Ghost is unavoidable in marine seismic data acquisition, limiting the bandwidth of useful information and reducing the resolution of imaging results. In the deghosting method, the 3D algorithms can better eliminate the 3D effect compared with the conventional 2D algorithm. However, the 3D algorithm requires dense sampling in the crossline direction, which means greater storage space and computational cost. In this paper, we propose a pseudo-3D deghosting method to get rid of the limitation of dense spatial sampling. We arrange the conventional 2D multi-shot gathers in the form of 3D data cube by time, offset and shot number to achieve simultaneous deghosting for multi-shot gathers; We also introduce a sparse transform based L1 constraint to avoid local minimum. The basic idea of our method is including the information of the common offset gathers (COGs) into the deghosting to improve the inversion accuracy. The proposed method is easy to implemented without any pre-processing, and field example demonstrates the effectiveness of the proposed method.

Results are presented of the GASS/EUCLIPSE single-column model intercomparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate models for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pacific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple metrics to establish the model performance. Using this method, some longstanding problems in low-level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure, and the associated impact on radiative transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median exhibits the well-known “too few too bright” problem. The boundary-layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular, the vertical structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid parameterization.