Open AccessArticle
Influence of Decadal Climate Variability on Growing Degree Day, Precipitation, and Drought in Crop-Growing Seasons
Climate 2018, 6(2), 43; https://doi.org/10.3390/cli6020043 -
Abstract
Knowledge on the impact of climate variability on the decadal timescale is important for policy makers and planners in order for them to make decisions in a range of sectors, including agriculture, water resources, energy, and infrastructure. This study estimates the effects of
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Knowledge on the impact of climate variability on the decadal timescale is important for policy makers and planners in order for them to make decisions in a range of sectors, including agriculture, water resources, energy, and infrastructure. This study estimates the effects of the ocean-related decadal climate variability (DCV) on growing degree day, precipitation, and drought in the crop-growing seasons of major crops in the United States. The empirical results illustrate that DCV phase combinations are associated with variations in growing degree day, precipitation, and drought across the country using county-level data from 1950 to 2015. There are spatially-differentiated effects on the climate of major production areas of corn, soybeans, and wheat. The annual oscillations in growing degree day, precipitation, and drought reach extreme severity in some DCV scenarios. The results would facilitate the adoption of coping mechanisms with the potential to develop climate risk resiliency for agricultural planning and policy. Full article
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Open AccessArticle
Feasibility of Predicting Vietnam’s Autumn Rainfall Regime Based on the Tree-Ring Record and Decadal Variability
Climate 2018, 6(2), 42; https://doi.org/10.3390/cli6020042 -
Abstract
We investigate the feasibility of developing decadal prediction models for autumn rainfall ( RA ) over Central Vietnam by utilizing a published tree-ring reconstruction of October–November (ON) rainfall derived from the earlywood width measurements from a type of Douglas-fir (Pseudotsuga sinensis
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We investigate the feasibility of developing decadal prediction models for autumn rainfall ( RA ) over Central Vietnam by utilizing a published tree-ring reconstruction of October–November (ON) rainfall derived from the earlywood width measurements from a type of Douglas-fir (Pseudotsuga sinensis). Autumn rainfall for this region accounts for a large percentage of the annual total, and is often the source of extreme flooding. Central Vietnam’s RA is characterized by a pronounced decadal oscillation signal. We use the decadal mode of RA along with its notable autocorrelation and significant cross-correlation with basin-wide Pacific sea surface temperature (SST) variability, to develop four discrete time-series models. The sparse autoregressive model, with Pacific SST as an external variable, accounts for most of the autoregressive RA , while taking advantage of the predictability from the basin-wide Pacific climate oscillation. Using this model, the decadal prediction of RA can be reasonably achieved with a 10-year-ahead forecasting skill score (SS) about 0.46. We therefore suggest, with this paper, that forecasting RA for Central Vietnam for multiple years ahead is possible using a time-series model. Full article
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Open AccessReview
Effect of Climate Change on the Yield of Cereal Crops: A Review
Climate 2018, 6(2), 41; https://doi.org/10.3390/cli6020041 -
Abstract
By the end of this century, the average global temperature is predicted to rise due to the increasing release of greenhouse gases (GHGs) into the atmosphere. This change in climate can reduce agricultural yields, resulting in food insecurity. However, agricultural activities are one
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By the end of this century, the average global temperature is predicted to rise due to the increasing release of greenhouse gases (GHGs) into the atmosphere. This change in climate can reduce agricultural yields, resulting in food insecurity. However, agricultural activities are one of the major contributors of GHGs and lower yields can trigger increased activity to meet the demand for food, resulting in higher quantities of GHGs released into the atmosphere. In this paper, we discuss the growth requirements and greenhouse gas release potential of staple cereal crops and assess the impact of climate change on their yields. Potential solutions for minimizing the influence of climate change on crop productivity are discussed. These include breeding to obtain cereals that are more tolerant to conditions caused by climate change, increased production of these new cultivars, improved irrigation, and more effective use of fertilizers. Furthermore, different predictive models inferred that climate change would reduce production of major cereal crops, except for millets due to their ability to grow in variable climatic conditions, and in dry areas due to a strong root system. Moreover, millets are not resource-intensive crops and release fewer greenhouse gases compared to other cereals. Therefore, in addition to addressing food security, millets have an enormous potential use for reducing the impact of agriculture on global warming and should be grown on a global scale as an alternative to major cereals and grains. Full article
