How Do Deep Learning Forecasting Models Perform for Surface Variables in the South China Sea Compared to Operational Oceanography Forecasting Systems?

It is fundamental and useful to investigate how deep learning forecasting models(DLMs)perform compared to operational oceanography forecast systems(OFSs).However,few studies have intercompared their performances using an identical reference.In this study,three physically reasonable DLMs are implemented for the forecasting of the sea surface temperature(SST),sea level anomaly(SLA),and sea surface velocity in the South China Sea.The DLMs are validated against both the testing dataset and the“OceanPredict”Class 4 dataset.Results show that the DLMs'RMSEs against the latter increase by 44%,245%,302%,and 109%for SST,SLA,current speed,and direction,respectively,compared to those against the former.Therefore,different references have significant influences on the validation,and it is necessary to use an identical and independent reference to intercompare the DLMs and OFSs.Against the Class 4 dataset,the DLMs present significantly better performance for SLA than the OFSs,and slightly better performances for other variables.The error patterns of the DLMs and OFSs show a high degree of similarity,which is reasonable from the viewpoint of predictability,facilitating further applications of the DLMs.For extreme events,the DLMs and OFSs both present large but similar forecast errors for SLA and current speed,while the DLMs are likely to give larger errors for SST and current direction.This study provides an evaluation of the forecast skills of commonly used DLMs and provides an example to objectively intercompare different DLMs.

The Water-Bearing Numerical Model and Its Operational Forecasting Experiments PartII: The Operational Forecasting Experiments

おhe water-bearing numerical model is undergone all round examinations during the operational forecasting experiments from 1994 to 1996. A lot of difficult problems arising from the model′s water-bearing are successfully resolved in these experiments through developing and using a series of technical measures. The operational forecasting running of the water-bearing numerical model is realized stably and reliably, and satisfactory forecasts are obtained.

Validation of an operational forecasting system of sea dike risk in the southern Zhejiang Province, South China

In this study,an operational forecasting system of sea dike risk in the southern Zhejiang Province,South China was developed based on a coupled storm-surge and wave model.This forecasting system is important because of the high cost of storm-surge damage and the need for rapid emergency planning.A comparison with astronomical tides in 2016 and the validation of storm surges and high water marks of 20 typhoons verified that the forecast system has a good simulation ability.The system can forecast relatively realistic water levels and wave heights as shown under the parametric atmospheric forces simulated in a case study;the sea dikes in credible high risk were mainly located in the estuaries,rivers,and around the islands in the southern Zhejiang.Therefore,the forecast system is applicable in the southern Zhejiang with a support to the effective prevention from typhoon storm-surge damage.

OPERATIONAL ENSEMBLE FORECASTING AND ANALYSIS OF TROPICAL CYCLONES OVER THE WESTERN NORTH PACIFIC(INCLUDING THE SOUTH CHINA SEA)

Based on the tropical cyclone data from the Central Meteorological Observatory of China, Japan Meteorological Agency, Joint Typhoon Warning Center and European Centre for Medium-Range Weather Forecasts （ECMWF） during the period of 2004 to 2009, three consensus methods are used in tropical cyclone （TC） track forecasts. Operational consensus results show that the objective forecasts of ECMWF help to improve consensus skill by 2%, 3%-5% and 3%-5%, decrease track bias by 2.5 kin, 6-9 km and 10-12 km for the 24 h, 48 h and 72 h forecasts respectively over the years of 2007 to 2009. Analysis also indicates that consensus forecasts hold positive skills relative to each member. The multivariate regression composite is a method that shows relatively low skill, while the methods of arithmetic averaging and composite （in which the weighting coefficient is the reciprocal square of mean error of members） have almost comparable skills among members. Consensus forecast for a lead time of 96 h has negative skill relative to the ECMWF objective forecast.

Verification of an operational ocean circulation-surface wave coupled forecasting system for the China＇s seas

An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China＇s seas has been updated to（1/24）° from the global model with（1/2）°resolution. Besides, daily remote sensing sea surface temperature（SST） data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth（MLD） and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores（SS） is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value（more than 0.90）. Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.

