Retrieval of two-layer cloud properties from multispectral observations using optimal estimation

Watts, P. D.; Bennartz, Ralf; Fell, Frank

doi:10.1029/2011jd015883

Cited by 72 publications

(78 citation statements)

References 19 publications

(26 reference statements)

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“…Davis et al (2009) also showed that the presence of ice clouds can significantly bias the retrievals of liquid cloud properties in the MODIS algorithm (collection 5) (King et al, 1998). Watts et al (2011) confirmed that the simultaneous retrieval of liquid cloud properties can improve retrievals of ice-cloud properties significantly. More recently, a study by Sourdeval et al (2013) also demonstrated that the quality of retrievals of cirrus microphysical and optical properties can be strongly impacted by under-constrained properties of underlying liquid water clouds.…”

Section: Introductionsupporting

confidence: 63%

“…The emergence of such possibilities of synergism was a notable factor in the resurgence of algorithms based on variational methods, such as optimal estimation (e.g. Watts et al, 1998Watts et al, , 2011Hogan, 2008, 2010;Austin et al, 2009;Deng et al, 2010). Such methods indeed prove to be particularly efficient for dealing with large quantities of measurements, in order to retrieve different kinds of cloud parameters.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study

Sourdeval

C.‐Labonnote

Baran

et al. 2014

Quart J Royal Meteoro Soc

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This article presents a novel methodology dedicated to retrieving the optical and microphysical properties of ice and liquid water clouds simultaneously. An optimal estimation method is used to retrieve the ice water path of one ice-cloud layer and the optical thickness and droplet effective radius of up to two liquid-water cloud layers, along with rigorous uncertainties. In order to perform the retrievals, radiometric measurements in five channels ranging from the visible to the thermal infrared are utilized. The position of cloud layers is currently provided by lidar information, which narrows the retrievals to its track. In the first part of this article, theoretical information content analyses are performed under different atmospheric conditions, over an oceanic surface. This type of analysis quantifies prior to the retrievals the amount of information that should be available regarding each parameter to be retrieved and helps to identify which set of channels provides this information. It is observed that strong information can be expected for retrieving each parameter in double-layer cases, while yet stronger limitations appear in triple-layer cases. In the second part of this article, our methodology is applied to a case study. In agreement with a priori expectations, accurate retrievals of ice and liquid cloud properties are obtained. These results are later compared with the products of a single-layer retrieval method, CloudAerosol Lidar with Orthogonal Polarization (CALIOP) operational products and in situ estimates. We show that a much better consistency with the latter two is found when retrieving the properties of each layer simultaneously. However, further statistical analyses and comparisons with various operational products should be undertaken for validation of the methodology. Such results will be presented in the second part of this study.

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Section: Introductionsupporting

confidence: 63%

Section: Introductionmentioning

confidence: 99%

A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study

Sourdeval

C.‐Labonnote

Baran

et al. 2014

Quart J Royal Meteoro Soc

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show abstract

“…However, the use of such methods to simultaneously retrieve ice and liquid water cloud properties is still quite rare. It has nevertheless been shown that such algorithms do not only provide a much more complete and coherent description of the atmosphere, but can also improve retrievals of cirrus properties through optimal constraints on properties of liquid water clouds that may lie underneath [6]. This paper presents an algorithm developed to simultaneously retrieve properties of one ice cloud and two liquid water cloud layers.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous multi-layer retrievals of ice and liquid water cloud properties using passive measurements

Sourdeval¹,

C.‐Labonnote²,

Brogniez³

et al. 2013

AIP Conference Proceedings

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Abstract. Cirrus are recognized as having a major, yet poorly understood impact on the Earth-atmosphere radiation balance. The precise study of their properties is thus necessary nowadays, in order to supply accurate information to climate models. Therefore, many studies have been conducted during the past decades to characterize cirrus properties more accurately. Amongst them, the A-Train mission has proven to be particularly important, thanks to a multitude of active and passive instruments. Aiming to take advantage of these new possible of synergies, variational methods, such as optimal estimation, have become commonly used to retrieve properties of ice or liquid water cloud layers. Simultaneous retrievals of ice and liquid clouds properties nevertheless remain rare. In this study, an algorithm dedicated to performing such simultaneous multi-layer retrievals is presented. This algorithm uses the information contained in five channels situated in the visible, near infrared and thermal infrared regions, to retrieve the ice water content of one ice cloud layer, and the optical thickness and droplet effective radius of two possible liquid cloud layers. This paper presents preliminary results of the algorithm that correspond to one month of retrievals, under several CALIOP orbits. Comparisons with products of operational algorithms such as MODIS or DARDAR show good agreement with our retrievals.

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“…Many groups are now using optimal estimation techniques to estimate cloud properties (e.g. Heidinger et al, 2010;Watts et al, 1998); however the capability of optimal estimation to include a priori information is not always utilised due to a lack of collocated information of sufficient accuracy and independence. Heidinger et al (2010) have used climatological data as a priori information with mixed results, OCA (optimal cloud analysis) and ORAC use European Centre for Medium-range Weather Forecasting (ECMWF) ERA Interim reanalysis sea surface temperature data as a priori to the surface temperature state vector.…”

Section: Introductionmentioning

confidence: 99%

“…The ORAC (Optimal Retrieval of Aerosol and Cloud) algorithm (Poulsen et al, 2012;Watts et al, 1998) employs the optimal estimation approach (Rogers, 2000) based on radiometric retrieval principles and has been extensively applied to the Along Track Scanning Radiometer Instruments (ATSR), specifically ATSR-2 (1995, Mutlow et al, 1999 and the Advanced-ATSR (2002, LlewellynJones et al, 2001. The radiometric configuration of ATSR-2 and AATSR comprises seven channels at 0.…”

Section: Introductionmentioning

confidence: 99%

Synergy of stereo cloud top height and ORAC optimal estimation cloud retrieval: evaluation and application to AATSR

et al. 2016

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Abstract. In this paper we evaluate the impact on the cloud parameter retrievals of the ORAC (Optimal Retrieval of Aerosol and Cloud) algorithm following the inclusion of stereo-derived cloud top heights as a priori information. This is performed in a mathematically rigorous way using the ORAC optimal estimation retrieval framework, which includes the facility to use such independent a priori information. Key to the use of a priori information is a characterisation of their associated uncertainty. This paper demonstrates the improvements that are possible using this approach and also considers their impact on the microphysical cloud parameters retrieved. The Along-Track Scanning Radiometer (AATSR) instrument has two views and three thermal channels, so it is well placed to demonstrate the synergy of the two techniques. The stereo retrieval is able to improve the accuracy of the retrieved cloud top height when compared to collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), particularly in the presence of boundary layer inversions and high clouds. The impact of the stereo a priori information on the microphysical cloud properties of cloud optical thickness (COT) and effective radius (RE) was evaluated and generally found to be very small for single-layer clouds conditions over open water (mean RE differences of 2.2 (±5.9) microns and mean COD differences of 0.5 (±1.8) for single-layer ice clouds over open water at elevations of above 9 km, which are most strongly affected by the inclusion of the a priori).

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Retrieval of two-layer cloud properties from multispectral observations using optimal estimation

Cited by 72 publications

References 19 publications

A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study

A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study

Simultaneous multi-layer retrievals of ice and liquid water cloud properties using passive measurements

Synergy of stereo cloud top height and ORAC optimal estimation cloud retrieval: evaluation and application to AATSR

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