Bureau of Meteorology, Melbourne, Australia.
CSIRO Oceans and Atmosphere, Aspendale, Australia.
Sci Rep. 2022 Jul 8;12(1):11612. doi: 10.1038/s41598-022-14842-2.
Likelihood estimates of extreme winds, including those from tropical cyclones (TCs) at certain locations are used to inform wind load standards for structural design. Here, wind speed average recurrence intervals (ARIs) determined from TC climate data dating back to the 1970s in two quantile-quantile adjusted reanalysis datasets (ERA5 and BARRA [1990]), and best-track observations for context, were compared with Standardized ARIs (AS/NZS) across seven tropical and two subtropical Australian inland coastal regions. The novelty of this work lies in determining TC-wind speed ARIs from a range of datasets that are not typically used to evaluate this metric. Inherent differences between the data used to determine the Standard ARIs (large sample size allow for larger extrapolations; GEV function) and TC data ARIs (smaller sample size and less certain data; the more asymptotic Lognormal/Weibull functions are used) led to the use of different extreme value functions. Results indicated that although these are two distinct ways of determining design wind speeds, when they are considered equivalent, there was a moderate reproduction of the ARI curves with respect to the Standard in both reanalysis datasets, suggesting that similar analyses using climate model products can provide useful information on these types of metrics with some caveats. Trends in TC wind strength affecting coastal Australia were also analyzed, indicating a potential slight downtrend in tropical West coast TC wind strength and slight uptrend for tropical East coast TC wind strength, noting considerable uncertainty given the short time period and limitations of data quality including over longer time periods. Such trends are not only limited to the relationship between TC intensity and anthropogenic warming, but also to regional changes in TC frequency and track direction. This could lead to significant trends emerging in regional Australian TC wind gust strength before several decades of warming have occurred. It is hoped that climate models can provide both longer-term and a more homogenous base for these types of evaluations and subsequent projections with respect to climate change simulations.
在结构设计中,使用特定位置的极端风(包括热带气旋 (TC) 产生的风)的可能性估计来为风荷载标准提供信息。在这里,将从两个经过分位数调整的再分析数据集(ERA5 和 BARRA [1990])中的 20 世纪 70 年代以来的 TC 气候数据确定的风速平均重现期 (ARI) 与标准 ARI(AS/NZS)进行比较,并结合最佳路径观测结果,对七个热带和两个亚热带澳大利亚内陆沿海地区进行了比较。这项工作的新颖之处在于,从一系列通常不用于评估此指标的数据集确定 TC 风速 ARI。确定标准 ARI(较大的样本量允许更大的外推;GEV 函数)和 TC 数据 ARI(较小的样本量和不太确定的数据;使用更渐近的对数正态/威布尔函数)之间存在固有差异,这导致使用了不同的极值函数。结果表明,尽管这是确定设计风速的两种截然不同的方法,但当将它们视为等效时,两个再分析数据集的 ARI 曲线与标准值的复制程度适中,这表明使用气候模型产品进行类似的分析可以提供有关这些类型的指标的有用信息,但需要注意一些限制。还分析了影响澳大利亚沿海地区的 TC 风强度趋势,表明热带西海岸 TC 风强度可能略有下降,热带东海岸 TC 风强度略有上升,考虑到较短的时间跨度和数据质量的限制(包括更长的时间段),存在相当大的不确定性。这些趋势不仅限于 TC 强度与人为变暖之间的关系,还包括 TC 频率和轨迹方向的区域变化。在发生几十年的变暖之前,这可能导致澳大利亚 TC 阵风强度在区域上出现重大趋势。希望气候模型能够为这些类型的评估和随后的气候变化模拟提供更长期和更均匀的基础。