Monsoonal quasi-stationary ultralong waves of the tropical troposphere predicted by a real data prediction over a global tropical belt

The mechanisms of the maintenance of the tropical upper tropospheric quasi-stationary ultralong waves during the northern hemisphere summer season are briefly reviewed and discussed. Diagnostic and prognostic studies indicate that the waves are maintained by the land-ocean contrast heating. These scales of motion as a whole (sum of the zonal wavenumbers 1, 2 and 3) are considered to supply kinetic energy to all other scales of motion.The ultralong waves predicted in the real data numerical prediction experiment over the global tropics using a multi-level primitive equation model are examined and compared with the observed climatological waves. The predicted waves are found to have several similarities with the observations. Further investigations of the baroclinic nature of the waves indicate that their thermal structure is essential for understanding their dynamics.The vorticity budget computations are performed for the predicted ultralong waves at 200 mb and also compared with the climatological observations. It is found that the advection term is one of the leading terms in the vorticity equation.This study indicates that the tropical quasi-stationary ultralong waves are fully nonlinear, non-geostrophic, three-dimensional waves forced mainly by the convective heating over the monsoon Indian subcontient.     

TWP-ICE试验期间一次热带深对流过程的拉格朗日输送特征

本文使用高分辨率WRFV3.4.1模式对TWP-ICE试验期间的一次热带深对流过程进行了数值模拟,利用第四重嵌套每五分钟输出一次的模拟资料对对流系统的上升气流质量通量廓线特征进行了分析,并结合FLEXPART拉格朗日粒子扩散模式对热带深对流系统进行拉格朗日轨迹分析.质量通量廓线特征及拉格朗日轨迹的分析结果表明,在条件不稳定层顶附近便有部分水凝物被输送出深对流系统.深对流系统中的水凝物主要沿环境引导气流向深对流下游方向输送.由于受低层风场扰动的影响,少量的水凝物被输送到深对流系统的上游.深对流系统中的水凝物向其下游方向输送的最远距离为200~300 km,并约有10%~20%的水凝物对对流系统下游50~150 km附近卷云砧的形成产生影响,其影响的时间尺度约为4~6 h.     

A numerical study of the string function using a primitive equation ocean model

Abstract

We use results from a primitive-equation ocean numerical model (SCRUM) to test a theoretical 'string function' formulation put forward by Tyler and Käse in another article in this issue. The string function acts as a stream function for the large-scale potential energy flow under the combined beta and topographic effects. The model results verify that large-scale anomalies propagate along the string function contours with a speed correctly given by the cross-string gradient. For anomalies having a scale similar to the Rossby radius, material rates of change in the layer mass following the string velocity are balanced by material rates of change in relative vorticity following the flow velocity. It is shown that large-amplitude anomalies can be generated when wind stress is resonant with the string function configuration.     

Optimization of the Sefid-Roud Dam desiltation process using a sophisticated one-dimensional numerical model

Although water and soil conservation activities reduce reservoir sedimentation, it is inevitable that reservoirs fed by rivers transporting high amounts of sediment will experience sedimentation. The Ghezel-Ozan and Shah-Roud rivers, which flow to the Sefld-Roud reservoir dam, are both highly sediment-laden and transport significant amounts of sediment in both bed load and suspended load forms to the reservoir. Hence, it seems that the only practical way to remove the sediment from the reservoir is to flush it out using the Chasse method. In the present paper, field measurements of Chasse operation characteristics taken in previous years are presented, and a numerical model that simulates this process is introduced. After calibrating the model using field measured data, the calculated results （for reservoir pressure flushing and released sediment volume） of the numerical model were compared with other measured data for the same Chasse operation and the results agree well. Finally, using the numerical simulation results, the best approaches to ensure highly effective flushing while conserving reservoir water are presented （at least for the Sefid-Roud dam）. The operation of the bottom outlet gates, the shape of the output hydrograph, and the reservoir water level variation during flushing were optimized. In addition, the numerical model and related parameters, which need to be calibrated, are discussed.     

Lithology and fluid prediction from prestack seismic data using a Bayesian model with Markov process prior

We invert prestack seismic amplitude data to find rock properties of a vertical profile of the earth. In particular we focus on lithology, porosity and fluid. Our model includes vertical dependencies of the rock properties. This allows us to compute quantities valid for the full profile such as the probability that the vertical profile contains hydrocarbons and volume distributions of hydrocarbons. In a standard point wise approach, these quantities can not be assessed. We formulate the problem in a Bayesian framework, and model the vertical dependency using spatial statistics. The relation between rock properties and elastic parameters is established through a stochastic rock model, and a convolutional model links the reflectivity to the seismic. A Markov chain Monte Carlo (MCMC) algorithm is used to generate multiple realizations that honours both the seismic data and the prior beliefs and respects the additional constraints imposed by the vertical dependencies. Convergence plots are used to provide quality check of the algorithm and to compare it with a similar method. The implementation has been tested on three different data sets offshore Norway, among these one profile has well control. For all test cases the MCMC algorithm provides reliable estimates with uncertainty quantification within three hours. The inversion result is consistent with the observed well data. In the case example we show that the seismic amplitudes make a significant impact on the inversion result even if the data have a moderate well tie, and that this is due to the vertical dependency imposed on the lithology fluid classes in our model. The vertical correlation in elastic parameters mainly influences the upside potential of the volume distribution. The approach is best suited to evaluate a few selected vertical profiles since the MCMC algorithm is computer demanding.