Comparison and Analysis of Data at Traffic Meteorological Observation Station during Beijing Winter Olympic Games Period

This paper presents a comparison and analysis method of data at traffic meteorological observation station during Beijing Winter Olympic Games period based on Grubbs criterion. By comparing the data of a set of standard multi-element observation stations with the data of multiple measured traffic stations, the outliers of each element data at each station were analyzed. It could provide data support for the maintenance of Zhangjiakou traffic meteorological observation station and a guarantee for the accuracy of forest service during Beijing Winter Olympic Games period.

Scientific Advances and Weather Services of the China Meteorological Administration’s National Forecasting Systems during the Beijing 2022 Winter Olympics

Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.

Machine Learning-Based Temperature and Wind Forecasts in the Zhangjiakou Competition Zone during the Beijing 2022 Winter Olympic Games

Weather forecasting for the Zhangjiakou competition zone of the Beijing 2022 Winter Olympic Games is a challenging task due to its complex terrain.Numerical weather prediction models generally perform poorly for cold air pools and winds over complex terrains,due to their low spatiotemporal resolution and limitations in the description of dynamics,thermodynamics,and microphysics in mountainous areas.This study proposes an ensemble-learning model,named ENSL,for surface temperature and wind forecasts at the venues of the Zhangjiakou competition zone,by integrating five individual models—linear regression,random forest,gradient boosting decision tree,support vector machine,and artificial neural network(ANN),with a ridge regression as meta model.The ENSL employs predictors from the high-resolution ECMWF model forecast(ECMWF-HRES) data and topography data,and targets from automatic weather station observations.Four categories of predictors(synoptic-pattern related fields,surface element fields,terrain,and temporal features) are fed into ENSL.The results demonstrate that ENSL achieves better performance and generalization than individual models.The root-mean-square error(RMSE) for the temperature and wind speed predictions is reduced by 48.2% and 28.5%,respectively,relative to ECMWF-HRES.For the gust speed,the performance of ENSL is consistent with ANN(best individual model) in the whole dataset,whereas ENSL outperforms on extreme gust samples(42.7% compared with 38.7% obtained by ECMWF-HRES in terms of RMSE reduction).Sensitivity analysis of predictors in the four categories shows that ENSL fits their feature importance rankings and physical explanations effectively.

Evaluation and Promotion Model of Tourist Satisfaction in Ice and Snow Tourism Destinations

The successful bid for the Beijing Winter Olympics has brought historic opportunities for the development of ice and snow tourism in China.An index system for the evaluation of tourist satisfaction in ice and snow tourism destinations was constructed from the target layer-factor layer-index layer approach in this paper.Taking tourists with ice and snow tourism experience as the research object,and integrating a questionnaire survey and the Importance-Performance Analysis(IPA)method,a total of 840 valid questionnaires were collected to assess the satisfaction of tourists in snow and ice tourism destinations,and the promotion model of tourist satisfaction in ice and snow tourism destinations was put forward.This process led to three main results.(1)Ice and snow tourists in China are characterized as young and better-educated,with college students aged 19 to 25 as the main consumer group.More than 70%of ice and snow tourists are pretty satisfied with the current development of ice and snow destinations in China,and are willing to participate again.(2)Other than“ice and snow souvenirs”,tourists’perceptions of importance are all higher than the level of perceived satisfaction,and the importance values of the 13 indicators including“Scenic spot security”and“Diversity of ice and snow entertainment and sports”are especially high,showing that tourists have high expectations and demands of the destinations.However,the perceived satisfaction level of tourists for all indexes is generally low,mostly at the general satisfaction level,indicating that ice and snow tourism destinations have only partially met the demands of ice and snow tourists,and there is still much room for improvement.(3)After IPA analysis,five suggestions for improving the satisfaction of tourists in ice and snow tourism destinations were put forward,including diversification of the tourism business model,construction of tourism facilities,a market diversified cultivation model,a humanized mode of tourism service and a refined management model.The results of this study will help to enrich the theory of ice and snow tourist satisfaction and promote the high-quality development of China's ice and snow tourism in the post-Winter Olympics era.