Snowfall Statistics of Some SASE Field Stations in J&K

North-west Himalayan region comprises five mountain ranges. Their orientation and complexterrain influence the weather over the region. Sudden altitudinal changes also affect the weathersystems to a considerable extent . Due to the prevailing in homogeneous topography, various dynamicand thermal processes take place at mesoscale level. In synoptic scale, during winter seasons, weathersystems, named, western disturbance (WD), take their southerly track and travel over J&K, HP andhills of western UP, and yield considerable amount of precipitation. On the basis of past historicaldata collected over J&K region, the pattern of snowfall and its frequency distribution was studiedusing statistical means. Variation of these snowfall spells was also studied to understand spatial andtemporal changes in their distribution. A brief case study of a WD has been carried out to estimatemoisture flux inflow over Himalayas

Location-specific prediction of the probability of occurrence and quantity of precipitation over the Western Himalayas

Northwest India is composed, in part, of complex Himalayan mountain ranges having different altitudes and orientations, causing the prevailing weather conditions to be complex. During winter, a large amount of precipitation is received in this region due to eastward-moving low pressure synoptic weather systems called western disturbances (WDs). The objective of the present study is to use the perfect prognostic method (PPM) for probability of precipitation (PoP) forecasting and quantitative precipitation forecasting (QPF). Three observatories in the western Himalayan region, namely, Sonamarg, Haddan Taj, and Manali, are selected for development of statistical dynamical models for location-specific prediction of the occurrence and quantity of precipitation. Reanalysis data from the National Centers for Environmental Prediction (NCEP), and upper-air and surface observations from the India Meteorological Department (IMD), are used to develop statistical dynamical models for PoP and QPF for winter, that is, December, January, February, and March (DJFM). Models are developed with data from DJFM 1984-96 and tested with data from DJFM 1996-97. Four experiments are carried out with four different sets of predictors to evaluate the performance of the models with independent datasets. They are 1) NCEP-NCAR reanalysis data, 2) operational analyses from the National Centre for Medium RangeWeather Forecasting (NCMRWF) in India, 3) day 1 forecasts with a T80 global spectral model at NCMRWF, and 4) forecasts from the regional fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) day 1 forecast. Forecast skills are examined for these four experiments and for direct numerical model outputs of T80 day 1 and MM5 day 1 forecasts at these three stations. It is found that a best prediction is made with an accuracy of 89% at Haddan Taj using the MM5 day 1 forecast as predictors in the PoP model. In the case of the QPF model, a maximum 85% accuracy is achieved using the MM5 day 1 forecast variables as predictors. Thus, use of numerical model output from MM5 as predictors in statistical dynamical models based on the PPM concept provides definite improvements in the prediction of occurrence and quantity of precipitation as compared to the direct numerical model output

Numerical simulation of a rare winter hailstorm event over Delhi, India on 17 January 2013

This study analyzes the cause of the rare occurrence of a winter hailstorm over New Delhi/NCR (National Capital Region), India. The absence of increased surface temperature or low level of moisture incursion during winter cannot generate the deep convection required for sustaining a hailstorm. Consequently, NCR shows very few cases of hailstorms in the months of December-January-February, making the winter hail formation a question of interest. For this study, a recent winter hailstorm event on 17 January 2013 (16:00–18:00 UTC) occurring over NCR is investigated. The storm is simulated using the Weather Research and Forecasting (WRF) model with the Goddard Cumulus Ensemble (GCE) microphysics scheme with two different options: hail and graupel. The aim of the study is to understand and describe the cause of hailstorm event during over NCR with a comparative analysis of the two options of GCE microphysics. Upon evaluating the model simulations, it is observed that the hail option shows a more similar precipitation intensity with the Tropical Rainfall Measuring Mission (TRMM) observation than the graupel option does, and it is able to simulate hail precipitation. Using the model-simulated output with the hail option; detailed investigation on understanding the dynamics of hailstorm is performed. The analysis based on a numerical simulation suggests that the deep instability in the atmospheric column led to the formation of hailstones as the cloud formation reached up to the glaciated zone promoting ice nucleation. In winters, such instability conditions rarely form due to low level available potential energy and moisture incursion along with upper level baroclinic instability due to the presence of a western disturbance (WD). Such rare positioning is found to be lowering the tropopause with increased temperature gradient, leading to winter hailstorm formation

