Studies on ocean surface layer responses to atmospheric forcing in the North Indian Ocean

The present study on upper ocean responses to atmospheric forcing (associated with cyclone passage) in North Indian Ocean revealed significant variability between AS and BoB. The analysis of cyclone frequency during 1947 to 2006 exhibited lesser frequency of cyclones in AS than that of BoB. The analysis also revealed significant reduction in cyclone frequency after the year 1976 with substantial reduction during monsoon season. The long term SST data at selected points in AS and BoB could not reveal any relation with reduction in cyclone frequency. However the SLP at same locations exhibited considerable increase during mid 1970’s, which could have contributed to the observed reduction in cyclone frequency after the year 1976.The response in waves during cyclone passage exhibited significant asymmetry on either side of the track in AS and BoB and the response is observed at 100’s of kilometers away from the track. The significant clockwise rotation in wave direction is observed on the right side of the track starting from near the track to far away locations, which existed for a longer duration. However, the anticlockwise rotation in wave direction is observed over a shorter distance on the left side of the track and dissipated immediately.Inertial oscillation is observed in surface current and in the mixed layer temperature associated with cyclone passage, which revealed the role of relative location(s) on either side of the track. The inertial peak closer to the local inertial period indicates maximum transfer of energy during the cyclone passage in both AS and BoB. The absence of strong inertial oscillation even with clockwise rotation in surface current and wind indicates the dominant role of duration of strong wind in generating inertial oscillation.The oceanic response associated with cyclone passage reveal the variable response(s) which depends on cyclone intensity, the proximity to track and cyclone translation speed. It is observed that resonance with wind generates higher response in surface current, wave and SST on the right side of the track and it lasts for a longer duration. The maximum oceanic response is observed at a few kilometers away on right side of the track. However lesser rightward bias in the location of maximum cooling is observed for cyclones with low cyclone translation speed. The response on the left side of the track is less and is limited over a shorter distance and dissipates immediately. It is observed that the ocean response, in general, increases with intensity of cyclones. However the differential cooling produced by the same intensity cyclones in AS and in BoB indicates the dominant role of low cyclone translation speed in oceanic response.The surface cooling exhibited strikingly differential responses between AS and BoB. The TMI-SST and buoy observations exhibited significant cooling for a longer duration in AS compared to that of BoB. The spatial extent of cooling is also much higher in AS than that of BoB. The wide spread cooling associated with cyclone passage in AS indicates the dominant role of thermal structure in oceanic response in AS than that of BoB.

Environmental Influences on the Frequency and Intensity of North Indian Ocean Tropical Cyclones

Tropical cyclones genesis, movement and intensification are highly dependent on its environment both oceanic and atmospheric. This thesis has made a detailed study on the environmental factors related to tropical cyclones of North Indian Ocean basin. This ocean basin has produced only 6% of the global tropical cyclones annually but it has caused maximum loss of human life associated with the strong winds, heavy rain and particularly storm surges that accompany severe cyclones as they strike the heavily populated coastal areas. Atmospheric factors studied in the thesis are the moisture content of the atmosphere, instability of the atmosphere that produces thunderstorms which are the main source of energy for the tropical cyclone, vertical wind shear to which cyclones are highly sensitive and the Sub-Tropical westerly Jetsteram and its Asian high speed center. The oceanic parameters studied are sea surface temperature and heat storage in the top layer of the ocean. A major portion of the thesis has dealt with the three temporal variabilities of tropical cyclone frequency namely intra-seasonal (mainly the influence of Madden Julian Oscillation), inter- annual (the relation with El Nino Southern Oscillation) and decadal variabilities. Regarding decadal variability, a prominent four decade oscillation in the frequency of both tropical cyclones and monsoon depressions unique to the Indian Ocean basin has been brought out. The thesis consists of 9 chapters.

Spatial and temporal characteristics of rain intensity in the peninsular Malaysia using TRMM rain rate

The present study is focused on the intensity distribution of rainfall in different classes and their contribution to the total seasonal rainfall. In addition, we studied the spatial and diurnal variation of the rainfall in the study areas. For the present study, we retrieved data from TRMM (Tropical Rain Measuring Mission) rain rate available in every 3 h temporal and 25 km spatial resolutions. Moreover, station rainfall data is used to validate the TRMM rain rate and found significant correlation between them (linear correlation coefficients are 0.96, 0.85, 0.75 and 0.63 for the stations Kota Bharu, Senai, Cameron highlands and KLIA, respectively). We selected four areas in the Peninsular Malaysia and they are south coastal, east coastal, west coastal and highland regions. Diurnal variation of frequency of rain occurrence is different for different locations. We noticed bimodal variation in the coastal areas in most of the seasons and unimodal variation in the highland/inland area. During the southwest monsoon period in the west coastal stations, there is no distinct diurnal variation. The distribution of different intensity classes during different seasons are explained in detail in the results

Long term trends of seasonal and monthly rainfall in different intensity ranges over Indian subcontinent

In general Indian summer monsoon rainfall did not show any significant trend in all Indian summer monsoon rainfall series, however, it was reported that the ISMR is subjected to spatial trends. This paper made an attempt to bring out long term trends of different intensity classes of summer monsoon rainfall in different regions of Indian subcontinent. The long term trend of seasonal and monthly rainfall were also made using the India Meteorological Department gridded daily rainfall data with a spatial resolution of 1° × 1° latitude-longitude grid for the period from 1st January, 1901 to 31st December, 2003. The summer monsoon rainfall shows an increasing trend in southeast, northwest and northeast regions, whereas decreasing trend in the central and west coastal regions. In monthly scale, July rainfall shows decreasing trend over west coastal and central Indian regions and significant increasing trend over northeast region at 0.1% significant level. During the month August, decreasing trend is observed in the west coastal stations at 10% significant level. In most of the stations, mean daily rainfall shows an increasing trend for low and very high intense rainfall. For the moderate rainfall, the trend is different for different regions. In the central and southern regions the trend of moderate and moderately high classes show increasing trend. And for the high and very high intensity classes, the trend is decreasing significantly. In the northeastern regions, above 10 mm/day rainfall shows significantly increasing trend with 0.1% significant level.

A New Gridding Technique for High Density Microarray Images Using Intensity Projection Profile of Best Sub Image

As the technologies for the fabrication of high quality microarray advances rapidly, quantification of microarray data becomes a major task. Gridding is the first step in the analysis of microarray images for locating the subarrays and individual spots within each subarray. For accurate gridding of high-density microarray images, in the presence of contamination and background noise, precise calculation of parameters is essential. This paper presents an accurate fully automatic gridding method for locating suarrays and individual spots using the intensity projection profile of the most suitable subimage. The method is capable of processing the image without any user intervention and does not demand any input parameters as many other commercial and academic packages. According to results obtained, the accuracy of our algorithm is between 95-100% for microarray images with coefficient of variation less than two. Experimental results show that the method is capable of gridding microarray images with irregular spots, varying surface intensity distribution and with more than 50% contamination

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.