Long- term dynamics of OH* temperatures over central Europe: trends and solar correlations
Long- term dynamics of OH* temperatures over central Europe: trends and solar correlations
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DOI：
10.5194/acp-16-15033-2016
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发表时间：
2016-12-06
影响因子：
6.3
通讯作者：
Wintel, Johannes
中科院分区：
文献类型：
--
作者：
Kalicinsky, Christoph;Knieling, Peter;Wintel, Johannes
我们提出了在1988年至2015年的时间间隔内，在Wuppertal（51度N，7度E）的地基红外P分支光谱仪（GRIPS）的测量中，中层顶区域的年平均OH* 温度的分析。这项新研究使用的温度时间序列比最新的长期动态分析长7年。这一额外的观测时间导致观测到的长期动力学特性的变化。我们使用太阳射电通量F10.7 cm（11年太阳活动周期）和时间进行多元线性回归来描述温度演变。分析得出线性趋势为（-0.089 +/- 0.055）Kyear（-1），对太阳活动的敏感度为（4.2 +/- 0.9）K（100 SFU）（-1）（r（2）= 0.6）。然而，一个线性趋势与11年的太阳周期相结合，不足以解释所有观测到的长期动态。事实上，我们发现在2008年中期的温度时间序列中有一个明显的趋势突破。在这一转折点之前，有一个明显的负线性趋势，为（-0.24 +/- 0.07）千年-（1），2008年之后，线性趋势转为正值，为（0.64 +/- 0.33）千年（-1）。这种明显的趋势突变也可以用长周期振荡来描述。一种可能性是使用22年的太阳周期来描述太阳磁场的逆转（黑尔周期）。以太阳射电流量和太阳极区磁场为参数进行多元线性回归，得到回归系数C-solar =（5.0 ± 0.7）K（100 SFU）（-1）和C-hale =（1.8 ± 0.5）K（100 μ T）（-1）（r（2）= 0.71）。描述OH* 温度时间序列的第二种方法是使用太阳射电通量和振荡。最小二乘拟合得到对太阳活动的灵敏度为（4.1 +/- 0.8）K（100 SFU）（-1），周期P =（24.8 +/- 3.3）年，振荡幅度C sin D（1.95 +/- 0.44）K（r（2）= 0.78）。这里最重要的发现是，使用这种描述不再需要额外的线性趋势。此外，随着这25年振荡的知识，在这方面的线性趋势，并在以前的研究theWuppertal数据系列可以重现拟合线的相应部分（时间间隔）的振荡。这实际上意味着，根据分析的时间间隔，可以观察到关于幅度和符号的完全不同的线性趋势。这一事实对于不同观测和模型模拟之间的任何比较都至关重要。
We present the analysis of annual average OH* temperatures in the mesopause region derived from measurements of the Ground-based Infrared P-branch Spectrometer (GRIPS) atWuppertal (51 degrees N, 7 degrees E) in the time interval 1988 to 2015. The new study uses a temperature time series which is 7 years longer than that used for the latest analysis regarding the long-term dynamics. This additional observation time leads to a change in characterisation of the observed longterm dynamics.We perform a multiple linear regression using the solar radio flux F10.7 cm (11-year cycle of solar activity) and time to describe the temperature evolution. The analysis leads to a linear trend of (-0.089 +/- 0.055) Kyear(-1) and a sensitivity to the solar activity of (4.2 +/- 0.9) K (100SFU)(-1) (r(2) of fit 0.6). However, one linear trend in combination with the 11-year solar cycle is not sufficient to explain all observed long-term dynamics. In fact, we find a clear trend break in the temperature time series in the middle of 2008. Before this break point there is an explicit negative linear trend of (-0.24 +/- 0.07) Kyear-(1), and after 2008 the linear trend turns positive with a value of (0.64 +/- 0.33) Kyear(-1). This apparent trend break can also be described using a long periodic oscillation. One possibility is to use the 22-year solar cycle that describes the reversal of the solar magnetic field (Hale cycle). A multiple linear regression using the solar radio flux and the solar polar magnetic field as parameters leads to the regression coefficients C-solar = (5.0 +/- 0.7) K (100SFU)(-1) and C-hale = (1.8 +/- 0.5) K (100 mu T )(-1) (r(2) = 0.71). The second way of describing the OH* temperature time series is to use the solar radio flux and an oscillation. A leastsquare fit leads to a sensitivity to the solar activity of (4.1 +/- 0.8) K (100SFU)(-1), a period P = (24.8 +/- 3.3) years, and an amplitude C sin D (1.95 +/- 0.44) K of the oscillation (r(2) = 0.78). The most important finding here is that using this description an additional linear trend is no longer needed. Moreover, with the knowledge of this 25-year oscillation the linear trends derived in this and in a former study of theWuppertal data series can be reproduced by just fitting a line to the corresponding part (time interval) of the oscillation. This actually means that, depending on the analysed time interval, completely different linear trends with respect to magnitude and sign can be observed. This fact is of essential importance for any comparison between different observations and model simulations.