太阳辐射对热层和电离层变化性的影响
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摘要
波长小于400 nm的太阳紫外辐射(UV)是高层大气物理过程的一个重要能量源。太阳紫外辐射光子在传播过程中通过分子的光致离解、分子和原子的光化电离、以及光致激发(包括共振散射)被行星大气层吸收,同时遍及和穿过日光层,从而影响整个太阳系空间。本文利用TIMED SEE观测的太阳辐射数据,以及常用的太阳活动指数,如F10.7和Mg II,结合CHAMP卫星观测的热层密度数据和DMSP卫星观测的顶部电离层离子密度数据,系统地研究了太阳辐射对热层和电离层变化性的影响。
首先,本文研究了2002-2004期间太阳辐射流量的变化对410 km高度热层密度的影响。分析结果表明,密度与不同太阳辐射特征谱线和不同波段的太阳辐射流量之间的相关性显示出不同的特征。密度与除了低层色球辐射线O I (130.4 nm)以外的其它所选太阳辐射流量之间的相关性都相当好。对短期变化(≤27天)而言,在所选太阳活动指数中,Mg II,EUV (30-120 nm)和F10.7与密度的相关性最好。无论是对长期变化(> 27天)而言,还是对短期变化而言,从低纬到高纬的线性相关系数都呈现出下降趋势。同时利用多种太阳活动指数能够非常有效地拟合密度的变化,即能够解释71%的密度的变化。文中所用的太阳活动指数包括时间延迟为1天的F10.7和SEUV(EUV 30-120 nm指数),以及时间延迟为5天的SFUV(FUV 120-193 nm指数)。在我们的回归方程中,SEUV对密度变化的贡献最大(40%),其次是F10.7的贡献32%和SFUV的贡献28%。此外,在2003年太阳辐射和密度变化中都存在一个显著的27天周期(太阳自转周期);在2004年除了存在27天周期以外,还存在一个显著的54.4天周期(太阳自转周期的两倍)。但是软X-ray和FUV在2004并没有显著的54天周期,尽管它们与密度之间的相关性很好。Ap指数在2004也显示出54天周期,这样一来,地磁活动和太阳活动一起影响密度变化中的54天周期。我们比较了CHAMP观测密度与NRLMSISE00,DTM-2000和JB2006模式的预测值,结果表明这些模式都低估了热层密度对太阳自转活动的响应。
其次,本文分析了2002-2005期间太阳辐射流量变化对赤道顶部电离层总离子密度Ni的影响。分析结果表明,Ni与不同波段的太阳辐射之间的相关性显著不同。对长期变化而言,XUV (0-35 nm)和EUV (115-130 nm)与Ni之间的相关性较好;但是对短期变化而言,EUV (35-115 nm)与Ni之间的相关性更好。进一步的偏相关分析结果表明,Ni的长期变化主要受XUV (0-35 nm)和EUV (35-115 nm)的影响,其中受XUV (0-35 nm)的影响更大一些;短期变化主要受EUV (35-115 nm)的影响。此外,在2003年太阳辐射和Ni变化中都存在一个显著的27天周期;在2004除了存在27天周期以外,还存在一个显著的54天周期。
最后,考虑到太阳辐射能量输入是引起热层密度“半年变化”的一个重要驱动源。本文分析了2002-2005年期间400公里高度的热层密度的年内变化。这里的年内变化,通常指半年变化,其主要特征包括显著的纬度结构、半球不对称性、年际变化。年最大值与年最小值之间差值的年际变化为60%;年最大值与年最小值出现的时间的年际变化大概是20-40天。年内变化的年谐波成份,也就是年变化,半年变化,三分之一年变化,四分之一年变化,从2002年到2005年呈现出下降趋势,即与太阳活动的下降趋势是相关的。此外,这些年谐波的变化也与地磁活动相关。可见,太阳EUV辐射与焦耳加热是导致了热层大气密度的年内变化的主要因素。最近的热层经验模式并不能预测观测数据中显示出来的年谐波成份的纬度依赖性。此外,谐波成份中存在的纬度变化和年际变化并不能很好地用太阳活动和地磁活动指数拟合。这可能与其它一些影响因素有关,比如说在匀质层顶高度的季节-纬度变化,电离层藕合过程等都可能影响这里描述的年内变化,我们的研究结果提供了新的数据,这将挑战和验证热层-电离层大气环流模型中给出的热层年内变化,同时也有助于我们理解各种影响因素对年内变化的相对贡献。而且,我们建议用“年内变化”(“intra-annual variation”)一词来描述热层和电离层参数中可以用年变化,半年变化,三分之一年变化,四分之一年变化来表征的各种变化;“半年变化”一词仅限于描述周期为6个月的正弦变化。另外,我们还建议用“季节内变化”(“intra-seasonal variation”)来描述更短周期的各种变化,也就是比四分之一年周期更短的各种变化。
Solar ultraviolet (UV) radiation at wavelengths less than 400 nm is an important source of energy for aeronomic processes throughout the solar system. Solar UV photons are absorbed in planetary atmospheres, as well as throughout the heliosphere, via photodissociation of molecules, photoionization of molecules and atoms, and photoexcitation toexcitation including resonance scattering. In this paper, the solar irradiances data measured by TIMED SEE, as well as the solar proxies such as F10.7 and Mg II, thermosphere neutral density of CHAMP measurements and topside ionospheric plasmas densities from DMSP, are used to analyze solar irradiance effects on the variabilities of the thermosphere and the ionosphere.
