Response of local weather to urban induced land-use change: A study over eastern and southern Indian cities

Abstract

Urban transition is an unstoppable process in developing countries. Despite the planning measures, the growing cities face the impact of urbanisation in the form of severe LU alteration. Though land use and land cover (LULC) change process, during urbanization, is relatively localised, it has regional and global impacts. Urban induced LULC change affects land-atmospheric interactions due to changes in surface energy budget and anthropogenic activities. Urbanisation process can severely affect the diurnal temperature, circulation pattern and spatial-temporal rainfall distribution over a city. Therefore, the main objectives of the thesis includes both observational and numerical modelling techniques for quantifying the urban sprawl and dynamics, analyzing the longterm urban climatology and examining the role of urban induced LU change during extreme weather events like heatwaves, thunderstorms and urban floods. Urban dynamics of cities using satellite data and ‘spatial metrics” based indices are analysed to quantify the urban LU increase in different cities. Observational data is used to understand the effect of urban growth on long-term climatology. For both urban growth, dynamics and climatological analyses, the Tier-I cities like Chennai, Bengaluru, Hyderabad and Kolkata and the Tier-II cities like Bhubaneswar-Cuttack, Ranchi, Visakhapatnam and Coimbatore are considered. Multiple numerical simulation-based experiments were carried out considering the mentioned weather events over some of these cities. The urban induced LU change impact is examined using different types of LULC data in the weather research and forecasting (WRF) model with varying urban fractions. The concerned cities of this study experienced a massive load of population inflow, industrialisation, and economic development. Since all these cities have the potential to grow as a future megacity, there is an urge to assess the current scenario of urban sprawl dynamics for careful design of the city and policymaking. Tier-I cities like Chennai and Hyderabad experience spreading of the city core, but Kolkata and Bengaluru mostly show infill growth. These cities show compact development up to ~25–35km radius and mushrooming of satellite townships towards the periphery is seen. Ribbon developments along the expressways are found connecting to the nearby small towns. Among the tier- II cities, Visakhapatnam develops a secondary core and expanding rapidly than the central core, while Ranchi shows the highest degree of sprawling. Fanning and fringe development are predominant for Coimbatore city. Both Cuttack and Bhubaneswar are approaching towards each other to form a single metropolitan. The analysis suggests the growth of the cities expanding its boundary irrespective of their geographical location and type. Climatological analysis suggests both increase and decrease of the diurnal temperature range (DTR) over different cities. The decrease and increase in DTR are due to the increase in minimum temperature and overall general warming due to global warming respectively. An overall increase in rainfall and lighting activity is seen for pre and post-monsoon days indicating the enhancement of convective processes over cities. Urban induced LU change incorporated in the model using updated ISRO LU. The impact of LU change is examined by analyzing the outputs from updated ISRO and older USGS LU based simulations. During HW episodes, the analysis revealed that the Tmax is hardly affected due to the LU change while most prominent increment in Tmin is seen. The increment in Tmin contributed to the decrease in DTR, causing maximum discomfort for city dwellers during the HW episode. Computed urban heat island (UHI) shows higher values for updated LU considerations indicating the feedback from larger impervious areas. For all the simulated cases, higher UHI variation found over industrial cities followed by near coastal cities similarly the LU change simulation is mostly noticed over the industrial city, while moderate and least effect seen for near-coastal ones. Comparative analysis has confirmed that UHI development is highly localised and unique to each city, while the amplitude of UHI is related to the type of the city whether industry dominated or not. The UHI correlation to the size of the city did not hold good for our case because of the geographical location and influence of large water body inside the city. Experiments for thunderstorms (TS) using recent LU based simulations predict most of the rainfall inside the city boundary towards the northern and southern part of the Bhubaneswar-Cuttack urban-complex with significant improvements in the amount. Major amount of rainfall is found to be distributed in the downwind direction being influenced by the southwesterly circulation. The simulations confirm that the urban area does play an important role in the spatial distribution and temporal variation of precipitation in the current scenario. For the case of Kolkata metropolitan, model results reveal a higher precipitation distribution over high-density urban areas. Results for the impacts during urban flooding event over Chennai were found to be sensitive to urban growth incorporated in different LU data sets for prediction of rainfall and surface runoff. The most significant impact was noted with updated urban LU. Urban induced LU change played an important role in redistributing the rainfall and the convection build-up. Higher runoff is simulated by the experiments with a high fraction of urban LU than the low urban LU, which inhibits the percolation process and enhances more surface flow of runoff water. The flood scenario was due to the enhanced runoff as a consequence of the increased urban built-ups and impervious layers in the metropolitan area. Though the large scale systems caused the extreme rainfall event prevailed over the Bay of Bengal, the role of urban impervious layers in enhancing the surface runoff and thereby causing the flood scenario cannot be denied. The impressions of updated urban LU is apparent in simulating the weather events like HW, TS and extreme rainfall causing urban flood and must be accounted for in emerging urban modelling systems.