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Open AccessArticle
Vulnerability of Structural Concrete to Extreme Climate Variances
Climate 2018, 6(2), 40; https://doi.org/10.3390/cli6020040 -
Abstract
For modern infrastructures, structural concrete has been widely adopted for various components and structures such as railway stations, platforms, walkways, railway bridges, tunnelling, concrete sleepers, concrete foundation of overhead wiring structures, etc. These infrastructures are subject to various changes of time, operation, and
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For modern infrastructures, structural concrete has been widely adopted for various components and structures such as railway stations, platforms, walkways, railway bridges, tunnelling, concrete sleepers, concrete foundation of overhead wiring structures, etc. These infrastructures are subject to various changes of time, operation, and environment. Environmental conditions are a considerably influential factor to life cycle and durability of concrete structures. This study aims at identifying the influence of climate change on the performance and durability of concrete structures using statistical regression analysis of a number of pertinent experimental and field data. The study into the influence of elevated temperature on compressive strength and splitting tensile strength also has been carried out using experimental data on the basis of environmental temperature and relative humidity, as well as CO2 concentration to the concrete carbonation and steel corrosion rates. The results indicate that environmental temperature, CO2 concentration, and a certain range of relative humidity play an important role in the concrete carbonation rates. Temperature and relative humidity affect the rate of steel corrosion as well. In addition, it is found that there exists a nearly direct correlation between the environmental temperature and the concrete carbonation rates, as well as the corrosion rate of steel embedded in concrete from 25 °C to 60 °C, and a nearly inverse proportion between the environmental relative humidity and the concrete carbonization from 48.75% to 105%. Indeed, the results exhibit that even in extreme natural high temperature, the capacity of compressive strength and splitting tensile strength is not affected significantly. Full article
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Open AccessArticle
Clustering Indian Ocean Tropical Cyclone Tracks by the Standard Deviational Ellipse
Climate 2018, 6(2), 39; https://doi.org/10.3390/cli6020039 -
Abstract
The standard deviational ellipse is useful to analyze the shape and the length of a tropical cyclone (TC) track. Cyclone intensity at each six-hour position is used as the weight at that location. Only named cyclones in the Indian Ocean since 1981 are
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The standard deviational ellipse is useful to analyze the shape and the length of a tropical cyclone (TC) track. Cyclone intensity at each six-hour position is used as the weight at that location. Only named cyclones in the Indian Ocean since 1981 are considered for this study. The K-means clustering algorithm is used to cluster Indian Ocean cyclones based on the five parameters: x-y coordinates of the mean center, variances along zonal and meridional directions, and covariance between zonal and meridional locations of the cyclone track. Four clusters are identified across the Indian Ocean; among them, only one cluster is in the North Indian Ocean (NIO) and the rest of them are in the South Indian Ocean (SIO). Other characteristics associated with each cluster, such as wind speed, lifespan, track length, track orientation, seasonality, landfall, category during landfall, total accumulated cyclone energy (ACE), and cyclone trend, are analyzed and discussed. Cyclone frequency and energy of Cluster 4 (in the NIO) have been following a linear increasing trend. Cluster 4 also has a higher number of landfall cyclones compared to other clusters. Cluster 2, located in the middle of the SIO, is characterized by the long track, high intensity, long lifespan, and high accumulated energy. Sea surface temperature (SST) and outgoing longwave radiation (OLR) associated with genesis of TCs are also examined in each cluster. Cyclone genesis is co-located with the negative OLR anomaly and the positive SST anomaly. Localized SST anomalies are associated with clusters in the SIO; however, TC geneses of Cluster 4 are associated with SSTA all over the Indian Ocean (IO). Full article
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Open AccessErratum
Erratum: Norman C. Treloar. Deconstructing Global Temperature Anomalies: An Hypothesis. Climate 2017, 5, 83
Climate 2018, 6(2), 38; https://doi.org/10.3390/cli6020038 -
Abstract
The authors would like to correct Section 1.2 of this article [1] as follows[...] Full article
Open AccessArticle
