El Niño event has a significant impact on global climate, especially on regional droughts and floods, being an important source of signals for climate prediction. In order to understand the impact of El Niño on summer droughts and floods in North China,based on the monthly precipitation data of ore than 2 400 stations from 1961 to 2022, the monthly sea surface temperature data reconstructed by NOAA and the reanalysis circulation data from NCEP/NCAR, this paper comprehensively studies the relationship between interannual variability of El Niño and summer droughts and floods in North China and its impact mechanism by using seasonal evolu⁃tion empirical orthogonal function decomposition (SEOF), regression reconstruction of circulation anomalies, circulation composition analysis. The main results are as follows: (1) There is a significant negative correlation between the summer precipitation in North China and the El Niño state in summer of the current year. That is, El Niño begins to appear in the spring, develops in the summer and has a strong intensity, which results in less summer precipitation in North China and is prone to drought. Further analysis shows when the La Niña states in spring, summer, autumn and winter in the previous year change to El Niño states in spring, summer, autumn and winter in the current year, the summer precipitation in North China is significantly less and prone to drought. (2) El Niño affects summer precipitation in North China mainly by regulating the high and low level circulation. The circulation patterns of the 200, 500 and 850 hPa induced by El Niño in the summer of that year are consistent with the circulation patterns of the drought summer years in North China. (3) When the upper westerly jet at 200 hPa over North China and its north side is weak, the ascending motion caused by upper air disturbance will be obviously weak. The position of the western Pacific subtropical high at 500 hPa is southward, and North China is controlled by a circulation pattern of “high in the west and low in the east”. The low trough system moves eastward at a fast speed, which is not conducive to maintaining long-term precipitation processes in North China. The tropical Indian summer monsoon and the East Asian subtropical summer monsoon at 850 hPa are relatively weak, and North China lacks effective sources of water vapor transport. This high and low level circulation configuration will result in less precipitation in summer in North China, making it prone to drought. 

The self-developed global/regional assimilation and prediction system-regional ensemble prediction system (GRAPES-REPS) was put into operation in 2014 in China. In order to deeply understand the precipitation ensemble forecast ability of this system and conveniently apply the precipitation probability forecast, in this paper, the 24 h accumulated precipitation with different magnitudes forecasted by GRAPES-REPS at different lead time within 72 hours is evaluated by using statistical analysis and case analysis taking three continuous precipitation processes in southern China from mid-May to late June 2017 for example. The results are as follows: (1) The ensemble mean forecast of GRAPES-REPS has obvious advantage for light rain and moderate rain. The advantage decreases gradually with the increase of precipitation magnitude and no advantage appears for rainstorm. The ensemble mean forecast is close to the observation for light rain, while it has a tendency of null (missing) forecast for moderate rain (rainstorm) or heavy rain at a longer lead time. (2) The optimal members include control forecast and two perturbation forecasts that use a combination of MRF boundary layer scheme and KF-eta cumulus convection scheme, which is different to the other members. (3) The spread of precipitation ensemble forecasts is insufficient overall, especially at 0-24 h forecast lead time with the U-shaped Talagrand distribution and the higher (lower) forecast probability for small- (large-) magnitude precipitation. The spread increases obviously with the increase of forecast lead time, and the Talagrand distribution is gradually close to the expected-probability distribution. (4) The ensemble forecasts do have a reference value for precipitation with different magnitudes at every forecast lead time, with the probability forecast of heavy rain and rainstorm being better than that of light rain and moderate rain. (5) The ensemble gives a better forecast for precipitation pattern with different magnitudes as a whole, especially it has an ability of probability forecast for the warm-sector rainstorms in the central and southern Guangdong Province, which is missing in the forecasts of National Meteorological Observatory.

Based on the observation data from Shaanxi expressway automatic meteorological stations including the road surface temperature, air temperature, relative humidity, wind speed and cloud cover of reanalysis data of ECMWF from August 2013 to December 2017, the distribution characteristics of the road surface temperature in different seasons and sky conditions were analyzed, and relations between the road surface temperature and meteorological factors were studied, and relevant multivariate regression equations were established. The results show that the road surface temperature had obvious diurnal variation in different seasons. It was easier to freeze on the road surface from 00:00 BST to 08:00 BST after snow. The air temperature was one of the most important factors affecting the road surface temperature. By fitting the measured and caculated values of the road surface temperature, the results show that the model fitted the minimum road surface temperature well in winter with the correlation coefficient above 0.94, and the standard deviation was less than 1 ℃, and the frequency of difference between the observed and mesured temperature ranging from -2 to 2 ℃ was 98%. In addition, the model fitted better when the road surface temperature was 0 ℃.

There was a rare rainstorm weather process in the North of China on July 21，2012，which led to the most severe flooding disasters．The weather system of the process was the cold front with the upper trough，but such a system would not lead to more than 200 mm rainfall in 24 hours according to the statistical results of the last decade ( 2000 － 2011) ． After the precipitation in Beijing ，the torrential rain occurred in the middle of Hebei Province ( Langfang and the northeast of Baoding) ，where heavy rainfall occurred relatively less in the past． Thus，some reasons of the torrential rainfall in Hebei and the forecasting focus were analyzed in the article，based on the conventional observation data，reanalysis data from NCEP at 1° × 1° spatial resolution，regional automatic meteorological observation data and Doppler weather radar data． The comparative study of weather patterns，physics conditions and meso － and micro－ scale systems were carried out with another rainstorm process which occurred on the 24th July 2011． The results show that there were great differences between two weather processes in extreme value of precipitation and rainfall area，although their precipitation efficiency and meso － and micro － scale systems which directly resulted  in two precipitation processes were similar under the same synoptic scale circulation situation ( low － cold front type) ． The extreme precipitation in 7． 21 process had a closely relation to strong moisture transport，intense dynamic condition and high precipitation efficiency，but the train effect for 6 hours was the leading cause of the heavy rainfall． The configuration of low frontal zone of se and low － level jet on the south of shear line led to the train effect in the middle of Hebei Province，which was concluded as a forecast point of the kind heavy rain events． And，the ground mesoscale convergence line ahead of the cold front was a key point for accurately forecasting heavy rainfall area，which was better than based on the southeast quadrant of the lower vortex，because strong precipitation occurred along with lines．

By using meteorological observation data from eight weather stations in Southwest Guizhou and Micpas data and NCEP reanalysis data in recent five years， the spatial and temporal distribution of fog weather in Southwest Guizhou was analyzed in this paper． The results show that the main synoptic patterns resulted to fog weather here were the westerly flow in front of the southern trough and the northwest flow behind the upper trough，and physical quantity fields analysis indicated that the low － level air was wet when frontal fog appeared，and the atmosphere structure was relatively stable，there was a temperature inversion layer in lower level，and a weak upward motion nearby frontal area．