Retrieval of atmospheric parameters from GOMOS data
Retrieval of atmospheric parameters from GOMOS data
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DOI：
10.5194/acp-10-11881-2010
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发表时间：
2010-12
影响因子：
6.3
通讯作者：
E. Kyrölä;J. Tamminen;V. Sofieva;J. Bertaux;Alain Hauchecorne;F. Dalaudier;D. Fussen;F. Vanhellemont;O. F. d'Andon;G. Barrot;M. Guirlet;A. Mangin;L. Blanot;T. Fehr;L. S. D. Miguel;R. Fraisse
中科院分区：
文献类型：
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作者：
E. Kyrölä;J. Tamminen;V. Sofieva;J. Bertaux;Alain Hauchecorne;F. Dalaudier;D. Fussen;F. Vanhellemont;O. F. d'Andon;G. Barrot;M. Guirlet;A. Mangin;L. Blanot;T. Fehr;L. S. D. Miguel;R. Fraisse
抽象的。欧洲航天局 ENVISAT 卫星上的掩星全球臭氧监测 (GOMOS) 仪器可测量掩星几何中恒星光的衰减。白天测量还记录来自大气的散射太阳光。波长区域为紫外-可见波段 248-690 nm 和两个红外波段 755-774 nm 和 926-954 nm。从紫外可见光谱和红外光谱中，可以检索 O3、NO2、NO3、H2O、O2 和气溶胶的垂直剖面。此外，还有两个 1 kHz 光度计，蓝色 473–527 nm 和红色 646–698 nm。光度计数据用于校正光谱仪的闪烁测量并检索高分辨率温度分布以及重力波和湍流参数。测量范围覆盖5-150公里的海拔区域。大气有效数据在 15-100 公里范围内获得。在本文中，我们概述了用于恒星掩星测量的 GOMOS 检索算法。恒星的点源性质导致的低信噪比和折射效应一直是 GOMOS 反演算法发展的重要驱动力。我们首先介绍 1b 级算法，用于校正光谱仪和光度计测量中与仪器相关的干扰。2 级算法处理大气气体成分、气溶胶和高分辨率温度的垂直剖面的检索。我们将演示分为折射效应校正、高分辨率温度反演和光谱/垂直反演。本文还讨论了 GOMOS 算法的开发、预期的改进、GOMOS 数据的访问和替代检索方法。
Abstract. The Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the European Space Agency's ENVISAT satellite measures attenuation of stellar light in occultation geometry. Daytime measurements also record scattered solar light from the atmosphere. The wavelength regions are the ultraviolet-visible band 248–690 nm and two infrared bands at 755–774 nm and at 926–954 nm. From UV-Visible and IR spectra the vertical profiles of O3, NO2, NO3, H2O, O2 and aerosols can be retrieved. In addition there are two 1 kHz photometers at blue 473–527 nm and red 646–698 nm. Photometer data are used to correct spectrometer measurements for scintillations and to retrieve high resolution temperature profiles as well as gravity wave and turbulence parameters. Measurements cover altitude region 5–150 km. Atmospherically valid data are obtained in 15–100 km. In this paper we present an overview of the GOMOS retrieval algorithms for stellar occultation measurements. The low signal-to-noise ratio and the refractive effects due to the point source nature of stars have been important drivers in the development of GOMOS retrieval algorithms. We present first the Level 1b algorithms that are used to correct instrument related disturbances in the spectrometer and photometer measurements The Level 2 algorithms deal with the retrieval of vertical profiles of atmospheric gaseous constituents, aerosols and high resolution temperature. We divide the presentation into correction for refractive effects, high resolution temperature retrieval and spectral/vertical inversion. The paper also includes discussion about the GOMOS algorithm development, expected improvements, access to GOMOS data and alternative retrieval approaches.