While destruction associated with floods during the monsoon season and cyclones receives wide att... more 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.
Rainfall in India has very high temporal and spatial variability. The rainfall variability affect... more Rainfall in India has very high temporal and spatial variability. The rainfall variability affects the livelihood and food habits of people from different regions. In this study, the rainfall trends in two stations in the north-eastern state of Tripura, namely Agartala and Kailashahar have been studied for the period 1955-2017. The state experiences an annual mean of more than 2000 mm of rainfall, out of which, about 60% occurs during the monsoon season and about 30% in pre-monsoon. An attempt has been made to analyze the trends in seasonal and annual rainfall, rainy days and heavy rainfall in the two stations, during the same period.Non-parametric Mann-Kendall test has been used to find out the significance of these trends. Both increasing and decreasing trends are observed over the two stations. Increasing trends in rainfall, rainy days and heavy rainfall are found at Agartala during pre-monsoon season and decreasing trends in all other seasons and at annual scale. At Kailashahar,...
Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring ar... more Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring areas in the pre-monsoon season. In this paper, the synoptic conditions, stability indices and lower level wind pattern associated with squalls at Agartala (23.90° N, 93.25° E) during 2011-2020 are analysed to obtain their percentage contributions and critical values in occurrence of the events. Five major synoptic conditions are found to have contribution to the events, with varying percentages. The critical values of Showalter Index, Lifted Index, K-Index, SWEAT Index, Total Totals Index are obtained based on their contribution for at least 80% of the events. Wind direction at 925 hPa and 850 hPa with southerly component is found to be another important precursor for occurrence of the squalls.
Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring ar... more Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring areas in the pre-monsoon season. In this paper, the synoptic conditions, stability indices and lower level wind pattern associated with squalls at Agartala (23.90° N, 93.25° E) during 2011 - 2020 are analysed to obtain their percentage contributions and critical values in occurrence of the events. Five major synoptic conditions are found to have contribution to the events, with varying percentages. The critical values of Showalter Index, Lifted Index, K-Index, SWEAT Index, Total Totals Index are obtained based on their contribution for at least 80% of the events. Wind direction at 925 hPa and 850 hPa with southerly component is found to be another important precursor for occurrence of the squalls.
While destruction associated with floods during the monsoon season and cyclones receives wide att... more 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.
Rainfall in India has very high temporal and spatial variability. The rainfall variability affect... more Rainfall in India has very high temporal and spatial variability. The rainfall variability affects the livelihood and food habits of people from different regions. In this study, the rainfall trends in two stations in the north-eastern state of Tripura, namely Agartala and Kailashahar have been studied for the period 1955-2017. The state experiences an annual mean of more than 2000 mm of rainfall, out of which, about 60% occurs during the monsoon season and about 30% in pre-monsoon. An attempt has been made to analyze the trends in seasonal and annual rainfall, rainy days and heavy rainfall in the two stations, during the same period.Non-parametric Mann-Kendall test has been used to find out the significance of these trends. Both increasing and decreasing trends are observed over the two stations. Increasing trends in rainfall, rainy days and heavy rainfall are found at Agartala during pre-monsoon season and decreasing trends in all other seasons and at annual scale. At Kailashahar,...
Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring ar... more Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring areas in the pre-monsoon season. In this paper, the synoptic conditions, stability indices and lower level wind pattern associated with squalls at Agartala (23.90° N, 93.25° E) during 2011-2020 are analysed to obtain their percentage contributions and critical values in occurrence of the events. Five major synoptic conditions are found to have contribution to the events, with varying percentages. The critical values of Showalter Index, Lifted Index, K-Index, SWEAT Index, Total Totals Index are obtained based on their contribution for at least 80% of the events. Wind direction at 925 hPa and 850 hPa with southerly component is found to be another important precursor for occurrence of the squalls.
Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring ar... more Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring areas in the pre-monsoon season. In this paper, the synoptic conditions, stability indices and lower level wind pattern associated with squalls at Agartala (23.90° N, 93.25° E) during 2011 - 2020 are analysed to obtain their percentage contributions and critical values in occurrence of the events. Five major synoptic conditions are found to have contribution to the events, with varying percentages. The critical values of Showalter Index, Lifted Index, K-Index, SWEAT Index, Total Totals Index are obtained based on their contribution for at least 80% of the events. Wind direction at 925 hPa and 850 hPa with southerly component is found to be another important precursor for occurrence of the squalls.
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Papers by Ranjan Phukan