A Multi-Criteria Approach to Achieve Constrained Cost-Optimal Energy Retrofits of Buildings by Mitigating Climate Change and Urban Overheating
Climate 2018, 6(2), 37; https://doi.org/10.3390/cli6020037 -
Abstract
About 40% of global energy consumption is due to buildings. For this reason, many countries have established strict limits with regard to building energy performance. In fact, the minimization of energy consumption and related polluting emissions is undertaken in the public perspective with
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About 40% of global energy consumption is due to buildings. For this reason, many countries have established strict limits with regard to building energy performance. In fact, the minimization of energy consumption and related polluting emissions is undertaken in the public perspective with the main aim of fighting climate change. On the other hand, it is crucial to achieve financial benefits and proper levels of thermal comfort, which are the principal aims of the private perspective. In this paper, a multi-objective multi-stage approach is proposed to optimize building energy design by addressing the aforementioned public and private aims. The first stage implements a genetic algorithm by coupling MATLAB® and EnergyPlus pursuing the minimization of energy demands for space conditioning and of discomfort hours. In the second stage, a smart exhaustive sampling is conducted under MATLAB® environment with the aim of finding constrained cost-optimal solutions that ensure a drastic reduction of global costs as well as of greenhouse gas (GHG) emissions. Furthermore, the impact of such solutions on heat emissions into the external environment is investigated because these emissions highly affect urban overheating, external human comfort and the livability of our cities. The main novelty of this approach is the possibility to properly conjugate the public perspective (minimization of GHG emissions) and the private one (minimization of global costs). The focus on the reduction of heat emissions, in addition to the assessment of energy demands and GHG emissions, is novel too for investigations concerning building energy efficiency. The approach is applied to optimize the retrofit of a reference building related to the Italian office stock of the 1970s. Full article
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Open AccessArticle
On-Farm Evaluation of the Potential Use of Greenhouse Gas Mitigation Techniques for Rice Cultivation: A Case Study in Thailand
Climate 2018, 6(2), 36; https://doi.org/10.3390/cli6020036 -
Abstract
Environmental and socio-economic evaluations that imply techniques for mitigating greenhouse gas (GHG) emissions from rice cultivation are a challenging and controversial issue. This study was designed to investigate the potential use of mitigation techniques for rice cultivation. Mid-season drainage (MD), using ammonium sulfate
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Environmental and socio-economic evaluations that imply techniques for mitigating greenhouse gas (GHG) emissions from rice cultivation are a challenging and controversial issue. This study was designed to investigate the potential use of mitigation techniques for rice cultivation. Mid-season drainage (MD), using ammonium sulfate instead of urea (AS), and site-specific nutrient management (SSNM) were chosen as mitigation techniques. Data were collected using field surveys and structured questionnaires at the same 156 farms, covering four crop years. The GHG emissions were evaluated based on the concept of the life cycle assessment of the GHG emissions of products. The farmers’ assessments of mitigation techniques, with multiple criteria evaluation, were obtained by face-to-face interviews. Opinions on all mitigation techniques were requested two times covering four years with the same 156 farm owners. The multinomial logistic regression model was used to examine the factors influencing the farmers’ decisions. The results show that SSNM was evaluated as the highest abatement potential (363.52 kgCO2eq ha−1), the negative value of abatement cost (−2565 THB ha−1), and the negative value of the average abatement cost (−14 THB kgCO2eq−1). Among the different techniques, SSNM was perceived as the most suitable one, followed by MD and AS. Highly significant factors influencing decision making consisted of planted area, land size, farmer liability, farmer perception of yield, and GHG emissions. Subsidies or cost-sharing measures to convince farmers to adopt new techniques can enhance their practices, and more support for the development of water systems can increase their availability. Full article
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Open AccessArticle
Simulating the Impacts of Tree, C3, and C4 Plant Functional Types on the Future Climate of West Africa
Climate 2018, 6(2), 35; https://doi.org/10.3390/cli6020035 -
Abstract
This study investigates the future climatic impacts of different percentages of trees/shrubs, C4 and C3 plant functional types (PFTs) over the West Africa region. The ratio of co-existence among the different PFTs was done as a representation of agri-silviculture practices over the region.
