FAME-C: Retrieval of cloud top pressure with vertically inhomogeneous cloud profiles

Henken, Cintia Carbajal; Lindstrot, R.; Filipitsch, Florian; Walther, A.; Preusker, R.; Fischer, Jürgen

doi:10.1063/1.4804794

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…For two case studies with vertically extended clouds it was shown that the choice of the cloud vertical extinction profile can have a large impact on the retrieved MERIS cloud-top pressure. Comparisons to CPR cloud heights showed that on average the bias was reduced by a large amount when using the mean CPR-profiles instead of vertically homogeneous profiles (HOM) (Henken et al, 2013). This can be mainly attributed to lower extinction values in the upper cloud layers for the CPR-profiles than for the HOM profiles, which appears to be closer to reality for these vertically extended clouds.…”

Section: Introductionmentioning

confidence: 90%

“…Since the vertical extent is fixed, no further assumption on the CGT in the forward model are needed for these profiles. More details on the resulting profiles and their incorporation into the FAME-C algorithm can be found in Henken et al (2013) and Carbajal Henken et al (2014). The derived normalized extinction profiles (from here on called CPR-profiles/clouds) were then used in the MOMO radiative transfer simulations to generate look-up tables (LUTs) for each of the nine cloud types.…”

Section: Sensitivity Studymentioning

confidence: 99%

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Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

Henken¹,

Doppler

Lindstrot

et al. 2015

Atmos. Meas. Tech.

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Abstract. This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud-top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud-top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band and a nearby window channel. Both CTT and CTP are converted to cloud-top height (CTH) using atmospheric profiles from a numerical weather prediction model. First, a sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared was performed to demonstrate, in a quantitative manner, the larger impact of the assumed cloud vertical extinction profile, described in terms of shape and vertical extent, on MERIS than on AATSR top-of-atmosphere measurements. Consequently, cloud vertical extinction profiles will have a larger influence on the MERIS than on the AATSR cloud height retrievals for most cloud types.Second, the difference in retrieved CTH ( CTH) from AATSR and MERIS are related to cloud vertical extent (CVE), as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. Similarly to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the CTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is stronger for single-layer clouds than for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent is accompanied with large uncertainties.Yet, estimates of the CVE provide an additional parameter, next to CTH, that can be obtained from passive imager measurements and can be used to further describe cloud vertical distribution, thus contributing to the characterization of a cloudy scene.To further demonstrate the plausibility of the approach, an estimate of the CVE was applied to a case study. In light of the follow-up mission Sentinel-3 with AATSR and MERIS like instruments, Sea and Land Surface Temperature Radiometer (SLSTR) and (Ocean and Land Colour Instrument) OLCI, respectively, for which the FAME-C algorithm can be easily adapted, a more accurate estimate of the CVE can be expected. OLCI will have three channels in the oxygen-A absorption band, possibly providing enhanced information on cloud vertical distributions.

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Section: Introductionmentioning

confidence: 90%

Section: Sensitivity Studymentioning

confidence: 99%

Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

Henken¹,

Doppler

Lindstrot

et al. 2015

Atmos. Meas. Tech.

View full text Add to dashboard Cite

show abstract

“…This increase depends on the vertical extinction profile of the cloud. To derive "realistic" cloud vertical extinction profiles for nine cloud types based on the ISCCP cloud classification (ISCCP), 1 year (2010) of layer optical thicknesses as provided by the CloudSat database is used as described in Henken et al (2013). The geometrical thickness of each cloud type, i.e., the number of adjacent cloud layers with a thickness of 20 hPa, is taken constant and based on an empirical analysis of a number of CloudSat scenes.…”

Section: Meris Cloud Top Pressurementioning

confidence: 99%

FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

et al. 2014

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Abstract.A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years [2007][2008][2009]. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 µm and −0.18 g m −2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root-mean-square deviation. Furthermore, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several Atmospheric Radiation Measurement (ARM) sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations. The lowest bias of −0.3 km is found for AATSR cloud top heights for single-layer clouds, while the highest bias of −3.0 km is found for AATSR cloud top heights for multilayer clouds. Variability is low for MERIS cloud top heights for low-level clouds, and high for MERIS cloud top heights for mid-level and high-level single-layer clouds, as well as for both AATSR and MERIS cloud top heights for multilayer clouds.

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The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission

Sayer¹,

Lelli²,

Cairns³

et al. 2023

Atmos. Meas. Tech.

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Abstract. This paper provides the theoretical basis and simulated retrievals for the Cloud Height Retrieval from O2 Molecular Absorption (CHROMA) algorithm. Simulations are performed for the Ocean Color Instrument (OCI), which is the primary payload on the forthcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, and the Ocean Land Colour Instrument (OLCI) currently flying on the Sentinel 3 satellites. CHROMA is a Bayesian approach which simultaneously retrieves cloud optical thickness (COT), cloud-top pressure and height (CTP and CTH respectively), and (with a significant prior constraint) surface albedo. Simulated retrievals suggest that the sensor and algorithm should be able to meet the PACE mission goal for CTP error, which is ±60 mb for 65 % of opaque (COT ≥3) single-layer clouds on global average. CHROMA will provide pixel-level uncertainty estimates, which are demonstrated to have skill at telling low-error situations from high-error ones. CTP uncertainty estimates are well-calibrated in magnitude, although COT uncertainty is overestimated relative to observed errors. OLCI performance is found to be slightly better than OCI overall, demonstrating that it is a suitable proxy for the latter in advance of PACE's launch. CTP error is only weakly sensitive to correct cloud phase identification or assumed ice crystal habit/roughness. As with other similar algorithms, for simulated retrievals of multi-layer systems consisting of optically thin cirrus clouds above liquid clouds, retrieved height tends to be underestimated because the satellite signal is dominated by the optically thicker lower layer. Total (liquid plus ice) COT also becomes underestimated in these situations. However, retrieved CTP becomes closer to that of the upper ice layer for ice COT ≈3 or higher.

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FAME-C: Retrieval of cloud top pressure with vertically inhomogeneous cloud profiles

Cited by 3 publications

References 4 publications

Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission

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