Climate

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17 pages, 1882 KiB

Open AccessArticle

Perceptions, Knowledge and Adaptation about Climate Change: A Study on Farmers of Haor Areas after a Flash Flood in Bangladesh

by Kanis Fatama Ferdushi, Mohd. Tahir Ismail and Anton Abdulbasah Kamil

Climate 2019, 7(7), 85; https://doi.org/10.3390/cli7070085 - 1 Jul 2019

Cited by 35 | Viewed by 7806

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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18 pages, 3481 KiB

Open AccessArticle

Impacts of Climate Change and Urban Expansion on Hydrologic Ecosystem Services in the Milwaukee River Basin

by Feng Pan and Woonsup Choi

Climate 2019, 7(4), 59; https://doi.org/10.3390/cli7040059 - 20 Apr 2019

Cited by 4 | Viewed by 5266

Abstract

Land use/land cover (LULC) and climate changes could affect water quantity and quality and thus hydrologic ecosystem services (ES). However, studies of these impacts on hydrologic ES are limited by the current methods and techniques. We attempted to find out how the LULC [...] Read more.

Land use/land cover (LULC) and climate changes could affect water quantity and quality and thus hydrologic ecosystem services (ES). However, studies of these impacts on hydrologic ES are limited by the current methods and techniques. We attempted to find out how the LULC and climate changes impact hydrologic ES at different temporal scales so that decision-makers can easily understand hydrologic ES variations for guiding management plans. In this study, we analyzed the impacts of LULC and climate changes on hydrologic ES in the Milwaukee River basin, USA with a conceptual modeling framework for hydrologic ES. The model framework was applied to a series of climate and urban expansion scenarios. Two hydrologic responses (streamflow and sediment) and three hydrologic ES (water provision index (WPI), flood regulation index (FRI), and sediment regulation index (SRI)) were calculated. Major findings include: (1) Climate change has much larger impacts than LULC at the monthly scale. For example, the impacts of climate change on streamflow were −6 to 9 m³/s whereas those of LULC change were −0.4 to 0.2 m³/s. Also, WPI (ranging from 0 to 1) changed between −0.16 and 0.07 with climate change but between −0.02 and −0.001 with LULC changes. (2) Compared to changes at the annual scale, the results show much larger variabilities as monthly time-series and mean monthly numbers. These findings suggest that the climate change weighs more than the realistic LULC change in term of impacts on hydrologic ES and those impacts can be identified with results at the monthly temporal scale. This approach with the framework and scenarios can better support management planning for decision-makers with detailed results and temporal precision. Full article

(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)

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27 pages, 876 KiB

Open AccessArticle

Insurer Resilience in an Era of Climate Change and Extreme Weather: An Econometric Analysis

by L. James Valverde and Matteo Convertino

Climate 2019, 7(4), 55; https://doi.org/10.3390/cli7040055 - 8 Apr 2019

Cited by 8 | Viewed by 5816

Abstract

Having sustained, over the course of more than two decades, record-breaking natural catastrophe losses, American insurers and reinsurers are justifiably questioning the potential linkage between anthropogenic climate change and extreme weather. Here, we explore issues pertaining to this linkage, looking at both the [...] Read more.

Having sustained, over the course of more than two decades, record-breaking natural catastrophe losses, American insurers and reinsurers are justifiably questioning the potential linkage between anthropogenic climate change and extreme weather. Here, we explore issues pertaining to this linkage, looking at both the likely short-term implications for the insurance industry, as well as potential longer-term impacts on financial performance and corporate resilience. We begin our discussion with an overview of the implications that climate change is likely to have on the industry, especially as it relates to how catastrophic risks are construed, assessed, and managed. We then present the rudiments of an econometric analysis that explores the financial resilience of the property/casualty (P/C) industry in the face of both natural and man-made catastrophes. In this analysis, we explore the profitability consequences of several illustrative scenarios involving large-scale losses from extreme weather—specifically, a sequence of storms like those striking the U.S. in 2004—and a scenario that explores the prospect of a Katrina-scale storm in combination with a mass terror attack on the scale of 9/11. At systemic levels of aggregation, our analysis suggests a high degree of macro-resilience for the P/C industry. Moreover, we find that insurer resilience is higher for larger impacts, considering both the speed of recovery, as well as the inverse of the area under the unaffected system profile. We conclude with a summary of our findings and a closing commentary that explores the potential implications of these results for P/C insurers moving forward. Full article

