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<p>High-resolution urban climate downscaling is used to assess city-scale climate risks, yet its key sources of uncertainty remain insufficiently examined. While most studies address emissions and model-driven uncertainties, those from local urbanisation pathways are rarely quantified. As a result, the reliability of urban climate projections used for impact assessment and adaptation remains poorly constrained. This study quantifies the uncertainties in urban climate projections associated with future urbanisation, with a case study of Hanoi, a rapidly urbanising metropolis in Southeast Asia. Urban climate is simulated using the Weather Research and Forecasting model within the pseudo-global warming dynamical downscaling approach under three urban growth scenarios (Status Quo, Objective Prediction, and Master Plan) and two emissions pathways (RCP 8.5 and RCP 4.5). The findings reveal that greenhouse-gas forcing and urban expansion significantly intensify local warming, with projected July temperatures rising by up to 3.8&#xa0;°C under RCP 8.5 and the Master Plan scenario. Notably, temperature differences among urban scenarios reach 0.5&#xa0;°C, with locally higher values of up to 1.0&#xa0;°C in areas experiencing substantial land-use change. This difference is comparable to the spread between the two RCPs of 1.5&#xa0;°C, highlighting the apparent uncertainty introduced by alternative urban transition pathways. It is worth noting that this urbanisation effect is spatially confined to the city and its immediate surroundings, rather than to the broader impacts of global warming. Together, this study highlights an often-overlooked challenge: the magnitude of urbanisation-related uncertainty, though limited in spatial extent, can be comparable to that associated with emissions scenarios or model spread. The results emphasise the need to explicitly integrate urban development scenarios into climate downscaling. This study contributes both methodological insights and a policy-relevant warning: future urban climate cannot be credibly assessed without accounting for the shape of the cities themselves.</p>

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More than just emissions: urbanisation scenarios as a significant source of climate projection uncertainty

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月7日

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  • Lidia Lazarova Vitanova,
  • Thanh-Hung Nguyen,
  • Nguyen-Xuan Thanh,
  • Do Ngoc Khanh,
  • Quang-Van Doan

摘要

High-resolution urban climate downscaling is used to assess city-scale climate risks, yet its key sources of uncertainty remain insufficiently examined. While most studies address emissions and model-driven uncertainties, those from local urbanisation pathways are rarely quantified. As a result, the reliability of urban climate projections used for impact assessment and adaptation remains poorly constrained. This study quantifies the uncertainties in urban climate projections associated with future urbanisation, with a case study of Hanoi, a rapidly urbanising metropolis in Southeast Asia. Urban climate is simulated using the Weather Research and Forecasting model within the pseudo-global warming dynamical downscaling approach under three urban growth scenarios (Status Quo, Objective Prediction, and Master Plan) and two emissions pathways (RCP 8.5 and RCP 4.5). The findings reveal that greenhouse-gas forcing and urban expansion significantly intensify local warming, with projected July temperatures rising by up to 3.8 °C under RCP 8.5 and the Master Plan scenario. Notably, temperature differences among urban scenarios reach 0.5 °C, with locally higher values of up to 1.0 °C in areas experiencing substantial land-use change. This difference is comparable to the spread between the two RCPs of 1.5 °C, highlighting the apparent uncertainty introduced by alternative urban transition pathways. It is worth noting that this urbanisation effect is spatially confined to the city and its immediate surroundings, rather than to the broader impacts of global warming. Together, this study highlights an often-overlooked challenge: the magnitude of urbanisation-related uncertainty, though limited in spatial extent, can be comparable to that associated with emissions scenarios or model spread. The results emphasise the need to explicitly integrate urban development scenarios into climate downscaling. This study contributes both methodological insights and a policy-relevant warning: future urban climate cannot be credibly assessed without accounting for the shape of the cities themselves.