Früher|Nächster

O2-O2 cloud retrieval algorithm and application to TROPOMI

  • role： First author第一作者
  • Affiliation：

    School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China

  • Email：zwq16@mail.ustc.edu.cn
  • Introduction：张文强，1994年生，男，硕士研究生，研究方向为大气中云卫星遥感反演。E-mail: zwq16@mail.ustc.edu.cn
ZHANG Wenqiang1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China

    School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China

    Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China

    Anhui Province Key Laboratory of Polar Environment and Global Change, University of Science and Technology of China, Hefei 230026, China

  • Email：chliu81@ustc.edu.cn
  • Introduction：刘诚，1981年生，男，教授，研究方向为大气物理化学、卫星与飞机遥感及应用和环境污染监测。E-mail: chliu81@ustc.edu.cn
LIU Cheng2345*,  
  • Affiliation：

    European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt 64295, Germany

HAO Nan6,  
  • Affiliation：

    European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt 64295, Germany

GIMENO GARCIA Sebastian6,  
  • Affiliation：

    School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China

XING Chengzhi3,  
  • Affiliation：

    School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China

ZHANG Chengxin3,  
  • Affiliation：

    School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China

SU Wenjing3,  
  • Affiliation：

    Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China

LIU Jianguo2

Resümee

The cloud covers more than 50% of the Earth, which plays a major role in radiation budget of Earth climate system and hydrological cycle through their strong impact on radiation process. Cloud is an important factor to affect the retrieval accuracy of trace gases during the measurement of air pollution based on remote sensing method. The effective cloud fraction and cloud pressure should be used in the process of correcting cloud effects. In this paper, O2-O2 cloud retrieval algorithm based on O2-O2 absorption band at 477 nm will be described.The O2-O2 cloud retrieval algorithm is developed based on the Look-Up Table (LUT) method. Effective cloud fraction and cloud pressure LUTs were generated using VLIDORT radiation transfer model based on the relationships of effective cloud fraction, cloud pressure, continuum reflectance and O2-O2 slant column density. Then, the Differential Optical Absorption Spectroscopy (DOAS) is used to fit the radiance of top-of-atmosphere measured by the satellite payload, to obtain O2-O2 slant column density and the continuum reflectance. Finally, combined with the auxiliary data, the effective cloud fraction and cloud pressure are retrieved by the interpolation based on the LUTs.We have a validation between the O2-O2 cloud retrieval algorithm results based on OMI data and OMCLDO2 products. The spatial distribution of the effective cloud fraction and cloud pressure show great consistency, and the correlation coefficients (R) between them are greater than 0.97. Then the O2-O2 cloud retrieval algorithm was applied to the new generation of atmospheric sounding instrument TROPOMI. The cloud retrieval results also show high correlation compared with the FRESCO+ results, and R of effective cloud fraction and cloud pressure between above two results are greater than 0.97 and 0.95, respectively, when the surface type is ocean. The time series analysis of three months in Beijing from the two algorithms shows the good consistency of the retrieval results. Moreover, we compared with CALIOP Cloud Layer products using all the retrieved cloud pressure results of FRESCO+ and O2-O2 cloud retrieval algorithm. O2-O2 cloud retrieval algorithm performed better than FRESCO+ under low cloud condition. However, the FRESCO+ retrieval results are closer to CALIOP cloud pressure than O2-O2 cloud retrieval algorithm under high cloud condition.The O2-O2 cloud retrieval algorithm was used during the cloud retrieval of OMI and TROPOMI, and it shows high accuracy and feasibility. This kind of algorithm can provide information of effective cloud fraction and cloud pressure in the process of atmospheric trace gases retrieval. The more important is that O2-O2 cloud retrieval algorithm could provide reference for the development of cloud retrieval algorithm applied to the same type of satellite payload of China.

Schlüsselwort

remote sensing;O2-O2;effective cloud fraction;cloud pressure;look-up table;OMI;TROPOMI;CALIPSO