(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)

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18 pages, 1624 KiB

Open AccessArticle

Temperature Variability Differs in Urban Agroecosystems across Two Metropolitan Regions

by Monika H. Egerer, Brenda B. Lin and Dave Kendal

Climate 2019, 7(4), 50; https://doi.org/10.3390/cli7040050 - 3 Apr 2019

Cited by 9 | Viewed by 4352

Abstract

Climatically similar regions may experience different temperature extremes and weather patterns that warrant global comparisons of local microclimates. Urban agroecosystems are interesting sites to examine the multidimensional impacts of climate changes because they rely heavily on human intervention to maintain crop production under [...] Read more.

Climatically similar regions may experience different temperature extremes and weather patterns that warrant global comparisons of local microclimates. Urban agroecosystems are interesting sites to examine the multidimensional impacts of climate changes because they rely heavily on human intervention to maintain crop production under different and changing climate conditions. Here, we used urban community gardens across the California Central Coast metropolitan region, USA, and the Melbourne metropolitan region, Australia, to investigate how habitat-scale temperatures differ across climatically similar regions, and how people may be adapting their gardening behaviors to not only regional temperatures, but also to the local weather patterns around them. We show that, while annual means are very similar, there are strong interregional differences in temperature variability likely due to differences in the scale and scope of the temperature measurements, and regional topography. However, the plants growing within these systems are largely the same. The similarities may be due to gardeners’ capacities to adapt their gardening behaviors to reduce the adverse effects of local temperature variability on the productivity of their plot. Thus, gardens can serve as sites where people build their knowledge of local weather patterns and adaptive capacity to climate change and urban heat. Climate-focused studies in urban landscapes should consider how habitat-scale temperature variability is a background for interesting and meaningful social-ecological interactions. Full article

(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)

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Study regions in the California Central Coast, CA, USA, and Melbourne, Victoria, Australia. Community gardens (white balloons) located in the California Central Coast (a) spanning two ecoregions including the Santa Clara Valley (b) and the Monterey Bay Plains (c,d); Gardens located in the Melbourne Metropolitan Region spanning two ecoregions including the Gippsland Plain and Victorian Volcanic Plain (e); an example of a garden in this system (f). Images are courtesy of Google Earth satellite imagery [<a href="#B38-climate-07-00050" class="html-bibr">38</a>] and M. Egerer. Full article ">Figure 2
Average, maximum and minimum temperatures and their variation as measured by standard deviation (SD) observed in the gardens over the study period for the regional models (a–f). In gray, available WorldClim v2 Bioclim data plotted for a context of long-term temperature averages (a,c). WorldClim data are the mean temperature of the warmest quarter (BIO9) (a) and the maximum temperature of the warmest month (BIO5) (c). Box-and-whisker plots of the grouped values indicate the median, maximum, minimum, and 75% and 25% quantiles. Circles indicate outliers. Significant differences between local-scale temperature measurements (from logger data) are denoted by asterisks (*** p < 0.001, ** p < 0.01,* p < 0.05) and no difference denoted by “NS”. Full article ">Figure 3
Average, maximum and minimum temperatures and their variation as measured by standard deviation (SD) in the gardens for the ecoregional models (a–f). In gray, available WorldClim v2 Bioclim data plotted for a context of long-term temperature averages (a,c). WorldClim data are the mean temperature of the warmest quarter (BIO9) (a) and the maximum temperature of the warmest month (BIO5) (c). Box-and-whisker plots of the grouped values indicate the median, maximum, minimum, and 75% and 25% quantiles. Circles indicate outliers. Different lowercase letters indicate statistically significant differences between local-scale temperature measurements (from logger data) among ecoregions assessed using post-hoc tests. (California: MBP, Monterey Bay Plains; SCV, Santa Clara Valley; Melbourne: GP, Gippsland Plain; VVP, Victorian Volcanic Plain). Full article ">

21 pages, 522 KiB

Open AccessArticle

Communicating Climate Mitigation and Adaptation Efforts in American Cities

by Constantine Boussalis, Travis G. Coan and Mirya R. Holman

Climate 2019, 7(3), 45; https://doi.org/10.3390/cli7030045 - 24 Mar 2019

Cited by 13 | Viewed by 7223

Abstract

City governments have a large role to play in climate change mitigation and adaptation policies, given that urban locales are responsible for disproportionately high levels of greenhouse gas (GHG) emissions and are on the “front lines” of observed and anticipated climate change impacts. [...] Read more.

