Simulation and evaluation of dust emissions with WRF-Chem (v3.7.1) and its relationship to the changing climate over East Asia from 1980 to 2015

天气研究与预报模式 微粒 环境科学 大气科学 降水 风速 东亚 气候学 风积作用 气候变化 气候模式 中国 气象学 地理 化学 地质学 考古 有机化学 地貌学 海洋学
作者
Hongquan Song,Kai Wang,Yang Zhang,Chaopeng Hong,Shenghui Zhou
出处
期刊:Atmospheric Environment [Elsevier BV]
卷期号:167: 511-522 被引量:41
标识
DOI:10.1016/j.atmosenv.2017.08.051
摘要

Dust particles have been long recognized to affect the atmospheric radiative balance and are influenced by climate change. Impacts of climate change on dust emissions in East Asia, however, are not well understood. In this work, we conduct an evaluation of meteorological variables and dust emissions using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and examine the relationships between dust emissions and meteorological variables (wind speed, precipitation, and temperature) over East Asia during the period of 1980–2015. Model simulated surface meteorological variables compared well overall with surface-based observations, consistent with other WRF studies. Compared to observations, the coarse particulate matter (PM10-2.5) concentrations were underpredicted for most dust source regions of East Asia with a domain-wide mean bias and correlation of −40.2 μg m−3 and 0.5 against observations, respectively. Dust particulate concentrations simulated by WRF-Chem were found to reproduce the observed spatial variability in surface dust particulates over East Asia. The average annual dust emission (0 < r < 20 μm) is around 67.4 Tg yr−1 and the dust emission increased with the trend of 0.173 Tg yr−1 (R2 = 0.03, P = 0.32) in China and Mongolia over the past four decades. The spatial and temporal variations of dust emissions in China and Mongolia indicate that the annual dust flux has increased in desert areas of China and Mongolia, but decreased in most Gobi regions of China. Dust emission is significantly positively and negatively correlated with wind velocity and precipitation at the regional scale. Spatial patterns of seasonal correlations between dust flux and climate varies greatly during the period of 1980–2015.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
学好玩好才是真的好完成签到 ,获得积分10
刚刚
4秒前
打打应助曾经若南采纳,获得10
5秒前
5秒前
故意的白昼完成签到 ,获得积分10
6秒前
英姑应助丁丁采纳,获得10
6秒前
梦里的大子刊完成签到 ,获得积分10
8秒前
snowflake发布了新的文献求助10
8秒前
YEEze发布了新的文献求助10
11秒前
12秒前
王小敏敏儿完成签到,获得积分10
12秒前
chuang发布了新的文献求助10
14秒前
14秒前
16秒前
小肥肉发布了新的文献求助10
17秒前
我是树完成签到,获得积分20
19秒前
19秒前
TomasLiu完成签到,获得积分10
20秒前
21秒前
23秒前
SERINA应助kiki采纳,获得10
23秒前
23秒前
23秒前
伽古拉40k完成签到,获得积分10
24秒前
既温柔发布了新的文献求助10
25秒前
万能图书馆应助徐蹇采纳,获得30
25秒前
25秒前
26秒前
Arain456完成签到 ,获得积分10
26秒前
酷酷幻灵完成签到 ,获得积分10
26秒前
zgy527948846完成签到,获得积分10
27秒前
华凯完成签到,获得积分10
27秒前
28秒前
YEEze发布了新的文献求助10
28秒前
liaomr发布了新的文献求助10
29秒前
29秒前
好嘞完成签到 ,获得积分10
29秒前
Lucas应助ruqinmq采纳,获得10
30秒前
丁丁发布了新的文献求助10
30秒前
31秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359701
求助须知:如何正确求助?哪些是违规求助? 8173732
关于积分的说明 17215390
捐赠科研通 5414697
什么是DOI,文献DOI怎么找? 2865615
邀请新用户注册赠送积分活动 1842916
关于科研通互助平台的介绍 1691124