scholarly journals The CASA Integrated Project 1 Networked Radar System

2010 ◽  
Vol 27 (1) ◽  
pp. 61-78 ◽  
Author(s):  
Francesc Junyent ◽  
V. Chandrasekar ◽  
D. McLaughlin ◽  
E. Insanic ◽  
N. Bharadwaj
Keyword(s):  
Radar System ◽  
Research Center ◽  
Weather Data ◽  
Software Architectures ◽  
Test Bed ◽  
Engineering Research ◽  
Adaptive Sensing ◽  
Radar Network ◽  
Integrated Project ◽  
Key Features

Abstract This paper describes the Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project 1 (IP1) weather radar network, the first distributed collaborative adaptive sensing test bed of the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere. The radar network and radar node hardware and software architectures are described, as well as the different interfaces between the integrated subsystems. The system’s operation and radar node control and weather data flow are explained. The key features of the radar nodes are presented, as well as examples of different data products.

scholarly journals Evaluation of Distributed Collaborative Adaptive Sensing for Detection of Low-Level Circulations and Implications for Severe Weather Warning Operations

2010 ◽  
Vol 25 (1) ◽  
pp. 173-189 ◽  
Author(s):  
J. Brotzge ◽  
K. Hondl ◽  
B. Philips ◽  
L. Lemon ◽  
E. J. Bass ◽  
...  
Keyword(s):  
Severe Weather ◽  
Special Focus ◽  
Test Bed ◽  
Scanning Strategy ◽  
Engineering Research ◽  
Low Level ◽  
Adaptive Sensing ◽  
Low Levels ◽  
Casa System ◽  
Better Than

Abstract The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is a multiyear engineering research center established by the National Science Foundation for the development of small, inexpensive, low-power radars designed to improve the scanning of the lowest levels (<3 km AGL) of the atmosphere. Instead of sensing autonomously, CASA radars are designed to operate as a network, collectively adapting to the changing needs of end users and the environment; this network approach to scanning is known as distributed collaborative adaptive sensing (DCAS). DCAS optimizes the low-level volume coverage scanning and maximizes the utility of each scanning cycle. A test bed of four prototype CASA radars was deployed in southwestern Oklahoma in 2006 and operated continuously while in DCAS mode from March through June of 2007. This paper analyzes three convective events observed during April–May 2007, during CASA’s intense operation period (IOP), with a special focus on evaluating the benefits and weaknesses of CASA radar system deployment and DCAS scanning strategy of detecting and tracking low-level circulations. Data collected from nearby Weather Surveillance Radar-1988 Doppler (WSR-88D) and CASA radars are compared for mesoscyclones, misocyclones, and low-level vortices. Initial results indicate that the dense, overlapping coverage at low levels provided by the CASA radars and the high temporal (60 s) resolution provided by DCAS give forecasters more detailed feature continuity and tracking. Moreover, the CASA system is able to resolve a whole class of circulations—misocyclones—far better than the WSR-88Ds. In fact, many of these are probably missed completely by the WSR-88D. The impacts of this increased detail on severe weather warnings are under investigation. Ongoing efforts include enhancing the DCAS data quality and scanning strategy, improving the DCAS data visualization, and developing a robust infrastructure to better support forecast and warning operations.

Evaluation of Distributed Collaborative Adaptive Sensing in a Four-Node Radar Network: Integrated Project 1

2008 ◽  
Author(s):  
V. Chandrasekar ◽  
Dave McLaughlin ◽  
Jerry Brotzge ◽  
Michael Zink ◽  
Brenda Philips ◽  
...  
Keyword(s):  
Adaptive Sensing ◽  
Radar Network ◽  
Integrated Project

scholarly journals The CASA quantitative precipitation estimation system: a five year validation study

2012 ◽  
Vol 12 (9) ◽  
pp. 2811-2820 ◽  
Author(s):  
V. Chandrasekar ◽  
Y. Wang ◽  
H. Chen
Keyword(s):  
Lower Atmosphere ◽  
Foundation Engineering ◽  
Test Bed ◽  
Spatiotemporal Resolution ◽  
Engineering Research ◽  
Adaptive Sensing ◽  
Weather Events ◽  
Hourly Rainfall ◽  
Precipitation Estimation ◽  
Estimation System