Recent improvements to the physical model of the Bohai Sea,the Yellow Sea and the East China Sea Operational Oceanography Forecasting System

In order to satisfy the increasing demand for the marine forecasting capacity,the Bohai Sea,the Yellow Sea and the East China Sea Operational Oceanography Forecasting System(BYEOFS)has been upgraded and improved to Version 2.0.Based on the Regional Ocean Modeling System(ROMS),a series of comparative experiments were conducted during the improvement process,including correcting topography,changing sea surface atmospheric forcing mode,adjusting open boundary conditions,and considering atmospheric pressure correction.(1)After the topography correction,the volume transport and meridional velocity maximum of Yellow Sea Warm Current increase obviously and the unreasonable bending of its axis around 36.1°N,123.5°E disappears.(2)After the change of sea surface forcing mode,an effective negative feedback mechanism is formed between predicted sea surface temperature(SST)by the ocean model and sea surface radiation fluxes fields.The simulation errors of SST decreased significantly,and the annual average of root-mean-square error(RMSE)decreased by about 18%.(3)The change of the eastern lateral boundary condition of baroclinic velocity from mixed Radiation-Nudging to Clamped makes the unreasonable westward current in Tsushima Strait disappear.(4)The adding of mean sea level pressure correction option which forms the mean sea level gradient from the Bohai Sea and the Yellow Sea to the western Pacific in winter and autumn is helpful to increasing the fluctuation of SLA and outflow of the Yellow Sea when the cold high air pressure system controls the Yellow Sea area.

Tide forecasting method based on dynamic weight distribution for operational evaluation

Through analysis of operational evaluation factors for tide forecasting, the relationship between the evaluation factors and the weights of forecasters was examined. A tide forecasting method based on dynamic weight distribution for operational evaluation was developed, and multiple-forecaster synchronous forecasting was realized while avoiding the instability cased by only one forecaster. Weights were distributed to the forecasters according to each one＇s forecast precision. An evaluation criterion for the professional level of the forecasters was also built. The eligibility rates of forecast results demonstrate the skill of the forecasters and the stability of their forecasts. With the developed tide forecasting method, the precision and reasonableness of tide forecasting are improved. The application of the present method to tide forecasting at the Huangpu Park tidal station demonstrates the validity of the method.

A Review on the Research Progress in Operational Earthquake Forecasting(OEF)in the World

In this paper,the research progress of the Operational Earthquake Forecasting( OEF) is introduced from the major areas of concern,the concept of probability gain,hybrid model development,and the application to earthquake disaster reduction. Due to the development of OEF based on the global "Collaboratory for the Study of Earthquake Predictability( CSEP) " plan,it provides a significant technical foundation for earthquake forecast modeling and a practical foundation for solving the actual problems in earthquake preparedness and disaster mitigation. Therefore, related research and technical ideas provide inspirational and referential significance for earthquake forecasting/prediction.

The Operational Forecasting of Total Precipitation in Flood Seasons (April to September) of 5 Years (1983-1987)

Ⅰ.INTRODUCTION We have discovered that there exists a good corresponding relationship between theanomalous axes of soil temperature at a depth of 1.6m in winter (December to February) andprecipitations in following flood season (Tang et al., 1982a). We have also designed a simplethermodynamical model and applied it to the forecasting of precipitations in the flood season(Tang et al., 1982 b,c). The practical forecast started from 1975. Before 1980, however, therewere only 40-50 stations in China for measuring the soil temperature at a 1.6m depth. Since1980, the stations have been increased to a total of about 180, but no available mean valueshad been obtained from newly added stations before 1982. Therefore the analysis and map-ping of anomalies of soil temperature was not performed until 1983, and from then on theprecision of analysis has been greatly improved. The following is the actual situation of forecast in five years from 1983 to 1987.

Development of a skill assessment tool for the Korea operational oceanographic system

A standard skill assessment （SA） tool was developed and implemented to evaluate the performance of op- erational forecast models in the Korea operational oceanographic system. The SA tool provided a robust way to assess model skill in the system by comparing predictions and observations, and involved the com- putation of multiple skill metrics including correlation and error skills. User- and system-based acceptance criteria of skill metrics were applied to determine whether predictions were acceptable for the system. To achieve this, the tool produced a time series comparison plot, a skill score table, and an advanced sum- marized diagram to effectively demonstrate the multiple skill scores. Moreover, the SA was conducted to evaluate both atmospheric and hydrodynamic forecast variables. For the atmospheric variables, acceptable error criteria were preferable to acceptable correlation criteria over short timescales, since the mean square error overwhelmed the observation variance. Conversely, for the hydrodynamic variables, acceptable root mean square percentage error （e.g., perms） criteria were preferable to acceptable error （e.g., erms） criteria owing to the spatially variable tidal intensity around the Korean Peninsula. Furthermore, the SA indicated that predetermined acceptance error criteria were appropriate to satisfy a target central frequency （fc） for which errors fell within the specified limits （i.e., the .fc equals 70%）.

