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Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain

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Abstract

The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM2.5 predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM2.5 which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM2.5 concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM2.5 to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM2.5 by a chemical transport model.

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Data availability statement

The datasets generated during and/or analyzed during the current study are available upon request from Dr. Sachin D. Ghude (sachinghude@tropmet.res.in).

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Acknowledgements

We are grateful to the Executive Director and the Director General of C-DAC. We would like to acknowledge the Director, IITM, for the support and for providing the necessary facilities to carry out the research work. We would like to thank the high-performance computing support from Aditya and Pratyush provided by the Indian Institute of Tropical Meteorology, Pune. We would like to thank CPCB, Winter Fog Experiment (WiFEX) campaign, for providing surface PM2.5 data; GFS, NCMRWF, and ECMWF for providing reanalysis dataset.

Funding

This work was supported by the National Supercomputing Mission (NSM) program grant.

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Authors and Affiliations

  1. Indian Institute of Tropical Meteorology (IITM), Ministry of Earth Sciences, Pune, India

    Preeti Gunwani, Gaurav Govardhan, Prafull Yadav, Sreyashi Debnath, Pooja V. Pawar, Sandeep Wagh, Dilip Chate & Sachin D. Ghude

  2. National Centre for Medium-Range Weather Forecasting, Ministry of Earth Sciences, Noida, India

    Gaurav Govardhan

  3. India Meteorological Department, Ministry of Earth Sciences, Delhi, India

    Chinmay Jena

  4. Computational Earth Science Group, Centre for Development of Advanced Computing, Pune, India

    Santosh Kulkarni, Manoj Khare & Akshara Kaginalkar

  5. National Center for Atmospheric Research, Boulder, USA

    Rajesh Kumar

  6. Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India

    Prafull Yadav & Sreyashi Debnath

  7. Meteorological Centre Ranchi, India Meteorological Department, Ministry of Earth Sciences, Ranchi, India

    Preeti Gunwani

  8. Department of Chemical Technology, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India

    Pooja V. Pawar

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  1. Preeti Gunwani
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  2. Gaurav Govardhan
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Correspondence to Preeti Gunwani or Gaurav Govardhan.

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Gunwani, P., Govardhan, G., Jena, C. et al. Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain. Environ Monit Assess 195, 560 (2023). https://doi.org/10.1007/s10661-023-10987-3

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