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Paper
4 February 2013 Improvement of web-based data acquisition and management system for GOSAT validation lidar data analysis
Hiroshi Okumura, Shoichiro Takubo, Takeru Kawasaki, Indra Nugraha Abdullah, Osamu Uchino, Isamu Morino, Tatsuya Yokota, Tomohiro Nagai, Tetsu Sakai, Takashi Maki, Kohei Arai
Author Affiliations +
Proceedings Volume 8654, Visualization and Data Analysis 2013; 86540X (2013) https://doi.org/10.1117/12.2003921
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
A web-base data acquisition and management system for GOSAT (Greenhouse gases Observation SATellite) validation lidar data-analysis has been developed. The system consists of data acquisition sub-system (DAS) and data management sub-system (DMS). DAS written in Perl language acquires AMeDAS (Automated Meteorological Data Acquisition System) ground-level local meteorological data, GPS Radiosonde upper-air meteorological data, ground-level oxidant data, skyradiometer data, skyview camera images, meteorological satellite IR image data and GOSAT validation lidar data. DMS written in PHP language demonstrates satellite-pass date and all acquired data. In this article, we briefly describe some improvement for higher performance and higher data usability. GPS Radiosonde upper-air meteorological data and U.S. standard atmospheric model in DAS automatically calculate molecule number density profiles. Predicted ozone density prole images above Saga city are also calculated by using Meteorological Research Institute (MRI) chemistry-climate model version 2 for comparison to actual ozone DIAL data.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hiroshi Okumura, Shoichiro Takubo, Takeru Kawasaki, Indra Nugraha Abdullah, Osamu Uchino, Isamu Morino, Tatsuya Yokota, Tomohiro Nagai, Tetsu Sakai, Takashi Maki, and Kohei Arai "Improvement of web-based data acquisition and management system for GOSAT validation lidar data analysis", Proc. SPIE 8654, Visualization and Data Analysis 2013, 86540X (4 February 2013); https://doi.org/10.1117/12.2003921
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KEYWORDS
Data acquisition

LIDAR

Meteorology

Data modeling

Ozone

Atmospheric modeling

Data analysis

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