References

  1. 1.
    Acarreta J R, De Haan J F and Stammes P. 2004. Cloud pressure retrieval using the O2-O2 absorption band at 477 nm. Journal of Geophysical Research, 109(D5): D05204
  2. 2.
    Anderson G P, Clough S, Kneizys F X, Chetwynd J H and Shettle E P. 1986. AFGL Atmospheric Constituent Profiles (0—120 km). AFGL-TR-86-0110. Air Force Geophysics Laboratory
  3. 3.
    Brion J, Chakir A, Charbonnier J, Daumont D, Parisse C and Malicet J. 1998. Absorption spectra measurements for the ozone molecule in the 350-830 nm region. Journal of atmospheric chemistry, 30(2): 291-299
  4. 4.
    Chance K V and Spurr R J D. 1997. Ring effect studies: Rayleigh scattering, including molecular parameters for rotational Raman scattering, and the Fraunhofer spectrum. Applied Optics, 36(21): 5224-5230
  5. 5.
    Danielson J J and Gesch D B. 2011. Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010. Open-File Report 2011-1073. US Geological Survey
  6. 6.
    Deschamps P Y, Fouquart Y, Tanre D, Herman M, Lenoble J, Buriez J C, Dubuisson P, Parol F and Vanbauce C. 1994. Study on the Effects of Scattering on the Monitoring of Atmospheric Constituents. ESA Report 3838, ESA contract number 9740/91 /NL/BI. Eur Space Agency
  7. 7.
    Dirksen R, Dobber M, Voors R and Levelt P. 2006. Prelaunch characterization of the Ozone Monitoring Instrument transfer function in the spectral domain. Applied Optics, 45(17): 3972-3981
  8. 8.
    Joiner J, Vasilkov A P, Flittner D E, Gleason J F and Bhartia P K. 2004. Retrieval of cloud pressure and oceanic chlorophyll content using Raman scattering in GOME ultraviolet spectra. Journal of Geophysical Research, 109(D1): D01109
  9. 9.
    Kleipool Q, Ludewig A, Babić L, Bartstra R, Braak R, Dierssen W, Dewitte P J, Kenter P, Landzaat R, Leloux J, Loots E, Meijering P, van der Plas E, Rozemeijer N, Schepers D, Schiavini D, Smeets J, Vacanti G, Vonk F and Veefkind P. 2018. Pre-launch calibration results of the TROPOMI payload on-board the Sentinel 5 Precursor satellite. Atmospheric Measurement Techniques Discussions
  10. 10.
    Koelemeijer R B A and Stammes P. 1999. Validation of Global Ozone Monitoring Experiment cloud fractions relevant for accurate ozone column retrieval. Journal of Geophysical Research, 104(D15): 18801-18814
  11. 11.
    Koelemeijer R B A, Stammes P, Hovenier J W and de Haan J F. 2001. A fast method for retrieval of cloud parameters using oxygen A band measurements from the Global Ozone Monitoring Experiment. Journal of Geophysical Research, 106(D4): 3475-3490
  12. 12.
    Kokhanovsky A A and Rozanov V V. 2008. The uncertainties of satellite DOAS total ozone retrieval for a cloudy sky. Atmospheric Research, 87(1): 27-36
  13. 13.
    Letu H, Ishimoto H, Riedi J, Nakajima T Y, Labonnote L C, Baran A J, Nagao T M and Sekiguchi M. 2016. Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission. Atmospheric Chemistry and Physics, 16(18): 12287-12303
  14. 14.
    Letu H, Nagao T M, Nakajima T Y, Riedi J, Ishimoto H, Baran A J, Shang H Z, Sekiguchi M and Kikuchi M. 2019. Ice cloud properties from Himawari-8/AHI next-generation geostationary satellite: capability of the AHI to monitor the DC cloud generation process. IEEE Transactions on Geoscience and Remote Sensing, 57(6): 3229-3239
  15. 15.
    Li L, Shi R H, Chen Y Y, Xu Y M, Bai K X and Zhang J. 2013. Spatio-temporal characteristics of NO2 in China and the anthropogenic influences analysis based on OMI Data. Journal of Geo-Information Science, 15(5): 688-694
  16. 16.
    Liu X, Newchurch M J, Loughman R and Bhartia P K. 2004. Errors resulting from assuming opaque Lambertian clouds in TOMS ozone retrieval. Journal of Quantitative Spectroscopy and Radiative Transfer, 85(3/4): 337-365
  17. 17.
    Loyola D G, Gimeno García S, Lutz R, Argyrouli A, Romahn F, Spurr R J D, Pedergnana M, Doicu A, Molina García V and Schüssler O. 2018. The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor. Atmospheric Measurement Techniques, 11(1): 409-427
  18. 18.
    Platt U and Stutz J. 2008. Differential Optical Absorption Spectroscopy: Principles and Applications. Berlin: Springer
  19. 19.
    Rozanov V V and Kokhanovsky A A. 2004. Semianalytical cloud retrieval algorithm as applied to the cloud top altitude and the cloud geometrical thickness determination from top-of-atmosphere reflectance measurements in the oxygen A band. Journal of Geophysical Research, 109(D5): D05202
