Relationship between stable isotope ratios and drop size distribution in tropical rainfall     

Rohit Srivastava  R. Ramesh  T. Narayana Rao 《Journal of Atmospheric Chemistry》2012,69(1):23-31

We carried out simultaneous measurements of drop size distribution (DSD) and stable oxygen and hydrogen isotopic compositions (??¹⁸O and ??D) of rain at the National Atmospheric Research Laboratory (NARL), Gadanki (13.5°N, 79.2°E), southern India, during September?COctober 2006, with the aim of understanding microphysical processes leading to rain formation. The MST radar at NARL was operated continuously during rain events, while rain samples were collected at very short time intervals (<1?h), to capture small changes (>0.2?? and >2??) in their ??¹⁸O and ??D. The slope of the local meteoric water line (??D?C??¹⁸O line), was 8.07?±?0.47, similar to that of global meteoric water line, confirming that the precipitation occurred under isotopic equilibrium, and was unaffected by some anomalous process; further, the evaporation of rain drops at the cloud base was insignificant. Whenever the isotopic variations were larger during a rain event (>2??) there was a significant negative correlation between the ??¹⁸O and DSD. The possible explanation is that larger drops are mostly associated with convective rather than stratiform rain, and ¹⁸O (and D) depletion in convective rain is relatively more. Bin-resolved microphysical models incorporating water isotopologues could benefit by considering drop size spectra, which could improve the match with stable isotope observations of precipitation.  相似文献   

High-energy afterglow emission from gamma-ray bursts     

Yi-Zhong Fan †  Tsvi Piran †  Ramesh Narayan †  Da-Ming Wei † 《Monthly notices of the Royal Astronomical Society》2008,384(4):1483-1501

We calculate the very high-energy (sub-GeV to TeV) inverse Compton emission of GRB afterglows. We argue that this emission provides a powerful test of the currently accepted afterglow model. We focus on two processes: synchrotron self-Compton emission within the afterglow blast wave, and external inverse Compton emission which occurs when flare photons (produced by an internal process) pass through the blast wave. We show that if our current interpretations of the Swift X-ray telescope (XRT) data are correct, there should be a canonical high-energy afterglow emission light curve. Our predictions can be tested with high-energy observatories such as GLAST , Whipple, HESS and MAGIC. Under favourable conditions we expect afterglow detections in all these detectors.  相似文献   

A novel mathematical morphology based algorithm for shoreline extraction from satellite images     

C. A. Rishikeshan  H. Ramesh 《地球空间信息科学学报》2017,20(4):345-352

Abstract

Shoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments.  相似文献   

Variability and teleconnections of South and East Asian summer monsoons in present and future projections of CMIP5 climate models     

Bhaskar Preethi  Milind Mujumdar  Amita Prabhu  Ramesh Kripalani 《Asia-Pacific Journal of Atmospheric Sciences》2017,53(2):305-325

Coupled Model Inter-comparison Project Phase 5 (CMIP5) model outputs of the South and East Asian summer monsoon variability and their tele-connections are investigated using historical simulations (1861-2005) and future projections under the RCP4.5 scenario (2006-2100). Detailed analyses are performed using nine models having better representation of the recent monsoon teleconnections for the interactive Asian monsoon sub-systems. However, these models underestimate rainfall mainly over South Asia and Korea-Japan sector, the regions of heavy rainfall, along with a bias in location of rainfall maxima. Indeed, the simulation biases, underestimations of monsoon variability and teleconnections suggest further improvements for better representation of Asian monsoon in the climate models. Interestingly, the performance of Australian Community Climate and Earth System Simulator version 1.0 (ACCESS1.0) in simulating the annual cycle, spatial pattern of rainfall and multi-decadal variations of summer monsoon rainfall over South and East Asia appears to more realistic. In spite of large spread among the CMIP5 models, historical simulations as well as future projections of summer monsoon rainfall indicate multi-decadal variability. These rainfall variations, displaying certain epochs of more rainfall over South Asia than over East Asia and vice versa, suggest an oscillatory behaviour. Teleconnections between South and East Asian monsoon rainfall also exhibit a multi-decadal variation with alternate epochs of strengthening and weakening relationship. Furthermore, large-scale circulation features such as South Asian monsoon trough and north Pacific subtropical high depict zonal oscillatory behaviour with east-west-east shifts. Periods with eastward or westward extension of the Mascarene High, intensification and expansion of the upper tropospheric South Asian High are also projected by the CMIP5 models.  相似文献   

Artificial neural network simulation for prediction of suspended sediment concentration in the River Ramganga,Ganges Basin,India     

Mohd Yawar Ali Khan  Fuqiang Tian  Faisal Hasan  Govind Joseph Chakrapani 《国际泥沙研究》2019,34(2):95-107

The relation between the water discharge (Q) and suspended sediment concentration (SSC) of the River Ramganga at Bareilly, Uttar Pradesh, in the Himalayas, has been modeled using Artificial Neural Networks (ANNs). The current study validates the practical capability and usefulness of this tool for simulating complex nonlinear, real world, river system processes in the Himalayan scenario. The modeling approach is based on the time series data collected from January to December (2008-2010) for Q and SSC. Three ANNs (T1-T3) with different network configurations have been developed and trained using the Levenberg Marquardt Back Propagation Algorithm in the Matlab routines. Networks were optimized using the enumeration technique, and, finally, the best network is used to predict the SSC values for the year 2011. The values thus obtained through the ANN model are compared with the observed values of SSC. The coefficient of determination (R2), for the optimal network was found to be 0.99. The study not only provides insight into ANN modeling in the Himalayan river scenario, but it also focuses on the importance of understanding a river basin and the factors that affect the SSC, before attempting to model it. Despite the temporal variations in the study area, it is possible to model and successfully predict the SSC values with very simplistic ANN models.  相似文献   

