Stauffer Ryan M, Thompson Anne M, Young George S
Earth System Science Interdisciplinary Center (ESSIC), University of Maryland - College Park, College Park, Maryland, USA.
Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania, USA.
J Geophys Res Atmos. 2016 Feb 16;121(3):1320-1339. doi: 10.1002/2015JD023641. Epub 2016 Jan 10.
Sonde-based climatologies of tropospheric ozone (O) are vital for developing satellite retrieval algorithms and evaluating chemical transport model output. Typical O climatologies average measurements by latitude or region, and season. Recent analysis using self-organizing maps (SOM) to cluster ozonesondes from two tropical sites found clusters of O mixing ratio profiles are an excellent way to capture O variability and link meteorological influences to O profiles. Clusters correspond to distinct meteorological conditions, e.g. convection, subsidence, cloud cover, and transported pollution. Here, the SOM technique is extended to four long-term U.S. sites (Boulder, CO; Huntsville, AL; Trinidad Head, CA; Wallops Island, VA) with 4530 total profiles. Sensitivity tests on k-means algorithm and SOM justify use of 3×3 SOM (nine clusters). At each site, SOM clusters together O profiles with similar tropopause height, 500 hPa height/temperature, and amount of tropospheric and total column O. Cluster means are compared to monthly O climatologies. For all four sites, near-tropopause O is double (over +100 parts per billion by volume; ppbv) the monthly climatological O mixing ratio in three clusters that contain 13 - 16% of profiles, mostly in winter and spring. Large mid-tropospheric deviations from monthly means (-6 ppbv, +7 - 10 ppbv O at 6 km) are found in two of the most populated clusters (combined 36 - 39% of profiles). These two clusters contain distinctly polluted (summer) and clean O (fall-winter, high tropopause) profiles, respectively. As for tropical profiles previously analyzed with SOM, O averages are often poor representations of U.S. O profile statistics.
基于探空仪的对流层臭氧（O）气候学对于开发卫星反演算法和评估化学传输模型输出至关重要。典型的O气候学按纬度、区域和季节对测量数据进行平均。最近使用自组织映射（SOM）对两个热带站点的臭氧探空仪进行聚类分析发现，O混合比廓线的聚类是捕捉O变率并将气象影响与O廓线联系起来的绝佳方法。聚类对应于不同的气象条件，例如对流、下沉、云量和传输的污染。在此，SOM技术扩展到美国的四个长期站点（科罗拉多州博尔德；阿拉巴马州亨茨维尔；加利福尼亚州特立尼达角；弗吉尼亚州沃洛普斯岛），共有4530条廓线。对k均值算法和SOM的敏感性测试证明使用3×3的SOM（九个聚类）是合理的。在每个站点，SOM将具有相似对流层顶高度、500百帕高度/温度以及对流层和总柱O含量的O廓线聚类在一起。将聚类均值与每月的O气候学进行比较。对于所有四个站点，在包含13 - 16%廓线的三个聚类中，近对流层顶的O是每月气候学O混合比的两倍（超过体积分数十亿分之一百；ppbv），主要出现在冬季和春季。在人口最密集的两个聚类（占廓线总数的36 - 39%）中发现了对流层中部与月均值的较大偏差（在6千米处为-6 ppbv，O为+7 - 10 ppbv）。这两个聚类分别包含明显受污染的（夏季）和清洁的O（秋冬，对流层顶较高）廓线。至于先前用SOM分析过的热带廓线，O平均值往往不能很好地代表美国的O廓线统计数据。
