Prediction of convective events using multi-frequency radiometric observations at Kolkata

Abstract: The behaviors of various meteorological parameters during 1981–2010 are investigated to obtain any asymmetric variability of summertime near surface wind over Indian coastal boundaries. No significant changes were obtained in the trends of surface pressure, surface relative humidity, 2-metre temperature and surface precipitation; although, near surface wind speed is found to have significantly declined on the eastern coast with respect to the western coast during this period. Summertime surface wind speed on the eastern coast have decreased from 3.5 to 2.5 m s − 1 (7 to 5 knots) whereas 4.5 to 4 m s − 1 (9 to 8 knots) during the last three decades (statistical significance level ~ 95%). A decrease in the atmospheric instability may serve as the potential reason for the suppression of severe convective occurrences manifested by a parallel decrease in surface wind speeds over these regions. The local heating up of middle atmosphere (300–500 hPa pressure level) due to increased humidity and the difference in net heat flux over Arabian Sea and Bay of Bengal due to the variance of temperature gradient (1000–925 hPa) along the coastal boundaries might be responsible for this climatic disparity between the coastal regions of India since the last three decades. Summertime near surface wind speed projections for Indian sub-continent based on 7 best climate models, for RCP8.5 scenarios, has been calculated to show a mean increase by ~ 10–15% on the eastern coast (Eastern Ghats), ~ 1–2% on the western coasts (Western Ghats), ~ 1–5% decrease in the Indo-Gangetic Basin and ~ 3% decrease in the Gangetic West Bengal and adjoining Bangladesh.

Abstract: 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.

Abstract: An evaluation of convective cloud forecasts performed with the numerical weather prediction (NWP) model COSMO and extrapolation of cloud fields is presented using observed data derived from the geostationary satellite Meteosat Second Generation (MSG). The present study focuses on the nowcasting range (1–5 h) for five severe convective storms in their developing stage that occurred during the warm season in the years 2012–2013. Radar reflectivity and extrapolated radar reflectivity data were assimilated for at least 6 h depending on the time of occurrence of convection. Synthetic satellite imageries were calculated using radiative transfer model RTTOV v10.2, which was implemented into the COSMO model. NWP model simulations of IR10.8 μm and WV06.2 μm brightness temperatures (BTs) with a horizontal resolution of 2.8 km were interpolated into the satellite projection and objectively verified against observations using Root Mean Square Error (RMSE), correlation coefficient (CORR) and Fractions Skill Score (FSS) values. Naturally, the extrapolation of cloud fields yielded an approximately 25% lower RMSE, 20% higher CORR and 15% higher FSS at the beginning of the second forecasted hour compared to the NWP model forecasts. On the other hand, comparable scores were observed for the third hour, whereas the NWP forecasts outperformed the extrapolation by 10% for RMSE, 15% for CORR and up to 15% for FSS during the fourth forecasted hour and 15% for RMSE, 27% for CORR and up to 15% for FSS during the fifth forecasted hour. The analysis was completed by a verification of the precipitation forecasts yielding approximately 8% higher RMSE, 15% higher CORR and up to 45% higher FSS when the NWP model simulation is used compared to the extrapolation for the first hour. Both the methods yielded unsatisfactory level of precipitation forecast accuracy from the fourth forecasted hour onward.

Abstract: Convection has a significant role in maintaining the atmospheric dynamics and thermodynamics, particularly in the tropical regions during pre-monsoon season, which may be due to the changing patterns in atmospheric instability and pollution. A critical analysis is done on the variability of instability indices and their significant signature to meteorological parameters and atmospheric pollution over Indian region in the warming atmosphere during 2005–2015. The present study represents that the solid as well as gaseous pollutants, in combination, produce a damping force in suppressing convective activities over the eastern coastal regions of India. A significant anti-correlation (r ~ − 0.6 to − 0.8) between instability parameters [Convective Available Potential Energy (CAPE) and Lifted Index (LI)] and atmospheric pollutants [gaseous (NO2 and SO2) and solid (BC and PM2.5)] has been obtained in the eastern coastal regions on a long-term basis. To improve the level of agreement between pollution and instability, a unitless and dimensionless index called KLURT index has been introduced, which provides correlation (r) value as high as ~ 0.6. On a real time basis, KLURT index is found to be useful as an effective precursor of thunderstorm events. The final part of this study indicates a prediction technique using KLURT index which gives a high prediction efficacy of 75%, low FAR value, extremely good BS 0.06, an excellent bias (~ 0.96) and a good lead time of 1 h for a threshold value of 12.5 in terms of predicting intense convections at the urban location, Kolkata. Thus, the present study provides an appropriate means to manifest convection as a function of changing anthropogenic factors both in long and short-term basis with high correlation values and provides significant efficacy in predicting severe weather, thereby demonstrating the usefulness of this hypothesis in various socio-economic aspects especially at the current tropical urban location.