Progress in Climate Prediction and Weather Forecast Operations in China

The current status of weather forecasting and climate prediction, and the main progress China has made in recent years, are summarized in this paper. The characteristics and requirements of modern weather forecast operations are described briefly, and the significance of Numerical Weather Prediction （NWP） for future development is emphasized. Tile objectives and critical tasks for seamless short-term climate predic- tion that covers the extended-range （15 30 days）, monthly, seasonal, annual, interannual and interdecadal timescales, are proposed.

Optimal Operation Strategies for a Large Multi-Chiller System Based on Cooling Load Forecast

In semiconductor and electronics factories, large multi-chiller systems are needed to satisfy strict cooling load requirements. In order to save energy, it is worthwhile to design the chilled water system operation. In this paper, an optimal flexible operation scheme is developed based on a two-dimensional time-series model to forecast the cooling load of multi-chiller systems with chiller units of different cooling capacities running in parallel. The optimal integrity scheme can be obtained using the Mixed Integer Nonlinear Programming method, which minimizes the energy consumption of the system within a future time period. In order to better adapt the change of cooling load, the operation strategy of regulating the chilled water flowrates is employed. The chilled water flowrates are set as a design variable. When the chillers are running, their chilled water flowrates can vary within limits, whereas the flowrates are zero when the chillers are unloaded. This forecasting method provides integral optimization within a future time period and offers the operating reference for operators. The power and advantages of the proposed method are presented using an industrial case to help readers delve into this matter.

Development and assessment of artificial neural network models for direct normal solar irradiance forecasting using operational numerical weather prediction data

Accurate operational solar irradiance forecasts are crucial for better decision making by solar energy system operators due to the variability of resource and energy demand.Although numerical weather prediction(NWP)models can forecast solar radiation variables,they often have significant errors,particularly in the direct normal irradiance(DNI),which is especially affected by the type and concentration of aerosols and clouds.This paper presents a method based on artificial neural networks(ANN)for generating operational DNI forecasts using weather and aerosol forecasts from the European Center for Medium-range Weather Forecasts(ECMWF)and the Copernicus Atmospheric Monitoring Service(CAMS),respectively.Two ANN models were designed:one uses as input the predicted weather and aerosol variables for a given instant,while the other uses a period of the improved DNI forecasts before the forecasted instant.The models were developed using observations for the location of´Evora,Portugal,resulting in 10 min DNI forecasts that for day 1 of forecast horizon showed an improvement over the downscaled original forecasts regarding R2,MAE and RMSE of 0.0646,21.1 W/m^(2)and 27.9 W/m^(2),respectively.The model was also evaluated for different timesteps and locations in southern Portugal,providing good agreement with experimental data.

A Regional Ensemble Forecast System for Stratiform Precipitation Events in the Northern China Region.Part Ⅱ:Seasonal Evaluation for Summer 2010

In this study, the Institute of Atmospheric Physics, Chinese Academy of Sciences - regional ensemble forecast system （IAP-REFS） described in Part I was further validated through a 65-day experiment using the summer season of 2010. The verification results show that IAP-REFS is skillful for quantitative precipitation forecasts （QPF） and probabilistic QPF, but it has a systematic bias in forecasting near-surface variables. Applying a 7-day running mean bias correction to the forecasts of near-surface variables remarkably improved the reliability of the forecasts. In this study, the perturbation extraction and inflation method （proposed with the single case study in Part I） was further applied to the full season with different inflation factors. This method increased the ensemble spread and improved the accuracy of forecasts of precipitation and near-surface variables. The seasonal mean profiles of the IAP-REFS ensemble indicate good spread among ensemble members and some model biases at certain vertical levels.

A Regional Ensemble Forecast System for Stratiform Precipitation Events in Northern China.Part I:A Case Study

A single-model, short-range, ensemble forecasting system （Institute of Atmospheric Physics, Regional Ensemble Forecast System, IAP REFS） with 15-km grid spacing, configured with multiple initial conditions, multiple lateral boundary conditions, and multiple physics parameterizations with 11 ensemble members, was developed using the Weather and Research Forecasting Model Advanced Research modeling system for prediction of stratiform precipitation events in northern China. This is the first part of a broader research project to develop a novel cloud-seeding operational system in a probabilistic framework. The ensemble perturbations were extracted from selected members of the National Center for Environmental Prediction Global Ensemble Forecasting System （NCEP GEFS） forecasts, and an inflation factor of two was applied to compensate for the lack of spread in the GEFS forecasts over the research region. Experiments on an actual stratiform precipitation case that occurred on 5-7 June 2009 in northern China were conducted to validate the ensemble system. The IAP REFS system had reasonably good performance in predicting the observed stratiform precipitation system. The perturbation inflation enlarged the ensemble spread and alleviated the underdispersion caused by parent forecasts. Centering the extracted perturbations on higher-resolution NCEP Global Forecast System forecasts resulted in less ensemble mean root-mean-square error and better accuracy in probabilistic quantitative precipitation forecasts （PQPF）. However, the perturbation inflation and recentering had less effect on near-surface-level variables compared to the mid-level variables, and its influence on PQPF resolution was limited as well.

Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts

Atmospheric chemistry models usually perform badly in forecasting wintertime air pollution because of their uncertainties. Generally, such uncertainties can be decreased effectively by techniques such as data assimilation（DA） and model output statistics（MOS）. However, the relative importance and combined effects of the two techniques have not been clarified. Here,a one-month air quality forecast with the Weather Research and Forecasting-Chemistry（WRF-Chem） model was carried out in a virtually operational setup focusing on Hebei Province, China. Meanwhile, three-dimensional variational（3 DVar） DA and MOS based on one-dimensional Kalman filtering were implemented separately and simultaneously to investigate their performance in improving the model forecast. Comparison with observations shows that the chemistry forecast with MOS outperforms that with 3 DVar DA, which could be seen in all the species tested over the whole 72 forecast hours. Combined use of both techniques does not guarantee a better forecast than MOS only, with the improvements and degradations being small and appearing rather randomly. Results indicate that the implementation of MOS is more suitable than 3 DVar DA in improving the operational forecasting ability of WRF-Chem.

Strong Earthquakes in the Yunnan-Sichuan Region: Evaluation of a Forward Long-to-intermediate-term PI Forecast

Since the initial international cooperation in the framework of Collaboratory for the Study of Earthquake Predictability(CSEP)in 2007,a lot of forecast models have been developed and served for the earthquake forecasting experiment in different CSEP testing centers(Schorlemmer et al.,2018).

Operations Management Perspectives in the Air Transport Management

The area of operations management has had a substantial effect on the today’s air transportation management.Having moved with huge demand from management to obtain a competitive advantage in the market,the airlines are utilizing advanced optimization techniques to develop decision support systems for operations management and control.In order to provide a service with high quality and low cost,airlines spend a tremendous amount of resources and effort to generate profitable and cost-effective fare classes,flight schedules,fleet plans,aircraft routes,crew scheduling,gate assignment,etc.In this paper,the techniques and operations management applications that are used in the air transportation industry are reviewed including demand forecasting,fleet assignment,aircraft routing,crew scheduling,runway scheduling problem and gate assignment.

Evaluation of the Forecast Performance for North Atlantic Oscillation Onset

By utilizing operational forecast products from TIGGE(The International Grand Global Ensemble) during 2006 to 2015,the forecasting performances of the European Centre for Medium-Range Weather Forecasts(ECMWF), National Centers for Environmental Prediction(NCEP), Japan Meteorology Agency(JMA) and China Meteorological Administration(CMA) for the onset of North Atlantic Oscillation(NAO) events are assessed against daily NCEP–NCAR reanalysis data. Twenty-two positive NAO(NAO+) and nine negative NAO(NAO-) events are identified during this time period. For these NAO events,control forecasts, one member of the ensemble that utilizes the currently most proper estimate of the analysis field and the best description of the model physics, are able to predict their onsets three to five days in advance. Moreover, the failure proportion for the prediction of NAO-onset is higher than that for NAO+ onset, which indicates that NAO-onset is harder to forecast. Among these four operational centers, ECMWF has performs best in predicting NAO onset, followed by NCEP,JMA, and then CMA.The forecasting performance of the ensemble mean is also investigated. It is found that, compared with the control forecast, the ensemble mean does not improve the forecasting skill with respect to the onset time of NAO events. Therefore,a confident forecast of NAO onset can only be achieved three to five days in advance.

Study on short-range numerical forecasting of ocean current in the East China Sea——Ⅰ Basic problems of ocean current forecasting and structure of the models

Ocean current forecasting is still in explorative stage of study. In the study, we face some problems that have not been met before. The solving of these problems has become fundamental premise for realizing the ocean current forecasting. In the present paper are discussed in depth the physical essence for such basic problems as the predictability of ocean current, the predictable currents, the dynamical basis for studying respectively the tidal current and circulation, the necessity of boundary model, the models on regions with different scales and their link. The foundations and plans to solve the problems are demonstrated. Finally a set of operational numerical forecasting system for ocean current is proposed.