Abstract. Flooding is one of the most common natural hazards that produce substantial loss of life and property. The QPE products that are derived at high spatiotemporal resolution, which is enabled by the deployment of a dense radar network, have the potential to improve the prediction of flash-flooding threats when coupled with hydrological models. The US National Science Foundation Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is dedicated to revolutionizing our ability to observe, understand, predict, and respond to hazardous weather events, especially in the lower atmosphere. CASA's technology enables precipitation observation close to the ground and QPE is one of the important products generated by the system. This paper describes the CASA QPE system built on the various underlying technologies of networked X-band radar systems providing high-resolution (in space and time) measurements, using the rainfall products from the radar. Evaluation of the networked rainfall product using 5 yr of data from the CASA IP-1 test bed is presented. Cross validation of the product using 5 yr of data with a gauge network is also provided. The validation shows the excellent performance of the CASA QPE system with a standard error of 25% and a low bias of 3.7%. Examples of various CASA rainfall products including instantaneous and hourly rainfall accumulations are shown.

PERUBAHAN GARIS PANTAI DI TELUK PRIGI, KABUPATEN TRENGGALEK, JAWA TIMUR

2020 ◽  
Vol 2 (1) ◽  
pp. 16
Author(s):  
Khairana Ayu Shabrina ◽  
Rudi Siap Bintoro ◽  
Giman Giman
Keyword(s):  
Coastal Engineering ◽  
Research Center ◽  
Engineering Research ◽  
Water Index

<p>Teluk Prigi merupakan perairan di pesisir Samudera Hindia yang dikelilingi oleh bentang alam tebing yang tinggi sehingga wilayah pesisir yang memiliki kondisi dinamis dapat mengakibatkan terjadinya perubahan garis pantai apabila tidak dikelola dengan baik. Maka dari itu pada penelitian ini bertujuan untuk mengetahui faktor oseanografi yang menyebabkan terjadinya perubahan garis pantai. Metode yang digunakan terdiri dari pemisahan arus, peramalan gelombang, gelombang pecah, energi gelombang dan refraksi gelombang dengan menggunakan metode menurut <em>Coastal Engineering Research Center </em>(CERC). Selain itu ekstraksi garis pantai dengan metode <em>NDWI (Normal Differential Water Index)</em>, dan analisis jenis sedimen menggunakan modul yang dikeluarkan oleh Pusjatan Balitbang PU. Faktor oseanografi yang dominan menjadi penyebab perubahan garis pantai adalah gelombang bangkitan angin yang pola gelombangnya mengalami perubahan arah yang cenderung tegak lurus pantai, selain itu arus pasang surut menjadi faktor pendukung dengan kecepatan 0,0037 m/s bergerak menuju Utara. Sehingga, kondisi garis pantai pada tahun 2003 dan 2014, 2014 dan 2018 luasan sedimentasi terbesar mencapai 28.949 m<sup>2</sup> dan 52.020 m<sup>2</sup> yang berada di Desa Prigi. Sedangkan Sedangkan lokasi abrasi pada tahun 2003 dan 2014, 2014 dan 2018 luasnya mencapai 4.204 m<sup>2</sup> dan 3.326 m<sup>2</sup>.</p>

scholarly journals Review of Weather Forecast Services for Ship Routing Purposes

2019 ◽  
Vol 26 (4) ◽  
pp. 80-89
Author(s):  
Marcin Życzkowski ◽  
Joanna Szłapczyńska ◽  
Rafał Szłapczyński
Keyword(s):  
Collision Avoidance ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Weather Data ◽  
Ocean Engineering ◽  
Ship Routing ◽  
Engineering Research ◽  
Fishing Vessels ◽  
Analysis Of Stability

Abstract Weather data is nowadays used in a variety of navigational and ocean engineering research problems: from the obvious ones like voyage planning and routing of sea-going vessels, through the analysis of stability-related phenomena, to detailed modelling of ships’ manoeuvrability for collision avoidance purposes. Apart from that, weather forecasts are essential for passenger cruises and fishing vessels that want to avoid the risk associated with severe hydro-meteorological conditions. Currently, there is a wide array of services that offer weather predictions. These services include the original sources – services that make use of their own infrastructure and research models – as well as those that further postprocess the data obtained from the original sources. The existing services also differ in their update frequency, area coverage, geographical resolution, natural phenomena taken into account and finally – output file formats. In the course of the ROUTING project, primarily addressing ship weather routing accounting for changeable weather conditions, the necessity arose to prepare a report on the state-of-the-art in numerical weather prediction (NWP) modelling. Based on the report, this paper offers a thorough review of the existing weather services and detailed information on how to access the data offered by these services. While this review has been done with transoceanic ship routing in mind, hopefully it will also be useful for a number of other applications, including the already mentioned collision avoidance solutions.

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