The myxosporean Enteromyxum leei is known to infect a wide range of marine fish hosts. The objective of the present study was to determine whether freshwater fish species are also receptive hosts to this parasite. Seventeen species of freshwater fish were experimentally fed E. leeiinfected gut tissue from donor gilthead sea bream Sparus aurata obtained from a commercial sea bream cage farm. Four of the tested species, tiger barb Puntius tetrazona, zebra danio Danio rerio, oscar Astronotus ocellatus and Mozambique tilapia Oreochromis mossambicus, were found to be susceptible with prevalences ranging from 53 to 90%. The course of infection and pathology was limited to the gut mucosa epithelium and was similar to that observed in marine hosts. Little is known of the differences in physiological conditions encountered by a parasite in the alimentary tract of freshwater vs. marine teleost hosts, but we assume that a similar osmotic environment is maintained in both. Parasite infectivity may be influenced by differences in the presence or absence of a true stomach, acidic gastric pH and digestive enzyme activity both in the stomach and intestine. Variability in susceptibility among species may also stem from differences in innate immunity. Dimensions of spores produced in the donor sea bream and recipient freshwater species are variable in size, as previously observed in other captive marine host species. KEY WORDS: Direct transmission · Myxosporea · Sparus aurata · Danio · Oreochromis · Puntius · AstronotusResale or republication not permitted without written consent of the publisher

Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in an attempt to predict thunderstorm activity on any given day. A combination of multiple regression, logistic regression, and range analysis provides new insight into the prediction of these storms. A supervised machine learning-based logistic regression model is developed in this study for thunderstorm prediction over Patna and can be further extended for operational forecasting of Thunderstorms over the region. Critical thresholds for the instability indices are determined over the considered locations providing valuable insight into the domain of Thunderstorm prediction

The statistical characteristics like frequencies of occurrence, time of onset, duration, time of dispersal and intensity of fog over Guwahati airport are found out and analysed using 10 years data during 1994-95 to 2003-04 for the months of November to February. Also the interannual and intraseasonal variations of occurrence of fog are analysed by calculating the coefficient of variation of monthly frequency of fog and by calculating the significant periodicities in the daily probability of occurrence of fog respectively. The meteorological parameters at 1200 UTC leading to fog in the following night or morning over Guwahati airport are analysed to find out the precursors for occurrence of fog. Statistical characteristics are given in tables and their significance discussed. It is observed that monitoring of Dew Point Depression (DPD) and surface wind can help prediction of occurrence of fog and its intensity over Guwahati airport.

A study is undertaken to analyse the characteristics of squall over Delhi and to find out the potential precursors for its prediction. For this purpose, the squall data of Indira Gandhi International (IGI) airport along with the surface and upper air meteorological parameters recorded by India Meteorological Department have been considered for all individual months over the period of 2001-2010. Apart from the characteristics like period of occurrence, intensity, duration, frequency and nature of squall, the environmental changes due to squall and thermodynamic features and indices leading to squall have been analysed. Higher than normal warming of lower troposphere upto 700 hPa level in March, April & June and at 925 hPa in May accompanied with cold dry air advection leading to lower than normal dew point in middle and upper levels (500-300 hPa in March, May and June, 400-300 hPa in April) are favourable for occurrence of the squall over Delhi. The lower level inversion in March and April only also helps in the occurrence of squall. In monsoon months of July- September, cold and dry air advection in middle and upper tropospheric levels (8- 15° C below normal dew point at 400-300 hPa in July, about 15° C below normal dew point at 300-200 hPa in August and 17- 24° C below normal dew point at 500-300 hPa in September) favours occurrence of squall over Delhi. Unlike pre-monsoon months lower level moisture does not play any role for the occurrence of squall over Delhi in monsoon months. Significantly higher than normal SWEAT index in March to September at 0000 UTC can be used as predictor of squall over Delhi on that day. Total totals index is the next suitable precursor for all the months except June.

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