In order to explore the characteristics and influence factors of atmospheric boundary layer inversion in Yinchuan City and their relationship with winter PM2.5 pollution, based on the sounding and surface meteorological observation data at Yinchuan meteorological station and the air quality monitoring data in Yinchuan City from 2015 to 2020, the characteristics of atmospheric boundary layer inversion and surface meteorological elements are analyzed. And on this basis that the influence of inversion and surface meteorological elements on PM2.5 pollution weathers in winter is explored. The results are as follows: (1) The inversions in atmospheric boundary layer are more easily to occur in the early morning than in the evening in Yinchuan City, and most of the inversions are ground inversions, they are stronger and thinner than suspension inversions. The inversion frequency and thickness are the largest in winter and the smallest in summer, while the inversion intensity is the strongest in autumn and the weakest in summer. (2) In winter, the inversions are easily to occur on a sunny day with average surface wind speed from 1.0 to 1.5 m·s-1 and relative humidity from 30% to 60%. (3) Ground inversion is one of the main meteorological factors affecting PM2.5 pollution weathers in winter. When the inversion thickness exceeds 596 m and the intensity exceeds 1.4 ℃·(100 m)-1, PM2.5 pollution weathers are easily to occur, and the pollution is aggravated with the increase of inversion thickness and intensity. (4) Under PM2.5 pollution weathers in winter, the sky is mostly sunny in the early morning, the average surface wind speed is usually less than 1.3 m·s-1, the relative humidity is greater than 54%, and the pollution is aggravated with the increase of humidity. (5) The boundary layer height is significantly negatively correlated with PM2.5 mass concentration, and the lower boundary layer height is, the heavier PM2.5 pollution is.
Meteorological prediction is one of the most important and challenging task in the modern world．In general，climate is highly non －linear and complicated phenomena，which require advanced method and computer modeling for their accurate prediction． This paper provides a survey of available literature of some methodologies employed by different researchers for the weather forecast based on the methods of data mining at home and abroad． It briefly introduced the concepts and traits of some data mining methods in atmospheric science，separately discussed the basic principles of these data mining methods used in weather forecasting，including the advantages and disadvantages． Finally，the author points out some existing difficulties of data mining methods used in weather forecasting ，and puts forward key points of future research and current trends of the research．
Based on themonthly p recip itation data during 1951 - 2000 from 19 meteorological stations in Guizhou p rovince, the regional characteristics of p recip itation anomalies in summer are studied by usingmethods of the fuzzy assembling analysis, emp irical orthogonal function ( EOF) analysis and wavelet analysis on normalized anomaly of 19 stations’monthly averaged rainfall. The results show that five obvious rainfall periods occurred in the recent 50 years, includingwet in the early 1950 s, dry from the middle of the 1950 s to the early 1960 s, wet from the middle of 1960 s to the end of 1960 s, dry in the 1970 s and 1980 s, wet after the 1990 s, at the same time , the total rainfall p resented increasing trend. The coincident variability occurred in summer rainfall of Guizhou, but some regional differ2 ence also existed. The variations of p recip itation anomalies in summer can be divided into five spatial patterns, namely dry (wet) in the whole p rovince, dry (wet) in the east and wet ( dry) in the west, dry (wet) in the south and wet ( dry) in the north, dry (wet ) in the middle and east part butwet ( dry) in the southwest, dry (wet) in the southwest and wet ( dry) in other areas. It p resented ob2 viousmultip le time scales of 10 - 12 years, 4 - 5 years and 2 - 3 years variations for different rainfall patterns.
Based on precipitation data in 126 surface stations in Northwest China, using REOF and tial characteristics of summer preclpltahon mNnlthwest China were analyzed in the paper. Results Blur-clustering method, the spa-show that the northeastern side of Tibetan Plateau is the most tion is mostly a half of that nant. PTPClpltatlOn trend In sensitive region to summer precipitation in Northwest China, the rainy 凡e月凡On (July to August) precipita-m a peal pears Wlth less Taln are mOTe than Ta1nV VeaTS in the region, and dry and flood years al'e a.Itel'- .Tune is ascending changing in recent 40 years, changing slowly in July, and descending in August, fiom the liner trend, the summer precipitation is nnconspicnonsly. Moreover, temperature departure and precipitation departure percent present reverse phase, and temperature is rising in recent 40 years.
Analysis of the climatological features of Jiangnan rainy season precipitation anomalies shows that the month with the most frequent anomalies of precipitation in Jiangnan is J une and the region is located in the middle of Jiangnan. The SVD analysis points out that the related sea surface temperature anomaly (SSTA) distributes in the pattern as a“seesaw”. The key region is just located in the most evident correlation area. The key period of SSTA impact is from May to J uly in the previous year in which SSTA has the best negative correlation with April to May precipitation in Jiangnan. Under the influence of SSTA“seesaw”pattern the precipitation anomalies in the following April to J une in East China exhibit opposite phase on both sides of the Yangtze River , the most evident correlative region is Jiangnan and the middle of which is located in the most obvious area of SSTA impacts.
