Future urban rainfall projections considering the impacts of climate change and urbanization with statistical–dynamical integrated approach

  • Hiteshri Shastri
  • Subimal GhoshEmail author
  • Supantha Paul
  • Hossein Shafizadeh-Moghadam
  • Marco Helbich
  • Subhankar Karmakar


Impacts of global warming and local scale urbanization on precipitation are evident from observations; hence both must be considered in future projections of urban precipitation. Dynamic regional models at a fine spatial resolution can capture the signature of urbanization on precipitation, however simulations for multiple decades are computationally expensive. In contrast, statistical regional models are computationally inexpensive but incapable of assessing the impacts of urbanization due to the stationary relationship between predictors and predictand. This paper aims to develop a unique modelling framework with a demonstration for Mumbai, India, where future urbanization is projected using a Markov Chain Cellular Automata approach, long term projections with climate change impacts are performed using statistical downscaling and urban impacts are simulated with a dynamic regional model for limited number of years covering different precipitation characteristics. The evaluation of the statistical downscaling methodology over historical time period reveals large underestimation of the extreme rainfall, which is improved effectively by applying another regression model, for extreme days. The limited runs of dynamic downscaling models with different stages of urbanization for Mumbai, India, reveal spatially non uniform changes in precipitation, occurring primarily at the higher quantiles. The statistical and dynamical outputs are further integrated using quantile transformation for precipitation projection in Mumbai during 2050s. The projections show dominant impacts of urbanization compared to those from large scale changing patterns. The uniqueness of this computationally efficient framework lies in an integration of global and local factors for precipitation projections through a conjugal statistical–dynamical approach.


Precipitation downscaling Extreme precipitation Urbanization Mumbai India 



The work presented here is supported financially by Ministry of Water Resources (Project no.: 06/23/2013-INCSW/194-213); Ministry of Earth Sciences (MoES), Government of India, (Project reference numbers MoES/PAMC/H&C/35/2013-PC-II and MoES/PAMC/H&C/36/2013-PC-II); and Department of Science and Technology. The authors sincerely thank the Editor and the two anonymous reviewers for reviewing this manuscript and providing constructive comments to improve the quality. The precipitation data is collected from India Meteorological department, Pune and is available from this organization. The reanalysis data used are from ERA-Interim and available at the website. The land use data is collected from LANDSAT.

Supplementary material

382_2018_4493_MOESM1_ESM.docx (2 mb)
Supplementary material 1 (DOCX 2017 KB)


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Authors and Affiliations

  1. 1.Interdisciplinary Program in Climate StudiesIndian Institute of Technology BombayMumbaiIndia
  2. 2.M. S. Patel Deartment of Civil EngineeringC. S. Patel Institute of Technology, Charotar University of Science and TechnologyAnandIndia
  3. 3.Department of Civil EngineeringIndian Institute of Technology BombayMumbaiIndia
  4. 4.Department of GIS and Remote SensingTarbiat Modares UniversityTehranIran
  5. 5.Department of Human Geography and Spatial PlanningUtrecht UniversityUtrechtThe Netherlands
  6. 6.Centre for Environmental Science and EngineeringIndian Institute of Technology BombayMumbaiIndia

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