Modeling Whitecaps on Global Scale

Whitecaps play an important role in the surface-atmosphere interactions across the ocean. They are directly linked to the energy dissipation rate during wave breaking and transfer of heat, momentum, and gas/aerosol exchange from the wind to the sea surface. Although the first models of W were dependent only on wind speeds, a large number of diverse models based on wind and sea state which include wave height, wave age, friction velocity, and stability effects have been proposed since then. However, it is recognized that most of the proposed W models have strong systematic (e.g., zonal bias) and random errors when compared against observations. This is partly due to the differences in environmental conditions, measurement techniques, and geographical locations among these studies. But, some of these biases are linked to the inability of the proposed models to capture the variability in W in certain wind/wave regimes. Despite the knowledge of existing biases, W residual relationships from the models with wind and wave fields remain highly uncertain, with residual trends varying between the published studies. Here, we take advantage of the availability of relatively dense observations of W from WindSat microwave satellite retrievals in combination with the University of Miami wave model which was recently incorporated within the NASA GMAO/GEOS system (GEOS-UMWM). We use Windsat W retrievals to assess and constrain the previously published W models and understand the relationships of residuals from models in different wind/wave regimes. We link these unexplained residual variations to additional factors such as swell index, drag coefficient etc and add information to the existing whitecap models. Since Windsat retrievals cover wide range of environmental conditions, it helps to reduce the uncertainties associated with differences in measurement techniques. Regression of wind-wave fields against all Windsat data points (CTL) results in larger residuals for lower wave age and W is overestimated upto ~4% for wave age < 10 and underestimated by upto ~2% as wave age increases. We attest to this bias by considering two approaches. One is to perform regression separately for different stages of wave development such as developing sea, fully developed, and wind sea regimes thereby understanding the sensitivity of regression coefficients to sea state (EXP1). Another is to derive coefficients of W models in EXP1 as a function of additional wind/wave factors such as swell index, drag coefficient, and mean squared slope, deriving more nonlinear W models (EXP2). EXP2 provides reduction in Root Mean Squared Error (RMSE) by 0.1-0.3%. Sea surface drag has a stronger relationship with regression coefficients compared to swell index.These additional factors provide improved parameterizations in different wind and wave age regimes, with smaller unexplained/residual variations in W that has been a major concern in the W community

Knowledge, attitude and practices of general practitioners about use of antiviral drugs in viral infections other than HIV

Background: Antiviral drugs for viral infections other than HIV are effective only for hepatitis, herpes and influenza. It has been observed that general practitioners (GPs) treat viral infections with antibiotics. The use of antibiotics in viral infections is not rational. Hence, authors conducted this study to assess the Knowledge, Attitude and Practices of General Practitioners (GPs) about treatment of viral infections other than HIV.Methods: It was a descriptive, observational, cross- sectional study among 100 GPs in Southern Pune. A pretested questionnaire was used to assess their knowledge, attitude and practices about treatment of viral infections other than HIV. Prior informed written consent was taken from the GPs who were grouped under MBBS, BHMS and BAMS categories according to their qualifications. Correct answers among these groups were analysed using chi-square test, Spearman’s coefficient test and ANOVA.Results: The percentages of correct answers in the groups were comparable.56% GPs have poor knowledge of Influenza treatment.30-36% do not treat Herpes genitalis and zoster with antiviral drugs. Authors found that 44%, 30% and 28% of total GPs don’t have proper knowledge, attitude and practice respectively about common viral infections other than HIV and antiviral drugs.Conclusions: GPs are significantly unaware about rational use of antiviral drugs. They have poor knowledge about management of influenza

Challenges in Developing Better Observational Constraints and Models for Aerosols : Emerging Ideas for Design and Use of Future Observing Systems

No abstract availabl

Sea State Based Estimation of White Cap Fraction: Implications for Primary Marine Aerosol Fluxes

