The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020
<p>A comprehensive and robust dataset of tropospheric aerosol properties is important for understanding the effects of aerosol–radiation feedback on the climate system and reducing the uncertainties of climate models. The “Third Pole” of Earth (Tibetan Plateau, TP) is highly challenging for ob...
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Copernicus Publications
2024-03-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/16/1185/2024/essd-16-1185-2024.pdf |
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| author | H. Pan H. Pan H. Pan H. Pan H. Pan H. Pan J. Huang J. Li Z. Huang M. Wang M. Wang M. Wang M. Wang M. Wang A. Mamtimin A. Mamtimin A. Mamtimin A. Mamtimin A. Mamtimin W. Huo W. Huo W. Huo W. Huo W. Huo F. Yang F. Yang F. Yang F. Yang F. Yang T. Zhou K. R. Kumar |
| author_facet | H. Pan H. Pan H. Pan H. Pan H. Pan H. Pan J. Huang J. Li Z. Huang M. Wang M. Wang M. Wang M. Wang M. Wang A. Mamtimin A. Mamtimin A. Mamtimin A. Mamtimin A. Mamtimin W. Huo W. Huo W. Huo W. Huo W. Huo F. Yang F. Yang F. Yang F. Yang F. Yang T. Zhou K. R. Kumar |
| author_sort | H. Pan |
| collection | DOAJ |
| description | <p>A comprehensive and robust dataset of tropospheric aerosol properties is important for understanding the effects of aerosol–radiation feedback on the climate system and reducing the uncertainties of climate models. The “Third Pole” of Earth (Tibetan Plateau, TP) is highly challenging for obtaining long-term in situ aerosol data due to its harsh environmental conditions. Here, we provide the more reliable new vertical aerosol index (AI) parameter from the spaceborne-based lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) on board CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) for daytime and nighttime to investigate the aerosol's climatology over the TP region during 2007–2020. The calculated vertical AI was derived from the aerosol extinction coefficient (EC), which was rigorously quality-checked and validated for passive satellite sensors (MODIS) and ground-based lidar measurements. Generally, our results demonstrated that there was agreement of the AI dataset with the CALIOP and ground-based lidar. In addition, the results showed that, after removing the low-reliability aerosol target signal, the optimized data can obtain the aerosol characteristics with higher reliability. The data also reveal the patterns and concentrations of high-altitude vertical structure characteristics of the tropospheric aerosol over the TP. They will also help to update and make up the observational aerosol data in the TP. We encourage climate modelling groups to consider new analyses of the AI vertical patterns, comparing the more accurate datasets, with the potential to increase our understanding of the aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI) and their climate effects. Data described in this work are available at <a href="https://doi.org/10.11888/Atmos.tpdc.300614">https://doi.org/10.11888/Atmos.tpdc.300614</a> (Huang, 2023).</p> |
| first_indexed | 2024-03-07T14:25:50Z |
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| institution | Directory Open Access Journal |
| issn | 1866-3508 1866-3516 |
| language | English |
| last_indexed | 2024-03-07T14:25:50Z |
| publishDate | 2024-03-01 |
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| series | Earth System Science Data |
| spelling | doaj.art-10945734b8774d1cb41e00dc2f4039952024-03-06T08:01:14ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162024-03-01161185120710.5194/essd-16-1185-2024The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020H. Pan0H. Pan1H. Pan2H. Pan3H. Pan4H. Pan5J. Huang6J. Li7Z. Huang8M. Wang9M. Wang10M. Wang11M. Wang12M. Wang13A. Mamtimin14A. Mamtimin15A. Mamtimin16A. Mamtimin17A. Mamtimin18W. Huo19W. Huo20W. Huo21W. Huo22W. Huo23F. Yang24F. Yang25F. Yang26F. Yang27F. Yang28T. Zhou29K. R. Kumar30Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, ChinaNational Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, ChinaTaklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, ChinaXinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, ChinaKey Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, ChinaCollaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, ChinaCollaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, ChinaCollaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, ChinaNational Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, ChinaTaklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, ChinaXinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, ChinaKey Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, ChinaNational Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, ChinaTaklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, ChinaXinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, ChinaKey Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, ChinaNational Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, ChinaTaklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, ChinaXinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, ChinaKey Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, ChinaNational Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, ChinaTaklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, ChinaXinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, ChinaKey Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, ChinaCollaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, ChinaDepartment of Engineering Physics, College of Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur 522302, Andhra Pradesh, India<p>A comprehensive and robust dataset of tropospheric aerosol properties is important for understanding the effects of aerosol–radiation feedback on the climate system and reducing the uncertainties of climate models. The “Third Pole” of Earth (Tibetan Plateau, TP) is highly challenging for obtaining long-term in situ aerosol data due to its harsh environmental conditions. Here, we provide the more reliable new vertical aerosol index (AI) parameter from the spaceborne-based lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) on board CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) for daytime and nighttime to investigate the aerosol's climatology over the TP region during 2007–2020. The calculated vertical AI was derived from the aerosol extinction coefficient (EC), which was rigorously quality-checked and validated for passive satellite sensors (MODIS) and ground-based lidar measurements. Generally, our results demonstrated that there was agreement of the AI dataset with the CALIOP and ground-based lidar. In addition, the results showed that, after removing the low-reliability aerosol target signal, the optimized data can obtain the aerosol characteristics with higher reliability. The data also reveal the patterns and concentrations of high-altitude vertical structure characteristics of the tropospheric aerosol over the TP. They will also help to update and make up the observational aerosol data in the TP. We encourage climate modelling groups to consider new analyses of the AI vertical patterns, comparing the more accurate datasets, with the potential to increase our understanding of the aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI) and their climate effects. Data described in this work are available at <a href="https://doi.org/10.11888/Atmos.tpdc.300614">https://doi.org/10.11888/Atmos.tpdc.300614</a> (Huang, 2023).</p>https://essd.copernicus.org/articles/16/1185/2024/essd-16-1185-2024.pdf |
| spellingShingle | H. Pan H. Pan H. Pan H. Pan H. Pan H. Pan J. Huang J. Li Z. Huang M. Wang M. Wang M. Wang M. Wang M. Wang A. Mamtimin A. Mamtimin A. Mamtimin A. Mamtimin A. Mamtimin W. Huo W. Huo W. Huo W. Huo W. Huo F. Yang F. Yang F. Yang F. Yang F. Yang T. Zhou K. R. Kumar The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020 Earth System Science Data |
| title | The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020 |
| title_full | The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020 |
| title_fullStr | The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020 |
| title_full_unstemmed | The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020 |
| title_short | The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020 |
| title_sort | tibetan plateau space based tropospheric aerosol climatology 2007 2020 |
| url | https://essd.copernicus.org/articles/16/1185/2024/essd-16-1185-2024.pdf |
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