To improve the forecast and early warning ability for the low visibility along the expressway, the hourly observation data of 10 traffic meteorological stations along Shaanxi section of the Lian-Huo expressway and the hourly reanalysis data of the European Center for Medium-Range Weather Forecasts are employed to analyze the distribution characteristics of low visibility and to explore the relationship of low visibility with other meteorological factors. The results show that along Shaanxi section of the Lian-Huo expressway, January has the most low visibility, while February has the least. During a day, the low visibility mostly happens from 00:00 to 10:00, and the low visibility of 0-50 m mainly occurs from 05:00 to 06:00. The low visibility duration is short with the majority of within 2 hours and the longest of 17 hours. The low visibility weathers occur frequently from Xingping to Changxing and Chencang section, where attention should be paid in daily traffic meteorological service. Accordingly to the analysis of the relationship between low visibility and other meteorological factors, the low visibility generally occurs under the conditions of air temperature from 0 to 5 ℃, relative humidity above 90%, wind speed less than 1.0 m·s^-1 and northeast to east winds. The low visibility weather in summer and winter is mostly associated with precipitation, which usually occurs during or after the precipitation and is accompanied by weather systems always. Compared with the low visibility caused by radiation cooling, the low visibility associated with precipitation exhibits longer duration and the wider range. The low visibility weathers occur at different relative humilities in different seasons, which in winter, summer and autumn are high, while in spring are relatively low.

Research on highway traffic disaster risk is a new direction for the development of professional meteorological services, and it is an important content of traffic weather forecasting services in future. Based on the ground observation data at 94 weather stations in Shaanxi from 1980 to 2017, the temporal-spatial change characteristics of road icing under different weather conditions were analyzed by using EOF method, etc., firstly. And the risk warning model of road icing in Shaanxi was discussed and established. The results show that there were two centers of road icing in the northwest of Guanzhong to the west of northern Shaanxi and Shenmu of northern Shaanxi, and the ratio of sleet or snowfall road icing was the maximum. The road icing mainly occurred from November to next March in Shaanxi, and the beginning date of road icing generally occurred in mid-to-late October in northern Shaanxi and Guanzhong, while that occurred later in November in southern Shaanxi, but the ending date of road icing mainly occurred in March and April in three regions, and the road icing days in January was the most. After the 1990s, the days of road icing decreased. The risk warning model of road icing was established and applied to business system in Shaanxi, and it could complete automatic production, the prediction effect was better.

Based on the observation data of hourly temperature，daily maximum and minimum temperature，daily mean total cloud cover and rainfall from ten stations in Shaanxi Province from 2006 to 2010，a forecast method of hourly temperature was established by using linear regression method on the basis of forecast values of daily maximum and minimum temperature and observed values of hourly temperature，which was tested by comparing forecast values with observed values of hourly temperature at ten stations in Shaanxi Province in 2011． The results show that the forecasting ability of the forecast method of hourly temperature under sunny or lightly cloudy conditions was better than that under heavily cloudy or rainy conditions． The forecasting effect of the method was better between 2 o clock
and 18 o clock than that between 19 o clock and 1 o clock of the next day on sunny or lightly cloudy days，and was better between 1 o clock and 10 o clock than that at other time on heavily cloudy or rainy days． When the forecasted daily maximum and minimum temperature were comparatively accurate，the forecast accuracy of hourly temperature was more than 60% at Xi an station． The accuracy was 100% on sunny days and from 96% to 99% on lightly cloudy days between 14 o clock and 17 o clock． But the accuracy on heavily cloudy or rainy days was about 12% ～ 27% lower than that on sunny or lightly cloudy days between 11 o clock and 17 o clock． With the characteristic of diurnal variations of temperature change in different areas，seasons and sky conditions，the method can turn
the forecasted daily maximum and minimum temperature into forecast of hourly temperature well． To some extent the forecast method of hourly temperature has application and extension values．