Diagnostic analysis has been performed to study the characteristics of snow cover and contributing factor of temperature in an extreme rain-snow event over Shandong Province during 5 -7 January 2020 by hourly precipitation measurement instrument, automatic weather stationintensive snow depth observation data and NCEP/NCAR 1°×1° reanalysis data.Main results are as follows: (1) The rain-snow process is an extreme weather event caused by Jianghuai cyclone with weak cold advection and severe precipitation.So snow depth has presented a challenge to forecasters.(2)The averaged snow-liquid ratio in Shandong Province is 0.46 cm·mm-1, less than that average of all snowstorms produced by Jianghuai cyclone over the past 20 years.(3) Snow depth is related to configuration of temperature, relative humidity and vertical velocity in upper level.The environment temperature at the level where maximum ascending motion accompanied relative humidity larger than 90% is favorable to branch ice crystal growth, while that with large snow depth and snow-liquid ratio is favorable to hollow columnar ice crystal growth.Temperature under the cloud higher than 0 ℃ can decrease snow depth.(4) The relationship between surface temperature and snow depth shows that obvious snow cover can form with the temperature of most stations lower than 0.5 ℃ and ground surface temperature at 0 cm lower than 0.4 ℃.The impact of ground surface temperature occurs before snow cover forms.Snow surface temperature maintains about 0 ℃ in 2 h prior to or after the formation of obvious snow cover, similar to air temperature in other time.(5) Generally, snow-liquid ratio decreases with air temperature increasing, with air temperature lower than 0.4 ℃ when the snow-liquid ratio is larger than 0.5 cm·mm-1 during snowfall.The analysis of this snowstorm event revealed that forecasting snow depth and snow-liquid ratio need to consider various meteorological conditions.
Chengfang YANG
,
Yu ZHAO
. Study on Snow Cover Characteristic of Extreme Rain-snow Event based on Intensive Observation Data[J]. Plateau Meteorology, 2021
, 40(4)
: 853
-865
.
DOI: 10.7522/j.issn.1000-0534.2020.00072
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