Nonlinear Evolution of Kinetic Alfvén Waves and Filament Formation

The transfer of wave energy to plasma energy is a very crucial issue in coronal holes and helmet streamer regions. Mixed mode Alfvén waves, also known as kinetic Alfvén wave (KAW) can play an important role in the energization of the plasma particles because of their potential ability to heat and accelerate the plasma particles via Landau damping. This paper presents an investigation of the growth of a Gaussian perturbation on a non-uniform kinetic Alfvén wave having Gaussian wave front. The effect of the nonlinear coupling between the main KAW and the perturbation has been studied. The dynamical equations for the field of the main KAW and the perturbation have been established and their semi-analytical solution has been obtained in the low (β≪ m_e/m_i≪ 1) and the high (β≫ m_e/m_i≪ 1) β cases. The critical field of the main KAW and the perturbation has been evaluated. Nonlinear evolution of the main KAW and the perturbation into the filamentary structures and its dependence on various parameters of the solar wind and the solar corona have been investigated in detail. These filamentary structures can act as a source for the particle acceleration by wave particle interaction because the KAWs are mixed modes and Landau damping is possible. Especially, in the solar corona, the low β and the high β cases could correspond to the coronal holes and the helmet streamer. The presence of the primary and the secondary filaments of the perturbation may change the spectrum of the Alfvénic turbulence in the solar wind.     

The study of indoor radon in the urban dwellings using plastic track detectors

Radon and its progeny have been recognized as one of the major contributors to the natural radiation and health hazards in the human dwellings. Even lung cancer is expected if it is present in enhanced levels beyond maximum permissible limit. This paper reports the measurements of indoor radon and its progeny in the urban dwellings of the Etah district of Uttar Pradesh province in Northern India using the cellulose nitrate (LR-115 type-II) plastic track detectors. It is found that the values of radon concentration vary from 3.52 to 248.64 Bq m⁻³ with a standard deviation of 69.19. The values of radon progeny concentration vary from 0.38 to 26.88 mWL with a standard deviation of 7.48. The effective dose has been calculated and found to vary from 0.05 to 3.76 mSv year⁻¹ with a standard deviation of 1.05. The lifetime fatality risk is found to vary from 0.04 × 10⁻⁴ to 2.90 × 10⁻⁴. The results have been compared with the results reported in the rural areas of the same district.     

Sensitivity of Kelani streamflow in Sri Lanka to ENSO

As part of an effort to demonstrate the use of climate predictions for water resources management, the El Niño/Southern Oscillation (ENSO) influences on stream flow in the Kelani River in Sri Lanka were investigated using correlation analysis, composite analysis and contingency tables. El Niño (warm phase of ENSO) was associated with decreased annual stream flow and La Niña (cold phase of ENSO) with increased annual flows. The annual stream flow had a negative correlation with the simultaneous ENSO index of NINO3·4 that was significant at the 95% level. This negative correlation is enhanced to a 99% level if the aggregate January to September or the April to September stream flow alone were considered. Although, there is little correlation between ENSO indices and stream flow during the October to December period, there is a high correlation between rainfall and NINO3·4 (r = 0·51, significant at the 99% level). Therefore ENSO based rainfall predictions can be used along with a hydrological model to predict the October to December stream flow. This study demonstrates the viability of using ENSO based predictors for January to September or April to September stream flow predictions in the Kelani River. The October to December stream flow may be predicted by exploiting the strong relationship between ENSO and rainfall during that period. Copyright © 2003 John Wiley & Sons, Ltd.     

Spatial Distribution of Shear Wave Velocity for Late Quaternary Alluvial Soil of Kanpur City,Northern India

Empirical correlation between standard penetration resistance (SPT-N) and shear wave velocity measured by seismic downhole techniques are prepared of the alluvial soil of quaternary age for the Kanpur city. The Kanpur city is having seismic threat from Himalaya and it falls in seismic zone III according to seismic zones of India. Standard penetration test as well seismic downhole test has been carried out up to 30 m at twelve different locations of Kanpur city. The measured SPT-N values and shear wave velocity values are used to develop empirical correlation between SPT-N and shear wave velocity. The proposed correlations have been compared with the existing regression equations by various other investigators. It is found that the proposed correlation exhibit good performance (10 % error bar). Also the measured shear wave velocity has been used to prepare spatially distributed contour map of 50, 75 and 100 m/s using ArcGIS-9 software. It is observed that the shear wave velocity values for the northern part of Kanpur city vary from 125 to 825 m/s. In southern part, it is varying from 125 to 500 m/s where as in the central part of the city the shear wave velocity varies from 125 to 375 m/s. The eastern part of the city also shows some variation in shear wave velocity which ranges from 250 to 625 m/s. The western part of the city shows the variation of shear wave velocity from ≤125 to 500 m/s. The soil type of the study area are classified as per NEHRP and new Italian O.P.M.C classification system as B, C and D type soil with having site period of 0.1–0.9 s and Poisson’s ratio varying from 0.1 to 0.4.     

Development of a new wavelet-based hybrid model to forecast multi-scalar SPEI drought index (case study: Zanjan city,Iran)

Theoretical and Applied Climatology - Drought forecasting plays a vital role in managing drought and reducing its effects on agricultural systems and water resources. In the present study, three...     

Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks

We present a detailed analysis of summer monsoon rainfall over the Indian peninsular using nonlinear spatial correlations. This analysis is carried out employing the tools of complex networks and a measure of nonlinear correlation for point processes such as rainfall, called event synchronization. This study provides valuable insights into the spatial organization, scales, and structure of the 90th and 94th percentile rainfall events during the Indian summer monsoon (June–September). We furthermore analyse the influence of different critical synoptic atmospheric systems and the impact of the steep Himalayan topography on rainfall patterns. The presented method not only helps us in visualising the structure of the extreme-event rainfall fields, but also identifies the water vapor pathways and decadal-scale moisture sinks over the region. Furthermore a simple scheme based on complex networks is presented to decipher the spatial intricacies and temporal evolution of monsoonal rainfall patterns over the last 6 decades.     

Adaptive state estimation of groundwater contaminant boundary input flux in a 2-dimensional aquifer

In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the domain.Therefore,the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes imperative.Adaptive state estimator(ASE)is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique,thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman filters.The ASE is particularly designed for a system that encompasses independent unknowns and/or random switching of input and measurement biases.The present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE,which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10%in 2-dimensional problems.Numerical simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux scenarios.Results also show that ASE enjoys a better estimation performance than its competitor,Recursive Least Square Estimator(RLSE)due to its larger error tolerance in greater process noise regimes.ASE's inherent deficiency of being slower than the RLSE,resulting from the complexity of algorithm,was also noticed.The chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location.