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To address the requirement for improvement of forecasting of thunderstorms over the Indian subcontinent a special project was started since 2005 during the summer season. The present chapter provides details of developments since 2017, undertaken as a part of the Severe Thunderstorm Observation and Regional Modelling (STORM) program. The Forecast Demonstration Project of the STORM program as coordinated by India, is conducted during March to June every year. As a part of this project, there has been rapid expansion of observation tools as well as mesoscale model products that forecast weather associated with thunderstorms such as lightning, gusty winds and hail. Correspondingly there have been major improvements in forecasting quality in short range to nowcast scale with quantitative forecasts for thunderstorms being issued round the clock at three hour intervals for all districts of India and more than a thousand stations. Using the same metrics and a constant verification dataset, significant improvement is noted in all scores, both in short range as well as nowcasts scale for all subdivisions of India and all months of the FDP period (March to June). However, there are consistently higher forecast detection errors in short range scale over the arid western parts of India. On a monthly scale, all India short range thunderstorm forecast skill is generally lower in March as compared to April and May and June. However upon detailed analysis, it reflects a practical aspect of the forecast methodology adopted by an operational forecaster vis-à-vis the gradual increase in atmospheric moisture as the season progresses. With the increase in moisture in the lower troposphere as the season progresses, the probability of maturation of cumulus cells into cumulonimbus stage significantly increases and time taken to do so, decreases. The slight deterioration in scores in 2022 and 2023 compared to previous years may be ascribed to the unfavourable middle tropospheric conditions resulting in subdued thunderstorm activity over the Indian region compared to previous years.

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Severe Storms Forecasting and Forecast Demonstration Project Over the Indian Region

  • 章节

  • 发表日期：

    2025年

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  • Soma Sen Roy,
  • Pradeep Sharma,
  • M. Mohapatra

摘要

To address the requirement for improvement of forecasting of thunderstorms over the Indian subcontinent a special project was started since 2005 during the summer season. The present chapter provides details of developments since 2017, undertaken as a part of the Severe Thunderstorm Observation and Regional Modelling (STORM) program. The Forecast Demonstration Project of the STORM program as coordinated by India, is conducted during March to June every year. As a part of this project, there has been rapid expansion of observation tools as well as mesoscale model products that forecast weather associated with thunderstorms such as lightning, gusty winds and hail. Correspondingly there have been major improvements in forecasting quality in short range to nowcast scale with quantitative forecasts for thunderstorms being issued round the clock at three hour intervals for all districts of India and more than a thousand stations. Using the same metrics and a constant verification dataset, significant improvement is noted in all scores, both in short range as well as nowcasts scale for all subdivisions of India and all months of the FDP period (March to June). However, there are consistently higher forecast detection errors in short range scale over the arid western parts of India. On a monthly scale, all India short range thunderstorm forecast skill is generally lower in March as compared to April and May and June. However upon detailed analysis, it reflects a practical aspect of the forecast methodology adopted by an operational forecaster vis-à-vis the gradual increase in atmospheric moisture as the season progresses. With the increase in moisture in the lower troposphere as the season progresses, the probability of maturation of cumulus cells into cumulonimbus stage significantly increases and time taken to do so, decreases. The slight deterioration in scores in 2022 and 2023 compared to previous years may be ascribed to the unfavourable middle tropospheric conditions resulting in subdued thunderstorm activity over the Indian region compared to previous years.