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Climate, Volume 7, Issue 7 (July 2019)

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Cover Story (view full-size image) Local climate change and urban heat islands (UHIs) increase the ambient temperature in urban areas [...] Read more.
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Open AccessArticle
Study on Temporal Variations of Surface Temperature and Rainfall at Conakry Airport, Guinea: 1960–2016
Climate 2019, 7(7), 93; https://doi.org/10.3390/cli7070093
Received: 15 March 2019 / Revised: 25 June 2019 / Accepted: 3 July 2019 / Published: 18 July 2019
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Abstract
The monthly averaged data time series of temperatures and rainfall without interruption of Conakry Airport (9.34° N 13.37° W, Guinea) from 1960 to 2016 were used. Inter-annual and annual changes in temperature and rainfall were investigated. Then, different models: Mann-Kendall Test, Multi-Linear-Regression analysis, [...] Read more.
The monthly averaged data time series of temperatures and rainfall without interruption of Conakry Airport (9.34° N 13.37° W, Guinea) from 1960 to 2016 were used. Inter-annual and annual changes in temperature and rainfall were investigated. Then, different models: Mann-Kendall Test, Multi-Linear-Regression analysis, Theil-Sen’s slope estimates and wavelet analysis where used for trend analysis and the dependency with these climate forcings. Results showed an increase in temperature with semi-annual and annual cycles. A sharp and abrupt rise in the temperature in 1998 was found. The results of study have shown increasing trends for temperature (about 0.21°/year). A decrease in rainfall (about −8.14 mm/year) is found since the end of 1960s and annual cycle with a maximum value of about 1118.3 mm recorded in August in average. The coherence between the two parameters and climate indices: El Niño 3.4, Atlantic Meridional Mode, Tropical Northern Atlantic and Atlantic Niño, were investigated. Thus, there is a clear need for increased and integrated research efforts in climate parameters variations to improve knowledge in climate change. Full article
(This article belongs to the Special Issue Climate variability and change in the 21th Century)
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Open AccessArticle
Climate Shocks and Responses in Karnali-Mahakali Basins, Western Nepal
Climate 2019, 7(7), 92; https://doi.org/10.3390/cli7070092
Received: 12 June 2019 / Revised: 10 July 2019 / Accepted: 11 July 2019 / Published: 18 July 2019
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Abstract
The Himalayas are highly susceptible to the impacts of climate change, as it consequently increases the vulnerability of downstream communities, livelihoods and ecosystems. Western Nepal currently holds significant potential as multiple opportunities for water development within the country are underway. However, it is [...] Read more.
The Himalayas are highly susceptible to the impacts of climate change, as it consequently increases the vulnerability of downstream communities, livelihoods and ecosystems. Western Nepal currently holds significant potential as multiple opportunities for water development within the country are underway. However, it is also identified as one of the most vulnerable regions to climate change, with both an increase in the occurrence of natural disasters and exacerbated severity and impacts levels. Regional climate model (RCM) projections indicate warmer weather with higher variability in rainfall for this region. This paper combines bio-physical and social approaches to further study and understand the current climate shocks and responses present in Western Nepal. Data was collected from 3660 households across 122 primary sampling units across the Karnali, Mahakali and Mohana River basins along with focus group discussions, which provided a rich understanding of the currently perceived climatic shocks and related events. Further analysis of climatology was carried out through nine indices of precipitation and temperature that were found to be relevant to the discussed climate shocks. Results show that 79% of households reported experiencing at least one type of climate shock in the five-year period and the most common occurrence was droughts, which is also supported by the climate data. Disaggregated results show that perception varies with the region and among the basins. Analysis of climatic trends further show that irregular weather is most common in the hill region, although average reported frequency of irregular weather is higher in the mountain. Further analysis into the severity and response to climatic shocks suggest an imminent need for better adaptation strategies. This study’s results show that a vast majority of respondents lack proper access to knowledge and that successful adaptation strategies must be adapted to specific regions to meet communities’ local needs. Full article
(This article belongs to the Special Issue Social-Ecological Systems, Climate and Global Change Impacts)
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Open AccessArticle
Observed Mesoscale Hydroclimate Variability of North America’s Allegheny Mountains at 40.2° N
Climate 2019, 7(7), 91; https://doi.org/10.3390/cli7070091
Received: 3 June 2019 / Revised: 6 July 2019 / Accepted: 6 July 2019 / Published: 18 July 2019
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Abstract
Spatial hydroclimatic variability of Eastern North America’s Allegheny Mountain System (AMS) is commonly oversimplified to elevation differences and the rain-shadow effect. Descriptive and higher order statistical properties of hourly meteorological observations (1948–2017) from seven airports were analyzed to better understand AMS climatic complexity. [...] Read more.