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This study investigates the future climatic impacts of different percentages of trees/shrubs, C4 and C3 plant functional types (PFTs) over the West Africa region. The ratio of co-existence among the different PFTs was done as a representation of agri-silviculture practices over the region. Nine sensitivity experiments of different percentages of trees/shrubs, and C4 and C3 PFTs were carried out with a regional climate model (RegCM4) driven by Global Climate Model (HADGEM2-ES) outputs. These experiments were carried out along the Guinea Savana zone of West Africa using both prescribed and dynamic vegetation options of the model. The model simulated the seasonal evolution of precipitation and temperature fields quite well, with correlations greater than 0.8, but exhibited cold and wet biases of about 1–2 °C and 1–4 mm/day, respectively. Widespread warming (1–3 °C) and drying (1–2 mm/day) is projected in the near future across most parts of West Africa all year round. The West African future climate change associated with the different percentages of trees/shrubs, and C4 and C3 PFTs varied with the vegetation state (prescribed or dynamic) and model domain sizes. The prescribed vegetation experiments induced cooling of about 0.5–2 °C in most areas along the designated agri-silviculture zone, except Liberia and Sierra Leone. Similarly, enhanced precipitation occurred over most parts of Ghana and coastal parts of Nigeria (0.5–3 mm/day). On the other hand, the dynamic vegetation option did not exhibit pronounced changes in temperature and precipitation, except with a larger domain size. This study suggests the implementation of agri-silviculture as a mitigation and adaptation land-use practice across West Africa if drought-tolerant crops and the deciduous trees are adopted. Full article
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Open AccessArticle
Evaluation of Small-Scale Fishers’ Perceptions on Climate Change and Their Coping Strategies: Insights from Lake Malawi
Climate 2018, 6(2), 34; https://doi.org/10.3390/cli6020034 -
Abstract
The effects of climate change have negatively affected Malawi’s agricultural production. In this context, fisheries have been providing alternative livelihoods. However, there is a knowledge gap around the responses of small-scale fishers to climate-related changes. Therefore, a study was conducted on the Western
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The effects of climate change have negatively affected Malawi’s agricultural production. In this context, fisheries have been providing alternative livelihoods. However, there is a knowledge gap around the responses of small-scale fishers to climate-related changes. Therefore, a study was conducted on the Western shores of Lake Malawi between August 2015 and April 2016. The study evaluated the perceived effects of climate change on small-scale fishers and their coping strategies by employing a wide range of methods for data collection and analysis. The study used explorative surveys, household surveys, focus group discussions and key informant interviews to collect data. The study randomly sampled 112 household heads who owned either fishing gear or a fishing vessel or both. Content analysis for themes was used to analyse the qualitative data. The Mann–Kendal Test was used to analyse trends in meteorological data, and binary logistic regression was used to determine factors that influence coping with low fish catches. Despite the respondents noticing an increased incidence of extreme weather events and low fish catches, their perceptions could not be validated using time series meteorological data. However, such perceptions were influenced by experience from long-time exposure to extreme weather events and to low fish catches. The majority of the fishers had adjusted to these changes by increasing their fishing time, using highly efficient illegal fishing nets, expanding farming land, operating small businesses and undertaking casual labour in agriculture and fishing activities. The fishers’ propensity to adjust to these changes increased due to the presence of the following factors: older age of household head, higher education level, being married and having an annual income. In contrast, being a member of fish conservation club decreased the probability of adjusting. This study emphasizes the need to be cautious when defining and framing perceptions of local communities on extreme weather events as data obtained could be misleading. Furthermore, a multi-sectoral approach to balance sustainable livelihoods and management of fisheries is needed. These findings provide theoretical and practical lessons that can inform design, planning and implementation of policies that enhance adaptive capacity in fisheries and promote sustainable livelihoods in sub-Saharan Africa. Full article
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Open AccessArticle
Intercomparison of Univariate and Joint Bias Correction Methods in Changing Climate From a Hydrological Perspective
Climate 2018, 6(2), 33; https://doi.org/10.3390/cli6020033 -
Abstract
In this paper, the ability of two joint bias correction algorithms to adjust biases in daily mean temperature and precipitation is compared against two univariate quantile mapping methods when constructing projections from years 1981–2010 to early (2011–2040) and late (2061–2090) 21st century periods.
