Fangli Qiao

Three‐dimensional structure of the summertime circulation in the Yellow Sea from a wave‐tide‐circulation coupled model

[1] The three-dimensional structure of the summertime circulation of the Yellow Sea (hereafter YS) is studied by using a prognostic wave-tide-circulation coupled model based on the Princeton Ocean Model (POM) and a surface wave model. The simulated tidal harmonic constants and temperature structure agree with the observations well. The patterns of the simulated salinity generally agree also with the observations. The simulated results show that the horizontal circulation has a three-layer structure: in the surface layer (0–4 m), the prevailing current direction is northeastward; in the upper layer (4–40 m) it is dominated by a basin scale anticlockwise (cyclonic) gyre; in the bottom layer (below 40 m) the water diverges from the center area and there exists a weak southward current along the YS trough. The stream function of the YS shows that the net circulation of the YS is an anticlockwise (cyclonic) one, and the net transport is about 0.1 Sv. Diagnostic analysis of the momentum balance and sensitivity show that the cyclonic circulation in the upper layers is mainly a quasi-geostrophic flow along tidal-induced temperature front, and it is also strengthened by the tide residual currents. The tidal residual current and the compensation for northward surface layer wind transport contribute to the formation of southward flow in the bottom layer. The vertical circulations vary along different sections. A circulation cell is found in the frontal area near the Korean coast, and an upwelling is found along the slope.

The Sunway TaihuLight supercomputer: system and applications

The Sunway TaihuLight supercomputer is the world’s first system with a peak performance greater than 100 PFlops. In this paper, we provide a detailed introduction to the TaihuLight system. In contrast with other existing heterogeneous supercomputers, which include both CPU processors and PCIe-connected many-core accelerators (NVIDIA GPU or Intel Xeon Phi), the computing power of TaihuLight is provided by a homegrown many-core SW26010 CPU that includes both the management processing elements (MPEs) and computing processing elements (CPEs) in one chip. With 260 processing elements in one CPU, a single SW26010 provides a peak performance of over three TFlops. To alleviate the memory bandwidth bottleneck in most applications, each CPE comes with a scratch pad memory, which serves as a user-controlled cache. To support the parallelization of programs on the new many-core architecture, in addition to the basic C/C++ and Fortran compilers, the system provides a customized Sunway OpenACC tool that supports the OpenACC 2.0 syntax. This paper also reports our preliminary efforts on developing and optimizing applications on the TaihuLight system, focusing on key application domains, such as earth system modeling, ocean surface wave modeling, atomistic simulation, and phase-field simulation.

ON INTRINSIC MODE FUNCTION

Empirical Mode Decomposition (EMD) has been widely used to analyze non-stationary and nonlinear signal by decomposing data into a series of intrinsic mode functions (IMFs) and a trend function through sifting processes. For lack of a firm mathematical foundation, the implementation of EMD is still empirical and ad hoc .I n this paper, we prove mathematically that EMD, as practiced now, only gives an approximation to the true envelope. As a result, there is a potential conflict between the strict definition of IMF and its empirical implementation through natural cubic spline. It is found that the amplitude of IMF is closely connected with the interpolation function defining the upper and lower envelopes: adopting the cubic spline function, the upper (lower) envelope of the resulting IMF is proved to be a unitary cubic spline line as long as the extrema are sparsely distributed compared with the sampling data. Furthermore, when natural spline boundary condition is adopted, the unitary cubic spline line degenerates into a straight line. Unless the amplitude of the IMF is a strictly monotonic function, the slope of the straight line will be zero. It explains why the amplitude of IMF tends to be a constant with the number of sifting increasing ad infinitum. Therefore, to get physically meaningful IMFs the sifting times for each IMF should be kept low as in the practice of EMD. Strictly speaking, the resolution of these difficulties should be either to change the EMD implementation method and eschew the spline, or to define the stoppage criterion more objectively and leniently. Short of the full resolution of the conflict, we should realize that the EMD as implemented now yields an approximation with respect to cubic

NOTES AND CORRESPONDENCE An Experiment on the Nonbreaking Surface-Wave-Induced Vertical Mixing

Abstract Mixing induced by nonbreaking surface waves was investigated in a wave tank by measuring the thermal destratification rate of the water column. One experiment without waves and four experiments with waves of amplitudes ranging from 1.0 to 1.5 cm and wavelength from 30 to 75 cm were conducted. Water temperature variations at depths from 4 to 12 cm below the surface were measured. In the layer from 4 to 7 cm, the originally dense isothermal lines disperse soon after the waves are generated, whereas the vertical gradient from 9 to 12 cm is maintained for a relatively long time. The time span, during which the water temperature becomes well mixed, changes from about 20 h for the case with no waves to tens of minutes for the case with waves, and it decreases with increasing wave amplitude and wavelength. A one-dimensional diffusion numerical model with wave-induced mixing parameterization shows consistent results with the measurement. The study demonstrates that the mixing induced by nonbreaking waves...