Spatial hydroclimatic variability of Eastern North America’s Allegheny Mountain System (AMS) is commonly oversimplified to elevation differences and the rain-shadow effect. Descriptive and higher order statistical properties of hourly meteorological observations (1948–2017) from seven airports were analyzed to better understand AMS climatic complexity. Airports were located along a longitudinal transect (40.2 °N) and observation infrastructure was positioned to minimize climatic gradients associated with insolation, slope, and aspect. Results indicated average ambient temperature was well correlated with airport elevation (R2 = 0.97). However, elevation was relatively poorly correlated to dew point temperature (R2 = 0.80) and vapor pressure deficit (R2 = 0.61) heterogeneity. Skewness and kurtosis of ambient and dew point temperatures were negative at all airports indicating hourly values below the median were more common and extreme values were less common than a normal distribution implies. Westerly winds accounted for 54.5% of observations indicating prevailing winds misrepresented nearly half of AMS weather phenomena. The sum of maximum hourly precipitation rates was maximized in Philadelphia, PA implying a convective precipitation maximum near the border of Piedmont and Coastal Plain provinces. Results further indicate the AMS represents a barrier to omnidirectional moisture advection suggesting physiographic provinces are characterized by distinct evapotranspiration and precipitation regimes. The current work draws attention to observed mesoscale hydroclimatic heterogeneity of the AMS region and identifies mechanisms influencing local to regional water quantity and quality issues that are relevant to many locations globally. Full article
(This article belongs to the Special Issue Landscape and Climate Change)
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Open AccessArticle
Mitigating Climate Change in the Cultural Built Heritage Sector
Climate 2019, 7(7), 90; https://doi.org/10.3390/cli7070090
Received: 14 May 2019 / Revised: 25 June 2019 / Accepted: 8 July 2019 / Published: 11 July 2019
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Abstract
Climate change mitigation targets have put pressure to reduce the carbon footprint of cultural heritage buildings. Commonly adopted measures to decrease the greenhouse gas (GHG) emissions of historical buildings are targeted at improving their energy efficiency through insulating the building envelope, and upgrading [...] Read more.
Climate change mitigation targets have put pressure to reduce the carbon footprint of cultural heritage buildings. Commonly adopted measures to decrease the greenhouse gas (GHG) emissions of historical buildings are targeted at improving their energy efficiency through insulating the building envelope, and upgrading their heating, cooling and lighting systems. However, there are complex issues that arise when mitigating climate change in the cultural built heritage sector. For instance, preserving the authenticity of heritage buildings, maintaining their traditional passive behaviours, and choosing adaptive solutions compatible with the characteristics of heritage materials to avoid an acceleration of decay processes. It is thus important to understand what the enablers, or the barriers, are to reduce the carbon footprint of cultural heritage buildings to meet climate change mitigation targets. This paper investigates how climate change mitigation is considered in the management and preservation of the built heritage through semi-structured interviews with cultural heritage experts from the UK, Italy and Norway. Best-practice approaches for the refurbishment of historical buildings with the aim of decreasing their energy consumption are presented, as perceived by the interviewees, as well as the identification of the enablers and barriers in mitigating climate change in the cultural built heritage sector. The findings emphasise that adapting the cultural built heritage to reduce GHG emissions is challenging, but possible if strong and concerted action involving research and government can be undertaken to overcome the barriers identified in this paper. Full article
(This article belongs to the Special Issue World Heritage and Climate Change: Impacts and Adaptation)
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Open AccessArticle
Spatiotemporal Analysis of Diurnal Temperature Range: Effect of Urbanization, Cloud Cover, Solar Radiation, and Precipitation
Climate 2019, 7(7), 89; https://doi.org/10.3390/cli7070089
Received: 5 May 2019 / Revised: 30 June 2019 / Accepted: 3 July 2019 / Published: 6 July 2019
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Abstract
High daily temperatures in the Mediterranean and Europe have been documented in observation and modeling studies. Long-term temperature data, from 1988 to 2017, from a suburban station and an urban station in Nicosia, Cyprus have been analyzed, and the diurnal temperature range (DTR) [...] Read more.
