design of ensemble projections to understand and quantify the uncertainty associated with interannual-to-interdecadal predictability. With a predictable structure elaborated by exponential smoothing, the projections indicate for the horizon 2015–2054 a weak increase of drought, followed by almost the same pace as in previous decades, presenting remarkable wavelike variations with durations of more than one year. Results were compared with a linear transfer function model approach where Pacific Decadal Oscillation and El Niño Southern Oscillation indices were both used as input time series. The forecasted pattern shows that variations attributed to such internal climate modes may not provide more reliable predictions than the one provided by purely internal variability of drought persistence cycles, as present in the PDSI time series. Full article
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13 pages, 2326 KiB  
Article
Integrating Satellite and Ground Measurements for Predicting Locations of Extreme Urban Heat
by Vivek Shandas, Jackson Voelkel, Joseph Williams and Jeremy Hoffman
Climate 2019, 7(1), 5; https://doi.org/10.3390/cli7010005 - 3 Jan 2019
Cited by 70 | Viewed by 23100
Abstract
The emergence of urban heat as a climate-induced health stressor is receiving increasing attention among researchers, practitioners, and climate educators. However, the measurement of urban heat poses several challenges with current methods leveraging either ground based, in situ observations, or satellite-derived surface temperatures [...] Read more.
The emergence of urban heat as a climate-induced health stressor is receiving increasing attention among researchers, practitioners, and climate educators. However, the measurement of urban heat poses several challenges with current methods leveraging either ground based, in situ observations, or satellite-derived surface temperatures estimated from land use emissivity. While both techniques contain inherent advantages and biases to predicting temperatures, their integration may offer an opportunity to improve the spatial resolution and global application of urban heat measurements. Using a combination of ground-based measurements, machine learning techniques, and spatial analysis, we addressed three research questions: (1) How much do ambient temperatures vary across time and space in a metropolitan region? (2) To what extent can the integration of ground-based measurements and satellite imagery help to predict temperatures? (3) What landscape features consistently amplify and temper heat? We applied our analysis to the cities of Baltimore, Maryland, and Richmond, Virginia, and the District of Columbia using geocomputational machine learning processes on data collected on days when maximum air temperatures were above the 90th percentile of historic averages. Our results suggest that the urban microclimate was highly variable across all of the cities—with differences of up to 10 °C between coolest and warmest locations at the same time—and that these air temperatures were primarily dependent on underlying landscape features. Additionally, we found that integrating satellite data with ground-based measures provided highly accurate and precise descriptions of temperatures in all three study regions. These results suggest that accurately identifying areas of extreme urban heat hazards for any region is possible through integrating ground-based temperature and satellite data. Full article
(This article belongs to the Special Issue Climate Change, Heat Waves, and Human Health)
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11 pages, 1113 KiB  
Article
Spatial and Seasonal Variations and Inter-Relationship in Fitted Model Parameters for Rainfall Totals across Australia at Various Timescales
by Md Masud Hasan, Barry F. W. Croke and Fazlul Karim
Climate 2019, 7(1), 4; https://doi.org/10.3390/cli7010004 - 2 Jan 2019
Cited by 4 | Viewed by 3855
Abstract
Probabilistic models are useful tools in understanding rainfall characteristics, generating synthetic data and predicting future events. This study describes the results from an analysis on comparing the probabilistic nature of daily, monthly and seasonal rainfall totals using data from 1327 rainfall stations across [...] Read more.
Probabilistic models are useful tools in understanding rainfall characteristics, generating synthetic data and predicting future events. This study describes the results from an analysis on comparing the probabilistic nature of daily, monthly and seasonal rainfall totals using data from 1327 rainfall stations across Australia. The main objective of this research is to develop a relationship between parameters obtained from models fitted to daily, monthly and seasonal rainfall totals. The study also examined the possibility of estimating the parameters for daily data using fitted parameters to monthly rainfall. Three distributions within the Exponential Dispersion Model (EDM) family (Normal, Gamma and Poisson-Gamma) were found to be optimal for modelling the daily, monthly and seasonal rainfall total. Within the EDM family, Poisson-Gamma distributions were found optimal in most cases, whereas the normal distribution was rarely optimal except for the stations from the wet region. Results showed large differences between regional and seasonal ϕ-index values (dispersion parameter), indicating the necessity of fitting separate models for each season. However, strong correlations were found between the parameters of combined data and those derived from individual seasons (0.70–0.81). This indicates the possibility of estimating parameters of individual season from the parameters of combined data. Such relationship has also been noticed for the parameters obtained through monthly and daily models. Findings of this research could be useful in understanding the probabilistic features of daily, monthly and seasonal rainfall and generating daily rainfall from monthly data for rainfall stations elsewhere. Full article
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15 pages, 5407 KiB  
Article
Temporal Changes in Precipitation and Temperature and their Implications on the Streamflow of Rosi River, Central Nepal
by Ngamindra Dahal, Uttam Babu Shrestha, Anita Tuitui and Hemant Raj Ojha
Climate 2019, 7(1), 3; https://doi.org/10.3390/cli7010003 - 28 Dec 2018
Cited by 45 | Viewed by 7138
Abstract
Nepal has experienced recent changes in two crucial climatic variables: temperature and precipitation. Therefore, climate-induced water security concerns have now become more pronounced in Nepal as changes in temperature and precipitation have already altered some hydrological processes such as the river runoff in [...] Read more.