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In this paper, the ability of two joint bias correction algorithms to adjust biases in daily mean temperature and precipitation is compared against two univariate quantile mapping methods when constructing projections from years 1981–2010 to early (2011–2040) and late (2061–2090) 21st century periods. Using both climate model simulations and the corresponding hydrological model simulations as proxies for the future in a pseudo-reality framework, these methods are inter-compared in a cross-validation manner in order to assess to what extent the more sophisticated methods have added value, particularly from the hydrological modeling perspective. By design, bi-variate bias correction methods improve the inter-variable relationships in the baseline period. Cross-validation results show, however, that both in the early and late 21st century conditions the additional benefit of using bi-variate bias correction methods is not obvious, as univariate methods have a comparable performance. From the evaluated hydrological variables, the added value is most clearly seen in the simulated snow water equivalent. Although not having the best performance in adjusting the temperature and precipitation distributions, quantile mapping applied as a delta change method performs well from the hydrological modeling point of view, particularly in the early 21st century conditions. This suggests that retaining the observed correlation structures of temperature and precipitation might in some cases be sufficient for simulating future hydrological climate change impacts. Full article
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Open AccessArticle
The Effects of Changing Climate and Market Conditions on Crop Yield and Acreage Allocation in Nepal
Climate 2018, 6(2), 32; https://doi.org/10.3390/cli6020032 -
Abstract
This study examines the impact of changing climate and product market conditions on crop yield and land allocations in Nepal. Zellner’s seemingly unrelated regression approach is used to estimate the acreage and yield functions. The potential impact of price endogeneity on estimated parameters
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This study examines the impact of changing climate and product market conditions on crop yield and land allocations in Nepal. Zellner’s seemingly unrelated regression approach is used to estimate the acreage and yield functions. The potential impact of price endogeneity on estimated parameters is corrected using an instrumental variable method. The results show that farm input prices and output prices play a crucial role in determining acreage allocation. While the variation in daily temperature during planting season affects acreage allocations for all crops except wheat, the total precipitation is critical for upland crops, particularly for millet. Literacy rate and the number of rainy days significantly affect yield for most crops. Moreover, the rising winter warming is enhancing wheat and potato yields. The results also show that a ten percent decrease in the number of rainy days during the growing season is likely to reduce yields for rice, maize, and wheat by 4.8, 1.7, and 0.8 percent, respectively. Full article
Open AccessArticle
Projected Changes in Precipitation, Temperature, and Drought across California’s Hydrologic Regions in the 21st Century
Climate 2018, 6(2), 31; https://doi.org/10.3390/cli6020031 -
Abstract
This study investigated potential changes in future precipitation, temperature, and drought across 10 hydrologic regions in California. The latest climate model projections on these variables through 2099 representing the current state of the climate science were applied for this purpose. Changes were explored
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This study investigated potential changes in future precipitation, temperature, and drought across 10 hydrologic regions in California. The latest climate model projections on these variables through 2099 representing the current state of the climate science were applied for this purpose. Changes were explored in terms of differences from a historical baseline as well as the changing trend. The results indicate that warming is expected across all regions in all temperature projections, particularly in late-century. There is no such consensus on precipitation, with projections mostly ranging from −25% to +50% different from the historical baseline. There is no statistically significant increasing or decreasing trend in historical precipitation and in the majority of the projections on precipitation. However, on average, precipitation is expected to increase slightly for most regions. The increases in late-century are expected to be more pronounced than the increases in mid-century. The study also shows that warming in summer and fall is more significant than warming in winter and spring. The study further illustrates that, compared to wet regions, dry regions are projected to become more arid. The inland eastern regions are expecting higher