High daily temperatures in the Mediterranean and Europe have been documented in observation and modeling studies. Long-term temperature data, from 1988 to 2017, from a suburban station and an urban station in Nicosia, Cyprus have been analyzed, and the diurnal temperature range (DTR) trend was investigated. The seasonal Mann–Kendall test revealed a decreasing DTR trend of −0.24 °C/decade at the urban station and −0.36 °C/decade at the suburban station, which were attributed to an increase in the daily minimum temperature. Variations in precipitation, longwave radiation, ultraviolet-A (UVA), ultraviolet-B (UVB), cloud cover, water vapor, and urbanization were used to assess their possible relationship with regional DTR. The clustering of daytime and night-time data showed a strong relationship between the DTR and observed cloud cover, net longwave radiation, and precipitation. Clouds associated with smaller shortwave and net longwave radiation reduce the DTR by decreasing the surface solar radiation, while atmospheric absolute humidity denotes an increased daytime surface evaporative cooling and higher absorption of the short and longwave radiation. The intra-cluster variation could be reduced, and the inter-cluster variance increased by the addition of other meteorological parameters and anthropogenic sources that affect DTR in order to develop a quantitative basis for assessing DTR variations. Full article
(This article belongs to the Special Issue Urban Heat Islands)
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Open AccessFeature PaperArticle
Projected Changes in the Frequency of Peak Flows along the Athabasca River: Sensitivity of Results to Statistical Methods of Analysis
Climate 2019, 7(7), 88; https://doi.org/10.3390/cli7070088
Received: 8 May 2019 / Revised: 12 June 2019 / Accepted: 3 July 2019 / Published: 4 July 2019
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Abstract
Flows originating from alpine dominated cold region watersheds typically experience extended winter low flows followed by spring snowmelt and summer rainfall driven high flows. In a warmer climate, there will be a temperature-induced shift in precipitation from snowfall towards rain along with changes [...] Read more.
Flows originating from alpine dominated cold region watersheds typically experience extended winter low flows followed by spring snowmelt and summer rainfall driven high flows. In a warmer climate, there will be a temperature-induced shift in precipitation from snowfall towards rain along with changes in precipitation intensity and snowmelt timing, resulting in alterations in the frequency and magnitude of peak flow events. This study examines the potential future changes in the frequency and severity of peak flow events in the Athabasca River watershed in Alberta, Canada. The analysis is based on simulated flow data by the variable infiltration capacity (VIC) hydrologic model driven by statistically downscaled climate change scenarios from the latest coupled model inter-comparison project (CMIP5). The hydrological model projections show an overall increase in mean annual streamflow in the watershed and a corresponding shift in the freshet timing to an earlier period. The river flow is projected to experience increases during the winter and spring seasons and decreases during the summer and early fall seasons, with an overall projected increase in peak flow, especially for low frequency events. Both stationary and non-stationary methods of peak flow analysis, performed at multiple points along the Athabasca River, show that projected changes in the 100-year peak flow event for the high emissions scenario by the 2080s range between 4% and 33% depending on the driving climate models and the statistical method of analysis. A closer examination of the results also reveals that the sensitivity of projected changes in peak flows to the statistical method of frequency analysis is relatively small compared to that resulting from inter-climate model variability. Full article
(This article belongs to the Special Issue Impact of Climate-Change on Water Resources)
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Open AccessArticle
An Unusual Cold February 2019 in Saskatchewan—A Case Study Using NCEP Reanalysis Datasets
Climate 2019, 7(7), 87; https://doi.org/10.3390/cli7070087
Received: 31 May 2019 / Revised: 28 June 2019 / Accepted: 1 July 2019 / Published: 3 July 2019
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Abstract
In February 2019, central Canada, and especially the province of Saskatchewan, experienced extreme cold weather. It was the coldest February in 82 years and the second coldest in 115 years. In this study, we examine National Centers for Environmental Prediction (NCEP)/National Center for [...] Read more.
