The determination of the three-dimensional distribution of rain from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar

This paper describes a recent development in rainfall estimation using satellite-flown and ground-based radars. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), its algorithms and data processing are discussed. The ground validation algorithms and processing of the ground-based radar reflectivity data are explained. The estimates of attenuation-corrected radar reflectivity factor and rainfall rate are given at each resolution cell of the PR. The estimated near-surface rainfall rate and average rainfall rate at the altitudes of 2 km are calculated for each beam position. The TRMM PR profiling algorithm and processing of the PR reflectivity for rain distribution are explained. The TRMM rain products and their geophysical parameters are derived from the measurements from the satellite and ground-based radar. The derived geophysical parameters include vertical rain and hydrometeor profile, rain type, radar back-scatter cross-section, raindrop size distribution, rain gauge rain rates and 5-day and monthly average rain rates. For validation purposes the instantaneous and climatological comparison of the rain estimates from both the Precipitation Radar and ground-based radar at Melbourne, Florida, was carried out on the basis of rain type; i.e. convective/stratiform, vertical structure and rain maps. The error sources in rain profile retrieval from space-borne radar; i.e. the PR and ground-based radar with their algorithm limitations are discussed. A second set of data, this time for an area where no simultaneous ground data are available has also been analysed; the data were chosen for the three-dimensional rain distribution over some parts of India. The issues such as discrimination of rain from surface clutter, calibration accuracy and sensitivity of precipitation radar and discrimination of rain echo from noise are discussed.     

Multi‐sensor data fusion and comparison of total column ozone

With many remote‐sensing instruments onboard satellites exploring the Earth's atmosphere, most data are processed to gridded daily maps. However, differences in the original spatial, temporal, and spectral resolution—as well as format, structure, and temporal and spatial coverage—make the data merging, or fusion, difficult. NASA Goddard Earth Sciences Data and Information Services Center (GES‐DISC) has archived several data products for various sensors in different formats, structures, and multi‐temporal and spatial scales for ocean, land, and atmosphere. In this investigation using Earth science data sets from multiple sources, an attempt was made to develop an optimal technique to merge the atmospheric products and provide interactive, online analysis tools for the user community. The merged/fused measurements provide a more comprehensive view of the atmosphere and improve coverage and accuracy, compared with a single instrument dataset. This paper describes ways of merging/fusing several NASA Earth Observing Systems (EOS) remote‐sensing datasets available at GES‐DISC. The applicability of various methods was investigated for merging total column ozone to implement these methods into Giovanni, the online interactive analysis tool developed by GES‐DISC. Ozone data fusion of MODerate resolution Imaging Spectrometer (MODIS) Terra and Aqua Level‐3 daily data sets was conducted, and the results were found to provide better coverage. Weighted averaging of Terra and Aqua data sets, with the consequent interpolation through the remaining gaps using Optimal Interpolation (OI), also was conducted and found to produce better results. Ozone Monitoring Instrument (OMI) total column ozone is reliable and provides better results than Atmospheric Infrared Sounder (AIRS) and MODIS. However, the agreement among these instruments is reasonable. The correlation is high (0.88) between OMI and AIRS total column ozone, while the correlation between OMI and MODIS Terra/Aqua fused total column ozone is 0.79.     

A New Approach of Tool Wear Monitoring and Compensation in RµEDM Process

This paper presents a new approach of tool wear compensation based on “volume removal per discharge” (VRD) in “reverse-micro-electrical-discharge machining.” In this process, a plate with predrilled microhole is used as a tool, the erosion of which limits the fabrication of desired height of microrod(s). Therefore, in order to achieve the dimensional accuracy of this microrod(s), such tool plate wear needs to be compensated. Since this approach is based on the real-time estimation of volume removal from workpiece, which is obtained by multiplying the number of “contributing” pulses with VRD, an accurate estimation of VRD is very much essential for availing correct tool wear compensation. In this work, VRD is estimated by considering two new aspects: the number of actual “contributing” pulses and the variation of VRD with machining depth. These pulses are identified by a “pulse discriminating” system developed in house. The real-time material removal volume from workpiece is then used to estimate the “real-time height” of microrods after considering the over cut and taperness of each microrod. The proposed method is also compared with the normal machining method and “uniform wear method” and found to be more accurate with a negligible error of maximum 1.7%.     

A survey on providing customer and public administration based services using AI: chatbot

Multimedia Tools and Applications - A chatbot is emerged as an effective tool to address the user queries in automated, most appropriate and accurate way. Depending upon the complexity of the...     

Thermal modeling of single discharge in prospect of tool wear compensation in μEDM

The International Journal of Advanced Manufacturing Technology - Due to the non-isoenergetic nature of discharge pulses in resistance-capacitance (RC) based micro electrical discharge machining...     

Microwave measurement of rain and sea surface temperature by the TRMM Microwave Imager (TMI)

The Tropical Rainfall Measuring Mission (TRMM) is important for studies of the global hydrological cycle and for testing the realism of climate models and their ability to simulate and predict climate accurately; the effect of El Nino on climate could be addressed as well. This paper investigates the microwave rain measurement using satellite data from the TRMM Microwave Imager (TMI). The physical bases of rainfall estimation algorithms, vertical structure of rain and its physical processes are explained. The algorithms for processing TMI radiance and brightness temperature data are presented. Various rain maps and sea surface temperature (SST) maps are produced using TMI microwave data. The performance, calibration, analysis of results and sources of errors in the averaged monthly surface rain rate estimation are discussed.     

Real-time data acquisition and discharge pulse analysis in controlled RC circuit based Micro-EDM

Microsystem Technologies - Owing to the non-isoenergetic discharge pulses in an RC-based micro-electrical discharge machining (µEDM) process, the unit material removal analysis is difficult....