FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2

Desmons, Marine; Wang, Ping; Stammes, P.; Tilstra, L. G.

doi:10.5194/amt-12-2485-2019

Cited by 14 publications

(12 citation statements)

References 28 publications

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“…The GOME-2 NO 2 measurements have been widely used in trend studies, satellite dataset intercomparisons, and NO 2 emission estimations (e.g. Mijling et al, 2013;Hilboll et al, 2013Hilboll et al, , 2017Krotkov et al, 2017;Irie et al, 2012;Gu et al, 2014;Miyazaki et al, 2017;Ding et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

et al. 2020

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Abstract. An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parameterisation over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS (CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a clouds-as-layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current clouds-as-reflecting-boundaries (CRB) model, which assumes that the clouds are Lambertian reflectors. On average, improvements in the AMF calculation affect the tropospheric NO2 columns by ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and the aerosol-induced cloud parameters (implicit aerosol correction). Compared with the implicit aerosol correction utilising the CRB cloud parameters, the use of the CAL approach reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based multi-axis differential optical absorption spectroscopy (MAXDOAS) measurements at different BIRA-IASB stations. At the suburban Xianghe station, the improved tropospheric NO2 dataset shows better agreement with coincident ground-based measurements with a correlation coefficient of 0.94.

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Section: Introductionmentioning

confidence: 99%

“…In addition, owing to the generally unavailable full surface BRDF under all conditions and the complexity of accounting for the BRDF, most of the current NO 2 and cloud retrievals still rely on Lambertian surface reflection (e.g. Krotkov et al, 2017;Boersma et al, 2018;van Geffen et al, 2019;Loyola et al, 2018;Desmons et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

et al. 2020

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“…The list of wavelength bands was extended with wavelength bands at 328, 585, 685, 697, and 712 nm. The wavelength bands at 685, 697, and 712 nm were introduced specifically to support cloud and aerosol retrieval near the O 2 -B band, as explained in Desmons et al (2019). See Sect.…”

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confidence: 99%

Directionally dependent Lambertian-equivalent reﬂectivity (DLER) of the Earth's surface measured by the GOME-2 satellite instruments

Tilstra¹,

Tuinder²,

Wang³

et al. 2021

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Abstract. In this paper we introduce the new concept of directionally dependent Lambertian-equivalent reflectivity (DLER) of the Earth's surface retrieved from satellite observations. This surface DLER describes Lambertian (isotropic) surface reflection which is extended with a dependence on the satellite viewing geometry. We apply this concept to data of the GOME-2 satellite instruments, to create a global database of the reflectivity of the Earth's surface, providing surface DLER for 26 wavelength bands between 328 and 772 nm as a function of the satellite viewing angle via a second-degree polynomial parameterisation. The resolution of the database grid is 0.25 by 0.25 degrees but the real, intrinsic spatial resolution varies over the grid from 1.0 by 1.0 degrees to 0.5 by 0.5 degrees down to 0.25 by 0.25 degrees by applying dynamic gridding techniques. The database is based on more than ten years (2007–2018) of GOME-2 data from the MetOp-A and MetOp-B satellites. The relation between surface DLER and surface BRDF is studied using radiative transfer simulations. For the shorter wavelengths (λ 500 nm). Based on this outcome, the GOME-2 surface DLER is compared with MODIS surface BRDF data from MODIS band 1 (centred around 645 nm), using both case studies and global comparisons. The conclusion of this validation is that the GOME-2 DLER compares well to MODIS BRDF, and that it does so much better than the non-directional LER database. The DLER approach for describing surface reflectivity is therefore an important improvement over the standard isotropic (non-directional) LER approaches used in the past. The GOME-2 surface DLER database can be used for the retrieval of atmospheric properties from GOME-2 and from previous satellite instruments like GOME and SCIAMACHY. It will also be used to support retrievals from the future Sentinel-5/UVNS satellite instrument.

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“…In many previous studies on the retrieval of cloud information, the results of FRESCO were validated with other cloud algorithms and ground-based observation, and its accuracy has been verified. For example, [17] compared the cloud parameters from Along-Track Scanning Radiometer 2 (ATSR-2) with GOME FRESCO; [18] compared Atmospheric Radiation Measurement (ARM) active ground-based remote sensing cloud boundaries data and SCIAMACHY FRESCO; and [19] compared GOME-2 FRESCO with the Cloudnet level 2 classification product composed of the vertical Doppler cloud radar and backscatter lidar. They showed good agreement with each comparison target of the FRESCO algorithm.…”

Section: Instrument and Datamentioning

confidence: 99%

“…GOME, GOME-2, and SCIAMACHY use the oxygen A-band (in the three windows of 758-759, 760-761, and 765-766 nm) to obtain information on clouds very rapidly using the Fast Retrieval Scheme for Clouds from the Oxygen A-band (FRESCO) algorithm [17,18]. Additionally, an algorithm using the oxygen B-band (in the three windows: 685-686, 686.8-687.8, and 690-691 nm) has been developed [19]. Obtaining cloud information using a fast scheme can be supplied in the step of near real time (NRT), which can be used to correct or mask the cloud regions in other retrieval algorithms.…”

Section: Introductionmentioning

confidence: 99%

A Fast Retrieval of Cloud Parameters Using a Triplet of Wavelengths of Oxygen Dimer Band around 477 nm

et al. 2021

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Clouds act as a major reflector that changes the amount of sunlight reflected to space. Change in radiance intensity due to the presence of clouds interrupts the retrieval of trace gas or aerosol properties from satellite data. In this paper, we developed a fast and robust algorithm, named the fast cloud retrieval algorithm, using a triplet of wavelengths (469, 477, and 485 nm) of the O2–O2 absorption band around 477 nm (CLDTO4) to derive the cloud information such as cloud top pressure (CTP) and cloud fraction (CF) for the Geostationary Environment Monitoring Spectrometer (GEMS). The novel algorithm is based on the fact that the difference in the optical path through which light passes with regard to the altitude of clouds causes a change in radiance due to the absorption of O2–O2 at the three selected wavelengths. To reduce the time required for algorithm calculations, the look-up table (LUT) method was applied. The LUT was pre-constructed for various conditions of geometry using Vectorized Linearized Discrete Ordinate Radiative Transfer (VLIDORT) to consider the polarization of the scattered light. The GEMS was launched in February 2020, but the observed data of GEMS have not yet been widely released. To evaluate the performance of the algorithm, the retrieved CTP and CF using observational data from the Global Ozone Monitoring Experiment-2 (GOME-2), which cover the spectral range of GEMS, were compared with the results of the Fast Retrieval Scheme for Clouds from the Oxygen A band (FRESCO) algorithm, which is based on the O2 A-band. There was good agreement between the results, despite small discrepancies for low clouds.

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FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2

Cited by 14 publications

References 28 publications

An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

Directionally dependent Lambertian-equivalent reﬂectivity (DLER) of the Earth's surface measured by the GOME-2 satellite instruments

A Fast Retrieval of Cloud Parameters Using a Triplet of Wavelengths of Oxygen Dimer Band around 477 nm

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