Full
Outline
The present study took the two typical haze/fog low visibility episodes in Tianjin as a point of departure for the following investigation, developed data assimilation methods applicable to visibility observations, in order to improve the numerical forecast effect of visibility through the simulation optimization of PM2.5 concentration, relative humidity and fog water content. Theresults showed that the visibility change of typical haze episode was primarily influenced by PM2.5 concentration, the minimum value of visibilitywas approximately 1km, with the daily change about 2~3km in the result of relative humidity change. The relative humidity of the haze-fog mixing episode was high, and visibility was lower than 50min localities due to the significant influence of fog during nighttime. The typical characteristic of the haze-fog episode were largedaily change and extreme value being low in visibility. The simulation of haze-fog low visibilitywas significantly enhanced with assimilation of visibility observation, root mean square error of the two episodes reduced from 7km and 4km to approximately 2km. Furthermore, the simulation deviation was corrected in time with 6-hour interval assimilation, with an enhancement effect observed to be more pronounced during specific time periods. Through the assimilation to achieve the optimization of the PM2.5 concentration and the relative humidity simulation, the deviation of the haze visibility simulation was reduced by a maximum of 6~8km.By adding fog water content correction, combined with relative humidity assimilation improvement, the underestimate of fog water content was reduced during nocturnal periods, the visibility simulation deviation was reduced from 1~2km to 300~500m and the degree and range of the low visibility was significantly improved. One-month simulation showed that the root mean square error of visibility below 10 km was reduced from 4.4 km to 3.2 km.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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