Nowcasting of heavy rain events using microwave radiometer has been carried out at Kolkata (22.65°N, 88.45°E), a tropical location. Microwave radiometer can produce the temperature and humidity profiles of the atmosphere with fairly good accuracy. Definite changes are observed in temperature and humidity profiles before and at the onset of heavy rain events. Concurrent changes in the brightness temperatures (BT) at 22. GHz and 58. GHz are found to be suitable to nowcast rain. The time derivatives of brightness temperatures at 22. GHz and 58. GHz are used as inputs to the proposed nowcasting model. In addition, the standard deviation of the product of these time derivatives is also considered. The model has been developed using the data of 2011 and validated for rain events of 2012-2013 showing a prediction efficiency of about 90% with alarm generated about 25. min in advance. © 2014 Elsevier B.V.

R CHAKRABORTY

S DAS

S JANA

A MAITRA

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Journal of Hydrology

The behavior of atmospheric electric field in terms of potential gradient (PG) has been studied during the period of 2013 and 2014 at a tropical and urban location Kolkata (22°34′N, 88°22′E), India. The clear-weather PG is influenced by varying concentration of black carbon, which is a major pollutant in urban atmosphere. The diurnal variation of the clear-day PG follows that of the black carbon concentration in all the seasons. It is found that cloud base height and liquid water path correlate well with the PG change in convective events. It is shown that during a convective event the PG change measured over 10-min interval about 30&nbsp;min before the onset of rain can approximate impending rain accumulation. ©2019. American Geophysical Union. All Rights Reserved.

Fulltext

Journal of Geophysical Research: Atmospheres

Electric Field Variation in Clear and Convective Conditions at a Tropical Urban Location

The spectral reflectivity in terms of Doppler velocity obtained by micro rain radar (MRR) at a tropical location can reveal the splitting of Doppler spectrum of falling rain drops caused by strong downdraft. The phenomenon, known as aliasing, occurs in Doppler spectrum of MRR during intense convective events. In this case, the rain drop velocity exceeds the unambiguous Doppler velocity range that can be sensed by MRR. The downdraft affecting the raindrop velocity significantly causes an ambiguity in the Doppler spectrum of the radar signal scattered from raindrops. The aliasing effect is most prominent near the boundary layer height (0.8–2 km) for convective rain. Also at this altitude range, the resultant height gradient obtained from ECMWF vertical velocity of air mass data and drop terminal velocity, is maximum. The importance of the present study lies in the fact that the split in Doppler spectrum can be utilized to estimate downdraft velocity during rain. The de-aliasing technique has been applied to the raw Doppler spectrum of MRR to retrieve the rain drop size distribution conforming to ground based measurements. © 2018 COSPAR

Advances in Space Research

Aliasing effect due to convective rain in Doppler spectrum observed by micro rain radar at a tropical location

A nowcasting technique has been proposed to estimate the impending rain accumulation using ground-based radiometric measurements at Kolkata (22.65°N, 88.45°E), a tropical location. It has been observed that the normalized variation of brightness temperature (BT) at 31 GHz along with the standard deviation of BT at 22 GHz and instability indices, namely, lifting index, have shown definite changes before rain events. A combination of these three parameters can be effective in predicting rain events both qualitatively and quantitatively. Accordingly, a prediction model is developed and tested on several intense rain events during the period 2014-2015. The model is found to perform reasonably well in predicting intense rain about 70-75 min in advance with an efficiency of 80%. © 1980-2012 IEEE.

IEEE Transactions on Geoscience and Remote Sensing

Prediction of Rain Occurrence and Accumulation Using Multifrequency Radiometric Observations

Radiometric observations of relative humidity profile at Kolkata show a significant fall at around 1 to 2 km height during convective rain events. An extensive investigation shows that the fall of relative humidity is not seen during calm conditions but is strongly related to the characteristics of temperature lapse rate profiles. Moreover, the phenomenon may have strong association with boundary layer structure. The reason for such anomalies in the planetary boundary layer humidity profile might be due to the release of latent heat at the mentioned altitude. The abundance of pollutant aerosols in urban regions has also been found to contribute to this relative humidity anomaly. It has also been reported that this boundary layer relative humidity is accompanied by high latent heat release and condensation of vapour to liquid which is not much prominent in other rain types as observed in stratiform rain. Hence, convective rain produces some unique boundary layer characteristics which have also been partially supported with allied satellite and multi-station observations. © 2017 Elsevier B.V.

Atmospheric Research

Anomalies in relative humidity profile in the boundary layer during convective rain

Automatic nowcasting of convective initiation and thunderstorms has potential applications in several sectors including aviation planning and disaster management. In this paper, random forest based machine learning algorithm is tested for nowcasting of convective rain with a ground based radiometer. Brightness temperatures measured at 14 frequencies (7 frequencies in 22–31 GHz band and 7 frequencies in 51–58 GHz bands) are utilized as the inputs of the model. The lower frequency band is associated to the water vapor absorption whereas the upper frequency band relates to the oxygen absorption and hence, provide information on the temperature and humidity of the atmosphere. Synthetic minority over-sampling technique is used to balance the data set and 10-fold cross validation is used to assess the performance of the model. Results indicate that random forest algorithm with fixed alarm generation time of 30 min and 60 min performs quite well (probability of detection of all types of weather condition ∼90%) with low false alarms. It is, however, also observed that reducing the alarm generation time improves the threat score significantly and also decreases false alarms. The proposed model is found to be very sensitive to the boundary layer instability as indicated by the variable importance measure. The study shows the suitability of a random forest algorithm for nowcasting application utilizing a large number of input parameters from diverse sources and can be utilized in other forecasting problems. © 2017 COSPAR

A random forest algorithm for nowcasting of intense precipitation events

Nowcasting of thunderstorm has important implication on minimizing the loss of properties and life. Conventional approaches for such purpose using radiometer measured brightness temperature of only water vapor line usually tend to overestimate the occurrence probability. In this paper, we demonstrate that use of brightness values of oxygen absorption lines in addition with the water vapor absorption lines can provide unique signature of heavy rain. © 2012 IEEE.

Journal	Data powered by TypesetJournal of Hydrology
Publisher	Data powered by TypesetElsevier
ISSN	0022-1694