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Yuhe Song and Tao Tang

Abstract

The Turkel-Zwas-type schemes employ coarse grids to discretize the terms associated with the fast gravity-inertia waves and use fine grids to treat the terms associated with the slow Rossby waves. The ratio of the coarse and fine grids is an integer, p>1, and one can use time steps nearly p times larger than those allowed by the Courant-Friedrich-Lewy condition for the usual explicit leapfrog scheme. This paper investigates the Turkel-Zwas-type schemes with three spatial grids-namely, A (unstaggered), B, and C grids (staggered)-for two-dimensional shallow-water equations. A new method that uses the Laplace transform is introduced to solve the two-dimensional phase solutions. Comparisons of the three grids with coarse and fine-grid resolutions are made. One realistic model problem is tested to verify the linear analysis results. The test shows that the Turkel-Zwas-type schemes can be used for a larger time step in some practical simulations.

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Tao Song and Tom Rossby

Abstract

The balance of potential vorticity components following fluid parcel motion in Gulf Stream meanders was studied using RAFOS float data from the SYNOP Experiment. By introducing curvature dependent variations to the velocity and density fields, the authors relaxed the rigid field assumption used in earlier studies and examined closely 61 floats in the upper layers (13°–16°C) of the main thermocline. Float trajectories were segmented according to transition from crest to trough and trough to crest, and grouped by their positions relative to the current center. A total of 154 segments were collected to estimate the horizontal divergence and the mean lateral displacement of parcels under two distinct regimes: growing and decaying meanders.

Both spatial and temporal changes in curvature affect the regions of divergence in a meandering stream. On the one hand, horizontal divergence increases with increasing curvature magnitude, while on the other hand, the divergence pattern itself changes going from growing to decaying meanders. The growing amplitude meanders (i.e., cases where the magnitude of curvature increases in time) are found to be associated with divergence (convergence) upstream, and convergence (divergence) downstream of crests on the anticyclonic (cyclonic) side. This pattern is reversed for decaying meanders.

A parcel’s cross-stream motion is found to be consistent with the pattern established earlier: upwelling/onshore from trough to crest and downwelling/offshore from crest to trough. When referenced to the locus of the velocity maximum, which itself is curvature dependent, the mean cross-stream displacements of parcels on the cyclonic and anticyclonic sides appear to be opposite in direction relative to the current center and hence result in difluence (confluence) up- (down) stream of crests for growing amplitude meanders and vice versa for decaying ones.

Cross-frontal fluid exchange is enhanced by changes in meander amplitude. The growth and decay of a meander are found to affect both the pathways and the intensity of fluid exchange. Comparisons of satellite IR imagery with RAFOS float trajectories suggest that the detraining of water associated with Gulf Stream meandering process occurs in both growing and decaying regimes.

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Tao Song, Tom Rossby, and Everett Carter

Abstract

Between spring of 1988 and winter of 1990, 75 RAFOS floats were released east of Cape Hatteras near the center of the Gulf stream on the 26.8 σt surface, O (15°C). The purpose of this sequential deployment was to investigate the spatial and temporal characteristics of the meandering stream and the Lagrangian properties of fluid motion in the upper thermocline. These new observations were also intended to provide a database for comparative studies of fluid motion in the upper thermocline with similar observations made earlier (1984–85) in the middle and lower thermocline. Sixty-one of the 75 RAFOS float trajectories in the 13°–16°C layers have been analyzed from both a Lagrangian and Eulerian point of view. The results reconfirm the strong baroclinic structure of the Gulf Stream established earlier and reveal enhanced cross-stream motion with increasing depth and over the New England Seamounts, Float trajectories tend to be more convoluted east of the seamounts reflecting the large amplitude meandering in that region.

The lateral exchange of fluid between the current and surrounding waters has been grouped into three major, categories: ring formation, ring–stream interaction, and meandering. Of these, ring formation is responsible for less than 16% of the losses, while the other two contribute about equally. The loss of water to both sides of the stream is approximately symmmetric as evidenced by the statistics of float loss: 50% to the north and 54% to the south relative to the total numbers of floats that were launched on the same side with respect to the velocity maximum. These statistics are consistent with the results from earlier observations in the lower thermocline (1984–85).

Curvature of the flow has a slight but measurable effect on the velocity structure of the current, such that between troughs and crests the locus of maximum velocity shoals about 100 m or in terms of the tilt of the density structure displace about 10 km to the north. The maximum itself is remarkably independent of curvature, about 1.10 m s−1. A narrow band of nearly nonexistent shear is observed to be embedded within the anticyclonic side of the current. Its magnitude is more pronounced at crests than at troughs.