City governments have a large role to play in climate change mitigation and adaptation policies, given that urban locales are responsible for disproportionately high levels of greenhouse gas (GHG) emissions and are on the “front lines” of observed and anticipated climate change impacts. This study examines how US mayors prioritize climate policies within the context of the city agenda. Employing a computer-assisted content analysis of over 2886 mayoral press releases related to climate change from 82 major American cities for the period 2010–2016, we describe and explain the extent to which city governments discuss mitigation and adaptation policies in official communications. Specifically, we rely on a semi-supervised topic model to measure key climate policy themes in city press releases and examine their correlates using a multilevel statistical model. Our results suggest that while mitigation policies tend to dominate the city agenda on climate policy, discussion of adaptation efforts has risen dramatically in the past few years. Further, our statistical analysis indicates that partisanship influences city discussion on a range of climate policy areas—including emissions, land use policy, and climate resiliency—while projected vulnerability to climatic risks only influences discussion of climate resiliency and adaptation efforts. Full article

(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)

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Top 20 U.S. city emitters of carbon dioxide equivalent. This figure displays the carbon dioxide equivalent emissions (millions of metric tons) for the top 20 emitters amongst U.S. cities. Estimates are retrieved from Nangini et al. [<a href="#B15-climate-07-00045" class="html-bibr">15</a>]. Full article ">Figure 2
Discussion of key policy areas. (a) Provides the total number of words assigned to each of the main “seeded” topics using the model described in <a href="#sec2dot2-climate-07-00045" class="html-sec">Section 2.2</a>. (b–d) Quarterly discussion of Emissions and Transportation, Energy efficiency and Renewable energy, and Climate resiliency, respectively. Word totals are normalized by the number of press releases in each quarter. Full article ">Figure 3
Reducing GHG emissions versus promoting climate resiliency. The figure presents standardized (z-scores) word totals assigned to climate Emissions (x-axis) and Climate resiliency (y-axis). Prior to standardization, word totals were transformed using <math display="inline"><semantics> <mrow> <mi>ln</mi> <mo>(</mo> <mn>1</mn> <mo>+</mo> <mi>x</mi> <mo>)</mo> </mrow> </semantics></math>, given the presence of heavy-tailed word assignment distributions for both topics. Marker size indicates level of climate risk [<a href="#B43-climate-07-00045" class="html-bibr">43</a>]. Republican mayors are in red, while Democratic mayors are in blue [<a href="#B29-climate-07-00045" class="html-bibr">29</a>]. Full article ">Figure 4
Explaining variation of climate-related themes in city press releases. This plot illustrates the results of a set of Bayesian multi-level logistic regression models, which estimate the effect of climate risk, political partisanship, and other covariates on whether a city discusses the following climate-related themes in a given month: (a) Emissions, (b) Energy (Energy efficiency & Renewable energy), (c) Climate resiliency, and (d) Land use. Circles represent posterior means, thick whiskers represent 50% credible intervals, and thin whiskers represent 95% credible intervals. Standardized variables are denoted with an asterisk (*). Full article ">

20 pages, 2115 KiB

Open AccessEditor’s ChoiceArticle

Green Infrastructure Financing as an Imperative to Achieve Green Goals

by Rae Zimmerman, Ryan Brenner and Jimena Llopis Abella

Climate 2019, 7(3), 39; https://doi.org/10.3390/cli7030039 - 9 Mar 2019

Cited by 26 | Viewed by 8039

Abstract

Green infrastructure (GI) has increasingly gained popularity for achieving adaptation and mitigation goals associated with climate change and extreme weather events. To continue implementing GI, financial tools are needed for upfront project capital or development costs and later for maintenance. This study’s purpose [...] Read more.

