While destruction associated with floods during the monsoon season and cyclones receives wide attention, the extreme weather in the form of hail, lightning and high winds have also caused widespread devastation over India on a small spatial scale in recent years, especially during the period of March to June. India Meteorological Department (IMD) organized a special forecast improvement campaign during the period March to June of 2017–2019 when the weather forecasts at all offices of IMD were targeted towards an accurate forecast of the extreme form of thunderstorms and their associated impact in short range to nowcasting timescale and their dissemination. The purpose of this study is to quantify the improvement in operational thunderstorm forecast accuracy, in short range (24 h Severe Weather Guidance at subdivisional level) and nowcast scale (nowcasts for individual stations valid for 3 h and issued every three hours) during March to June of 2017 to 2019 and compare the same with the accuracy of previous years. As a result of these efforts, there has been a significant jump in forecast accuracy in the 24-h thunderstorm forecast as well as 3-h nowcast guidance for thunderstorms across the country. Probability of Detection (POD) scores for India as a whole for the 24-h thunderstorm forecast has doubled, while the false alarms (FAR) have remained at the same level as before the start of the forecast campaign. The results indicate that since a thunderstorm is a disastrous weather event, the forecasters generally tend towards spatial over-forecasting. However, this is not uniform across the months. There is systematic lower accuracy in the season transition months of March (winter to summer) and June (dry summer to wet summer). While POD decreases in both March and June, FAR decrease throughout the season. The significant evolution of atmospheric parameters (moisture in particular) as the season changes, favours the maturation of thunderstorms to cumulonimbus stage as the season progresses, and the problem of over forecasting in March becomes a problem of under forecasting of thunderstorms in June. Another reason for false alarms is the unconscious linkage of the thunderstorm with the pattern of rainfall occurrence. However, since all rain-giving clouds over India do not necessarily mature to the cumulonimbus stage, and vice versa, the two are not always related. This is particularly true for the more arid regions of the country, especially in March, where false alarms are higher. The poor density of reporting observatories compared to the mesoscale nature of the events may also increase false alarms, especially over the small maritime islands and the arid regions of the mainland. The accuracy of the All India 3 hourly station level nowcast also improved systematically since 2017. Despite these constraints, the improvements at all scales were possible due to (a) augmentation of observation network by the rapid expansion of Doppler radars network throughout the Indian mainland as well as the installation of a ground-based lightning detection network, (b) numerical modeling products introduced in 2019 to provide short-range forecasts for all aspects of convection; both of which are incorporated into the forecast framework through Standard Operating Procedures (SOP) to standardize the forecast procedure throughout the Indian region. A more objective forecast strategy, using data generated from a denser network of DWRs and crowdsourcing methods as well as more accurate mesoscale models will go a long way to further improve the thunderstorm forecasts.

尽管季风季节和旋风中与洪水有关的破坏受到广泛关注，但近年来，冰雹，闪电和强风等极端天气也造成了印度小范围的大规模破坏，尤其是在三月期间到六月 印度气象局（IMD）在2017-2019年3月至6月期间组织了一次特殊的预报改善运动，当时IMD所有办公室的天气预报都旨在准确预报雷暴的极端形式及其在短期内的相关影响即将播出的时标及其传播。这项研究的目的是量化操作雷暴预报准确性的提高，在2017年3月至6月至2019年的短期范围内（分区级别的24小时严酷天气指南）和临近预报规模（有效期3小时且每三小时发布的单个电台的临近预报），并将其与前几年的准确性进行比较。这些努力的结果是，全国24小时雷暴预报的预报准确性以及3小时雷暴预报的3h预报指南有了很大的提高。印度在整个24小时雷暴天气预报中的整体检测概率（POD）得分增加了一倍，而虚假警报（FAR）则保持与预报运动开始之前的水平相同。结果表明，由于雷暴是灾难性的天气事件，因此预报员通常倾向于空间过度预报。但是，这在整个几个月中并不统一。在三月（冬季至夏季）和六月（夏季干燥至潮湿的夏季）的季节过渡月份中，系统准确性较低。虽然三月和六月的POD下降，但整个季节的FAR下降。随着季节的变化，大气参数（尤其是水分）的显着变化，随着季节的进行，有利于雷暴向积雨阶段过渡，3月的过度预报问题变成了6月的雷暴预报不足的问题。造成误报的另一个原因是无意识的雷暴与降雨发生方式的联系。但是，由于印度上空的所有降雨云不一定都已经达到积雨云阶段，反之亦然，因此这两者并不总是相关的。对于该国较干旱的地区尤其如此，特别是在三月份，虚假警报的发生率更高。与事件的中尺度性质相比，报告天文台的密度较差，也可能增加误报，特别是在小海洋岛屿和大陆干旱地区。自2017年以来，全印度3小时站位临近预报的准确性也得到系统地提高。尽管存在这些限制，但由于（a）多普勒雷达网络在整个印度大陆的迅速扩展，扩大了观测网络，因此在所有规模上都有可能得到改善。以及安装了地面雷电检测网络，（b）2019年推出的数值模拟产品可提供对流各个方面的短期预报; 两者都通过标准操作程序（SOP）纳入了预测框架，以标准化整个印度地区的预测程序。使用更密集的DWR网络和众包方法生成的数据以及更准确的中尺度模型来制定更客观的预测策略，将对进一步改善雷暴预报有很大帮助。