  20. 20.
    Spurr R J D. 2006. VLIDORT: a linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media. Journal of Quantitative Spectroscopy and Radiative Transfer, 102(2): 316-342
  21. 21.
    Stammes P. 2002. OMI algorithm theoretical basis document, Volume Ⅲ, Clouds, Aerosols, and Surface UV Irradiance. ATBD-OMI-03, Ver. 2.0. OMI: 17-29
  22. 22.
    Stammes P, Sneep M, de Haan J F, Veefkind J P, Wang P and Levelt P F. 2008. Effective cloud fractions from the Ozone Monitoring Instrument: theoretical framework and validation. Journal of Geophysical Research, 113(D16): D16S38
  23. 23.
    Stammes P, Sneep M and Wang P. 2017. Comparison Between FRESCO+ and O2-O2 Derived Cloud Properties from GOME-2. Version 0.2, EUMETSAT CONTRACT EUM/CO/16/4600001778/RL
  24. 24.
    Thalman R and Volkamer R. 2013. Temperature dependent absorption cross-sections of O2-O2 collision pairs between 340 and 630 nm and at atmospherically relevant pressure. Physical Chemistry Chemical Physics, 15(37): 15371-15381
  25. 25.
    Tilstra L G, Tuinder O N E, Wang P and Stammes P. 2017. Surface reflectivity climatologies from UV to NIR determined from Earth observations by GOME-2 and SCIAMACHY. Journal of Geophysical Research, 122(7): 4084-4111
  26. 26.
    van Diedenhoven B, Hasekamp O P and Landgraf J. 2007. Retrieval of cloud parameters from satellite-based reflectance measurements in the ultraviolet and the oxygen A-band. Journal of Geophysical Research, 112(D15): D15208
  27. 27.
    van Geffen J H G M, Boersma K F, Eskes H J, Maasakkers J D and Veefkind J P. 2018. TROPOMI ATBD of the Total and Tropospheric NO2 data Products. S5P-KNMI-L2-0005-RP. TROPOMI
  28. 28.
    Vandaele A C, Hermans C, Simon P C, Carleer M, Colin R, Fally S, Merienne M F, Jenouvrier A and Coquart B. 1998. Measurements of the NO2 absorption cross-section from 42 000 cm-1 to 10 000 cm-1 (238—1000 nm) at 220 K and 294 K. Journal of Quantitative Spectroscopy and Radiative Transfer, 59(3/5): 171-184
  29. 29.
    Vasilkov A, Joiner J, Spurr R, Bhartia P K, Levelt P and Stephens G. 2008. Evaluation of the OMI cloud pressures derived from rotational Raman scattering by comparisons with other satellite data and radiative transfer simulations. Journal of Geophysical Research, 113(D15): D15S19
  30. 30.
    Vaughan M A, Powell K A, Winker D M, Hostetler C A, Kuehn R E, Hunt W H, Getzewich B J, Young S A, Liu Z Y and McGill M J. 2009. Fully automated detection of cloud and aerosol layers in the CALIPSO Lidar measurements. Journal of Atmospheric and Oceanic Technology, 26(10): 2034-2050
  31. 31.
    Veefkind J P, de Haan J F, Sneep M and Levelt P F. 2016. Improvements to the OMI O2-O2 operational cloud algorithm and comparisons with ground-based radar-lidar observations. Atmospheric Measurement Techniques, 9(12): 6035-6049
  32. 32.
    Wagner T, Heland J, Zöger M and Platt U. 2003. A fast H2O total column density product from GOME-validation with in-situ aircraft measurements. Atmospheric Chemistry and Physics, 3(3): 651-663
  33. 33.
    Wagner T, Beirle S, Deutschmann T, Grzegorski M and Platt U. 2008. Dependence of cloud properties derived from spectrally resolved visible satellite observations on surface temperature. Atmospheric Chemistry and Physics, 8(9): 2299-2312
  34. 34.
    Wang P, Stammes P, van der A R, Pinardi G and van Roozendael M. 2008. FRESCO+: an improved O2 A-band cloud retrieval algorithm for tropospheric trace gas retrievals. Atmospheric Chemistry and Physics, 8(21): 6565-6576
  35. 35.
    Wang P, Tuinder O and Stammes P. 2010.Cloud Retrieval Algorithm for GOME-2: FRESCO+, Version 1.3. Eumetsat Contract EUM/CO/09/4600000655/RM
  36. 36.
    Wang P and Stammes P. 2014. Evaluation of SCIAMACHY Oxygen A band cloud heights using Cloudnet measurements. Atmospheric Measurement Techniques, 7(5): 1331-1350
  37. 37.
    Winker D M, Vaughan M A, Omar A, Hu Y X, Powell K A, Liu Z Y, Hunt W H and Young S A. 2009. Overview of the CALIPSO mission and CALIOP data processing algorithms. Journal of Atmospheric and Oceanic Technology, 26(11): 2310-2323
  38. 38.
    Zhang H, Yu C, Su L, Li L J, Fan M, Wang Y P and Chen L F. 2017. Emission control effects observed from space during the military parade 2015 in Beijing. Journal of Remote Sensing, 21(4): 622-632

Lesen Sie die ganze Passage

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website