Based on hourly meteorological and environmental monitoring data in Cangzhou of Hebei Province from 2014 to 2020, this paper analyzed the aggravation of ozone (O₃) pollution and its relationship with meteorological factors. The results are as follows: (1) The pollution of O₃ in Cangzhou had been increasing and O₃ had become the primary pollutant. The pollution of O₃ concentrated from May to September, and the diurnal variation of O₃ mass concentration showed single peak and single valley type, and the maximum concentration occurred around 16:00 BST. (2) During the period of O₃-8 h maximum value from May to September, the average temperature, maximum temperature, relative humidity and total radiation irradiance were strongly correlated with the O₃ mass concentration, while the correlation between station atmospheric pressure, water vapor pressure, mean wind speed and the O₃ mass concentration didn’t pass the significance test. (3) During the period of O₃-8 h maximum value from May to September, when the average temperature of 8 h was above 30.9 ℃, the maximum temperature of 8 h was above 32.7 ℃, the average relative humidity of 8 h was below 42.1% and the average total radiation irradiance of 8 h was above 505.8 W·m^-2, the probability pollution of O₃ was up to 84%. (4) Meteorological factors were not sufficient conditions for rapid increase of O₃ hourly mass concentration.

Based on hourly meteorological and environmental observation data from Cangzhou of Hebei Province from 2014 to 2019, the influences of precipitation on atmospheric pollutant concentration were further discussed by using wind and background concentration correction method. The results show that the correction method about wind and background concentration could better remove the own diurnal variation characteristics of pollutant concentration and eliminate the influence of wind speed, and the influence of precipitation on atmospheric pollutant concentration could be acquired more accurately. Under the condition of wind force and background concentration correction, the removal effect of rainfall on PM_2.5, PM₁₀, O₃ and NO₂ was better, but for SO₂ and CO it wasn’t obvious. The removal effects of rainfall with different intensities on PM_2.5, PM₁₀ and NO₂ were better, and the removal rate increased with enhance of rainfall intensity. The removal effect of rainfall intensity less than 8.0 mm·h^-1  on O₃ was significant, while the rainfall intensity above 6.0 mm·h^-1 had removing effect on SO₂. With the duration of rainfall, the mass concentration of PM_2.5, PM₁₀, NO₂ and O₃ continuously decreased, and the removal efficiency dropped, the removal effect wasn’t obvious when the mass concentration of pollutant dropped to a certain threshold.

Based on temperature and precipitation data from 68 national meteorological stations in Zhejiang Province from 1988 to 2017, mean summer temperature and precipitation were interpolated using thin-plate smoothing splines （ANUSPLIN), inverse distance weighting (IDW) and ordinary kriging interpolation methods. In order to explore the optimal interpolation method of meteorological elements under complex terrain and climate in Zhejiang Province, the cross-validation method was applied to evaluate the accuracy of three methods, and the spatial error was analyzed. The results are as follows: (1) The interpolation accuracy of temperature and precipitation was generally close by using three methods, and the spatial distribution was relatively consistent. However, ANUSPLIN method was significantly better than IDW and ordinary kriging methods in detail for areas with large heterogeneity of element. (2) The interpolation accuracy of air temperature and precipitation based on ANUSPLIN was higher than that based on IDW and ordinary kriging. For example, the mean absolute error (MAE)and root mean square error (RMSE) of air temperature interpolation were both less than 0.5 ℃. The RMSE (0.381 ℃) of temperature interpolation based on ANUSPLIN was smallest, it was second based on ordinary kriging（0.459 ℃）, and it was biggest （0.463 ℃） based on IDW. The RMSE (37.8 mm) of precipitation interpolation based on ANUSPLIN was smallest, it was second (42.2 mm) based on the ordinary kriging, and it was biggest (49.1 mm) based on IDW. (3) The average interpolation error of temperature in plain area was lower than that in mountainous area. The average interpolation error of precipitation in the coastal area had largest error, showing an obvious low estimation. In conclusion, ANUSPLIN was more suitable for the spatial treatment of meteorological elements in Zhejiang  Province under complex terrain and climate background.

From the view of climate system complexity, the nonlinear characteristics of drought were discussed in Northwest China from 1962 to 2017. Based on the monthly meteorological observation data at 159 stations of Northwest China, the standardized precipitation evapotranspiration index (SPEI) was calculated, firstly. Then, the temporal and spatial distribution of drought was analyzed by using empirical orthogonal function (EOF). And on this basis the abrupt change of decomposed time coefficient of SPEI was detected by using moving cut data- approximate entropy (MC-ApEn) method. Finally, the complexity of drought was discussed by using approximate entropy (ApEn) method in Northwest China. The results are as follows: (1) The first EOF mode of SPEI was consistently positive in Northwest China from 1962 to 2017, while the second EOF mode was positive in the east and negative in the west of Northwest China. Compared with time coefficient of the second mode, the climate was wetter in the west and drier in the east than that before the abrupt change, and the change point was approximately in 1980. The drought existed 2-3 a period in Northwest China during 1962-2017. (2) The complexity of drought increased after the abrupt change of 1980 in Northwest China as the whole, so the predictability of drought decreased. Moreover, the complexity of drought in autumn and winter was greater than that in spring and summer in Northwest China from 1962 to 2017, and the complexity was the largest in winter and the smallest in summer.