13.5 Model-Based Automation of Urban Effect Classification Taking the Example of Berlin, Germany

Thursday, 10 January 2019: 2:30 PM
North 127ABC (Phoenix Convention Center - West and North Buildings)
Judith M Lorenz, Technische Universität Dresden, Dresden, Germany; and J. Liu, L. Yang, M. L. Baeck, J. Smith, K. K. Osuri, C. Bernhofer, and D. Niyogi

The effect of increased urbanization on rainfall modification has been observed and modeled for multiple cities and regions in the past. Thorough event-based, long-term evaluations are often missing and there is a need for standard classification approaches for assessing and grouping the rainfall modification (splitting, enhancement, dissipation, etc). An observational event-based, gridded analysis of rainfall extremes around Berlin (Germany) for storms occurring between 2006 and 2016 has been carried out, revealing notable signatures of urban rainfall modification. Daytime storms were found to be attenuated (decayed), potentially due to UHI influence, whereas night time storms were found to be exaggerated (intensified) by urban feedbacks. The study also showed a weekday versus weekend changes in rainfall characteristics as well as wind-direction dependent storm morphologies. Building on these findings, we are further analyzing the role of urban areas on storm features by conducting WRF experiments on selected test cases. The findings of the experiments help improve our understandings of the local impacts of aerosols, temperature as well as land surface heterogeneity on storm patterns. Results are considered helpful to improve the classification scheme of storm behavior in urban vicinity. Additionally, this presentation will discuss an automated approach to classify the storm features, using a storm tracking algorithm. The synthesis of the gridded observational analysis, automated storm classification and experimental setups will build comprehensive understanding of role of cities play in rainfall modification.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner