Sutapa Chaudhuri

PREDICTABILITY OF CHAOS INHERENT IN THE OCCURRENCE OF SEVERE THUNDERSTORMS

The purpose of the present study is to investigate the existence of deterministic chaos in the time series of occurrence or non-occurrence of severe thunderstorms of the pre-monsoon season over the Northeastern part of India. Results from the current study reveal the existence of chaos in the relevant time series. The corresponding predictabilities are also computed quantitatively. The study recommends that the formulation of numerical weather prediction models for forecasting the occurrence of this high frequency meso-scale convective system must take into account the intrinsic chaos.

Mann-Kendall trend of pollutants, temperature and humidity over an urban station of India with forecast verification using different ARIMA models.

The purpose of the present research is to identify the trends in the concentrations of few atmospheric pollutants and meteorological parameters over an urban station Kolkata (22° 32′ N; 88° 20′ E), India, during the period from 2002 to 2011 and subsequently develop models for precise forecast of the concentration of the pollutants and the meteorological parameters over the station Kolkata. The pollutants considered in this study are sulphur dioxide (SO2), nitrogen dioxide (NO2), particulates of size 10-μm diameters (PM10), carbon monoxide (CO) and tropospheric ozone (O3). The meteorological parameters considered are the surface temperature and relative humidity. The Mann–Kendall, non-parametric statistical analysis is implemented to observe the trends in the data series of the selected parameters. A time series approach with autoregressive integrated moving average (ARIMA) modelling is used to provide daily forecast of the parameters with precision. ARIMA models of different categories; ARIMA (1, 1, 1), ARIMA (0, 2, 2) and ARIMA (2, 1, 2) are considered and the skill of each model is estimated and compared in forecasting the concentration of the atmospheric pollutants and meteorological parameters. The results of the study reveal that the ARIMA (0, 2, 2) is the best statistical model for forecasting the daily concentration of pollutants as well as the meteorological parameters over Kolkata. The result is validated with the observation of 2012.

Neuro-computing based short range prediction of some meteorological parameters during the pre-monsoon season

A Feed forward multi-layered artificial neural network model is designed in this paper to estimate the maximum surface temperature and relative humidity needed for the genesis of severe thunderstorms over Calcutta (22° 32′, 88° 20′). The performance of the model is found to be adroit. It has, thus, been discerned that the neural network technique is of great use in forecasting the occurrence of high frequency small-scale weather systems like Severe Local Storms. Filing up the missing values and extension of time series is observed to be possible with this model. Prediction error is computed and compared for single layer network and one hidden layer neural nets. Result reveals the efficiency of the one hidden layer neural net.

The reciprocal relation between lightning and pollution and their impact over Kolkata, India.

Aerosol loading in the atmosphere can cause increased lightning flashes, and those lightning flashes produce NOX, which reacts in sun light to produce surface ozone. The present study deals with the effect of surface pollutants on premonsoon (April–May) lightning activity over the station Kolkata (22.65° N, 88.45° E). Seven-year (2004–2010) premonsoon thunderstorms data are taken for the study. Different parameters like aerosol optical depth and cloud top temperature from the Moderate Resolution Imaging Spectroradiometer satellite products along with lightning flash data from Tropical Rainfall Measuring Mission’s (TRMM) Lightning Imaging Sensor are analyzed. Some surface pollution parameters like suspended particulate matter, particulate matter 10, nitrogen oxides (NOX), and surface ozone (O3) data during the same period are taken account for clear understanding of their association with lightning activity. Heights of convective condensation level and lifting condensation level are collected from radiosonde observations to anticipate about cloud base. It is found that increased surface pollution in a near storm environment is related to increased lightning flash rate, which results in increased surface NOX and consequently increased surface ozone concentration over the station Kolkata.

The Applicability of Bipartite Graph Model for Thunderstorms Forecast over Kolkata

Single Spectrum Bipartite Graph (SSBG) model is developed to forecast thunderstorms over Kolkata during the premonsoon season (April-May). The statistical distribution of normal probability is observed for temperature, relative humidity, convective available potential energy (CAPE), and convective inhibition energy (CIN) to quantify the threshold values of the parameters for the prevalence of thunderstorms. Method of conditional probability is implemented to ascertain the possibilities of the occurrence of thunderstorms within the ranges of the threshold values. The single spectrum bipartite graph connectivity model developed in this study consists of two sets of vertices; one set includes two time vertices (00UTC, 12UTC) and the other includes four meteorological parameters: temperature, relative humidity, CAPE, and CIN. Three distinct ranges of maximal eigen values are obtained for the three categories of thunderstorms. Maximal eigenvalues for severe, ordinary, and no thunderstorm events are observed to be , , and , respectively. The ranges of the threshold values obtained using ten year data (1997–2006) are considered as the reference range and the result is validated with the IMD (India Meteorological Department) observation, Doppler Weather Radar (DWR) Products, and satellite images of 2007. The result reveals that the model provides 12- to 6-hour forecast (nowcasting) of thunderstorms with 96% to 98% accuracy.

