Cloud information content in EPIC/DSCOVR’s oxygen A- and B-band channels: An optimal estimation approach

Davis, Anthony B.; Merlin, Guillaume; Cornet, Céline; C.‐Labonnote, Laurent; Riédi, J.; Ferlay, Nicolas; Dubuisson, Philippe; Min, Qilong; Yang, Yuekui; Marshak, Alexander

doi:10.1016/j.jqsrt.2018.05.007

Cited by 17 publications

(22 citation statements)

References 41 publications

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“…With the O 2 A-and B-band observations, EPIC provides an unprecedented opportunity to monitor cloud height from the L1 point. An information content analysis on EPIC A-and B-band observations is provided in Davis et al (2018a, b). Figure 3a shows the sensitivity of the EPIC A and B bands to the reflecting layer height change, represented here by the derivative of the above-cloud two-way transmittance (T ) with respect to height (z).…”

Section: Epic Cep/ceh Algorithmmentioning

confidence: 99%

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Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation

et al. 2019

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Abstract. This paper presents the physical basis of the Earth Polychromatic Imaging Camera (EPIC) cloud product algorithms and an initial evaluation of their performance. Since June 2015, EPIC has been providing observations of the sunlit side of the Earth with its 10 spectral channels ranging from the UV to the near-infrared. A suite of algorithms has been developed to generate the standard EPIC Level 2 cloud products that include cloud mask, cloud effective pressure/height, and cloud optical thickness. The EPIC cloud mask adopts the threshold method and utilizes multichannel observations and ratios as tests. Cloud effective pressure/height is derived with observations from the O2 A-band (780 and 764 nm) and B-band (680 and 688 nm) pairs. The EPIC cloud optical thickness retrieval adopts a single-channel approach in which the 780 and 680 nm channels are used for retrievals over ocean and over land, respectively. Comparison with co-located cloud retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the EPIC cloud product algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the Atmospheric Science Data Center at the NASA Langley Research Center for climate studies and for generating other geophysical products that require cloud properties as input.

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Section: Epic Cep/ceh Algorithmmentioning

confidence: 99%

“…From radiative transfer simulations, the differences between the two CEPs resulting from penetration depth difference should be small (Y. Davis et al, 2018a, b). In addition, potential instrument instability, surface albedo differences, calibration accuracy, and changes resulting from the differences in observation time (see Fig.…”

Section: Epic Cep/ceh Algorithmmentioning

confidence: 99%

Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation

et al. 2019

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“…Schuessler et al, 2014). Others rely on multi-angle (Ferlay et al, 2010) or combined A-and B-band information (Yang et al, 2013), although these tend to contain little information on low-altitude and relatively thin clouds like marine stratocumulus (Davis et al, 2018;Merlin et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

A new Orbiting Carbon Observatory 2 cloud flagging method and rapid retrieval of marine boundary layer cloud properties

et al. 2020

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Abstract. The Orbiting Carbon Observatory 2 (OCO-2) carries a hyperspectral A-band sensor that can obtain information about cloud geometric thickness (H). The OCO2CLD-LIDAR-AUX product retrieved H with the aid of collocated CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data to identify suitable clouds and provide a priori cloud top pressure (Ptop). This collocation is no longer possible, since CALIPSO's coordination flying with OCO-2 has ended, so here we introduce a new cloud flagging and a priori assignment using only OCO-2 data, restricted to ocean footprints where solar zenith angle <45∘. Firstly, a multi-layer perceptron network was trained to identify liquid clouds over the ocean with sufficient optical depth (τ>1) for a valid retrieval, and agreement with MODIS–CALIPSO (Moderate Resolution Imaging Spectroradiometer) is 90.0 %. Secondly, we developed a lookup table to simultaneously retrieve cloud τ, effective radius (re) and Ptop from A-band and CO2 band radiances, with the intention that these will act as the a priori state estimate in a future retrieval. Median Ptop difference vs. CALIPSO is 12 hPa with an inter-decile range of [-11,87]hPa, substantially better than the MODIS–CALIPSO range of [-83,81]hPa. The MODIS–OCO-2 τ difference is 0.8[-3.8,6.9], and re is -0.3[-2.8,2.1]µm. The τ difference is due to optically thick and horizontally heterogeneous cloud scenes. As well as an improved passive Ptop retrieval, this a priori information will allow for a purely OCO-2-based Bayesian retrieval of cloud droplet number concentration (Nd). Finally, our cloud flagging procedure may also be useful for future partial-column above-cloud CO2 abundance retrievals.

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“…One of the earthward instruments is the Earth Polychromatic Imaging Camera (EPIC), which can take images of the Earth with a spatial resolution of 10 km at nadir. EPIC continuously monitors the entire sunlit Earth for backscatter, with a nearly constant scattering angle between 168.5 and 175.5 • from sunrise to sunset with 10 narrowband filters: 317, 325, retrieval accuracy from this method can be affected by instrument noise (Davis et al, 2018a, b).…”

Section: Introductionmentioning

confidence: 99%

Cloud-top pressure retrieval with DSCOVR EPIC oxygen A- and B-band observations

et al. 2020

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Abstract. An analytic transfer inverse model for Earth Polychromatic Imaging Camera (EPIC) observations is proposed to retrieve the cloud-top pressure (CTP) with the consideration of in-cloud photon penetration. In this model, an analytic equation was developed to represent the reflection at the top of the atmosphere from above cloud, in cloud, and below cloud. The coefficients of this analytic equation can be derived from a series of EPIC simulations under different atmospheric conditions using a nonlinear regression algorithm. With estimated cloud pressure thickness, the CTP can be retrieved from EPIC observation data by solving the analytic equation. To simulate the EPIC measurements, a program package using the double-k approach was developed. Compared to line-by-line calculation, this approach can calculate high-accuracy results with a 100-fold computation time reduction. During the retrieval processes, two kinds of retrieval results, i.e., baseline CTP and retrieved CTP, are provided. The baseline CTP is derived without considering in-cloud photon penetration, and the retrieved CTP is derived by solving the analytic equation, taking into consideration in-cloud and below-cloud interactions. The retrieved CTPs for the oxygen A and B bands are smaller than their related baseline CTP. At the same time, both baseline CTP and retrieved CTP at the oxygen B band are larger than those at the oxygen A band. Compared to the difference in baseline CTP between the B band and A band, the difference in retrieved CTP between these two bands is generally reduced. Out of around 10 000 cases, in retrieved CTP between the A and B bands we found an average bias of 93 mb with a standard deviation of 81 mb. The cloud layer top pressure from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements is used for validation. Under single-layer cloud situations, the retrieved CTPs for the oxygen A band agree well with the CTPs from CALIPSO, the mean difference of which within 5 mb in the case study. Under multiple-layer cloud situations, the CTPs derived from EPIC measurements may be larger than the CTPs of high-level thin clouds due to the effect of photon penetration.

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Cloud information content in EPIC/DSCOVR’s oxygen A- and B-band channels: An optimal estimation approach

Cited by 17 publications

References 41 publications

Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation

Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation

A new Orbiting Carbon Observatory 2 cloud flagging method and rapid retrieval of marine boundary layer cloud properties

Cloud-top pressure retrieval with DSCOVR EPIC oxygen A- and B-band observations

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