A case of a snowstorm at the Great Wall Station was studied using data of NCEP(National Centers for Environmental Prediction) analysis,in situ observations and surface weather charts.The storm occurred on August 29th, 2006,and brought high winds and poor horizontal visibility to the region.It was found that the storm occurred under the synoptic situation of a high in the south and a low in the north.A low-level easterly jet from the Antarctic continent significantly decreased the air temperature and humidity.Warm air advection at high level brought sufficient vapor from lower latitudes for the snowstorm to develop. The dynamic factors relating to strong snowfall and even the development of a snowstorm were deep cyclonic vorticity at middle and low levels,the configuration of divergence at high level and convergence at low level,and strong vertical uplift.There was an inversion layer in the low-level atmosphere during the later phase of the storm.This vertical structure of cold air at low levels and warm air at high levels may have been important to the longevity of the snowstorm.
The variation of visibility at Great Wall Station(GWS)was analyzed using manual observational data for the period of1986 to 2012.Results show that the frequencies of occurrence of high(≥10 km)and low visibility(0-1 km)are 61.0%and8.0%,respectively.Visibility at GWS shows an evident seasonal variation:The highest visibility between November and March,and the lowest visibility from June to October.Sea fog and precipitation are the main factors for low visibility during summer,whereas frequent adverse weather,such as falling snow,blowing snow,or blizzards,are responsible for low visibility in winter.The frequency of occurrence of low visibility has decreased significantly from 1986 to 2012.Conversely,the frequency of occurrence of high visibility has shown a significant increasing trend,especially during winter.The decreasing tendencies of fog,blowing snow,and snowfall have contributed to the increasing trend of high visibility during winter.Visibility at GWS exhibits significant synoptic-scale(2.1 to 8.3 d),annual,and inter-annual periods(2 a,4.1 a,and 6.9 a to 8.2 a),among which the most significant period is 4.1 a.The visibility observed during 2012 indicates that instrumental observation can be applied in the continuous monitoring of visibility at GWS.
YANG QinghuaYU LejiangWEI LixinZHANG BenzhengMENG Shang
Based on the observed and NCEP reanalysis data from 1985 to 2006, the climate background and synoptic situation of fog at Great Wall Station were analyzed.It is shown that the seasonal variation of fog is controlled by the change of general circulation and local pressure field.Three favorable typical synoptic situations for fog development arc found,the Front-of-A-Depression type,the Saddle-Shaped-Field type and the Passing-Weak-Cyclone type.The first one is the most important situation.Advection cooling fog is dominant at Great Wall Station,but there are other kinds of fog as well.As a result,some helpful principles for local fog forecasting are given.
Sea surface winds from reanalysis(NCEP-2 and ERA-40 datasets)and satellite-based products(QuikSCAT and NCDC blended sea winds)are evaluated using in situ ship measurements from the Chinese National Antarctic Research Expeditions(CHINAREs)from 1989 through 2006,with emphasis on the Southern Ocean(south of 45°S).Compared with ship observations,the reanalysis winds have a positive mean bias(0.32 m·s^(-1)for NCEP-2 and 0.13 m·s^(-1)for ERA-40),and this bias is more pronounced in the Southern Ocean(0.57 m·s^(-1)and 0.45 m·s^(-1),respectively).However,mean biases are negative in the tropics and subtropics.The satellite-based winds also show positive mean biases,larger than those of the reanalysis data.All four wind products overestimate ship wind speed for weak winds(<4 m·s^(-1))but underestimate for strong winds(>10 m·s^(-1)).Differences between the reanalysis and satellite winds are examined to identify regions with large discrepancies.
LI MingYANG QinghuaZHAO JiechenZHANG LinLI ChunhuaMENG Shang