Upwelling off the west coast of Hainan Island in summer: Its detection and mechanisms

The summertime upwelling off the west coast of Hainan Island is newly detected by satellite remote sensing sea surface temperature, and confirmed by both historical field observations and numerical modeling. Furthermore, numerical experiments are conducted to gain understanding of the upwelling mechanisms. A tidal mixing front (TMF) is identified as the vital factor triggering the formation of the upwelling. The baroclinic pressure gradient force, which stems from the intense density difference across the TMF, causes a frontal-scale circulation at the TMF. As a result, upwelling appears as a branch of this circulation. The southwest monsoon induces downwelling, which competes with the front-induced upwelling. Climatologically, the upwelling dominates and can reach about 5 m below the sea surface above the slope bottom. In calm weather with no or weak winds, it is expected that the upwelling can reach all the way to the sea surface.

Coastal-Trapped Waves in the East China Sea Observed by a Mooring Array in Winter 2006

AbstractUsing five mooring array observations in the coastal water of the East China Sea (ECS) in winter 2006, the authors identify three kinds of low-frequency waves using the ensemble empirical mode decomposition (EEMD) method. The analysis indicates that the periods of the waves varied from 2 to 10 days, which are consistent with coastal-trapped wave (CTW) modes: the Kelvin wave (KW) mode, the first shelf wave (SW1) mode, and the second shelf wave (SW2) mode. An analytical model is established and the dispersion relation of the waves from the analytical method agrees well with the observations. The wind-forced, coastal-trapped wave theory is then applied. The calculation shows that over a wide shelf, the forcing term of wind stress curl plays an important role in shaping the CTW. Numerical solutions reproduce the sea level variation and the alongshore current. The results show that the sea level variation mainly resulted from the KW mode, but the alongshore current resulted from both the KW and SW1 modes.

Evaluating CMIP5 simulations of mixed layer depth during summer

The ability of CMIP5 models in simulating surface mixed layer depth (MLD) during summer is assessed using 45 climate models. Their ocean models differ greatly in terms of vertical mixing parameterizations and model configurations. In some models, effects of surface waves, Langmuir circulations, submesoscale eddies, as well as additional wind mixing are included to improve upper-ocean simulation. Similar to findings by previous studies, the summer MLDs are significantly underestimated in most of the models. Compared with the observation, only five of these models have deeper summer MLDs in the Southern Ocean, eight models have deeper summer MLDs in the central North Atlantic Ocean, and nine models have deeper summer MLDs in the central North Pacific Ocean. This underestimation of MLD is not caused by sea surface forcing, because most of the models tend to overestimate the surface wind stress, while they underestimate the net surface heat flux. Therefore, insufficient vertical mixing in the upper ocean may still be one of the potential reasons for this systematic underestimation of MLD in the climate models.

Wave-turbulence interaction-induced vertical mixing and its effects in ocean and climate models.

Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability.

The role of surface waves in the ocean mixed layer

Previously,most ocean circulation models have overlooked the role of the surface waves.As a result,these models have produced insufficient vertical mixing,with an under-prediction of the mixing layer(ML)depth and an over-prediction of the sea surface temperature(SST),particularly during the summer season.As the ocean surface layer determines the lower boundary conditions of the atmosphere,this deficiency has severely limited the performance of the coupled ocean-atmospheric models and hence the climate studies.To overcome this shortcoming,a new parameterization for the wave effects in the ML model that will correct this systematic error of insufficient mixing.The new scheme has enabled the mixing layer to deepen,the surface excessive heating to be corrected,and an excellent agreement with observed global climatologic data.The study indicates that the surface waves are essential for ML formation,and that they are the primer drivers of the upper ocean dynamics;therefore,they are critical for climate studies.

Intercomparison between observed and simulated variability in global ocean heat content using empirical mode decomposition, part I: modulated annual cycle

This study proposes a new more precise and detailed method to examine the performance of IPCC AR4 models in simulation of nonlinear variability of global ocean heat content (OHC) on the annual time scale during 1950–1999. The method is based on the intercomparison of modulated annual cycle (MAC) of OHC and its instantaneous frequency (IF), derived by Empirical Mode Decomposition and Hilbert-Huang Transformation. In addition to indicate the general agreement in gross features globally between models and observation, our results point out the problems both in observation and in modeling. In the well observed Northern Hemisphere, models exhibit extremely good skills to capture nonlinear annual variability of OHC. The simulated MACs are highly correlated with observations (>0.95) and the IF of MACs varies coherently with each other. However, in sparsely observed Southern Hemisphere (SH), even though the simulated MACs highly correlate with observations, the IF shows significant difference. This comparisons show that the models exhibit coherent variability of IF of MACs in SH with each other, but not with observations, revealing the problems in the objective analyzed dataset using sparse observations. In the well observed tropic region, the models lack the coherence with the observations, indicating inadequate physics of the models in the tropical area. These results illustrate that the proposed method can be used routinely to identify problems in both models and in observation of the global ocean as a critical component of global climate change.