increases in temperature than other regions. Particularly, the coolest region, North Lahontan, tends to have the highest increases in both minimum and maximum temperature and a significant amount of increase in wet season precipitation, indicative of increasing flood risks in this region. Overall, these findings are meaningful from both scientific and practical perspectives. From a scientific perspective, these findings provide useful information that can be utilized to improve the current flood and water supply forecasting models or develop new predictive models. From a practical perspective, these findings can help decision-makers in making different adaptive strategies for different regions to address adverse impacts posed by those potential changes. Full article
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Open AccessArticle
Evaluation of Statistical-Downscaling/Bias-Correction Methods to Predict Hydrologic Responses to Climate Change in the Zarrine River Basin, Iran
Climate 2018, 6(2), 30; https://doi.org/10.3390/cli6020030 -
Abstract
Modeling the hydrologic responses to future changes of climate is important for improving adaptive water management. In the present application to the Zarrine River Basin (ZRB), with the major reach being the main inflow source of Lake Urmia (LU), firstly future daily temperatures
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Modeling the hydrologic responses to future changes of climate is important for improving adaptive water management. In the present application to the Zarrine River Basin (ZRB), with the major reach being the main inflow source of Lake Urmia (LU), firstly future daily temperatures and precipitation are predicted using two statistical downscaling methods: the classical statistical downscaling model (SDSM), augmented by a trend-preserving bias correction, and a two-step updated quantile mapping (QM) method. The general circulation models (GCM) input to SDSM are climate predictors of the Canadian Earth System Model (CanESM2) GCM under the representative concentration pathway (RCP) emission scenarios, RCP45 and RCP85, whereas that to the QM is provided by the most suitable of several Climate Model Intercomparison Project Phase 5 (CMIP5) GCMs under RCP60, in addition. The performances of the two downscaling methods are compared to each other for a past “future” period (2006–2016) and the QM is found to be better and so is selected in the subsequent ZR streamflow simulations by means of the Soil and Water Assessment Tool (SWAT) hydrological model, calibrated and validated for the reference period (1991–2012). The impacts of climate change on the hydrologic response of the river basin, specifically the inflow to the Boukan Reservoir, the reservoir-dependable water release (DWR), are then compared for the three RCPs in the near- (2020–2038), middle- (2050–2068) and far- (2080–2098) future periods assuming (1) the “current” consumptive demand to be continued in the future, and (2) a more conservative “recommended” demand. A systematic future shortage of the available water is obtained for case (1) which can be mitigated somewhat for (2). Finally, the SWAT-predicted ZRB outflow is compared with the Montana-based estimated environmental flow of the ZR. The latter can successfully be sustained at good and fair levels for the near- and middle-future periods, but not so for the summer months of the far-future period, particularly, for RCP85. Full article
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Open AccessArticle
Climate Change Adaptation of Alpine Ski Tourism in Spain
Climate 2018, 6(2), 29; https://doi.org/10.3390/cli6020029 -
Abstract
Mountain ecosystems are considered to be vulnerable to climate change, with potential detrimental effects including the reduction of the snow seasons, the gradual retreat of glaciers, and changes in water storage and availability. One vulnerable sector to climate change is winter tourism, with
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Mountain ecosystems are considered to be vulnerable to climate change, with potential detrimental effects including the reduction of the snow seasons, the gradual retreat of glaciers, and changes in water storage and availability. One vulnerable sector to climate change is winter tourism, with some resorts likely to experience a significant reduction in the length of the skiing seasons and snow recreation areas throughout this century. This study assessed the vulnerability of 31 Spanish alpine ski resorts to climate change and evaluated the potential socio-economic and environmental implications of several adaptation measures. Results show that lower-altitude areas such as the Cantabrian Mountains and the Iberian System could be more vulnerable to climate change than higher-altitude areas of the Catalan Pyrenees or the Penibaetic System. Adaptation initiatives may include, inter alia, the production of artificial snow, the protection and conservation of the snow coverage area, and the diversification of recreation activities offered during the whole year. The study concludes that the design and implementation of adaptation strategies have to be adequate to the level of vulnerability associated with each resort as well as minimize their potential socio-economic and environmental costs. Full article
