Using space lidar to infer bubble cloud depth on a global scale

被引:0
作者
Josset, Damien [1 ]
Cayula, Stephanie [1 ]
Anguelova, Magdalena [2 ]
Rogers, W. Erick [1 ]
Wang, David [1 ]
机构
[1] NASA Stennis Space Ctr, Ocean Sci Div, US Naval Res Lab, John C Stennis Space Ctr, MS 39529 USA
[2] US Naval Res Lab, Remote Sensing Div, Washington, DC 20375 USA
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
关键词
CALIPSO; OCEAN;
D O I
10.1038/s41598-024-75551-6
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Visible and microwave satellite measurements can provide the global whitecap fraction. The bubble clouds are three-dimensional structures, and a space-based lidar can provide complementary observations of the bubble depth. Here, we use lidar measurements of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite to quantify global bubble depth from the depolarization. The relationship between CALIPSO bubble depth and wind speed from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and AMSR2 is similar to a recently derived relationship based on buoy measurements. The CALIPSO-based bubble depth data show global distributions and seasonal variations consistent with the high wind speed (> 7 m/s) but with some variance. We also found similarities between the CALIPSO bubble depth and the whitecap fraction from AMSR2 and WindSat. Our findings support the use of spaceborne lidar measurements for advancing the understanding of the 3D bubble properties, and the ocean physics at high wind speeds.
引用
收藏
页数:9
相关论文
共 39 条
  • [21] Development of China's first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration
    Ke, Ju
    Sun, Yingshan
    Dong, Changzhe
    Zhang, Xingying
    Wang, Zijun
    Lyu, Liqing
    Zhu, Wei
    Ansmann, Albert
    Su, Lin
    Bu, Lingbing
    Xiao, Da
    Wang, Shuaibo
    Chen, Sijie
    Liu, Jiqiao
    Chen, Weibiao
    Liu, Dong
    PHOTONIX, 2022, 3 (01)
  • [22] Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
    Hagihara, Yuichiro
    Ohno, Yuichi
    Horie, Hiroaki
    Roh, Woosub
    Satoh, Masaki
    Kubota, Takuji
    ATMOSPHERIC MEASUREMENT TECHNIQUES, 2023, 16 (12) : 3211 - 3219
  • [23] Assessments of Doppler Velocity Errors of EarthCARE Cloud Profiling Radar Using Global Cloud System Resolving Simulations: Effects of Doppler Broadening and Folding
    Hagihara, Yuichiro
    Ohno, Yuichi
    Horie, Hiroaki
    Roh, Woosub
    Satoh, Masaki
    Kubota, Takuji
    Oki, Riko
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [24] The diurnal cycle of cloud profiles over land and ocean between 51° S and 51° N, seen by the CATS spaceborne lidar from the International Space Station
    Noel, Vincent
    Chepfer, Helene
    Chiriaco, Marjolaine
    Yorks, John
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2018, 18 (13) : 9457 - 9473
  • [25] Assessing PM2.5, Aerosol, and Aerosol Optical Depth Concentrations in Hefei Using Modis, Calipso, and Ground-Based Lidar
    Zh. Fang
    H. Yang
    M. Zhao
    Y. Cao
    Ch. Li
    K. Xing
    X. Deng
    Ch. Xie
    D. Liu
    Journal of Applied Spectroscopy, 2021, 88 : 794 - 801
  • [26] Assessing PM2.5, Aerosol, and Aerosol Optical Depth Concentrations in Hefei Using Modis, Calipso, and Ground-Based Lidar
    Fang, Zh
    Yang, H.
    Zhao, M.
    Cao, Y.
    Li, Ch
    Xing, K.
    Deng, X.
    Xie, Ch
    Liu, D.
    JOURNAL OF APPLIED SPECTROSCOPY, 2021, 88 (04) : 794 - 801
  • [27] Evaluation on the Vertical Distribution of Liquid and Ice Phase Cloud Fraction in Community Atmosphere Model Version 5.3 using Spaceborne Lidar Observations
    Guo, Zengyuan
    Wang, Minqi
    Peng, Yiran
    Luo, Yong
    EARTH AND SPACE SCIENCE, 2020, 7 (03)
  • [28] Analysis of Near-Cloud Changes in Atmospheric Aerosols Using Satellite Observations and Global Model Simulations
    Varnai, Tamas
    Marshak, Alexander
    REMOTE SENSING, 2021, 13 (06)
  • [29] Time constraint on global-scale plate reorganizations using records of continental deformation
    Malekpour-Alamdari, Ahmadreza
    INTERNATIONAL GEOLOGY REVIEW, 2024, 66 (19) : 3371 - 3381
  • [30] Retrieval of Atmospheric Aerosol Optical Depth From AVHRR Over Land With Global Coverage Using Machine Learning Method
    Tian, Xiaoqing
    Gao, Ling
    Li, Jun
    Chen, Lin
    Ren, Jingjing
    Li, Chengcai
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60