Trends in surface temperature variability over Mumbai and Ratnagiri cities of coastal Maharashtra, India

Increasing urbanization and expansion of cities has led to intensification of the urban heat island (UHI). High consumption of fossil fuels and trapping of radiated heat leads to increase in surface temperature in and around city. Present research paper focuses on temperature variability over Mumbai and Ratnagiri cities, which are located in the same coastal climatic region and almost at same altitude. Trends in maximum and minimum temperature were investigated at annual and seasonal scale. The occurrences of temperature extremes were also analysed. In general, increasing trends were observed over both the stations, with high rate of increase in maximum temperature than the minimum temperatures statistically significant at 95% confidence level. Mumbai experienced significant warming with higher rates than Ratnagiri. Warm extremes have also increased significantly over Mumbai. Ratnagiri showed decrease in hot days during monsoon and hot nights during remaining seasons significant in summer.

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Spatial Temporal Analysis of Urban Heat Hazard on Education Area (University of Indonesia

Indonesian Journal of Geography ◽

10.22146/ijg.11821 ◽

2017 ◽

Vol 49 (1) ◽

pp. 1 ◽

Cited By ~ 2

Author(s):

Adi Wibowo ◽

Khairulmaini Osman Salleh ◽

Adi Wibowo

Keyword(s):

Land Use ◽

Land Cover ◽

Surface Temperature ◽

Land Surface ◽

Temporal Analysis ◽

Maximum Temperature ◽

Climate Index ◽

Landsat 8 ◽

Urban Heat ◽

Heat Hazard

As education area, campus or university is full with various activities which have an impact on the existence of land-use or land-cover. The variation of activities dynamically change the shape of land-use or land-cover within the campus area, thus also create variations in Land Surface Temperature (LST). The LST are impacting the coziness of human activity especially when reaches more than 30 oC. This study used the term Urban Heat Signature (UHS) to explain LST in different land-use or land-cover types. The objective of this study is to examine UHS as an Urban Heat Hazard (UHH) based on Universal Temperature Climate Index (UTCI) and Effective Temperature Index (ETI) in University of Indonesia. Thermal bands of Landsat 8 images (the acquisition year 2013-2015) were used to create LST model. A ground data known as Air Surface Temperature (AST) were used to validate the model. The result showed an increased level of maximum temperature during September-October since 2013 until 2014. The maximum temperature was reduced in October 2014, however it increased again in August 2015. The UTCI showed “moderate” and “strong heat stress”, while EFI showed “uncomfortable” and “very uncomfortable” categories during that period. This research concluded that build up area in UI Campus highest temperature on UI campus based on UHS. Range UHS in Campus UI on 2013 (21.8-31.1oC), 2014 (25.0-36.2oC) and 2015 (24.9-38.2oC). This maximum UHS on September (2014 and 2015) put on levelling UTCI included range temperature 32-35oC, with an explanation of sensation temperature is warm and sensation of comfort is Uncomfortable, Psychology with Increasing Stress Case by Sweating and Blood Flow and Health category is Cardiovascular Embarrassment. This UHS occurs in September will give impact on psychology and health, that’s become the UHH of the living on education area.

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Occurrence of extreme temperature events – A Probable risk on natural rubber cultivation

Journal of Plantation Crops ◽

10.19071/jpc.2015.v43.i3.2856 ◽

2015 ◽

Vol 43 (3) ◽

Cited By ~ 1

Author(s):

K.K. Jayasooryan ◽

P.R. Satheesh ◽

R. Krishnakumar ◽

James Jacob

Keyword(s):

Climate Change ◽

Ecological Impact ◽

Extreme Temperature ◽

Temporal Variations ◽

Maximum Temperature ◽

Extreme Temperature Events ◽

The Past ◽

Hot Days ◽

Expert Team ◽

Increasing Trends

<span style="line-height: 107%; font-family: 'Times New Roman','serif'; font-size: 12pt; mso-bidi-language: HI; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: EN-GB; mso-fareast-language: EN-US;" lang="EN-GB">Climate change and occurrence of extreme temperature events were studied in Kottayam, a major rubber growing district in Kerala. Occurrence of extreme temperature events can affect the livelihood of rubber growers apart from the ecological impact. The present study was conducted by analysing the occurrence of extreme temperature events in the past 40 years (1970-2010) using the RClimDex package developed by the Expert Team on Climate Change Detection Monitoring and Indices (ETCCDMI), Canada. Temporal variations in trends of occurrence of extreme temperature events were tested with Mann-Kendall trend analysis. The 5-year diurnal temperature range (DTR, difference between monthly mean maximum and minimum temperatures) increased from 7.8 (during 1970-1974) to 9.2 0C (during 2006-2010). The monthly mean maximum temperature increased by 0.035 0C per year. Frequency of occurrence of hot days increased at a rate of 0.56 per cent per year and the highest temperature recorded in a month showed an increase of 0.038 0C per year. As observed, the increasing trends in the occurrence of extreme temperature events may eventually lead to the warming up of the region in future. The study indicates that the projected warming tendency in the traditional rubber growing regions of India may affect the rubber cultivation adversely.</span>

