Role of planetary boundary layer physics in urban-scale WRF model for predicting the heat waves over tropical city Bhubaneswar - Karrevula, Narayana Reddy; Boyaj, Alugula; Sinha, P; Nadimpalli, Raghu; Mohanty, U C; Islam, Sahidul; Kaginalkar, Akshara; Vinoj, V (Journal of Earth System Science, 2024)
Heat waves (HWs) are currently one of the most dangerous natural catastrophes both globally and in India, particularly upsurged in urban areas. Bhubaneswar, the capital city of Odisha in India, experiences heatwaves (HWs) each year from the pre-monsoon season to the onset of the summer monsoon. The manifest increase in intensity and frequency of HWs over Bhubaneswar leads to a higher death toll, and increasing vulnerability demands accurate prediction in advance over HWs-prone zones. Numerical weather prediction models are capable of predicting these HWs, subject to the customization of suitable physical parameterization schemes. In this context, the role of five planetary boundary layer (PBL) schemes such as Yonsei University (YSU), Asymmetric Convection Model version 2 (ACM2), Medium Range Forecast (MRF), Mellor–Yamada–Janjic (MYJ), and Bougeault Lacarrere (BouLac) are assessed in predicting six HW events over Bhubaneswar city using a very high-resolution (500 m horizontal resolution) Weather Research and Forecast (WRF) model. The model simulated results are verified against the Indian Monsoon Data Assimilation and Analysis (IMDAA) reanalysis of high-resolution gridded hourly datasets. The performance of the PBL schemes varies with the meteorological parameters that have a physical relationship with HWs. The composite of statistical analysis shows that the ACM2 scheme performs better for the maximum temperature with lesser root mean square error (RMSE) by 1.67°C. The BouLac shows a lesser RMSE of 1.25°C for the early morning temperature. ACM2 and BouLac schemes have replicated the zonal (meridional) wind with an RMSE of 1.47 and 1.79 m/s (2.86 and 2.81 m/s), respectively. Both the BouLac and ACM2 performed well in representing PBL height and relative humidity. The aggregated rank analysis reveals that BouLac and ACM2 are suitable for the prediction of HW over Bhubaneswar city. The city is underwarming during the HW period, and the UHI is about 0.77°C. PBL schemes are overestimating the UHI, and a possible reason might be representations in fluxes and land-atmosphere interactions. The spatial and temporal distribution of energy fluxes simulates the same over built-up areas irrespective of the PBL schemes used in the WRF model.