Oceanic whitecaps (hereafter, W) or the characteristic whiteness of the sea foam is an important feature for predicting exchange of gases, sea spray aerosols (SSAs), heat and momentum transfer between the ocean and the atmosphere at the air-sea interface. Due to its increased surface emission and brightness temperature, whitecaps are critical for satellite retrievals of ocean albedo, ocean color, ocean surface wind vectors from satellite borne radiometer and microwave instruments. Most of the existing models predict W using wind speed and sea surface temperature (SST). However, numerous publications have pointed out that there are large uncertainties in the predicted W and using parameterizations based on wind-wave state can improve the precision of the predicted W. Here, we integrate the University of Miami Wave Model - 2.0 (UMWM) in Goddard Earth Observing System (GEOS) and use wave diagnostics to predict W. We choose the year 2006 for our global UMWM/GEOS runs because of the availability of W dataset from satellite observations. We run UMWM/GEOS at 0.5o x 0.5o by replaying to MERRA2 meteorology and evaluate the wave diagnostics using measurements from fixed buoys and satellite altimeters. We use three different parameterizations for W based on: 1) Reynolds number, 2) wave dissipation energy, and 3) volume of air entrained by breaking waves. We compare our results of W with previous studies and also with the satellite based observational dataset. Predicting W is important for understanding the processes at the air-sea interface. Therefore, this work is a step further in improving the uncertainties in the aerosol and atmospheric chemistry modules of the global models

Temporomandibular Joint Pain

Temporomandibular joint (TMJ) is a synovial articulation between mandibular condyle and glenoid fossa in the temporal bone. Any structural and/or functional changes can affect the TMJ and related structures. Temporomandibular disorder (TMD) is a heterogeneous group of musculoskeletal disorders mainly characterised by regional pain in the facial and preauricular area and/or limitations/interference of jaw movement. TMD has multifactorial aetiology, which includes biology, and environmental social, emotional, and cognitive factors. TMD is more common orofacial pain condition and nondental origin. Factors associated with TMD include other pain condition, auto-immune disorder and psychiatric illness. The clinical conditions may present with limitation in opening and closing mouth, pain and articular noise. So this chapter mainly deals with the classification of TMJ disorder, diagnosis and management particularly TENS and ultrasound therapy for TMJ disorder

Improving Constraints on Aerosols in the United States Using Ground Based Observations, Satellite Retrievals, and a Chemical Transport Model

Knowledge of distributions of aerosols is critical to human health, Earth's radiative budget, and air quality. However, the lack of sufficient direct measurements of aerosol type, number, mass concentrations and current limitations of satellite retrievals make it challenging to accurately model the aerosol variability. Such measurement gaps also hinder evaluation of aerosol source budget from emission inventories, modeling of aerosol chemistry, and sinks. In this context, the first study characterizes the potential of multivariate relationships between Aerosol Optical Depth (AOD), a quantity that represents light extinction by aerosols in the atmospheric column and a suite of surface and atmospheric parameters (e.g., vegetation, precipitation, fire characteristics) in order to assess trends in AOD anomalies for the U.S Southwest. This study covers the area that experiences North American Monsoon (NAM) and examines trends in AOD across different aerosol sources in this region such as dust storms, biomass burning, and anthropogenic emissions. We find that aerosols from anthropogenic processes and biomass burning exhibited a strong declining trend in AOD whereas trends along the NAM alley were obfuscated by the monsoon precipitation (sink) and convective dust storms (sources). In the second study, we develop constraints to improve characterization of anthropogenic apparent Elemental Carbon (ECa) using coemitted combustion products such as Carbon Monoxide (CO) and Nitrogen Oxides (NOx). We compare observational ratios of ECa vs CO and ECa vs NOx against those from emission inventories. We find that the observational ratios have increased at sites in the Urban-West due to increase in ECa from 2000-2007 to 2008-2015. Further, emission ratios do not match with observational ratios. We recommend that rigorous efforts are needed to better quantify and monitor the changes in these species in the Urban-West particularly for non-road and residential combustion sectors. The final study of this dissertation discusses a technique to produce forecasts of AOD by combining satellite retrievals and a chemical transport model in an analog based framework. We use model forecasts of AOD, particulate matter (PM) concentrations, and meteorological parameters from Weather Research and Forecasting model with Chemistry (WRF-Chem) to train the framework for choosing analogs (past forecasts similar to current simulations). MODIS Terra and Aqua satellite retrievals of AOD for analog days are then used in a Kalman Filter (KF) framework to determine the forecast error and referred to as KFAN. The analog based estimates better forecasts of AOD for the Western US compared to the East and the mean bias in AOD forecasts are reduced to the range of 0.001-0.1. The reduction in positive bias in AOD is drastic and the method captures the decrease in AOD from morning to afternoon. We find that higher root mean square error (RMSE) values in the East are due to the inability of KFAN to capture the AOD peaks during biomass burning episodes and AOD lows during days of high precipitation rates. A systematic statistical analysis using step-wise linear regression models also show that in the East, there is a stronger dependence of aerosol loading on meteorological factors such as air temperature, precipitation, and relative humidity. As a consequence, overall quality of the analogs in the East is impacted when uncertainties in the simulated meteorological fields are higher. Overall, this study shows that the correlative information from multi-satellite remote sensing retrievals and models provide additional constraints on aerosols using composition/source identification (e.g., aerosol type, landcover, emission sources, fuel consumption), coemitted gas phase species (e.g., CO and NOx), and meteorological parameters (e.g., wind speed, TPW). The synergy of information from these datasets can be beneficial for design of future remote sensing missions, deployment of ground networks, and studies related to feedbacks between meteorology and aerosols

