Cloud top heights and aerosol layer properties from EarthCARE lidar observations: the A-CTH and A-ALD products

Author:

Wandinger UllaORCID,Haarig MoritzORCID,Baars HolgerORCID,Donovan David,van Zadelhoff Gerd-JanORCID

Abstract

Abstract. The high-spectral-resolution Atmospheric Lidar (ATLID) on the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) provides vertically resolved information on aerosols and clouds with unprecedented accuracy. Together with the Cloud Profiling Radar (CPR), the Multi-Spectral Imager (MSI), and the Broad-Band Radiometer (BBR) on the same platform, it allows for a new synergistic view on atmospheric processes related to the interaction of aerosols, clouds, precipitation, and radiation at the global scale. This paper describes the algorithms for the determination of cloud top height and aerosol layer information from ATLID Level 1b (L1b) and Level 2a (L2a) input data. The ATLID L2a Cloud Top Height (A-CTH) and Aerosol Layer Descriptor (A-ALD) products are developed to ensure the provision of atmospheric layer products in continuation of the heritage from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Moreover, the products serve as input for synergistic algorithms that make use of data from ATLID and MSI. Therefore, the products are provided on the EarthCARE joint standard grid (JSG). A wavelet covariance transform (WCT) method with flexible thresholds is applied to determine layer boundaries from the ATLID Mie co-polar signal. Strong features detected with a horizontal resolution of 1 JSG pixel (approximately 1 km) or 11 JSG pixels are classified as thick or thin clouds, respectively. The top height of the uppermost cloud layer together with information on cloud layering are stored in the A-CTH product for further use in the generation of the ATLID-MSI Cloud Top Height (AM-CTH) synergy product. Aerosol layers are detected as weaker features at a resolution of 11 JSG pixels. Layer-mean optical properties are calculated from the ATLID L2a Extinction, Backscatter and Depolarization (A-EBD) product and stored in the A-ALD product, which also contains the aerosol optical thickness (AOT) of each layer, the stratospheric AOT, and the AOT of the entire atmospheric column. The latter parameter is used to produce the synergistic ATLID-MSI Aerosol Column Descriptor (AM-ACD) later in the processing chain. Several quality criteria are applied in the generation of A-CTH and A-ALD, and respective information is stored in the products. The functionality and performance of the algorithms are demonstrated by applying them to common EarthCARE test scenes. Conclusions are drawn for the application to real-world data and the validation of the products after the launch of EarthCARE.

Funder

European Space Agency

Publisher

Copernicus GmbH

Subject

Atmospheric Science

Reference50 articles.

1. Baars, H., Ansmann, A., Engelmann, R., and Althausen, D.: Continuous monitoring of the boundary-layer top with lidar, Atmos. Chem. Phys., 8, 7281–7296, https://doi.org/10.5194/acp-8-7281-2008, 2008. a, b, c, d

2. Baars, H., Kanitz, T., Engelmann, R., Althausen, D., Heese, B., Komppula, M., Preißler, J., Tesche, M., Ansmann, A., Wandinger, U., Lim, J.-H., Ahn, J. Y., Stachlewska, I. S., Amiridis, V., Marinou, E., Seifert, P., Hofer, J., Skupin, A., Schneider, F., Bohlmann, S., Foth, A., Bley, S., Pfüller, A., Giannakaki, E., Lihavainen, H., Viisanen, Y., Hooda, R. K., Pereira, S. N., Bortoli, D., Wagner, F., Mattis, I., Janicka, L., Markowicz, K. M., Achtert, P., Artaxo, P., Pauliquevis, T., Souza, R. A. F., Sharma, V. P., van Zyl, P. G., Beukes, J. P., Sun, J., Rohwer, E. G., Deng, R., Mamouri, R.-E., and Zamorano, F.: An overview of the first decade of PollyNET: an emerging network of automated Raman-polarization lidars for continuous aerosol profiling, Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, 2016. a

3. Barker, H. W., Cole, J. N. S., Qu, Z., Villefranque, N., and Shephard, M.: EarthCARE's continuous radiative closure assessment: Summary and application to data from a synthetic observing system, in preparation, 2023.​​​​​​​ a

4. Berthier, S., Chazette, P., Pelon, J., and Baum, B.: Comparison of cloud statistics from spaceborne lidar systems, Atmos. Chem. Phys., 8, 6965–6977, https://doi.org/10.5194/acp-8-6965-2008, 2008. a

5. Bravo-Aranda, J. A., de Arruda Moreira, G., Navas-Guzmán, F., Granados-Muñoz, M. J., Guerrero-Rascado, J. L., Pozo-Vázquez, D., Arbizu-Barrena, C., Olmo Reyes, F. J., Mallet, M., and Alados Arboledas, L.: A new methodology for PBL height estimations based on lidar depolarization measurements: analysis and comparison against MWR and WRF model-based results, Atmos. Chem. Phys., 17, 6839–6851, https://doi.org/10.5194/acp-17-6839-2017, 2017. a

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3