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.

Experiments in Forecasting Mesoscale Convective Weather over Changjiang Delta

The real time operational severe convective weather forecast experiment carried out during May to July in 1990 over the Changjiang Delta is briefly described. The heavy rainfall and severe conveetive weather forecast worksheets for the Changjiang Delta have been proposed and used in the daily forecasting. Results show that the ability of 0-12h convective weather prediction has been improved significantly after the development of the forecast methods and the establishment of a mesoscale forecast base at Shanghai Meteorological Center during 1986 to 1990.Three cases of convective weather systems (meso-alpha, meso-beta, meso-gamma) during the experiment period are described and discussed.

Forecasting the Quasi-stationary Front Rainstorm in Southeast China Using the Synthetically Multilevel Analog Forecast Technology

The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing mean vacant-forecast rate method,which pos-sesses many advantages with regard to filtering the analog term.Moreover,the similitude degree between samples is assessed using a combination of meteorological elements,which works better than that described using a single element in earlier analog forecast studies.Based on these techniques,the authors apply the model output,air sounding,surface observation and weather map data from 1990 to 2002 to perform an analog experiment of the quasi-stationary front rainstorm.The most important re-sults are as follows:(1) The forecast successful index is 0.36,and was improved after the forecast model was re-vised.(2) The forecast precise rate (0.59) and the lost-forecast rate (0.33) are also better than those of other methods.(3) Based on the model output data,the syn-thetically multilevel analog forecast technology can pro-duce more accurate forecasts of a quasi-stationary front rainstorm.(4) Optimal analog elements reveal that trig-gering mechanisms are located in the lower troposphere while upper level systems are more important in main-taining the phase of the rainstorm.These variables should be first taken into account in operational forecasts of the quasi-stationary front rainstorm.(5) In addition,experi-ments reveal that the position of the key zone is mainly decided by the position of the system causing the heavy rainfall.

Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

Upper ocean heat content(OHC)has been widely recognized as a crucial precursor to high-impact climate variability,especially for that being indispensable to the long-term memory of the ocean.Assessing the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate forecasts.Recently developed retrospective forecast experiments,based on a Community Earth System Model ensemble prediction system,offer a great opportunity to comprehensively explore OHC predictability.Our results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction extends.The spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill,indicating that the persistence of OHC serves as the primary predictive signal for its predictability.The decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean,particularly within tropical regions.Additionally,notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC variability.The potential predictability of OHC generally surpasses the actual prediction skill at all lead times,highlighting significant room for improvement in current OHC predictions,especially for the North Indian Ocean and the Atlantic Ocean.Achieving such improvements necessitates a collaborative effort to enhance the quality of ocean observations,develop effective data assimilation methods,and reduce model bias.

A Global Spectral Model and Test of Its Performance

A brief introduction is given of a global spectral model, its dynamical framework and diabatic physical processes involved. A number of real forecasts are shown to illustrate the forecasting capability of the model for various weather processes. It can even manage to predict some of those typical weather processes in summer which used to be difficult to forecasters.

Impact of GNSS radio occultation bending angle data assimilation in YH4DVAR system

Global Navigation Satellite System （GNSS） radio occultation measurements have been assimilated into the four- dimensional variational data assimilation system （YH4DVAR） using a one-dimensional bending angle operator （GBAO） as a new type of observation. For the sake of verifying the impact of GNSS radio occultation （RO） measurements to the data assimilation system, three experiments have been conducted. The statistical results of the analysis error experiment and forecast skill experiment show that the GNSS RO measurements have an impact on the analysis system. The typhoon forecast experiment shows the impact on the important weather process. They all have a positive impact on the weather forecast. Lastly, we look forward to future work on the observation system simulation experiment （OSSE） to investigate the impact of GNSS RO measurements as a function of observation number, which is an effective method to estimate the saturation of the observation number.