Retrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) system
Abstract 3) absorption and the lack of information about the lidar ratios at those wavelengths. Improving the characterization of lidar ratios at the abovementioned wavelengths will enable aerosol monitoring with different instruments and will also permit the correction of the aerosol impact on O3 lidar data. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) campaign in the New York City region utilized a comprehensive set of instruments that enabled the characterization of the lidar ratio for UVB aerosol retrieval. The NASA Langley High Altitude Lidar Observatory (HALO) produced the 532 nm aerosol extinction product along with the lidar ratio for this wavelength using a high-spectral-resolution technique. The Langley Mobile Ozone Lidar (LMOL) is able to compute the extinction provided that it has the lidar ratio at 292 nm. The lidar ratio at 292 nm and the Ångström exponent (AE) between 292 and 532 nm for the aerosols were retrieved by comparing the two observations using an optimization technique. We evaluate the aerosol extinction error due to the selection of these parameters, usually done empirically for 292 nm lasers. This is the first known 292 nm aerosol product intercomparison between HALO and Tropospheric Ozone Lidar Network (TOLNet) O3 lidar. It also provides the characterization of the UVB optical properties of aerosols in the lower troposphere affected by transported wildfire emissions.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Retrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) system ; volume:15 ; number:8 ; year:2022 ; pages:2465-2478 ; extent:14
Atmospheric measurement techniques ; 15, Heft 8 (2022), 2465-2478 (gesamt 14)
- Urheber
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Lei, Liqiao
Berkoff, Timothy A.
Gronoff, Guillaume
Su, Jia
Nehrir, Amin R.
Wu, Yonghua
Moshary, Fred
Kuang, Shi
- DOI
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10.5194/amt-15-2465-2022
- URN
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urn:nbn:de:101:1-2022042805283655954762
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:19 MESZ
Datenpartner
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Beteiligte
- Lei, Liqiao
- Berkoff, Timothy A.
- Gronoff, Guillaume
- Su, Jia
- Nehrir, Amin R.
- Wu, Yonghua
- Moshary, Fred
- Kuang, Shi
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