Cloud masks and cloud type classification using EarthCARE CPR and ATLID

IF 3.2 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Measurement Techniques Pub Date : 2024-08-05 DOI:10.5194/amt-2024-103
Hajime Okamoto, Kaori Sato, Tomoaki Nishizawa, Yoshitaka Jin, Shota Ogawa, Hiroshi Ishimoto, Yuichiro Hagihara, EIji Oikawa, Maki Kikuchi, Masaki Satoh, Wooosub Roh
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Abstract

Abstract. We develop the Japan Aerospace Exploration Agency (JAXA) level 2 cloud mask and cloud type classification algorithms for the Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE), a joint JAXA and European Space Agency (ESA) satellite mission. Cloud profiling radar (CPR)-only, atmospheric lidar (ATLID)-only, and combined CPR–ATLID algorithms for the cloud mask and cloud particle type are described. The algorithms are developed and evaluated using ground-based data, space-borne data from CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and simulation data from a Japanese global cloud-resolving model, the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with Joint simulator. The algorithms are based on our algorithms for CloudSat and CALIPSO with several improvements. The cloud particle type for ATLID is derived from an attenuation–depolarization diagram trained using 355 nm multiple-field-of-view multiple-scattering polarization lidar and changing the diagram from that developed for CALIPSO. The retrieved cloud particle phases (ice, water, and mixed phases) and those reported in the NICAM output data are compared. We found that the agreement for CPR-only, ATLID-only, and combined CPR–ATLID algorithms averaged roughly 80 %, 85 %, and 80 %, respectively, for 15 different cloud scenes corresponding to two EarthCARE orbits.
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利用 EarthCARE CPR 和 ATLID 进行云掩膜和云类型分类
摘要。我们为日本宇宙航空研究开发机构(JAXA)和欧洲航天局(ESA)的联合卫星任务--地球云层、气溶胶和辐射探测器(EarthCARE)--开发了日本宇宙航空研究开发机构(JAXA)的 2 级云掩膜和云类型分类算法。文中介绍了仅使用云轮廓雷达 (CPR)、仅使用大气激光雷达 (ATLID) 以及结合 CPR 和 ATLID 算法的云掩膜和云粒子类型。这些算法是利用地基数据、云卫星和云-气溶胶激光雷达及红外探路者卫星观测(CALIPSO)提供的星载数据以及日本全球云解析模式--非静力学二十面体大气模式(NICAM)联合模拟器提供的模拟数据开发和评估的。这些算法基于我们为 CloudSat 和 CALIPSO 研发的算法,并做了一些改进。ATLID 的云粒子类型来自使用 355 nm 多视场多散射偏振激光雷达训练的衰减-偏振图,并改变了为 CALIPSO 开发的图。我们将检索到的云粒子相(冰、水和混合相)与 NICAM 输出数据中报告的云粒子相进行了比较。我们发现,在两个 EarthCARE 轨道对应的 15 个不同云场景中,纯 CPR、纯 ATLID 和 CPR-ATLID 组合算法的平均一致性分别约为 80%、85% 和 80%。
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来源期刊
Atmospheric Measurement Techniques
Atmospheric Measurement Techniques METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
7.10
自引率
18.40%
发文量
331
审稿时长
3 months
期刊介绍: Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere. The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.
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