A NEW MODEL FOR CALCULATING PROPAGATION PRESSURE AND INITIATION PRESSURE OF PIPELINES WITH A LOCAL DENT

An analytical model of a ring with six yield hinges and two deformable arc segments is presented for. the prediction of the buckle propagation pressure and initiation pressure in offshore pipelines. The configuration of a fully collapsed ring is considered as a real dumbbell shape with a line touch between two 'bells', instead of the dumbbell shape with a point touch of two diametrically opposite points. Calculations are performed assuming that the dominant effect on the plastic energy dissipation has the circumferential bending mode. For the linear strain-hardening materials it is found that theoretical predictions based on the above model for both propagation pressure and initiation nressure are in good agreement with experimental results of Kyriakides et al.

CAS FGOALS-f3-L Model Datasets for CMIP6 DCPP Experiment

The outputs of the Chinese Academy of Sciences(CAS)Flexible Global Ocean-Atmosphere-Land System(FGOALSf3-L)model for the decadal climate prediction project(DCPP)of the Coupled Model Intercomparison Project Phase 6(CMIP6)are described in this paper.The FGOALS-f3-L was initialized through the upgraded,weakly coupled data assimilation scheme,referred to as EnOI-IAU,which assimilates observational anomalies of sea surface temperature(SST)and upper-level(0–1000-m)ocean temperature and salinity profiles into the coupled model.Then,nine ensemble members of 10-year hindcast/forecast experiments were conducted for each initial year over the period of 1960–2021,based on initial conditions produced by three initialization experiments.The hindcast and forecast experiments follow the experiment designs of the Component-A and Component-B of the DCPP,respectively.The decadal prediction output datasets contain a total of 44 monthly mean atmospheric and oceanic variables.The preliminary evaluation indicates that the hindcast experiments show significant predictive skill for the interannual variations of SST in the north Pacific and multi-year variations of SST in the subtropical Pacific and the southern Indian Ocean.

A STUDY ON THE PREDICT ABILITY OF GRAPES MODEL OVER SOUTH CHINA: COMPARISONS BY TWO INITIALIZATION CONDITIONS BETWEEN ECMWF AND NCEP

This paper aims to assess the performances of different model initialization conditions(ICs)and lateral boundary conditions between two global models(GMs),i.e.,the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP),on the accuracy of the Global/Regional Assimilation and Prediction System(GRAPES)forecasts for south China.A total of 3-month simulations during the rainy season were examined and a specific case of torrential rain over Guangdong Province was verified.Both ICs exhibited cold biases over south China,as well as a strong dry bias over the Pearl River Delta(PRD).In particular,the ICs from the ECMWF had a stronger cold bias over the PRD region and a more detailed structure than NCEP.In general,the NCEP provided a realistic surface temperature compared to the ECMWF over south China.Moreover,GRAPES initialized by the NCEP had better simulations of both location and intensity of precipitation than by the ECWMF.The results presented in this paper could be used as a general guideline to the operational numerical weather prediction that uses regional models driven by the GMs.

Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO

Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.

Prototype Validation Model of FY-4 Initiated

Major progress has been achieved in the development of the prototype of FY-4 meteorological satellite.After two years development,the FY-4 development team with SAST as the leader finished the electrical model of the satellite and passed the preliminary design review.The development of the prototype validation satellite has been initiated.FY-4 will be China's first geostationary Earth observation remote

Case studies of ERS-1 altimeter data applicating in China Sea

The impact of ERS-1 altimeter significant wave height on analysis of wave field and wave pre- dictions is tested through analysis of selected cases. Application of the altimeter data may modifg initial tield and thus 24-hour prediction of significant wave height. However the variations in initial wave field almost make no effect on 48-hour predictions.

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM(1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guantlng reservoir inlet and outlet （China）. The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What＇s more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.

Another Definition of Order-Sorted Algebra

In this paper the definition of order-sorted algebra is generalized by introducing transforma-tion functions between subtypes and supertypes. According to our definition, a type needn'tbe a subset of its supertype and a record model may form an order-sorted algebra. A newdefinition of equation is given. It has also been proved that equational theories and describingsingle inheritance have the initial model.