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Open AccessArticle
Land Surface Temperature Variation Due to Changes in Elevation in Northwest Vietnam
Climate 2018, 6(2), 28; https://doi.org/10.3390/cli6020028 -
Abstract
Land surface temperature (LST) is one of the most important variables for applications relating to the physics of land surface processes. LST rapidly changes in both space and time, and knowledge of LST and its spatiotemporal variation is essential to understand the interactions
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Land surface temperature (LST) is one of the most important variables for applications relating to the physics of land surface processes. LST rapidly changes in both space and time, and knowledge of LST and its spatiotemporal variation is essential to understand the interactions between human activity and the environment. This study investigates the spatiotemporal variation of LST according to changes in elevation. The newest version (version 6) of MODIS LST data for 2015 was used. An area of 40,000 km2 (200 × 200 km2) in northwest Vietnam with elevations ranging from 8 m to 3165 m was chosen as a case study. Our results showed that the drop in LST with increased elevation varied throughout the year during both the daytime and nighttime. The monthly averages in 2015 and an altitude increase of 1000 m resulted in a decrease in LST ranging from 3.8 °C to 6.1 °C and 1.5 °C to 5.8 °C for the daytime and nighttime, respectively. This suggests that in any study relating to the spatial distribution of LST, the effect of elevation on LST should be considered. In addition, the effects of land use/cover and elevation distribution on the relationship between LST and elevation are discussed. Full article
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Open AccessArticle
Vulnerability Assessment of the Livelihoods in Tanzania’s Semi-Arid Agro-Ecological Zone under Climate Change Scenarios
Climate 2018, 6(2), 27; https://doi.org/10.3390/cli6020027 -
Abstract
Despite the established literature on the vulnerability to climate change in various parts of Tanzania, it is worthwhile to assess the extent of this vulnerability of the peoples’ livelihoods and predict its future outcome. This is particularly important in the vulnerable ecosystems, that
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Despite the established literature on the vulnerability to climate change in various parts of Tanzania, it is worthwhile to assess the extent of this vulnerability of the peoples’ livelihoods and predict its future outcome. This is particularly important in the vulnerable ecosystems, that is, the semi-arid zones of Tanzania where the people’s livelihoods are highly attached to the declining local condition. The present study aims to assess the livelihoods vulnerability in Kongwa District, the semi-arid zone of Central Tanzania. In doing so, a wide range of methods were employed during data collection and analyses including surveys, informative interviews, discussions and observation. The study sampled 400 (≤10%) respondents during a survey. The Mann-Kendall Test with SPSS V20, Microsoft Excel and Theme content techniques were used for data analyses. The results indicate that climate stress has adversely impacted the quality of soil, vegetation, crop yields and intensified environmental degradation. Since most people depend upon the mentioned affected aspects, it is expected that also the level of livelihood vulnerability has elevated. Further, this situation has greatly contributed to increased poverty and thus, propagates the “tragedy of the common” to the available environmental resources. As a response to increased vulnerability, some farmers have abandoned thousands of hectares of agricultural farms that seemed to be less productive. Despite this, slight measures have been taken by both the government and other key stakeholders to limit vulnerability. The findings of this study provide a theoretical and practical basis for coordinating a sustainable man-environment relationship, ensuring the sustainability of the environment which is the major source of peoples’ livelihoods. Full article
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Open AccessArticle
Lighting Implications of Urban Mitigation Strategies through Cool Pavements: Energy Savings and Visual Comfort
Climate 2018, 6(2), 26; https://doi.org/10.3390/cli6020026 -
Abstract
Cool materials with higher solar reflectance compared with conventional materials of the same color are widely used to maintain cooler urban fabrics when exposed to solar irradiation and to mitigate the Urban Heat Island (UHI). Photo-catalytic coatings are also useful to reduce air
