Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool
The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the b...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2014/456065 |
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| author | Swagata Payra Manju Mohan |
| author_facet | Swagata Payra Manju Mohan |
| author_sort | Swagata Payra |
| collection | DOAJ |
| description | The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD) approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF) model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions. |
| format | Article |
| id | doaj-art-0f183185361444f58f965fa26111042f |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-0f183185361444f58f965fa26111042f2025-02-03T06:00:44ZengWileyAdvances in Meteorology1687-93091687-93172014-01-01201410.1155/2014/456065456065Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling ToolSwagata Payra0Manju Mohan1Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, IndiaCentre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, IndiaThe prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD) approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF) model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions.http://dx.doi.org/10.1155/2014/456065 |
| spellingShingle | Swagata Payra Manju Mohan Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool Advances in Meteorology |
| title | Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool |
| title_full | Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool |
| title_fullStr | Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool |
| title_full_unstemmed | Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool |
| title_short | Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool |
| title_sort | multirule based diagnostic approach for the fog predictions using wrf modelling tool |
| url | http://dx.doi.org/10.1155/2014/456065 |
| work_keys_str_mv | AT swagatapayra multirulebaseddiagnosticapproachforthefogpredictionsusingwrfmodellingtool AT manjumohan multirulebaseddiagnosticapproachforthefogpredictionsusingwrfmodellingtool |