Drivers influencing climate of growing cities
Abstract Population growth and affordable housing have boosted realty sector and urban sprawl in India. Understanding the interrelation between urbanization and local climate, though complex, is the need of the hour and the focus of this study. An analysis of the Expert Team on Climate Change Detect...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Springer
2022-09-01
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| Series: | Computational Urban Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43762-022-00055-w |
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| author | Sanskriti Mujumdar Chirayu Pandit Akash Patel |
| author_facet | Sanskriti Mujumdar Chirayu Pandit Akash Patel |
| author_sort | Sanskriti Mujumdar |
| collection | DOAJ |
| description | Abstract Population growth and affordable housing have boosted realty sector and urban sprawl in India. Understanding the interrelation between urbanization and local climate, though complex, is the need of the hour and the focus of this study. An analysis of the Expert Team on Climate Change Detection and Indices (ETCCDI) on temperature and precipitation was carried out, and it confirms the change in the local urban climate. A Clausius-Clapeyron (CC) scaling relationship has been developed between the range of daily maximum temperature and precipitation for finding precipitation intensity, which is influenced by a rise in maximum temperature. Land use and land cover change derived for the period 1970–2017 from Landsat images were used to understand the effect of urbanization on average daily temperature and extreme precipitation. Multivariate ENSO Index and Global Temperature Anomalies were taken as global physical drivers. Urbanization growth rate anomalies, annual mean temperature anomalies, and summer mean temperature anomalies were taken as local physical drivers that affect one-day extreme precipitation. 22 combinations of these physical drivers were used as covariates to develop extreme value models. Models were evaluated with the L-R test and AIC. It is found that global average temperature and urbanization, individually as well as in combination with local summer mean temperature, were found to be influencing local extreme precipitation. Changes in precipitation patterns have a direct impact on urban water management. |
| first_indexed | 2024-04-13T06:03:47Z |
| format | Article |
| id | doaj.art-ebc40c5105514900a07cd1756e095555 |
| institution | Directory Open Access Journal |
| issn | 2730-6852 |
| language | English |
| last_indexed | 2024-04-13T06:03:47Z |
| publishDate | 2022-09-01 |
| publisher | Springer |
| record_format | Article |
| series | Computational Urban Science |
| spelling | doaj.art-ebc40c5105514900a07cd1756e0955552022-12-22T02:59:21ZengSpringerComputational Urban Science2730-68522022-09-012111610.1007/s43762-022-00055-wDrivers influencing climate of growing citiesSanskriti Mujumdar0Chirayu Pandit1Akash Patel2Civil Engineering Department, Faculty of Technology & Engineering, The Maharaja Sayajirao University of BarodaCivil Engineering Department, Polytechnic, The Maharaja Sayajirao University of BarodaClimate Change Project, Civil Engineering Department, Faculty of Technology & Engineering, The Maharaja Sayajirao University of BarodaAbstract Population growth and affordable housing have boosted realty sector and urban sprawl in India. Understanding the interrelation between urbanization and local climate, though complex, is the need of the hour and the focus of this study. An analysis of the Expert Team on Climate Change Detection and Indices (ETCCDI) on temperature and precipitation was carried out, and it confirms the change in the local urban climate. A Clausius-Clapeyron (CC) scaling relationship has been developed between the range of daily maximum temperature and precipitation for finding precipitation intensity, which is influenced by a rise in maximum temperature. Land use and land cover change derived for the period 1970–2017 from Landsat images were used to understand the effect of urbanization on average daily temperature and extreme precipitation. Multivariate ENSO Index and Global Temperature Anomalies were taken as global physical drivers. Urbanization growth rate anomalies, annual mean temperature anomalies, and summer mean temperature anomalies were taken as local physical drivers that affect one-day extreme precipitation. 22 combinations of these physical drivers were used as covariates to develop extreme value models. Models were evaluated with the L-R test and AIC. It is found that global average temperature and urbanization, individually as well as in combination with local summer mean temperature, were found to be influencing local extreme precipitation. Changes in precipitation patterns have a direct impact on urban water management.https://doi.org/10.1007/s43762-022-00055-wAnomaliesGEVCovariateNon-stationarityUrbanization growthClimate change |
| spellingShingle | Sanskriti Mujumdar Chirayu Pandit Akash Patel Drivers influencing climate of growing cities Computational Urban Science Anomalies GEV Covariate Non-stationarity Urbanization growth Climate change |
| title | Drivers influencing climate of growing cities |
| title_full | Drivers influencing climate of growing cities |
| title_fullStr | Drivers influencing climate of growing cities |
| title_full_unstemmed | Drivers influencing climate of growing cities |
| title_short | Drivers influencing climate of growing cities |
| title_sort | drivers influencing climate of growing cities |
| topic | Anomalies GEV Covariate Non-stationarity Urbanization growth Climate change |
| url | https://doi.org/10.1007/s43762-022-00055-w |
| work_keys_str_mv | AT sanskritimujumdar driversinfluencingclimateofgrowingcities AT chirayupandit driversinfluencingclimateofgrowingcities AT akashpatel driversinfluencingclimateofgrowingcities |