Decreasing Aerosol Loading in the North American Monsoon Region

We examine the spatio-temporal variability of aerosol loading in the recent decade (2005–2014) over the North American Monsoon (NAM) region. Emerging patterns are characterized using aerosol optical depth (AOD) retrievals from the NASA Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) instrument along with a suite of satellite retrievals of atmospheric and land-surface properties. We selected 20 aerosol hotspots and classified them into fire, anthropogenic, dust, and NAM alley clusters based on the dominant driver influencing aerosol variability. We then analyzed multivariate statistics of associated anomalies during pre-, monsoon, and post-monsoon periods. Our results show a decrease in aerosol loading for the entire NAM region, confirming previous reports of a declining AOD trend over the continental United States. This is evident during pre-monsoon and monsoon for fire and anthropogenic clusters, which are associated with a decrease in the lower and upper quartile of fire counts and carbon monoxide, respectively. The overall pattern is obfuscated in the NAM alley, especially during monsoon and post-monsoon seasons. While the NAM alley is mostly affected by monsoon precipitation, the frequent occurrence of dust storms in the area modulates this trend. We find that aerosol loading in the dust cluster is associated with observed vegetation index and has only slightly decreased in the recent decade

Study of fusion energy A2158-171

Earth’s population is expected to rise from 7 billion to 10 billion by 2050. With an increased population comes with increased demand for energy. It is estimated that by the 2088, mankind would have run out of coal for energy generation. Burning of fossil fuels have also contributed to environmental effects such as global warming. In the recent decades, nuclear fission plants have steadily stepped up their energy yield and provided us with substantial amounts of power. However, nuclear fission is dangerous and has the potential to wreak havoc on mankind during a nuclear meltdown. Nuclear fission will be crucial in providing power to society however to produce power for the entirety of mankind would be a challenge. Several nuclear fission plants would have to be built and this increases the risk of danger within human spaces. Nuclear fusion on the other hand offers a better alternative to nuclear energy. This form of energy promises the advantages of nuclear fission while being safer. The fuel source for fusion is predominantly taken from seawater which is seen as an inexhaustible supply. While these claims are bold and promising, fusion is far from being commercially available. While the concept is true and proven, practical concepts are far from being economically viable. Fusion conditions are very difficult to achieve. Plasma physicists are trying very hard to tackle these challenges. In this paper, we will examine the methods and concepts that have been conceived in creating fusion reactions. The paper will seek to highlight the method that is seen to be the most probable solution in achieving a fusion futureBachelor of Engineerin

A Novel LBP Based Operator for Tone Mapping HDR Images

by Aishwarya Agrawal and Shanmuganathan Rama

Decreasing Aerosol Loading in the North American Monsoon Region.

We examine the spatio-temporal variability of aerosol loading in the recent decade (2005-2014) over the North American Monsoon (NAM) region. Emerging patterns are characterized using aerosol optical depth (AOD) retrievals from the NASA Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) instrument along with a suite of satellite retrievals of atmospheric and land-surface properties. We selected 20 aerosol hotspots and classified them into fire, anthropogenic, dust, and NAM alley clusters based on the dominant driver influencing aerosol variability. We then analyzed multivariate statistics of associated anomalies during pre-, monsoon, and post-monsoon periods. Our results show a decrease in aerosol loading for the entire NAM region, confirming previous reports of a declining AOD trend over the continental United States. This is evident during pre-monsoon and monsoon for fire and anthropogenic clusters, which are associated with a decrease in the lower and upper quartile of fire counts and carbon monoxide, respectively. The overall pattern is obfuscated in the NAM alley, especially during monsoon and post-monsoon seasons. While the NAM alley is mostly affected by monsoon precipitation, the frequent occurrence of dust storms in the area modulates this trend. We find that aerosol loading in the dust cluster is associated with observed vegetation index and has only slightly decreased in the recent decade