Green infrastructure (GI) has increasingly gained popularity for achieving adaptation and mitigation goals associated with climate change and extreme weather events. To continue implementing GI, financial tools are needed for upfront project capital or development costs and later for maintenance. This study’s purpose is to evaluate financing tools used in a selected GI dataset and to assess how those tools are linked to various GI technologies and other GI project characteristics like cost and size. The dataset includes over 400 GI U.S. projects, comprising a convenience sample, from the American Society of Landscape Architects (ASLA). GI project characteristics were organized to answer a number of research questions using descriptive statistics. Results indicated that the number of projects and overall cost shares were mostly located in a few states. Grants were the most common financial tool with about two-thirds of the projects reporting information on financial tools receiving grant funding. Most projects reported financing from only one tool with a maximum of three tools. Projects primarily included multiple GI technologies averaging three and a maximum of nine. The most common GI technologies were bioswales, retention, rain gardens, and porous pavements. These findings are useful for decision-makers evaluating funding support for GI. Full article

(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)

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Distribution by state of total projects (top) and total cost (bottom) represented in the ASLA convenience dataset. Note: This concentration of projects may not represent the actual concentration of GI investment and instead reflect the concentration of ASLA membership or awareness of projects. Full article ">Figure 2
Cost per square foot for different GI technologies. Note: The figure on the left represents the full dataset, including all of the outliers, while the figure on the right limits the x-axis to show the majority of the cases. The boxes represent the interquartile range (IQR), the bars within the boxes represent the median, the points marked with an “×” represent the mean, and the dots are the outliers defined as 1.5 times the IQR in either direction. Full article ">Figure 3
Total project cost by financial tool used to finance the project. Note: Only 102 cases (about 23%) provided information on the specific tools used. Projects often included more than one financial tool but did not specify the breakdown of how much funding came from each tool; this distribution represents the total cost of each project that used the given financial tool for at least a portion of the financing. The boxes represent the interquartile range (IQR), the bars within the boxes represent the median, the points marked with an “×” represent the mean, and the dots are the outliers defined as 1.5 times the IQR in either direction. Full article ">Figure 4
Total cost (top) and number of projects (bottom) by completion year (1988–2013). Note: Only 74 cases (about 17%) provided a completion year. This concentration of projects may not represent the actual concentration of GI investment and instead reflect the concentration of ASLA awareness of projects. Full article ">Figure 5
GI technology use by year (1988–2013). Full article ">

28 pages, 8435 KiB

Open AccessFeature PaperArticle

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 12 | Viewed by 5415

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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19 pages, 10541 KiB

Open AccessFeature PaperArticle

Observational Evidence of Neighborhood Scale Reductions in Air Temperature Associated with Increases in Roof Albedo

by Arash Mohegh, Ronnen Levinson, Haider Taha, Haley Gilbert, Jiachen Zhang, Yun Li, Tianbo Tang and George A. Ban-Weiss

Climate 2018, 6(4), 98; https://doi.org/10.3390/cli6040098 - 12 Dec 2018

Cited by 16 | Viewed by 4808

Abstract

The effects of neighborhood-scale land use and land cover (LULC) properties on observed air temperatures are investigated in two regions within Los Angeles County: Central Los Angeles and the San Fernando Valley (SFV). LULC properties of particular interest in this study are albedo [...] Read more.

The effects of neighborhood-scale land use and land cover (LULC) properties on observed air temperatures are investigated in two regions within Los Angeles County: Central Los Angeles and the San Fernando Valley (SFV). LULC properties of particular interest in this study are albedo and tree fraction. High spatial density meteorological observations are obtained from 76 personal weather-stations. Observed air temperatures were then related to the spatial mean of each LULC parameter within a 500 m radius “neighborhood” of each weather station, using robust regression for each hour of July 2015. For the neighborhoods under investigation, increases in roof albedo are associated with decreases in air temperature, with the strongest sensitivities occurring in the afternoon. Air temperatures at 14:00–15:00 local daylight time are reduced by 0.31 °C and 0.49 °C per 1 MW increase in daily average solar power reflected from roofs per neighborhood in SFV and Central Los Angeles, respectively. Per 0.10 increase in neighborhood average albedo, daily average air temperatures were reduced by 0.25 °C and 1.84 °C. While roof albedo effects on air temperature seem to exceed tree fraction effects during the day in these two regions, increases in tree fraction are associated with reduced air temperatures at night. Full article

(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)