Statistical model-based forecast of minimum and maximum temperatures at Manali

Various types of avalanches frequent northwest Himalayan regions during winter months. Winter season over this region is frequented by westwardmoving weather systems called western disturbances (WDs). These weather systems yield enormous amount of precipitation. Knowledge of minimum and maximum temperatures during winter months is very useful for assessing human and natural hazards. Models for forecasting minimum and maximum temperatures have been developed for Manali in Himanchal Pradesh, for the months of December, January and February. These models are based on statistical techniques and use surface and upper air meteorological data from 1984 to 1989. The models are also tested with independent data and the results for 1995-96 are presented. The models yield good results with independent cases providing about 88% correct forecast within ±2°C of the observed values

Transdermal Drug Delivery System in Veterinary Practice: An Overview

In veterinary practice drug delivery strategies are complicated by species diversity, body size variations, cost constraints and level of convenience. A new frontier in the administration of therapeutic drugs to veterinary species is transdermal drug delivery system. It implies topical drug application to achieve systemic pharmacological effects. Its efficacy is primarily dependent upon the barrier properties of the targeted species skin, as well as the ratio of the area of the patch to the species total body mass needed to achieve effective systemic drug concentrations. The candidate drug must have sufficient lipid solubility to be considered for transdermal delivery. The adhesive of the patches is critical to the safety, efficacy and quality of the product. This novel drug delivery system offers many advantages over conventional oral and invasive methods of drug delivery like reduction in hepatic first pass metabolism, enhancement of therapeutic efficiency, maintenance of steady plasma level of the drug and improved owner compliance. With efficient experimental designs and available transdermal patch technology, there are no obvious hurdles for the development of effective therapeutic agents in veterinary practice

Minimum temperature forecast at Manali, India

Northern India is comprised of complex Himalayan mountain ranges having different altitude and orientation. Knowledge of minimum temperature in this region during winter months is very useful for assessing human comfort and natural hazards. In the present study, Perfect Prognostic temperature at one of the stations, Manali, in Pir Panjal range of Himalayas. Firstly, a statistical dynamical model is developed for assessing next day's temperature category, i.e.≤0°C or >0°C. Once the category is known, then temperature forecast model is developed for that category. Statistical dynamical models are developed for winter season, December, January, February and March (DJFM) using multivariate regression analysis. Model is developed with data of DJFM for 12 years (1984-96) and tested with data of DJFM for the year 1996-97. Analysis data from National Center for Environmental Prediction (NCEP), US, station surface and upper air data of three stations of India Meteorological Department (IMD), India and surface data at Manali are used. Four experiments are carried out with four different sets of predictors to evaluate performance of the models with independent data sets. They are: (i) NCEP reanalysis Center for Medium Range Weather Forecasting (NCMRWF) in India, (iii) day 1 forecast with a T80 global spectral model at NCMRWF and (iv) forecasts from the regional mesoscale model MM% day 1 forecast. A comparison of skill is drawn among these four set of experiments. It is found that best prediction for temperature category is made with an accuracy of 71.2% with MM5 day 1 forecast as predictors in temperature category forecast model. Further, temperature forecast model for ≤0°C category selects only station data and shows skill of 62.1% with independent data, whereas, model for >0°C category selected predictor from numerical analysis also. Here MM5 day 1 forecast makes best prediction with 90.0% skill

Cloudbursts in Indian Himalayas: a review

Cloudbursts in and around the southern rim of the Indian Himalayas are elusive in terms of their position and time of occurrences. Most of the reported cloudbursts are in the interior of the Himalayas and hence their observation itself is limited. Most of these events are reported once their affect in terms of loss to life and property is experienced in the downstream habitats. In addition, they are mostly associated with flash floods as an impact of the torrential precipitation. The principal understanding of the cloudburst is associated with sudden heavy deluge of precipitation in very less time interval over a very small area. Except this understanding and India Meteorology Department (IMD) definition of > 100 mm/h precipitation over a geographical region of approximately 20–30 km2, nothing much else is known about these events. There are a very few studies carried out on understanding of these events. Present paper synthesizes the available information and research on cloudburst events and tries to define it based on associated dynamics, thermodynamics and physical processes leading to a cloudburst event. Thus in the present work, characterizations and impacts of cloudburst leading from precipitation to dynamical to thermodynamical to large scale forcings to orographical forcings to followed geomorphology to impacts are intertwined to present comprehensive portray of it. Most of the cloudburst events are seen occurring in the elevation range of 1000 m to 2500 m within the valley folds of the southern rim of the Indian Himalayas. Apart from some of the large scale flow shown by few of the studies, it is found that cloudburst events are convectively triggered followed by orographically locked systems. These intertwined mechanisms lead cloudburst events to form. Amiss of any one of these mechanisms will not lead the cloudburst mechanism to form. These interactions in the present paper established the vagaries associated with the cloudburst events