Nepal has experienced recent changes in two crucial climatic variables: temperature and precipitation. Therefore, climate-induced water security concerns have now become more pronounced in Nepal as changes in temperature and precipitation have already altered some hydrological processes such as the river runoff in some river systems. However, the linkage between precipitation patterns and streamflow characteristics are poorly understood, especially in small rivers. We analysed the temporal trends of temperature, precipitation, and extreme indices of wet and dry spells in the Rosi watershed in Central Nepal, and observed the temporal patterns of the streamflow of the Rosi river. We also examined the linkages between the average and extreme climate indices and streamflow. We found that the area has warmed up by an average of 0.03 °C/year, and has seen a significant decline in precipitation. The dry spell as represented by the maximum length of the dry spell (CDD) and the magnitude of dryness (AII) has become more pronounced, while the wet spell as represented by the number of heavy rainfall days (R5D) and the precipitation intensity on wet days (SDII) has diminished significantly. Our analysis shows that recent changes in precipitation patterns have affected the streamflow of the Rosi river, as manifested in the observed decline in annual and seasonal streamflows. The decrease in the availability of water in the river is likely to have severe consequences for water security in the area. Full article
(This article belongs to the Special Issue Impact of Climate-Change on Water Resources)
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22 pages, 2091 KiB  
Article
Change in Climate Extremes and Pan Evaporation Influencing Factors over Ouémé Delta in Bénin
by Rita Hounguè, Agnidé Emmanuel Lawin, Sounmaila Moumouni and Akambi Abel Afouda
Climate 2019, 7(1), 2; https://doi.org/10.3390/cli7010002 - 24 Dec 2018
Cited by 13 | Viewed by 4590
Abstract
This work focuses on trend analysis of rainfall, evaporation, temperature, relative humidity, wind speed, and sunshine duration over the Ouémé Delta in Bénin. Eight temperature based indices and fifteen rainfall based indices are computed from 1960 to 2016. Moreover, maximum 1, 2, 3, [...] Read more.
This work focuses on trend analysis of rainfall, evaporation, temperature, relative humidity, wind speed, and sunshine duration over the Ouémé Delta in Bénin. Eight temperature based indices and fifteen rainfall based indices are computed from 1960 to 2016. Moreover, maximum 1, 2, 3, 5, and 10 days precipitation indices were computed at the monthly scale. Trends are detected at 0.05 confidence level, using a combination of Mann-Kendall and prewhitened Mann-Kendall test. Partial correlation and stepwise regression are used to detect the set of meteorological variables that influence pan evaporation in Ouémé Delta. Results showed intensification of heavy rainfall over Ouémé Delta. Moreover, a significant increasing trend is detected in temperature. As consequence, diurnal temperature significantly decreases as proof of the global warming. Average pan evaporation showed a significant slither increasing trend over the area. Change in pan evaporation can be explained by wind speed and sunshine duration that hold almost 50% of pan evaporation variance. As future temperature is going to be increasing, pan evaporation may increase considerably. So, adaptation measures have to be reinforced in the Ouémé Delta area where farmer are used to rainfed agriculture for food security. Moreover, Ouémé Delta plan have to be developed for it resources sustainability. Full article
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28 pages, 8435 KiB  
Article
On the Development and Optimization of an Urban Design Comfort Model (UDCM) on a Passive Solar Basis at Mid-Latitude Sites
by Mohammad Fahmy, Hisham Kamel, Hany Mokhtar, Ibrahim Elwy, Ahmed Gimiee, Yasser Ibrahim and Marwa Abdelalim
Climate 2019, 7(1), 1; https://doi.org/10.3390/cli7010001 - 24 Dec 2018
Cited by 11 | Viewed by 5304
Abstract
Urban climatology is a complex field owed to the intersecting parameters. In city planning, neighborhood fabric and vegetation plays a great role in modifying arid microclimates. This work presents an approach to enable urban designers to find the optimum land use parameters to [...] Read more.
Urban climatology is a complex field owed to the intersecting parameters. In city planning, neighborhood fabric and vegetation plays a great role in modifying arid microclimates. This work presents an approach to enable urban designers to find the optimum land use parameters to achieve pedestrian thermal comfort. In this study, a model was developed based on ENVI-met simulations of two urban and suburban sites in Cairo, Egypt. Initial design parameters were; compactness degree, grass coverage, leaf area density, trees ground coverage, and asphalt and buildings areas. After regression analysis, the step-wise algorithm succeeded in creating the best fit of 94% R2 and 92% adjusted R2. The suggested Urban Design Comfort Model (UDCM) was examined using MATLAB to find the optimum design parameters. Optimum values were applied to generate primitive urban configurations using Grasshopper. The primitives were simulated again in ENVI-met to validate UDCM. The resulted value of Physiological Equivalent Temperature, PET at peak time was reduced from the initial result of ENVI-met (42.3 °C) in both sites to reach (38.7 °C) then (36.8 °C) after refinement with extra foliage. This approach, as a tool for urban designers, not only facilitates and speeds up urban form design process on a passive basis, but also provides deep insights on the development of UDCM considering all different city transects rather than two. Full article
(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)
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