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Temporal Climate Change Assessment In Semiarid Western Heilongjiang During 1961?2015

Posted on:2022-12-16Degree:MasterType:Thesis
Country:ChinaCandidate:Mahmoud Mohammed Ahmed Hamdy HFull Text:PDF
GTID:2480306611994419Subject:Industrial Current Technology and Equipment
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Studying regional climate change has a great significance in protecting the regional ecological environment and sustainable development.The main objectives of this study were to reveal and evaluate the main characteristics of temporal climate change for the semiarid western region of Heilongjiang in the northeast of China.Based on the meteorological data of 6 stations in a period from 1961-2015(55 years),the Standardized Precipitation Index(SPI),the Standardized Precipitation Evapotranspiration Index(SPEI)with potential evapotranspiration(PET)projected by the Penman-Monteith equation(pmSPEI)were estimated for various time scales(1,3,6,12,and 24 months).Whereas the drought characteristics of the study area were evaluated by using the results of SPI and SPEI.The coefficient of variation method(COV)was adopted to evaluate the variation characteristics of the main meteorological factors.Multiple Linear Regression(MLR)method was developed and used to evaluate the linear relationships between the main meteorological factors(air temperature,relative humidity,sunshine hours,and wind speed)and precipitation,and sensitivity analysis for each factor was evaluated.A linear model was developed for evaluating the linear relationship between SPI and SPEI of the time scale of 12 months.The main results of this study are follows.(1)In the period of 1961-2015,for the study area of the semiarid western Heilongjiang Province,the mean annual minimum temperature,mean annual maximum temperature and the mean annual air rtemperature showed an increased trend,the increased rate were 0.171?,0.510? and 0.342? per 10 years;the annual mean precipitation showed slight increased trend with 6.58 mm per 10 years;the mean annual wind speed showed a decreased trend with-0.232m/s per 10 years;the mean annual sunshine hours showed a decreased trend with-0.11h per 10 years;the mean annual relatively humidity increased by 0.33%per 10 years.The order of variability of meteorological factors from large to small is:the mean annual temperature>mean annual precipitation>mean annual wind speed>mean annual sunshine hours>mean annual relative humidity.(2)During 1961-2015,SPI and SPEI at different time scales showed similar change characteristics,and exhibited a slight wet trend in the semiarid western Heilongjiang Province.The wet trend of Spring,summer and winter was different,but not obvious;in autumn,SPI and SPEI showed a slightly opposite trend in the study area.(3)SPI and SPEI have good applicability in drought assessment of the study area.The analysis results of extreme weather events based on SPI and SPEI were consistent with the historical extreme weather events in the semiarid western Heilongjiang Province.(4)Among the four meteorological factors of temperature,relative humidity,sunshine hours and wind speed,the order of their influence on precipitation was:temperature>relative humidity>sunshine hours>wind speed.While the order of parameter sensitivity discriminant factor of the 4 meteorological for precipitation is relatively humidity>sunshine hours>air temperature>wind speed.(5)The linear fitting degree of SPI and SPEI for time scale of 12 months was more than 80%.The results reveal the drought characteristics and trend with a certain degree in the semiarid western Heilongjiang Province.The influence of annual temperature,relative humidity,solar radiation and wind speed on annual precipitation was evaluated.The linear correlation between SPI and SPEI was evaluated.The results are expected to provide basic data for further research and prediction of climate change in the semiarid western region of Heilongjiang Province.
Keywords/Search Tags:Semiarid western Heilongjiang, Climate change, Standardized Precipitation Index(SPI), Standardized Precipitation Evapotranspiration Index(SPEI), Multiple Linear Regression analysis
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