A climatology of the diurnal variations of stratospheric and mesospheric ozone over Bern, Switzerland
A climatology of the diurnal variations of stratospheric and mesospheric ozone over Bern, Switzerland
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瑞士伯尔尼上空平流层和中层臭氧日变化的气候学
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S. Studer
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作者：
S. Studer
设在瑞士伯尔尼（北纬47.95度，东经7.44度）的地面辐射计GROMOS有一个独特的数据集：它获得了从1994年11月至今的臭氧分布图，时间分辨率为30分钟，白天和晚上的质量相同。本文利用GRO-5 MOS卫星17年的观测资料，得到了臭氧日循环的月气候特征。给出了平流层和中间层臭氧的日变化。确定平流层臭氧日周期的特征对于根据卫星观测得出的臭氧层正确趋势估计数十分重要。将GROMOS的臭氧日循环与两个模型进行了比较：全大气社区气候模型（WACCM）和汉堡中性和电离大气模型（HAMMONIA）。从伯尔尼上空的夜间和白天立交桥获得的Aura微波临边探测器（Aura/MLS）臭氧数据也被列入比较。一般来说，观测和模式显示出良好的定性一致性：在中间层下部，GROMOS和模式的白天臭氧比夜间臭氧少约25%（参考时间为22：30-01：30）。在平流层，臭氧在下午达到最大值，比午夜值大几个百分点。重要的是，在合并不同的数据集以得出平流层臭氧的长期趋势时，必须考虑到这种数量级的臭氧日变化。此外，GROMOS和模式表明，平流层臭氧日变化的季节性行为，在2008年白天有一个较大的下午最大值。
The ground-based radiometer GROMOS, stationed in Bern (47.95 ◦ N, 7.44 ◦ E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night-and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GRO-5 MOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The di-urnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized 10 Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night-and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25 % less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches 15 its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging di ff erent data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in