Appraisal of the prevalence of severe tropical storms over Indian Ocean by screening the features of tropical depressions

Tropical cyclones are one of the nature’s most violent manifestations and potentially the deadliest of all meteorological phenomena. It is a unique combination of violent wind, heavy rainfall, and mountainous waves in sea. The maximum sustained wind speed, minimum sea level pressure, and the radius of maximum winds are important parameters for understanding a particular tropical cyclone and to differentiate it from a depression to tropical storms. The objective of this particular paper is to identify a possible range of maximum sustained wind speed, minimum sea level pressure, and radius of maximum winds which facilitates tropical depressions to lead to tropical storms over Bay of Bengal and Arabian Sea of Indian Ocean basin. The method of rough set theory which is based on condition—decision support system is implemented for the purpose. The result reveals that the threshold ranges of the maximum sustained wind speed, minimum sea level pressure and radius of maximum winds associated with tropical depression are possible that can aid in the predictability of tropical storm over Indian Ocean. The results are validated with significant tropical storms of 2009 and 2010 observations through Doppler and satellite imageries.

Swell Propagation over Indian Ocean Region

Swells are the ocean surface gravity waves that have propagated out of their generating fetch to the distant coasts without significant attenuation. Therefore they contain a clear signature of the nature and intensity of wind at the generation location. This makes them a precursor to various atmospheric phenomena like distant storms, tropical cyclones, or even large scale sea breeze like monsoon. Since they are not affected by wind once they propagate out of their generating region, they cannot be described by regional wave models forced by local winds. However, their prediction is important, in particular, for ship routing and off shore structure designing. In the present work, the propagation of swell waves from the Southern Ocean and southern Indian Ocean to the central and northern Indian Ocean has been studied. For this purpose a spectral ocean Wave Model (WAM) has been used to simulate significant wave height for 13 years from 1993–2005 using NCEP blended winds at a horizontal spatial resolution of 1° × 1°. It has been observed that Indian Ocean, with average wave height of approximately 2–3 m during July, is mostly dominated by swell waves generated predominantly under the extreme windy conditions prevailing over the Southern Ocean and southern Indian Ocean. In fact the swell waves reaching the Indian Ocean in early or mid May carry unique signatures of monsoon arriving over the Indian Subcontinent. Pre-monsoon month of April contains low swell waves ranging from 0.5–1 m. The amplitudes subsequently increase to approximately 1.5–2 meters around 7–15 days prior to the arrival of monsoon over the Indian Subcontinent. This embedded signature may be utilized as one of the important oceanographic precursor to the monsoon onset over the Indian Ocean.

CHAOTIC GRAPH THEORY APPROACH FOR IDENTIFICATION OF CONVECTIVE AVAILABLE POTENTIAL ENERGY (CAPE) PATTERNS REQUIRED FOR THE GENESIS OF SEVERE THUNDERSTORMS

Severe thunderstorms are a manifestation of deep convection. Conditional instability is known to be the mechanism by which thunderstorms are formed. The energy that drives conditional instability is convective available potential energy (CAPE), which is computed with radio sonde data at each pressure level. The purpose of the present paper is to identify the pattern or shape of CAPE required for the genesis of severe thunderstorms over Kolkata (22°32′N, 88°20′E) confined within the northeastern part (20°N to 24°N latitude, 85°E to 93°E longitude) of India. The method of chaotic graph theory is adopted for this purpose. Chaotic graphs of pressure levels and CAPE are formed for thunderstorm and non-thunderstorm days. Ranks of the adjacency matrices constituted with the union of chaotic graphs of pressure levels and CAPE are computed for thunderstorm and non-thunderstorm days. The results reveal that the rank of the adjacency matrix is maximum for non-thunderstorm days and a column with all zeros occurs very quickly on severe thunderstorms days. This indicates that CAPE loses connectivity with pressure levels very early on severe thunderstorm days, showing that for the genesis of severe thunderstorms over Kolkata short, and therefore broad, CAPE is preferred.

A hybrid model to estimate the depth of potential convective instability during severe thunderstorms

The purpose of the present paper is to view the role of theta parameters in the genesis of severe thunderstorms of pre-monsoon season over northeastern part of India. The method adopted to achieve the objective is a Hybrid soft computing system comprising of Ampliative Reasoning (AR) and Simulated Annealing (SA). The results of the study reveal a very important finding that the occurrence of such severe weather hazard requires conditional instability up to the altitude of 4.5 km. whereas convective instability persists up to 3.5 km altitude. Thus, for the genesis of severe thunderstorms of pre-monsoon season the atmosphere must have potential convective instability up to the altitude 3.5 km and the conditional instability has to persist little more.

The influence of El Niño on the Indian summer monsoon rainfall anomaly: a diagnostic study of the 1982/83 and 1997/98 events

AbstractThe Indian summer monsoon of 1982 and 1997 depicts disparities, however, maximum sea surface temperature anomaly over Niño 3 region is observed in the following winter of both the years. The inter-annual variation of sea surface temperature anomaly shows maximum peak during 1982/83 and 1997/98 El Niño events. The inter-annual variation of multivariate ENSO index also supports the above observation. The analyses of the entire tropical Pacific basin including the equatorial region reveal an anomalous behavior of the mean sea level pressure (MSLP) and the convective activities. The observations further reveal that the negative anomaly in monsoon rainfall over India prevails throughout the monsoon season except for the month of August in 1982, while in the year 1997 the monsoon rainfall anomaly shows random variations. The comparison between the summer monsoon rainfall of 1982 and 1997 depicts that the magnitude of the positive anomaly is same in the month of August. The condition over tropical Pacific during 1982/83 and 1997/98 has been investigated through the variation of outgoing long wave radiation (OLR), MSLP and pressure vertical velocity. The time–longitude plots of OLR and MSLP reveal the changes in pressure distribution and convective pattern over the tropical equatorial Pacific. The zonal and meridional cross section of pressure vertical velocity over the tropical Pacific and tropical Indian Ocean facilitates to understand the strength of the vertical motion during the monsoons of 1982 and 1997.