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2014 ◽  
Vol 15 (5) ◽  
pp. 2012-2029 ◽  
Author(s):  
Seyed Hamed Alemohammad ◽  
Dara Entekhabi ◽  
Dennis B. McLaughlin

Abstract The record of global precipitation mapping using Special Sensor Microwave Imager (SSM/I) measurements now extends over two decades. Similar measurements, albeit with different retrieval algorithms, are to be used in the Global Precipitation Measurement (GPM) mission as part of a constellation to map global precipitation with a more frequent data refresh rate. Remotely sensed precipitation retrievals are prone to both magnitude (precipitation intensity) and phase (position) errors. In this study, the ground-based radar precipitation product from the Next Generation Weather Radar stage-IV (NEXRAD-IV) product is used to evaluate a new metric of error in the long-term SSM/I-based precipitation records. The new metric quantifies the proximity of two multidimensional datasets. Evaluation of the metric across the years shows marked seasonality and precipitation intensity dependence. Drifts and changes in the instrument suite are also evident. Additionally, the precipitation retrieval errors conditional on an estimate of background surface soil moisture are estimated. The dynamic soil moisture can produce temporal variability in surface emissivity, which is a source of error in retrievals. Proper filtering has been applied in the analysis to differentiate between the detection error and the retrieval error. The identification of the different types of errors and their dependence on season, intensity, instrument, and surface conditions provide guidance to the development of improved retrieval algorithms for use in GPM constellation-based precipitation data products.


2014 ◽  
Vol 76 (3) ◽  
pp. 225-234 ◽  
Author(s):  
Chengen Yang ◽  
Hsing-Min Chen ◽  
Trevor N. Mudge ◽  
Chaitali Chakrabarti

2013 ◽  
Vol 785-786 ◽  
pp. 1564-1567
Author(s):  
Fei Qiao Xiong ◽  
Bang Qian Ao

In this paper, we design a full color LED display remote wireless control system, which based on the ARM microprocessor for embedded real-time operating system technology, and combine with the wireless WiFi broadband for wireless data transmission. The system uses the ARM microprocessor as the core and the device of FPGA. It can transport and update wireless data、refresh dynamic features、scan the display with cyclic and so on. It can achieves remote wireless control of LED display.


2013 ◽  
Vol 340 ◽  
pp. 1034-1038
Author(s):  
Yang Jia ◽  
Qiang Fu ◽  
Du Shi Ma ◽  
Ming Yang Zhu

Not only distribution automation system but the principle of the existing means of communication are studied systematically and distribution automation communication system model based on IP network is provided. Backbone network is set between master station in the control center and substation sub-station. Communication between electronic station and terminal connections rely on the branch network. Simulation experiment shows the test of data traffic and network delay of IP communications network. In the actual network environment the data refresh meet the application requirements. So the program on the improvement of distribution automation communication in this article is feasible.


2013 ◽  
Vol 336-338 ◽  
pp. 2388-2391
Author(s):  
Jian Jun Wang ◽  
Zhi Feng Liu ◽  
Ji Kai Ma

This paper analyses the master station redundancy technology in the POWERLINK network. Through the monitoring network and data refresh to achieve the master station redundancy function. The Managing Node redundancy ensures the POWERLINK cycle production continuance after the failure of the current master station, the switch-over time (recovery time) of the POWERLINK system is in the two POWERLINK cycle time at least. That ensures a very fast restoring of normal operation without any downtime for the control system.


2013 ◽  
Vol 52 (6) ◽  
pp. 1379-1393 ◽  
Author(s):  
Robert J. Kuligowski ◽  
Yaping Li ◽  
Yu Zhang

AbstractData from the Tropical Rainfall Measuring Mission (TRMM) have made great contributions to hydrometeorology from both a science and an operations standpoint. However, direct application of TRMM data to short-fuse hydrologic forecasting has been challenging because of the data refresh and latency issues inherent in an instrument in low Earth orbit (LEO). To evaluate their potential impact on low-latency satellite rainfall estimates, rain rates from both the TRMM Microwave Imager (TMI) and precipitation radar (PR) were ingested into a multisensor framework that calibrates high-refresh, low-latency IR brightness temperature data from geostationary platforms against the more accurate but low-refresh, higher-latency rainfall rates available from microwave (MW) instruments on board LEO platforms. The TRMM data were used in two ways: to bias adjust the other MW data sources to match the distribution of the TMI rain rates, and directly alongside the MW rain rates in the calibration dataset. The results showed a significant reduction in false alarms and also a significant reduction in bias for those pixels for which rainfall was correctly detected. The MW bias adjustment was found to have much greater impact than the direct use of the TMI and PR rain rates in the calibration data, but this is not surprising since the latter represented perhaps only 10% of the calibration dataset.


2009 ◽  
Vol 60-61 ◽  
pp. 219-223 ◽  
Author(s):  
Wei Qin ◽  
Wei Zheng Yuan ◽  
Hong Long Chang ◽  
Liang Xue ◽  
Guang Min Yuan

In the paper, an attitude and heading reference system based on MIMU/magnetometers with moderate accuracy is presented. To meet the requirements of the real-time measurement, a master/slave CPU structure is proposed in order to improve the data refresh rate effectively. In the algorithm part, an adaptive extended Kalman filter equation is applied in the system, where the filter equation uses three tilt angles of attitude and three bias errors for the gyroscopes as state vectors, the measurements of three accelerometers and magnetometers are used to drive the state update. When the system is in dynamic mode, the measured values of the accelerometers consist of the gravity vector and the dynamic accelerations, an adaptive extended Kalman filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance. The experiment result shows that the attitude and heading angle errors are within 0.2 deg and 0.5 deg respectively in stationary mode, and the result can reflect the attitude angles reasonably in dynamic mode.


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