Automated compact mobile Raman lidar for water vapor measurement: instrument description and validation by comparison with radiosonde, GNSS, and high-resolution objective analysis
書誌事項
- 公開日
- 2019-01-17
- 資源種別
- journal article
- 権利情報
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- https://creativecommons.org/licenses/by/4.0/
- DOI
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- 10.5194/amt-12-313-2019
- 公開者
- Copernicus GmbH
説明
<jats:p>Abstract. We developed an automated compact mobile Raman lidar (MRL) system for measuring the vertical distribution of the water vapor mixing ratio (w) in the lower troposphere, which has an affordable cost and is easy to operate. The MRL was installed in a small trailer for easy deployment and can start measurement in a few hours, and it is capable of unattended operation for several months. We describe the MRL system and present validation results obtained by comparing the MRL-measured data with collocated radiosonde, Global Navigation Satellite System (GNSS), and high-resolution objective analysis data. The comparison results showed that MRL-derived w agreed within 10 % (root-mean-square difference of 1.05 g kg−1) with values obtained by radiosonde at altitude ranges between 0.14 and 1.5 km in the daytime and between 0.14 and 5–6 km at night in the absence of low clouds; the vertical resolution of the MRL measurements was 75–150 m, their temporal resolution was less than 20 min, and the measurement uncertainty was less than 30 %. MRL-derived precipitable water vapor values were similar to or slightly lower than those obtained by GNSS at night, when the maximum height of MRL measurements exceeded 5 km. The MRL-derived w values were at most 1 g kg−1 (25 %) larger than local analysis data. A total of 4 months of continuous operation of the MRL system demonstrated its utility for monitoring water vapor distributions in the lower troposphere.</jats:p>
収録刊行物
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- Atmospheric Measurement Techniques
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Atmospheric Measurement Techniques 12 (1), 313-326, 2019-01-17
Copernicus GmbH
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詳細情報 詳細情報について
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- CRID
- 1360004240187516672
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- ISSN
- 18678548
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- 資料種別
- journal article
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- データソース種別
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- Crossref
- KAKEN
- OpenAIRE