Disturbance of oxidant/antioxidant balance, acute phase response and high mobility group box–1 protein in acute undifferentiated diarrhea in crossbred piglets

The objective of the present study was to investigate the status of high mobility group box–1 (HMGB1) protein, oxidative stress and acute phase proteins in natural cases of acute undifferentiated diarrhoea in piglets aged 1–15 days old. The study was conducted on 30 crossbred (Landrace × indigenous) piglets; fifteen suffering from acute enteritis (group 1) and fifteen healthy piglets as control (group 2). The diarrhoea was diagnosed on the basis of clinical symptoms. From the results of the study, it is concluded that HMGB1 protein, markers of oxidative stress and acute phase proteins might play important roles in the pathophysiology of piglet diarrhoea and that these may be targets for supportive therapy

Knockdown of MBP-1 in Human Foreskin Fibroblasts Induces p53-p21 Dependent Senescence

MBP-1 acts as a general transcriptional repressor. Overexpression of MBP-1 induces cell death in a number of cancer cells and regresses tumor growth. However, the function of endogenous MBP-1 in normal cell growth regulation remains unknown. To unravel the role of endogenous MBP-1, we knocked down MBP-1 expression in primary human foreskin fibroblasts (HFF) by RNA interference. Knockdown of MBP-1 in HFF (HFF-MBPsi-4) resulted in an induction of premature senescence, displayed flattened cell morphology, and increased senescence-associated beta-galactosidase activity. FACS analysis of HFF-MBPsi-4 revealed accumulation of a high number of cells in the G1-phase. A significant upregulation of cyclin D1 and reduction of cyclin A was detected in HFF-MBPsi-4 as compared to control HFF. Senescent fibroblasts exhibited enhanced expression of phosphorylated and acetylated p53, and cyclin-dependent kinase inhibitor, p21. Further analysis suggested that promyolocytic leukemia protein (PML) bodies are dramatically increased in HFF-MBPsi-4. Together, these results demonstrated that knockdown of endogenous MBP-1 is involved in cellular senescence of HFF through p53-p21 pathway

Ectopic Expression of E2F1 Stimulates β-Cell Proliferation and Function

OBJECTIVE-Generating functional beta-cells by inducing their proliferation may provide new perspectives for cell therapy in diabetes. Transcription factor E2F1 controls G(1)- to S-phase transition during the cycling of many cell types and is required for pancreatic beta-cell growth and function. However, the consequences of overexpression of E2F1 in beta-cells are unknown. RESEARCH DESIGN AND METHODS-The effects of E2F1 overexpression on beta-cell proliferation and function were analyzed in isolated rat beta-cells and in transgenic mice. RESULTS-Adenovirus AdE2F1-mediated overexpression of E2F1 increased the proliferation of isolated primary rat beta-cells 20-fold but also enhanced beta-cell death. Coinfection with adenovirus Ad Akt expressing a constitutively active form of Akt (protein kinase B) suppressed beta-cell death to control levels. At 48 h after infection, the total beta-cell number and insulin content were, respectively, 46 and 79% higher in AdE2F1+AdAkt-infected cultures compared with untreated. Conditional overexpression of E2F1 in mice resulted in a twofold increase of beta-cell proliferation and a 70% increase of pancreatic insulin content, but did not increase beta-cell mass. Glucose-challenged insulin release was increased, and the mice showed protection against toxin-induced diabetes. CONCLUSIONS-Overexpression of E2F1, either in vitro or in vivo, can stimulate beta-cell proliferation activity. In vivo E2F1 expression significantly increases the insulin content and function of adult beta-cells, making it a strategic target for therapeutic manipulation of beta-cell function. Diabetes 59:1435-1444, 201