Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments
Predicting the onset times of precipitation over densely populated cities for the purposes of timely evacuation is a challenge. This paper explored a flooding event over an urban built environment in a South Asian mega city, Chennai, where extant urban planning models rely on predicted rainwater amo...
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MDPI AG
2022-02-01
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author | Siddharth Gumber Satyajit Ghosh |
author_facet | Siddharth Gumber Satyajit Ghosh |
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description | Predicting the onset times of precipitation over densely populated cities for the purposes of timely evacuation is a challenge. This paper explored a flooding event over an urban built environment in a South Asian mega city, Chennai, where extant urban planning models rely on predicted rainwater amounts for early warning and impact assessment studies. However, the time duration of flooding events is related to the nature of the urban sprawl in the built environment. Any evacuation measure is invariably tied down to the time duration over which the precipitation event occurs, and therefore to the expected time of a precipitation event to begin. In this context, a crucial parameter useful to municipal authorities is the onset time of precipitation. This study used optimised analytical formulations to predict this time, and the derived analytical expressions for the case study yielded comparable times estimated from a computer-intensive full-scale large eddy model within an accuracy of 2%. It is suggested that municipal authorities (who are non-experts in fluid mechanics) use this early prediction for the purposes of quick alerts to a congested city’s most vulnerable citizens within urban sprawls. However, for the procedure to work at its best, it involves a two-stage procedure. The first step involves the use of a parcel model to obtain the expected cloud droplet spectral spreads based on the prevailing dynamical characterisations. The second step involves an optimisation procedure involving cloud spectral properties from the first step to quantify both the auto-conversion rates and the threshold. Thereafter, an onset time calculation based on cloud properties is estimated. These new results are cast in closed form for easy incorporation into meteorological applications over a variety of urban scales. Rain mass amounts were also predicted analytically and used to configure Aeronautical Reconnaissance Coverage Geographic Information System (ARCGIS) to compute low drainage flow rates over the vulnerable parts of Chennai city. It was found that heavy precipitation over the North Chennai region yielded discharge rates to the tune of ~250 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi mathvariant="normal">m</mi><mn>3</mn></msup><msup><mi mathvariant="normal">s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></semantics></math></inline-formula> during a 24 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mi mathvariant="normal">h</mi></mrow></mrow></semantics></math></inline-formula> period, causing intense flooding in the low-lying areas around the Cooum River basin with a large population density, with estimates sufficiently corroborating observations. |
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spelling | doaj.art-7ee7595a7f5f47c387454d64875d725d2023-11-24T00:25:44ZengMDPI AGAtmosphere2073-44332022-02-0113337010.3390/atmos13030370Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built EnvironmentsSiddharth Gumber0Satyajit Ghosh1School of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, IndiaSchool of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, IndiaPredicting the onset times of precipitation over densely populated cities for the purposes of timely evacuation is a challenge. This paper explored a flooding event over an urban built environment in a South Asian mega city, Chennai, where extant urban planning models rely on predicted rainwater amounts for early warning and impact assessment studies. However, the time duration of flooding events is related to the nature of the urban sprawl in the built environment. Any evacuation measure is invariably tied down to the time duration over which the precipitation event occurs, and therefore to the expected time of a precipitation event to begin. In this context, a crucial parameter useful to municipal authorities is the onset time of precipitation. This study used optimised analytical formulations to predict this time, and the derived analytical expressions for the case study yielded comparable times estimated from a computer-intensive full-scale large eddy model within an accuracy of 2%. It is suggested that municipal authorities (who are non-experts in fluid mechanics) use this early prediction for the purposes of quick alerts to a congested city’s most vulnerable citizens within urban sprawls. However, for the procedure to work at its best, it involves a two-stage procedure. The first step involves the use of a parcel model to obtain the expected cloud droplet spectral spreads based on the prevailing dynamical characterisations. The second step involves an optimisation procedure involving cloud spectral properties from the first step to quantify both the auto-conversion rates and the threshold. Thereafter, an onset time calculation based on cloud properties is estimated. These new results are cast in closed form for easy incorporation into meteorological applications over a variety of urban scales. Rain mass amounts were also predicted analytically and used to configure Aeronautical Reconnaissance Coverage Geographic Information System (ARCGIS) to compute low drainage flow rates over the vulnerable parts of Chennai city. It was found that heavy precipitation over the North Chennai region yielded discharge rates to the tune of ~250 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi mathvariant="normal">m</mi><mn>3</mn></msup><msup><mi mathvariant="normal">s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></semantics></math></inline-formula> during a 24 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mi mathvariant="normal">h</mi></mrow></mrow></semantics></math></inline-formula> period, causing intense flooding in the low-lying areas around the Cooum River basin with a large population density, with estimates sufficiently corroborating observations.https://www.mdpi.com/2073-4433/13/3/370planetary boundary layerurban meteorologyauto-conversionaccretionflooding alerts |
spellingShingle | Siddharth Gumber Satyajit Ghosh Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments Atmosphere planetary boundary layer urban meteorology auto-conversion accretion flooding alerts |
title | Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments |
title_full | Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments |
title_fullStr | Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments |
title_full_unstemmed | Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments |
title_short | Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments |
title_sort | quick predictions of onset times and rain amounts from monsoon showers over urban built environments |
topic | planetary boundary layer urban meteorology auto-conversion accretion flooding alerts |
url | https://www.mdpi.com/2073-4433/13/3/370 |
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