Study on clean technology-assisted combustion behavior and NO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> emission using thermal imager for alternate fuel blends     

P. Mohamed Shameer  K. Ramesh 《International Journal of Environmental Science and Technology》2017,14(12):2759-2768

The correlation between oxides of nitrogen emission and in-cylinder temperature of diesel engine fueled with various alternative fuels has been investigated in this research paper. Experimentations were performed in engine without any modifications using pure high-speed diesel fuel, used cooking oil biodiesel (UCO20), animal fat residue biodiesel (AFR20) and camphor oil (CMR20) at 20% volume concentration of biodiesel each. From combustion analysis, the heat release rate and peak cylinder pressure of biodiesel blends were about 13.487% lower and 4.819% higher than those of diesel fuel on an average, respectively. Longer combustion duration has been observed for all biodiesel blends at all load conditions. Oxides of nitrogen emission level show 16.405, 10.352 and 7.524% increment for UCO20, AFR20 and CMR20, respectively. Noteworthy NO _x reduction of about 43.8% was recorded for diesel blended with camphor oil when compared to other biodiesel blends. The relationship between in-cylinder temperature and NO _x emission concentration was premeditated through thermal imager. The result depicted that the increase in NO _x concentration depends on augmented in-cylinder temperature for all test fuels.  相似文献   

Response reduction factor of irregular RC buildings in Kathmandu valley     

Hemchandra Chaulagain  Hugo Rodrigues  Enrico Spacone  Ramesh Guragain  Radhakrishna Mallik  Humberto Varum 《地震工程与工程振动(英文版)》2014,13(3):455-470

Most current seismic design includes the nonlinear response of a structure through a response reduction factor(R). This allows the designer to use a linear elastic force-based approach while accounting for nonlinear behavior and deformation limits. In fact, the response reduction factor is used in modern seismic codes to scale down the elastic response of a structure. This study focuses on estimating the actual ‘R' value for engineered design/construction of reinforced concrete(RC) buildings in Kathmandu valley. The ductility and overstrength of representative RC buildings in Kathmandu are investigated. Nonlinear pushover analysis was performed on structural models in order to evaluate the seismic performance of buildings. Twelve representative engineered irregular buildings with a variety of characteristics located in the Kathmandu valley were selected and studied. Furthermore, the effects of overstrength on the ductility factor, beam column capacity ratio on the building ductility, and load path on the response reduction factor, are examined. Finally, the results are further analyzed and compared with different structural parameters of the buildings.  相似文献   

Vulnerability Assessment at Village Level Due to Tides,Surges and Wave Setup     

Indu Jain  A. D. Rao  K. J. Ramesh 《Marine Geodesy》2013,36(2-3):245-260

An assessment of cyclone risk and vulnerability at the village level has evolved, which is an important component of the information system for local level development action plans for preparedness and mitigation. Here, a case study for the Nellore district along the east coast of India is considered. Using maximum probable surges along the coast, total water level (TWL) due to the combined effect of surge, tide, and wind wave is computed for the most vulnerable coastal villages of the Nellore district due to any tropical cyclones. The computations suggest that the TWL along the Nellore coast varies from 2 m in the south to 4 m in the north.  相似文献   

Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records     

Ramesh S.V. Teegavarapu 《水文科学杂志》2013,58(3):383-406

Abstract

New mathematical programming models are proposed, developed and evaluated in this study for estimating missing precipitation data. These models use nonlinear and mixed integer nonlinear mathematical programming (MINLP) formulations with binary variables. They overcome the limitations associated with spatial interpolation methods relevant to the arbitrary selection of weighting parameters, the number of control points within a neighbourhood, and the size of the neighbourhood itself. The formulations are solved using genetic algorithms. Daily precipitation data obtained from 15 rain gauging stations in a temperate climatic region are used to test and derive conclusions about the efficacy of these methods. The developed methods are compared with some naïve approaches, multiple linear regression, nonlinear least-square optimization, kriging, and global and local trend surface and thin-plate spline models. The results suggest that the proposed new mathematical programming formulations are superior to those obtained from all the other spatial interpolation methods tested in this study.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Citation Teegavarapu, R.S.V., 2012. Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records. Hydrological Sciences Journal, 57 (3), 383–406.  相似文献   

Missing precipitation data estimation using optimal proximity metric-based imputation,nearest-neighbour classification and cluster-based interpolation methods     

Ramesh S. V. Teegavarapu 《水文科学杂志》2013,58(11):2009-2026

Abstract

New optimal proximity-based imputation, K-nearest neighbour (K-NN) classification and K-means clustering methods are proposed and developed for estimation of missing daily precipitation records. Mathematical programming formulations are developed to optimize the weighting, classification and clustering schemes used in these methods. Ten different binary and real-valued distance metrics are used as proximity measures. Two climatic regions, Kentucky and Florida, (temperate and tropical) in the USA, with different gauge density and network structure, are used as case studies to evaluate the new methods. A comprehensive exercise is undertaken to compare the performances of the new methods with those of several deterministic and stochastic spatial interpolation methods. The results from these comparisons indicate that the proposed methods performed better than existing methods. Use of optimal proximity metrics as weights, spatial clustering of observation sites and classification of precipitation data resulted in improvement of missing data estimates.