Abstract: Microwave radiometer is an effective instrument to monitor the atmosphere continuously in different weather conditions. It measures brightness temperatures at different frequency bands which are subjected to standard retrieval methods to obtain real time profiles of various atmospheric parameters such as temperature and humidity. But the retrieval techniques used by radiometer have to be adaptive to changing weather condition and location. In the present study, three retrieval techniques have been used to obtain the temperature and relative humidity profiles from brightness temperatures, namely; piecewise linear regression, feed forward neural network and neural back propagation network. The simulated results are compared with radiosonde observations using correlation analysis and error distribution. The analysis reveals that neural network with back propagation is the most accurate technique amongst the three retrieval methods utilized in this study.

Abstract: This paper reviews the status of forecasting convective precipitation for time periods less than a few hours (nowcasting). Techniques for nowcasting thunderstorm location were developed in the 1960s and 1970s by extrapolating radar echoes. The accuracy of these forecasts generally decreases very rapidly during the first 30 min because of the very short lifetime of individual convective cells. Fortunately more organized features like squall lines and supercells can be successfully extrapolated for longer time periods. Physical processes that dictate the initiation and dissipation of convective storms are not necessarily observable in the past history of a particular echo development; rather, they are often controlled by boundary layer convergence features, environmental vertical wind shear, and buoyancy. Thus, successful forecasts of storm initiation depend on accurate specification of the initial thermodynamic and kinematic fields with particular attention to convergence lines. For these reasons ...

Abstract: This paper presents the time-dependent analysis of the thunderstorm gust front with the use of Project NIMROD data. RHI cross sections of reflectivity and Doppler velocity are constructed to determine the entire vertical structure. The life cycle of the gust front is divided into four stages: (1) the formative stage; (2) the early mature stage; (3) the late mature stage; and (4) the dissipation stage. A new finding is a horizontal roll detected in the reflectivity pattern resulting from airflow that is deflected upward by the ground, while carrying some of the smaller precipitation ahead of the main echo core of the squall line. This feature is called a 'precipitation roll'. As determined from rawinsonde data, the cold air behind the gust front accounts for the observed surface pressure rise. Calculations confirm that the collision of two fluids produce a nonhydrostatic pressure at the leading edge of the outflow. The equation governing the propagation speed of a density current accurately predicts the movement of the gust front.

Abstract: [1] In the present study, the feasibility of nowcasting convective activity is examined by using thermodynamic indices derived from the ground-based microwave radiometer (MWR) observations located at a tropical station, Gadanki (13.5°N, 79.2°E). There is a good comparison between thermodynamic parameters derived from MWR and colocated GPS radiosonde observations, indicating that MWR observations can be used to develop techniques for nowcasting severe convective activity. Using MWR observations, a nowcasting technique was developed with the data of 26 thunderstorm cases observed at Gadanki. The analysis showed that there are sharp changes in some thermodynamic indices, such as the K index, the humidity index, precipitable water content, the stability index, and equivalent potential temperature lapse rates, about 2–4 h before the occurrence of thunderstorm. A superepoch analysis was made to examine the composite temporal variations of the thermodynamic indices associated with the occurrence of thunderstorms. The superepoch analysis revealed that 2–4 h prior to the storm occurrence, appreciable variations in many parameters are observed, suggesting thermodynamic evolution of the boundary layer convective instability. It is further demonstrated that by monitoring these variations it is possible to predict the ensuing thunderstorm activity over the region at least 2 h in advance. The association between the temporal evolution of thermodynamic indices and convective activity has been tested for the independent case of nine thunderstorms. The present results suggest that ground-based MWR observations can be used effectively to predict the occurrence of thunderstorms at least 2 h in advance.