Development and Application of a Novel Snow Peak Sighting Forecast System over Chengdu

Author:

Lu Chengwei12,Chen Ting3,Yang Xinyue2,Tan Qinwen2,Kang Xue4,Zhang Tianyue2,Zhou Zihang12,Yang Fumo1,Chen Xi2,Wang Yuancheng2

Affiliation:

1. College of Architecture and Environment, Sichuan University, Chengdu 610065, China

2. Institute of Environmental Forecast, Chengdu Academy of Environmental Sciences, Chengdu 610072, China

3. College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China

4. Chengdu Meteorological Service Center, Chengdu Meteorological Bureau, Chengdu 610072, China

Abstract

As air quality has improved rapidly in recent years, the public has become more interested in whether a famous snow peak, Yaomei Feng on the Tibetan Plateau, can be seen from Chengdu, a megacity located on the western plain of the Sichuan Basin, east of the plateau. Therefore, a threshold-method-based forecasting system for snow peak sighting was developed in this study. Variables from numerical models, including cloud–water mixing ratio, cloud cover over snow peak, water mixing ratio, PM2.5 concentration, and ground solar radiation, were used in the snow peak sighting forecast system. Terrain occlusion rate of each model grid was calculated. Monte Carlo simulations were applied for threshold determination. A WRF-CMAQ hindcast was conducted for 2020, owing to insufficient observation data, hindcast results on the snow peak sighting were compared with posts collected from social media. Estimations showed that the snow peak sighting forecast system performed well in reflecting the monthly trend of snow peak sightings, and the hindcast results matched the daily observations, especially from May to August. Accuracy of the snow peak sighting forecast model was 78.9%, recall value was 57.1%, and precision was 24.4%.

Funder

the Key Research Support Plan of Chengdu Science and Technology Bureau

National Key R&D Program of China

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

Reference44 articles.

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