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The Characteristics Of Temporal And Spatial Changes Of Humidity In The Arid Area Of ??northwestern China And Its Relationship With Climatic Elements

Posted on:2021-05-27Degree:MasterType:Thesis
Country:ChinaCandidate:R L XuFull Text:PDF
GTID:2430330605963944Subject:Physical geography
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Global warming has an important impact on hydrological changes and water cycles in different regions.Air humidity,as an important factor for measuring atmospheric water vapor content,is closely related to regional temperature and precipitation,and is also closely related to the natural environment,agricultural production,and human life.In addition,the dry and wet conditions in the arid regions of northwest China(ARNC)are important responses to climate change and hydrological cycles in the region.Therefore,the analysis of the spatiotemporal variation and influencing factors of air humidity in the arid regions can provide an in-depth understanding of the aridification problem in ecologically vulnerable regions.It has great guiding significance for the stability of the regional ecological environment and the rational utilization of water resources.Based on meteorological data from ARNC in the recent 50 years,this paper used relative humidity,absolute humidity,and specific humidity to analyze the spatial-temporal variation trend,abrupt change and periodic oscillation of near-surface to high-altitude humidity in the study area.The correlation and sensitivity analysis were employed to reveal the relationship between humidity changes and other factors,such as meteorological factors and circulation factors.Finally,based on Mean Generating Function-Optimal Subset Regression(MGF-OSR),a forecast model of humidity change was established and the humidity change was reasonably estimated in the next decade,which provided a scientific basis for coping with climate change and improving the prediction accuracy of climate dry and wet years.The main results are as follows:(1)From 1960 to 2016,the annual average relative humidity of near-surface in ARNC showed an insignificantly decreasing trend(-0.125%/10a),while the annual average absolute humidity and specific humidity showed significant increasing trends(P<0.001),and their rates were 0.068g/m~3/10a and 0.069g/kg/10a,respectively.Relative humidity in the lower troposphere showed an insignificant downward trend(-0.233%/10a)while there were significant upward trends(0.189%/10a,P<0.05 and 0.16%/10a,P<0.01)in the middle and upper troposphere.Absolute humidity and specific humidity showed insignificantly increasing trends in the lower and middle troposphere while the rate of change in the upper troposphere was close to zero.The average relative humidity from near-surface to high-altitude was the largest in winter,followed by autumn and summer,and the lowest in spring.Moreover,the absolute humidity and specific humidity were the highest in summer,but the lowest in winter,while those in autumn were slightly higher than in spring.From the interannual and seasonal variation curves,the humidity parameters showed a"stable-up-down",from mid-1980s to 2002,meanwhile the humidity increase significantly in the 1990s and reach a maximum in 2002 while turning into a substantial downward trend.(2)Under the conditions of a significance level of 0.05 and a confidence threshold value of±1.96,there was no mutation of near-surface relative humidity but the mutation of absolute humidity and specific humidity occurred in 1987.In the lower troposphere,the mutations of the three humidity parameters all occurred in the early 1960s.During the study period,the three humidity parameters near the ground all showed a 28-year main periodwith the large range of change and the average change cycle of humidity was 20 years and had a total of 3 times of alternation from high to low in humidity.The main cycle of relative humidity in the lower troposphere was 23 years,there were 3 alternating wet and dry changes.The first main cycle of absolute humidity and specific humidity was 29 years,and the second main cycle was 22 years.There were 4 alternating wet and dry changes for the absolute humidity and specific humidity.Each humidity parameter in the middle and upper troposphere mainly was 22 years as the main cycle,and the average cycle was 15 years,which had 4 alternating wet and dry changes.(3)From the perspective of spatial distribution changes,the near-surface relative humidity gradually increases from east to west and from south to north,while the absolute humidity and specific humidity increase from east to west and from north to south.Relative humidity shows a significant increase in southern Xinjiang(P<0.05),while in northern Xinjiang and Hexi corridors show no significant decline.Absolute humidity and specific humidity increase significantly in most areas(P<0.05).In the troposphere,each humidity parameter shows the most significant increasing trend in Urumqi and Kuqa(P<0.01).However,the decreasing trend is significant in the Beitashan and Zhangye(P<0.05).(4)The correlation between each humidity parameter and precipitation from near ground to high altitude is higher than that between air temperature and humidity.There is a significant positive correlation between the humidity parameters near the ground and precipitation(R=0.513,0.668,0.671,P<0.05),while there is no significant positive correlation between winter in lower troposphere and autumn in the middle troposphere.Relative humidity at different altitudes is negatively correlated with air temperature,and the correlation is higher in spring and summer near the surface(P<0.01)and winter in the lower troposphere(P<0.05).Absolute humidity and specific humidity near the surface show a significant positive correlation with air temperature(P<0.01),while only in autumn and winter in the lower troposphere,and winter in the middle troposphere has a significant positive correlation(P<0.01).In addition,the humidity parameters in ARNC have the most significant negative correlation with the Asia polar vortex area index(R=-0.397,-0.512,-0.503,P<0.01),and have the highest positive correlation with the Tibet Plateau Index(R=0.394,0.477,0.468,P<0.01).It also has strong correlations with the circulation indices such as the Northern Hemisphere Subtropical High,the Western Pacific Subtropical High,and the location of the East Asian trough(P<0.01).(5)From the quantitative analysis of the effect of temperature and precipitation on humidity,if the precipitation increases by 10%,the relative humidity,absolute humidity,and specific humidity near the ground will increase by 1.22%,2.08%,and 2.14%,respectively.If the temperature increases by 10%,the relative humidity will reduce by 0.96%,while absolute humidity and specific humidity increase by 2.29%and 2.47%,respectively.In addition,the degree of influence of temperature and precipitation on humidity variation in different seasons could also different,among which the climate factor change in summer has the largest influence degree on humidity.The near-surface relative humidity is more sensitive to air temperature,while the relative humidity in the troposphere is more closely related to precipitation.The absolute humidity and specific humidity at different altitudes are more sensitive to temperature than precipitation.(6)Based on the time series of each humidity parameter in ARNC,the humidity prediction model is established by using MGF-OSR.The determination coefficients R~2of them basically reach more than 0.6.However,the prediction effects at different heights in different regions have certain differences.The humidity parameters are best predicted by the near-surface humidity.According to the forecast data in the next 10 years,the near-surface humidity parameters show a downward trend in fluctuations,and the decreasing trend is more obvious in northern and southern Xinjiang.The humidity in the lower and middle troposphere show the trend of rising first and then decreasing;while in the upper troposphere,the humidity in northern and southern Xinjiang areas increases first and then decreases,and the Hexi Corridor decreases.
Keywords/Search Tags:air humidity, spatiotemporal variation, wavelet analysis, prediction model, arid area of Northwest China
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