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.

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.

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.

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.

Myths about Earthquakes:Quo vadis?

We are living in a world of numbers and calculations with enormous amount of pretty fast user-friendly software ready for an automatic output that may lead to a discovery or,alternatively,mislead to a deceptive conclusion,erroneous claims and predictions.As a matter of fact,nowadays,Science can disclose Natural Hazards,assess Risks,and deliver the state-of-the-art Knowledge of looming disaster in advance catastrophes along with useful Recommendations on the level of risks for decision making regarding engineering design,insurance,and emergency management.

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%）.

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.

Eureka Webair： Web-Based Air Quality Management, Real-Time Forecasting and Emission Control Optimization

For the assessment and management of regional to local air quality, an integrated environmental management information system was built within the multi national Eureka project 3266 Webair, http：//www.ess.co.at/WEBAIR. The system combines data bases and GIS and a range of coupled models and analytical tools that address a range of typical management problems and cover several levels of nesting from regional to city level and street canyons. The main functions are to support regulatory tasks, compliance monitoring, operational forecasting and reporting, impact assessment EIA （environmental impact assessment）, SEA （strategic environmental assessment） and public information within one consistent framework. A major objective is the improvement of air quality through emission control. The integrated model system together with its shared data bases provides a reliable, consistent basis for the non-linear techno-economic and multi-criteria optimization of emission control strategies （including greenhouse gases and energy efficiency）. A real-time expert system drives, supports and monitors the autonomous and interactive operations, and provides embedded QA/QC （quality assurance/quality control） functions for reliable operations and ease of use.

Recent progress in research and forecasting of tropical cyclone outer size

This review article summarizes the current understanding and recent updates to tropical cyclone outer size and structure forecasting and research primarily since 2018 as part of the World Meteorological Organization's 10th International Workshop on Tropical Cyclones.A more complete understanding of tropical cyclone outer wind and precipitation is key to anticipating storm intensification and the scale and magnitude of landfalling hazards.We first discuss the relevance of tropical cyclone outer size and structure,improvements in our understanding of its life cycle and inter-basin variability,and the processes that impact outer size changes.We next focus on current forecasting practices and differences among warning centers,recent advances in operational forecasting,and new observations of the storm outer wind field.We also summarize recent research on projected tropical cyclone outer size and structure changes by the late 21st century.Finally,we discuss recommendations for the future of tropical cyclone outer size forecasting and research.

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.

A review of recent advances(2018–2021)on tropical cyclone intensity change from operational perspectives,part 1:Dynamical model guidance

This review summarizes the rapporteur report on tropical cyclone(TC)intensity change from the operational perspective,as presented to the 10th International Workshop on TCs(IWTC-10)held in Bali,Indonesia,from Dec.5–9,2022.The accuracy of TC intensity forecasts issued by operational forecast centers depends on three aspects:real-time observations,TC dynamical model forecast guidance,and techniques and methods used by forecasters.The rapporteur report covers the progress made over the past four years(2018–2021)in all three aspects.This review focuses on the progress of dynamical model forecast guidance.The companion paper(Part II)summarizes the advance from operational centers.The dynamical model forecast guidance continues to be the main factor leading to the improvement of operational TC intensity forecasts.Here,we describe recent advances and developments of major operational regional dynamical TC models and their intensity forecast performance,including HWRF,HMON,COAMPS-TC,Met Office Regional Model,CMA-TYM,and newly developed HAFS.The performance of global dynamical models,including NOAA's GFS,Met Office Global Model(MOGM),JMA's GSM,and IFS(ECMWF),has also been improved in recent years due to their increased horizontal and vertical resolution as well as improved data assimilation systems.Recent challenging cases of rapid intensification are presented and discussed.

A review of recent advances(2018–2021)on tropical cyclone intensity change from operational perspectives,part 2:Forecasts by operational centers

This paper summarizes the progress and activities of tropical cyclone(TC)operational forecast centers during the last four years(2018–2021).It is part II of the review on TC intensity change from the operational perspective in the rapporteur report presented to the 10th International Workshop on TCs(IWTC)held in Bali,Indonesia,from Dec.5–9,2022.Part I of the review has focused on the progress of dynamical model forecast guidance.This part discusses the performance of TC intensity and rapid intensification forecasts from several operational centers.It is shown that the TC intensity forecast errors have continued to decrease since the 9th IWTC held in 2018.In particular,the improvement of rapid intensification forecasts has accelerated,compared with years before 2018.Consensus models,operational procedures,tools and techniques,as well as recent challenging cases from 2018 to 2021 identified by operational forecast centers are described.Research needs and recommendations are also discussed.©2023 The Shanghai Typhoon Institute of China Meteorological Administration.Publishing services by Elsevier B.V.on behalf of KeAi Communication Co.Ltd.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

SYSTEMATIC FORECAST ERROR IN U.S.NMC OPERATIONAL SPECTRAL MODEL

The distribution of monthly mean error of NMC model forecasts and its seasonal variation are investi- gated.The ratio of monthly mean error to standard deviation is used here to find out that the region where a correction of systematic error is needed and appropriate is mainly in low latitudes.The improvement,after the model's vertical resolution and some physical parameters were changed from April 1985,is investigated,and the NMC operational model forecasts have also compared with those of ECMWF.

Risk analysis of dynamic control of reservoir limited water level by considering flood forecast error

Flood control forecast operation mode is one of the main ways for determining the upper bound of dynamic control of flood limited water level during flood season. The floodwater utilization rate can be effectively increased by using flood forecast information and flood control forecast operation mode. In this paper, Dahuofang Reservoir is selected as a case study. At first, the distribution pattern and the bound of forecast error which is a key source of risk are analyzed. Then, based on the definition of flood risk, the risk of dynamic control of reservoir flood limited water level within different flood forecast error bounds is studied. The results show that, the dynamic control of reservoir flood limited water level with flood forecast information can increase the floodwater utilization rate without increasing flood control risk effectively and it is feasible in practice.

Multi model forecast biases of the diurnal variations of intense rainfall in the Beijing-Tianjin-Hebei region

Forecasts of the intense rainfall events are important for the disaster prevention and reduction in the Beijing-TianjinHebei region(BTHR). What are the common biases in the forecasts of intense rainfall in the current operational numerical models? What are the possible causes of model bias? In this study, intense rainfall events in the BTHR were categorized into two types: those mainly due to strong synoptic forcings(SSF) and those with weak synoptic forcings(WSF). The results showed that,the numerical forecasts tend to overestimate the frequency of intense rainfall events but underestimate the rainfall intensity. Of these, the overestimation of precipitation frequency mainly appeared in the mountainous areas in the afternoon. Compared with global models, high-resolution mesoscale models showed a notable improvement in forecasting the afternoon intense rainfall,while they all have an obvious bias in forecasting the nighttime rainfall. For the WSF type, both global model and mesoscale model have a low forecast skill, with large biases in subdaily propagation feature. The possible causes are related to a poor performance of the model in reproducing the local thermodynamical circulations and the dynamical processes in the planetary boundary layer. So, the biases in forecasting the WSF type intense rainfall showed notable features of nonlinearity, which made it really challenging to understand their physical processes and to improve the associated forecasts.