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Cool materials with higher solar reflectance compared with conventional materials of the same color are widely used to maintain cooler urban fabrics when exposed to solar irradiation and to mitigate the Urban Heat Island (UHI). Photo-catalytic coatings are also useful to reduce air pollutants. Many studies related to these topics have been carried out during the past few years, although the lighting implication of reflective coatings have hardly been explored. To investigate these aspects, reflective coatings were applied on portions of a road and intensely analyzed in a laboratory and on the field. The applied cool coatings were found to have much higher solar and lighting reflectance than the existing road, which lead to lower surface temperatures up to 9 °C. Non-significant variations of chromaticity coordinates were measured under different lighting conditions. However, these materials showed a relevant variation of directional properties depending on the lighting and observation conditions with respect to conventional pavements. The optical behavior of these materials affects the uniformity of visions for drivers and requires ad-hoc installation of light sources. On the other hand, potential energy savings of up to 75% were calculated for the artificial lighting of a reference road. Full article
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Open AccessArticle
Study of Mesoscale Cloud System Oscillations Capable of Producing Convective Gravity Waves
Climate 2018, 6(2), 25; https://doi.org/10.3390/cli6020025 -
Abstract
Mesoscale Convective cloud Systems (MCSs) are frequent in the greater area of the Mediterranean basin throughout the year. During their lifecycle, they can oscillate and produce vertically propagated, atmospheric gravity waves. This study is an effort to detect MCSs with oscillating behavior around
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Mesoscale Convective cloud Systems (MCSs) are frequent in the greater area of the Mediterranean basin throughout the year. During their lifecycle, they can oscillate and produce vertically propagated, atmospheric gravity waves. This study is an effort to detect MCSs with oscillating behavior around the Mediterranean, capable of producing convectively driven gravity waves (CGWs). Furthermore, typical MCS characteristics were calculated to identify the dynamics and the profile of the convective areas which can generate CGWs. Areal changes of the convective cloud tops in 15-min time-steps during the whole lifecycle of the MCSs were calculated to define the MCS oscillations. It was concluded that the MCSs that develop during nighttime as well as in the cold season of the year seem to contribute significantly to CGW production. Topography and specific sea areas like the Adriatic and the Ionian Sea play a catalytic role in triggering MCSs, which seem to contribute to CGW generation. Full article
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Open AccessArticle
Subjective Human Perception of Open Urban Spaces in the Brazilian Subtropical Climate: A First Approach
Climate 2018, 6(2), 24; https://doi.org/10.3390/cli6020024 -
Abstract
This research concerns a first approach to adapt the thermal comfort bands of the Physiological Equivalent Temperature (PET), New Standard Effective Temperature (SET), and Predicted Mean Vote (PMV) indices to Santa Maria’s population, Rio Grande do Sul, Brazil, on the basis of the
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This research concerns a first approach to adapt the thermal comfort bands of the Physiological Equivalent Temperature (PET), New Standard Effective Temperature (SET), and Predicted Mean Vote (PMV) indices to Santa Maria’s population, Rio Grande do Sul, Brazil, on the basis of the application of perception/sensation questionnaires to inhabitants while, at the same time, recording meteorological attribute data. Meteorological and thermal sensation data were collected from an automatic weather station installed on paved ground in the downtown area, which contained the following sensors: a scale gauge; a global radiation sensor; a temperature and humidity sensor; a speed and wind direction sensor; a gray globe thermometer. First of all, air temperature, gray globe temperature, relative air humidity, wind speed, wind gust, global solar radiation and precipitation were collected. People were interviewed using a questionnaire adapted from the model established by ISO 10551. The results demonstrated the efficiency of the linear regression model and the adequacy of the interpretive indexes, presenting results different from those analyzed by other authors in different climatic zones. These differences meet the analyzed literature and attest to the effectiveness of the calibration method of the PET, SET, and PMV indices for the Brazilian subtropical climate. After calibration, the PET index hit rate increased from 32.8% to 69.3%. The SET index, which had an initial hit rate of 34.6% before calibration, reached a hit-rate of 64.9%, while the PMV index increased from 35.9% to 58.7%. Full article
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