In February 2019, central Canada, and especially the province of Saskatchewan, experienced extreme cold weather. It was the coldest February in 82 years and the second coldest in 115 years. In this study, we examine National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) Reanalysis 1 data to understand the atmospheric processes leading to this cold snap. A detailed investigation of surface air temperature, sea level pressure, surface fluxes, and winds revealed a linkage between the North Pacific storm track and the February cold snap. A shift in the jet stream pattern triggered by the storm activity over the North Pacific caused a high-pressure blocking pattern, which resulted in unusual cold temperatures in Saskatchewan in February. This study demonstrates the potential for extreme cold in a warming climate; weather records in Saskatchewan show an increase in minimum winter temperature by 4–5 °C. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
Evaluation of Infilling Methods for Time Series of Daily Temperature Data: Case Study of Limpopo Province, South Africa
Climate 2019, 7(7), 86; https://doi.org/10.3390/cli7070086
Received: 3 May 2019 / Revised: 25 June 2019 / Accepted: 27 June 2019 / Published: 3 July 2019
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Abstract
Incomplete climate records pose a major challenge to decision makers that utilize climate data as one of their main inputs. In this study, different climate data infilling methods (arithmetic averaging, inverse distance weighting, UK traditional, normal ratio and multiple regression) were evaluated against [...] Read more.
Incomplete climate records pose a major challenge to decision makers that utilize climate data as one of their main inputs. In this study, different climate data infilling methods (arithmetic averaging, inverse distance weighting, UK traditional, normal ratio and multiple regression) were evaluated against measured daily minimum and maximum temperatures. Eight target stations that are evenly distributed in Limpopo province, South Africa, were used. The objective was to recommend the best approach that results in lowest errors. The optimum number of buddy/neighboring weather stations required for best estimate for each of the approaches was determined. The evaluation indices employed in this study were the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), accuracy rate (AR) and mean bias error (MBE). The results showed high correlation (r > 0.92) for all the stations, different methods and varying number of neighboring stations utilised. The MAE [RMSE] for the best performing methods (multiple regression and UK traditional) of estimating daily minimum temperature and maximum temperature was less than 1.8 °C [2.3 °C] and 1.0 °C [1.6 °C], respectively. The AR technique showed the MR method as the best approach of estimating daily minimum and maximum temperatures. The other recommended methods are the UK traditional and normal ratio. The MBEs for the arithmetic averaging and inverse-distance weighing techniques are large, indicating either over- or underestimating of the air temperature in the province. Based on the low values for the error estimating statistics, these data infilling methods for daily minimum and maximum air temperatures using neighboring stations data can be utilised to complete the datasets that are used in various applications. Full article
(This article belongs to the Special Issue Climate Services for Local Disaster Risk Reduction in Africa)
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Open AccessArticle
Perceptions, Knowledge and Adaptation about Climate Change: A Study on Farmers of Haor Areas after a Flash Flood in Bangladesh
Climate 2019, 7(7), 85; https://doi.org/10.3390/cli7070085
Received: 29 January 2019 / Revised: 4 June 2019 / Accepted: 18 June 2019 / Published: 1 July 2019
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Abstract
Bangladesh remains one of the most vulnerable countries in the world to the effects of climate change. Given the reliance of a large segment of the population on the agricultural sector for both their livelihoods as well as national food security, climate change [...] Read more.
Bangladesh remains one of the most vulnerable countries in the world to the effects of climate change. Given the reliance of a large segment of the population on the agricultural sector for both their livelihoods as well as national food security, climate change adaptation in the agricultural sector is crucial for continued national food security and economic growth. Using household data from lowland rice farmers of selected haor areas in Sylhet, the current work presents an analysis of the determinants behind the implementation of different climate change adaptation strategies by lowland rice farmers. The first objective of this study was to explore the extent of awareness of climate change within this population as well as the type of opinions held by lowland rice farmers with respect to climate change. To serve this purpose, a severity index (SI) was developed and subsequently employed to evaluate the perceptions and attitudes of 378 farmers with respect to climate change vulnerability. Respondents were interviewed with respect to climate change related circumstances they faced in their daily lives. Attained SI index values ranged from 69.18% to 93.52%. The SI for the perception “Climate change affects rice production” was measured as 93.52%. Using data collected from the same 378 farmers, a logistic regression was carried out to investigate the impact of socio-economic and institutional factors on adaptation. The results show that credit from non-government organizations is highly statistically significant for adaptation, and that rural market structure also has a positive effect on adaptation. Among the studied factors, credit from non-governmental organizations (NGOs) was found to be the most important factor for adaptation. The results of this work further indicate that marginal farmers would benefit from government (GoB) funded seasonal training activities that cover pertinent information regarding adaptation after flash floods. Additionally, the authors of this piece recommend timely issuance of government-assisted credit during early flash floods to afflicted farmers, as such an initiative can aid farmers in adapting different strategies to mitigate losses and enhance their productivity as well as livelihood. Full article
(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)
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