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The aggregation area, or “neighborhood” (green circle of radius 500 m) around an example weather station (red dot) in SFV. The underlying imagery shows the building footprint dataset. Full article ">Figure 2
Location of selected personal weather stations in the Los Angeles basin. Stations are color coded to identify study regions. Note that the dots are drawn to scale to indicate the size of each 500 m radius neighborhood. Full article ">Figure 3
Afternoon (14:00–15:00 LDT) temperature versus daily average reflected solar power from roofs per neighborhood (500 m radius circle around each station) in Central Los Angeles for each day during July 2015. Each subpanel represents one day, and each point represents a single weather station and associated LULC parameter. Slopes from least squares regressions are used to obtain daily sensitivities of the temperature to the LULC parameter under investigation. The mean irradiance (W/m2) at 14:00–15:00 LDT is shown above each subpanel. Red dots are removed from regressions as outliers. The red dotted regression line corresponds to linear regressions using all points (including outliers) and the black line corresponds to those using only the black squares (non-outliers). The size of each point (area) is proportional to its influence. Full article ">Figure 4
Boxplots for the diurnal cycle of sensitivity of temperature to (a,b) daily average solar power reflected by roofs, and (c,d) tree fraction. Panels (a,c) are for Central Los Angeles, and panels (b,d) are for San Fernando Valley (SFV). Each box contains the sensitivities per hour for the entire month (July 2015). The hours with statistically insignificant sensitivities (see Methodology section for details) have red hatching. Boxes show the inner-quartile range (IQR); whiskers show [(Q1 − 1.5 IQR), (Q3 + 1.5 IQR)], and the black line within the box represents the median. Hour of day 1 = 00:00 to 01:00 LDT. Full article ">Figure 4 Cont.
Boxplots for the diurnal cycle of sensitivity of temperature to (a,b) daily average solar power reflected by roofs, and (c,d) tree fraction. Panels (a,c) are for Central Los Angeles, and panels (b,d) are for San Fernando Valley (SFV). Each box contains the sensitivities per hour for the entire month (July 2015). The hours with statistically insignificant sensitivities (see Methodology section for details) have red hatching. Boxes show the inner-quartile range (IQR); whiskers show [(Q1 − 1.5 IQR), (Q3 + 1.5 IQR)], and the black line within the box represents the median. Hour of day 1 = 00:00 to 01:00 LDT. Full article ">Figure 5
Daily average solar power reflected by roofs vs. tree fraction for each region. Each point represents a different neighborhood (500 m radius around a weather station). Least squares linear regressions are also shown for SFV (black line) and Central Los Angeles (red line). Full article ">Figure 6
Comparison of daily average solar power reflected from (a) roof and (b) non-roof surfaces versus daily average solar power reflected from all surfaces in each corresponding neighborhood. Least squares linear regressions are also shown separately for the two areas (i.e., SFV and Central Los Angeles). The higher coefficients of determination (R2) in panel (a) versus (b) suggest that variations in roof albedo are responsible for the majority of variations in neighborhood albedo. Full article ">

13 pages, 6615 KiB

Open AccessFeature PaperArticle

Relationship between City Size, Coastal Land Use, and Summer Daytime Air Temperature Rise with Distance from Coast

by Hideki Takebayashi, Takahiro Tanaka, Masakazu Moriyama, Hironori Watanabe, Hiroshi Miyazaki and Kosuke Kittaka

Climate 2018, 6(4), 84; https://doi.org/10.3390/cli6040084 - 27 Oct 2018

Cited by 5 | Viewed by 4728

Abstract

The relationship between city size, coastal land use, and air temperature rise with distance from coast during summer day is analyzed using the meso-scale weather research and forecasting (WRF) model in five coastal cities in Japan with different sizes and coastal land use [...] Read more.

The relationship between city size, coastal land use, and air temperature rise with distance from coast during summer day is analyzed using the meso-scale weather research and forecasting (WRF) model in five coastal cities in Japan with different sizes and coastal land use (Tokyo, Osaka, Nagoya, Hiroshima, and Sendai) and inland cities in Germany (Berlin, Essen, and Karlsruhe). Air temperature increased as distance from the coast increased, reached its maximum, and then decreased slightly. In Nagoya and Sendai, the amount of urban land use in coastal areas is less than the other three cities, where air temperature is a little lower. As a result, air temperature difference between coastal and inland urban area is small and the curve of air temperature rise is smaller than those in Tokyo and Osaka. In Sendai, air temperature in the inland urban area is the same as in the other cities, but air temperature in the coastal urban area is a little lower than the other cities, due to an approximate one degree lower sea surface temperature being influenced by the latitude. In three German cities, the urban boundary layer may not develop sufficiently because the fetch distance is not enough. Full article

(This article belongs to the Special Issue Climate Change Resilience and Urban Sustainability)

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