Evaluation of WRF high-resolution simulation of extreme precipitation over the New York city metropolitan area

Extreme rainfall can lead to severe flooding, particularly in densely populated megacities where urban infrastructure alters natural hydrological processes. Understanding these dynamics is essential for accurate forecasting and risk mitigation. This study examines the New York City Metropolitan Area (NYCMA) during Superstorm Ida (September 2021) to assess how urbanization influences the simulation of precipitation patterns. Using the Weather Research and Forecasting (WRF) model, we tested multiple configurations of microphysics, cumulus, and urban parameterization schemes to evaluate model performance under urban conditions. Simulated rainfall was compared against ground-based observations and Multi-Radar Multi-Sensor (MRMS) data to identify strengths and limitations of WRF for urban forecasting. Results indicate that the best performance for urban areas was achieved with the Multi-layer Building Environment Parameterization (BEP) scheme, the Purdue Lin microphysics scheme, and the Betts-Miller cumulus scheme. These findings underscore the importance of tailored model configurations for improving operational forecasts of extreme precipitation in complex urban environments. When the WRF model was used operationally with Global Forecast System (GFS) data, the results were consistent with those obtained using ERA5 with the best-performing combination of schemes, suggesting that the WRF model can reliably and operationally predict heavy precipitation events over the NYCMA.