A comparative study of the surface and subsurface north walls reveals strong lateral diaplacements, O (15 km), of one relative to the other such that the surface front (i.e., the maximum thermal contrast in the SST field) extends farther north in meander crests and south in the troughs than the subsurface north wall defined by 15°C at 200 m. A longitudinal dependence of the north wall offset is also evident but its cause is unknown.

The influence of topography on the Gulf Stream can be seen in two ways. First; analysis of pseudo-Eulerian statistics based on the float data reveals a striking northward shift of the current as it passes over the New England Seamounts, a signature not reflected by individual floats but clearly discernible in the ensemble of float trajectories. Second, more than 60% of the float losses occur in the seamount region although this encompasses only 20% of the total distance spanned by float trajectories Changes in the ratio of MKE to EKE along the mean path of the current are consistent with varying meander envelope of a well-defined baroclinic jet.

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Tao Song, Zihe Wang, Pengfei Xie, Nisheng Han, Jingyu Jiang, and Danya Xu

Abstract

Accurate and real-time sea surface salinity (SSS) prediction is an elemental part of marine environmental monitoring. It is believed that the intrinsic correlation and patterns of historical SSS data can improve prediction accuracy, but they have been not fully considered in statistical methods. In recent years, deep-learning methods have been successfully applied for time series prediction and achieved excellent results by mining intrinsic correlation of time series data. In this work, we propose a dual path gated recurrent unit (GRU) network (DPG) to address the SSS prediction accuracy challenge. Specifically, DPG uses a convolutional neural network (CNN) to extract the overall long-term pattern of time series, and then a recurrent neural network (RNN) is used to track the local short-term pattern of time series. The CNN module is composed of a 1D CNN without pooling, and the RNN part is composed of two parallel but different GRU layers. Experiments conducted on the South China Sea SSS dataset from the Reanalysis Dataset of the South China Sea (REDOS) show the feasibility and effectiveness of DPG in predicting SSS values. It achieved accuracies of 99.29%, 98.44%, and 96.85% in predicting the coming 1, 5, and 14 days, respectively. As well, DPG achieves better performance on prediction accuracy and stability than autoregressive integrated moving averages, support vector regression, and artificial neural networks. To the best of our knowledge, this is the first time that data intrinsic correlation has been applied to predict SSS values.

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William S. Olson, Christian D. Kummerow, Song Yang, Grant W. Petty, Wei-Kuo Tao, Thomas L. Bell, Scott A. Braun, Yansen Wang, Stephen E. Lang, Daniel E. Johnson, and Christine Chiu

Abstract

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors.

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Jinyuan Xin, Yuesi Wang, Yuepeng Pan, Dongsheng Ji, Zirui Liu, Tianxue Wen, Yinghong Wang, Xingru Li, Yang Sun, Jie Sun, Pucai Wang, Gehui Wang, Xinming Wang, Zhiyuan Cong, Tao Song, Bo Hu, Lili Wang, Guiqian Tang, Wenkang Gao, Yuhong Guo, Hongyan Miao, Shili Tian, and Lu Wang

Abstract

Based on a network of field stations belonging to the Chinese Academy of Sciences (CAS), the Campaign on Atmospheric Aerosol Research network of China (CARE-China) was recently established as the country’s first monitoring network for the study of the spatiotemporal distribution of aerosol physical characteristics, chemical components, and optical properties, as well as aerosol gaseous precursors. The network comprises 36 stations in total and adopts a unified approach in terms of the instrumentation, experimental standards, and data specifications. This ongoing project is intended to provide an integrated research platform to monitor online PM2.5 concentrations, nine-size aerosol concentrations and chemical component distributions, nine-size secondary organic aerosol (SOA) component distributions, gaseous precursor concentrations (including SO2, NOx, CO, O3, and VOCs), and aerosol optical properties. The data will be used to identify the sources of regional aerosols, the relative contributions from nature and anthropogenic emissions, the formation of secondary aerosols, and the effects of aerosol component distributions on aerosol optical properties. The results will reduce the levels of uncertainty involved in the quantitative assessment of aerosol effects on regional climate and environmental changes and ultimately provide insight into how to mitigate anthropogenic aerosol emissions in China. The present paper provides a detailed description of the instrumentation, methodologies, and experimental procedures used across the network, as well as a case study of observations taken from one station and the distribution of main components of aerosol over China during 2012.

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