Establishment of Prediction Method of Tourism Meteorological Index in Langzhong Ancient City

Based on the meteorological data of Langzhong from 2010 to 2020,the human body comfort index was calculated,and tourism climate comfort was evaluated to establish the prediction equation of tourism meteorological index.OLS was used to compare the correlation between actual tourist flow and tourism meteorological index and test the model effect.Average correlation coefficient R was 0.7017,so the correlation was strong,and P value was 0.The two were significantly correlated at 0.01 level(bilateral).It can be seen that the forecast equation of tourism meteorological index had a strong correlation with the actual number of tourists,and the predicted value was basically close to the actual situation,and the forecast effect is good.

Analysis of the Correlation between Tourism and Climate in the Ancient City of Langzhong

Based on the meteorological data of Langzhong from 1981 to 2016,a comprehensive comfort index model of tourism climate suitable for Langzhong is established by calculating the meteorological and climatic factors affecting tourism in the ancient city of Langzhong.The model is used to evaluate the climate comprehensive comfort of Langzhong,and its grades and suitable tourism periods are divided.Based on the monthly index of passenger flow volume in the ancient city of Langzhong from 2013 to 2015,a mathematical model is established through OLS regression analysis to analyze the correlation between changes in monthly passenger flow volume in a year and the comprehensive comfort of tourism climate in the ancient city of Langzhong.The results show that the climate in Langzhong is suitable for tourism in spring and autumn.It is suitable for tourism from February to June and from September to December,of which it is most suitable for tourism from April to May and from September to October.It is less suitable for tourism in only January and from July to August,and there is no unsuitable period.The changes in monthly passenger flow volume in a year are mainly affected by the meteorology and climate.The changes of climate comprehensive comfort in various month have an extremely significant impact on passenger flow volume.The elastic coefficient of impact of climate comprehensive comfort index on the monthly index of passenger flow volume is 0.9614%.

Contribution of Meteorological Disaster Prevention and Reduction Services to Rural Revitalization

In the context of rural revitalization and development,meteorological services for agricultural disaster prevention and reduction are facing new opportunities and challenges.It is needed to fully understand the importance of strengthening meteorological disaster prevention and reduction services,accurately grasp the strategy of rural revitalization,recognize the shortcomings in work,adhere to modern capacity building,improve the meteorological monitoring network,build a meteorological service system for agriculture and meteorological disaster prevention mechanism in line with rural revitalization,enhance the research and development capability of meteorological service products,expand the coverage of meteorological services,and effectively make greater contributions to rural revitalization.

Design and Implementation of Multi-element Integration Platform Based on Tianqing Data

In order to better carry out meteorological service and improve service efficiency,based on Tianqing data multi-factor integration platform,using Tianqing intensive data source of big data cloud platform,daily and hourly precipitation,temperature and wind data can be acquired,and C#language can be used to realize data analysis,text template nesting,meteorological material generation and archive management functions.The application shows that the platform can quickly complete the production of rain information within 2 min,and the material filing management has zero errors,which is superior to the traditional methods in terms of framework design and data processing material management.