Model sensitivity in predicting extreme precipitation events in urban areas: A case study over Beijing

IF 4.5 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Research Pub Date : 2024-10-09 DOI:10.1016/j.atmosres.2024.107719
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Abstract

Understanding and forecasting the spatial and temporal distributions of extreme precipitation over urban areas is crucial for effective planning and mitigation efforts. However, this task remains challenging as accurate forecasting depends on properly representing urban surfacees and their interactions with the planetary boundary layer (PBL). We examined the hindcast of an extreme precipitation event over Beijing on 21–22 July 2012. The primary focus was assessing its sensitivity to two widely used PBL parameterizations (MYJ and YSU), two urban parameterizations (SLUCM and BEP_BEM), and two different land-use and land-cover (LULC) datasets.
Sensitivity experiments were initialized at different times to explore the model dependence on initial conditions. The analyses were conducted over three selected regions: the entire model domain covering the Beijing metropolitan area, an upwind region of Beijing, and the entire urban area of Beijing. The results show that the MYJ PBL scheme performs better than the YSU PBL scheme in capturing near-surface air temperature as well as the location and timing of the heaviest precipitation. The variability in simulated precipitation among the chosen PBL schemes is lower compared to that among different time of initializations. The LULC impacted the spatial distribution of precipitation but its effect on the amount of precipitation was minimal. Overall, using a combination of the MYJ PBL scheme, SLUCM urban parameterization, and locally-enhanced Beijing LULC, and initializing the model simulations at 0000 UTC July 20, 2012, demonstrated superior performance in capturing precipitation levels, despite some spatial discrepancies in the precipitation distribution. The performance of BEP_BEM urban parameterization is similar to SLUCM across various factors such as average rain rate, maximum rain rate, and rain volume. These findings offer valuable insights towards better simulations of extreme precipitation and flooding in rapidly urbanizing areas such as Beijing.
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预测城市地区极端降水事件的模型敏感性:北京上空的案例研究
了解和预报城市地区极端降水的时空分布对有效规划和减灾工作至关重要。然而,这项任务仍然具有挑战性,因为准确的预报取决于对城市表面及其与行星边界层(PBL)之间相互作用的正确描述。我们研究了 2012 年 7 月 21-22 日北京极端降水事件的后预报。主要重点是评估其对两种广泛使用的 PBL 参数化(MYJ 和 YSU)、两种城市参数化(SLUCM 和 BEP_BEM)以及两种不同的土地利用和土地覆盖(LULC)数据集的敏感性。对三个选定区域进行了分析:覆盖北京大都市区的整个模型域、北京的一个上风区域和整个北京城区。结果表明,MYJ PBL 方案在捕捉近地面气温以及最强降水的位置和时间方面优于 YSU PBL 方案。与不同初始化时间的降水量相比,所选 PBL 方案的模拟降水量变化较小。LULC 对降水的空间分布有影响,但对降水量的影响很小。总的来说,使用 MYJ PBL 方案、SLUCM 城市参数化和本地增强的北京 LULC,并在 2012 年 7 月 20 日 0000 UTC 时初始化模式模拟,尽管降水量分布在空间上存在一些差异,但在捕捉降水量方面表现优异。在平均降雨率、最大降雨率和雨量等各种因素上,BEP_BEM 城市参数化的性能与 SLUCM 相似。这些发现为更好地模拟北京等快速城市化地区的极端降水和洪水提供了宝贵的见解。
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来源期刊
Atmospheric Research
Atmospheric Research 地学-气象与大气科学
CiteScore
9.40
自引率
10.90%
发文量
460
审稿时长
47 days
期刊介绍: The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.
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