| Eleven major tourist attractions in Baoding City(referred to as scenic spots hereafter)were selected as the research objects;the meteorological data of the regional automatic stations in these scenic spots from 2015 to 2018,the daily meteorological data of the counties where the scenic spots are located or its surrounding weather stations from 1974 to 2018,and the survey data of the scenic spots during phenological periods,were adopted as the data samples,which were optimized through correlation and regression analyses.The characteristics of tourist climate,phenology and weather in the scenic spots were analyzed,and the quantitative calculation and qualitative evaluation methods for the three indexes were established in turn.Considering the impact of the above three indicators on tourism activities,the Comprehensive Index Forecasting Model for Baoding Tourism Meteorology was established at last in combining the evaluation methods of the three indicators.In addition,the model was written into a business software and put into daily weather service for testing and experimenting.The main results of the study are summarized as follows:(1)This study establishes three indexes,that is tourism climate index,tourism phenological index and tourism weather index,which are suitable for the study area(Baoding City).Subsequently,a preliminary comprehensive index model for the tourism meteorology is established.Each sub-index is graded to establish rating assessment criteria.Based on the weight distribution of the three sub-indexes on tourism activities,a comprehensive index calculation model is established.The domain set obtained through multiplying the quantitative evaluation criteria of the three sub-indexes by the weights is to be graded again,producing the quantitative and qualitative evaluation criteria for the tourism meteorological comprehensive indexes in Baoding.The model is implanted into the professional software for tourism weather service to realize the automatic forecasting of the scenic meteorologicalindexes at specific time and places.The preliminary application of the established model has shown that the model reflects the combined impact of climate,phenology and weather on tourism activities,and is of greater referential value compared with a single index.Besides,the model consists of three independent sub-indexes,each of which will indicate the impact of a single meteorological factor on tourism activities,offering opinions for decision-making from different perspectives.Preliminary application shows that the model has the advantages of flexible application and can provide decision-making opinions for service objects from different perspectives.(2)The distribution law of tourism climate comfort degree in each scenic spot is obtained,and the scenic spots with the most comfortable climate every month and the most comfortable months in climate for each scenic spot are summarized.The results show that: the months from March to November are relatively comfortable for tourists in Baoding,just corresponding to the spring,summer and autumn seasons herein but winter.During the appropriate periods,the most comfortable month for tourists is May in Baoding,during which the climate optimum days in the 11 scenic spots reach up to 31;while the most uncomfortable month for tourists is November,when the climate optimum days in all the scenic spots drop below 15,and what’s even worse is that the climate optimum days for four scenic spots are zero.Among the 11 scenic spots studied,the tourist climate of Tianpingqiao Scenic Spot in Fuping is the most pleasant,and its climate optimum days of a year can reach 222.While the climate comfort degree of Baiyang Lake Scenic Spot in Anxin is the worst with the climate optimum days of the whole year being just 151.These conclusions are consistent with the actual situation.After preliminary business tests,it is consistent with the actual situation.(3)The distribution patterns of tourism phenological landscape in each scenic spot are summarized,and the best phenological landscape of each month and the best phenological sightseeing period of each scenic spot are obtained.Among them,the florescene and the acme of red maple leaves are the best phenological sightseeing periods for each scenic spot.The periods of flourished red maple leaves in these scenic spots are relatively concentrated,mainly ranging from late September to the end of October with the exception of the Baiyang Lake scenic spot in Anxin.The florescenes for each scenic spot are unevenly distributed,with the earliest appearing in early May while the latest in late August,and the florescenes may overlap in several scenic spots in a singular month.The scenic spots will enter the primary stageof withering in succession since early November,and return to the regreening stage since the next early or earlier April.The transitional period between the two stages is the worst time for sightseeing the phenological landscape of all scenic spots.(4)The weather phenomena affecting scenic spots are classified,and the classification guidance suggestions of unfavorable weather in scenic spots are established.The time and spatial distribution of various adverse weather conditions are summarized in these scenic spots.The adverse weather affecting Baoding tourist scenic spots mainly includes rainfall,rainstorm,thunderstorm,hail,high temperature,gale,snowfall,fog and haze.Among them,rainfall weather occurs most,becoming a key weather phenomenon influencing the tourism activities in Baoding.Throughout the year,autumn tend to have the least adverse weather conditions,while spring,summer and winter tend to have more with the most occurring in summer.Rainfall,rainstorm,thunderstorm,hail,and high temperature usually occur during July,while strong wind usually occur during April,the fog mostly during December,haze during January,and snowfall during February.Among the 11 scenic spots,the Whitestone Mountain Scenic Spot in Laiyuan is an area mostly hit by unfavorable weather phenomena during July,while the Baiyang Lake Scenic Spot in Anxin is an area least hit by adverse weather phenomena.Tourism meteorological service is a new science.As an exploratory work,this paper can provide a reference for establishing a more quantitative model on the basis of quantitative economic theory. |
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