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A Study on the Characteristics of Academic Topics Related to Renewable Energy Using the Structural Topic Modeling and the Weak Signal Concept

Energies ◽

10.3390/en14051497 ◽

2021 ◽

Vol 14 (5) ◽

pp. 1497

Author(s):

Chankook Park ◽

Minkyu Kim

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Topic Modeling ◽

Academic Research ◽

High Rate ◽

Weak Signals ◽

Energy Potential ◽

Rate Of Increase ◽

Probabilistic Topic Modeling ◽

To Receive

It is important to examine in detail how the distribution of academic research topics related to renewable energy is structured and which topics are likely to receive new attention in the future in order for scientists to contribute to the development of renewable energy. This study uses an advanced probabilistic topic modeling to statistically examine the temporal changes of renewable energy topics by using academic abstracts from 2010–2019 and explores the properties of the topics from the perspective of future signs such as weak signals. As a result, in strong signals, methods for optimally integrating renewable energy into the power grid are paid great attention. In weak signals, interest in large-capacity energy storage systems such as hydrogen, supercapacitors, and compressed air energy storage showed a high rate of increase. In not-strong-but-well-known signals, comprehensive topics have been included, such as renewable energy potential, barriers, and policies. The approach of this study is applicable not only to renewable energy but also to other subjects.

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Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

Sustainability ◽

10.3390/su13031099 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1099

Author(s):

Yuhe Ma ◽

Mudan Zhao ◽

Jianbo Li ◽

Jian Wang ◽

Lifa Hu

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Urban Heat Island ◽

Land Surface Temperature ◽

Land Surface ◽

Cooling Effect ◽

Heat Island ◽

Land Cover Types ◽

Island Effect ◽

Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

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Exploring diurnal cycles of surface urban heat island intensity in Boston with land surface temperature data derived from GOES-R geostationary satellites

The Science of The Total Environment ◽

10.1016/j.scitotenv.2020.144224 ◽

2021 ◽

Vol 763 ◽

pp. 144224

Author(s):

Yue Chang ◽

Jingfeng Xiao ◽

Xuxiang Li ◽

Steve Frolking ◽

Decheng Zhou ◽

...

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Temperature Data ◽

Heat Island ◽

Diurnal Cycles ◽

Geostationary Satellites ◽

Urban Heat ◽

Surface Urban Heat Island ◽

Surface Temperature Data

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Change in mean and extreme temperature at Yingkou station in Northeast China from 1904 to 2017

Climatic Change ◽

10.1007/s10584-021-02981-w ◽

2021 ◽

Vol 164 (3-4) ◽

Author(s):

Xiaoying Xue ◽

Guoyu Ren ◽

Xiubao Sun ◽

Panfeng Zhang ◽

Yuyu Ren ◽

...

Keyword(s):

Northeast China ◽

Extreme Temperature ◽

Maximum Temperature ◽

Data Set ◽

The Past ◽

Significant Downward Trend ◽

Cold Events ◽

Temperature Indices ◽

Increasing Trends ◽

Change In Mean

AbstractThe understanding of centennial trends of extreme temperature has been impeded due to the lack of early-year observations. In this paper, we collect and digitize the daily temperature data set of Northeast China Yingkou meteorological station since 1904. After quality control and homogenization, we analyze the changes of mean and extreme temperature in the past 114 years. The results show that mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) all have increasing trends during 1904–2017. The increase of Tmin is the most obvious with the rate of 0.34 °C/decade. The most significant warming occurs in spring and winter with the rate of Tmean reaching 0.32 °C/decade and 0.31 °C/decade, respectively. Most of the extreme temperature indices as defined using absolute and relative thresholds of Tmax and Tmin also show significant changes, with cold events witnessing a more significant downward trend. The change is similar to that reported for global land and China for the past six decades. It is also found that the extreme highest temperature (1958) and lowest temperature (1920) records all occurred in the first half of the whole period, and the change of extreme temperature indices before 1950 is different from that of the recent decades, in particular for diurnal temperature range (DTR), which shows an opposite trend in the two time periods.

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ARIMA modeling for forecasting land surface temperature and determination of urban heat island using remote sensing techniques for Chennai city, India

Arabian Journal of Geosciences ◽

10.1007/s12517-021-07351-5 ◽

2021 ◽

Vol 14 (11) ◽

Author(s):

Ramesh Kesavan ◽

Misba Muthian ◽

Karuppasamy Sudalaimuthu ◽

Shirly Sundarsingh ◽

Saravanan Krishnan

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Heat Island ◽

Urban Heat ◽

Arima Modeling ◽

Remote Sensing Techniques ◽

Chennai City

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Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

Remote Sensing ◽

10.3390/rs13020323 ◽

2021 ◽

Vol 13 (2) ◽

pp. 323

Author(s):

Liang Chen ◽

Xuelei Wang ◽

Xiaobin Cai ◽

Chao Yang ◽

Xiaorong Lu

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Maximum Temperature ◽

Maximum Temperature Difference ◽

Rapid Urbanization ◽

The Impact ◽

The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

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