First, thermosphere densities near 410 km altitude are analyzed for solar irradiance variability effects during the period 2002-2004. Correlations between the densities and the solar irradiances for different spectral lines and wavelength ranges reveal significantly different characteristics. The density correlates remarkably well with all the selected solar irradiances except the lower chromospheric O I (130.4 nm) emission. Among the chosen solar proxies, the Mg II core-to-wing ratio index, EUV (30-120 nm) and F10.7 show the highest correlations with the density for short-term (< ~27 days) variations. For both long- (> ~27 days) and short-term variations, linear correlation coefficients exhibit a decreasing trend from low latitudes towards high latitudes. The density variability can be effectively modeled (capturing 71% of the variance) using multiple solar irradiance indices, including F10.7, SEUV (the EUV 30-120 nm index), and SFUV (the FUV 120-193 nm index), in which a lag time of 1 day was used for both F10.7 and SEUV, and 5 days for SFUV. In our regression formulation SEUV has the largest contribution to the density variation (40%), with the F10.7 having the next largest contribution (32%) and SFUV accounting for the rest (28%). Furthermore, a pronounced period of about 27.2 days (mean period of the Sun's rotation) is present in both density and solar irradiance data of 2003 and 2004, and a pronounced period of about 54.4 days (doubled period of the solar rotation) is also revealed in 2004. However, soft X-ray and FUV irradiances did not present a pronounced 54.4 day period in 2004, in spite of their high correlation with the densities. The Ap index also shows 54-day periodicities in 2004, and magnetic activity, together with solar irradiance, affects the 54-day variation in density significantly. In addition, NRLMSISE00, DTM-2000 and JB2006 model predictions are compared with density measurements from CHAMP to assess their accuracy, and the results show that these models underestimate the response of the thermosphere to variations induced by solar rotation.
Next, the equatorial topside ionospheric plasmas densities Ni are analyzed for solar irradiance variability effects during the period 2002-2005. Linear correlations between Ni and the solar irradiances for different wavelength ranges reveal significantly different characteristics. XUV (0-35 nm) and EUV (115-130 nm) show higher correlation with Ni for the long-term variations, whereas EUV (35-115 nm) show higher correlation for the short-term variations. Moreover, partial correlation analysis shows that the long-term variations of Ni are affected by both XUV (0-35 nm) and EUV (35-115 nm), whereas XUV (0-35 nm) play a more important role; the short-term variations of Ni are mostly affected by EUV (35-115 nm). Furthermore, a pronounced period of about 27 days is present in both Ni and solar irradiance data of 2003 and 2004, and a pronounced period of about 54 days is also revealed in 2004.
Finally, prompted by previous studies that have suggested solar EUV radiation as a means of driving the semiannual variation, we investigate the intra-annual variation in thermosphere neutral density near 400 km during 2002-2005. The intra-annual variation, commonly referred to as the‘semiannual variation’, is characterized by significant latitude structure, hemispheric asymmetries, and inter-annual variability. The magnitude of the maximum yearly difference, from the yearly minimum to the yearly maximum, varies by as much as 60% from year to year, and the phases of the minima and maxima also change by 20-40 days from year to year. Each annual harmonic of the intra-annual variation, namely, annual, semiannual, ter-annual and quatra-annual, exhibits a decreasing trend from 2002 through 2005 that is correlated with the decline in solar activity. In addition, some variations in these harmonics are correlated with geomagnetic activity, as represented by the daily mean value of Kp. Recent empirical models of the thermosphere are found to be deficient in capturing most of the latitude dependencies discovered in our data. In addition, the solar flux and geomagnetic activity proxies that we have employed do not capture some latitude and inter-annual variations detected in our data. It is possible that these variations are partly due to other effects, such as seasonal-latitudinal variations in turbopause altitude (and hence O/N2 composition) and ionosphere coupling processes that remain to be discovered in the context of influencing the intra-annual variations depicted here. Our results provide a new dataset to challenge and validate thermosphere-ionosphere general circulation models that seek to delineate the thermosphere intra-annual variation and to understand the various competing mechanisms that may contribute to its existence and variability. We furthermore suggest that the term“intra-annual”variation be adopted to describe the variability in thermosphere and ionosphere parameters that is well-captured through a superposition of annual, semiannual, ter-annual, and quatra-annual harmonic terms, and that“semiannual’be used strictly in reference to a pure 6-monthly sinusoidal variation. Moreover, we propose the term“intra-seasonal”to refer to those shorter-term variations that arise as residuals from the above Fourier representation.
首先,本文研究了2002-2004期间太阳辐射流量的变化对410 km高度热层密度的影响。分析结果表明,密度与不同太阳辐射特征谱线和不同波段的太阳辐射流量之间的相关性显示出不同的特征。密度与除了低层色球辐射线O I (130.4 nm)以外的其它所选太阳辐射流量之间的相关性都相当好。对短期变化(≤27天)而言,在所选太阳活动指数中,Mg II,EUV (30-120 nm)和F10.7与密度的相关性最好。无论是对长期变化(> 27天)而言,还是对短期变化而言,从低纬到高纬的线性相关系数都呈现出下降趋势。同时利用多种太阳活动指数能够非常有效地拟合密度的变化,即能够解释71%的密度的变化。文中所用的太阳活动指数包括时间延迟为1天的F10.7和SEUV(EUV 30-120 nm指数),以及时间延迟为5天的SFUV(FUV 120-193 nm指数)。在我们的回归方程中,SEUV对密度变化的贡献最大(40%),其次是F10.7的贡献32%和SFUV的贡献28%。此外,在2003年太阳辐射和密度变化中都存在一个显著的27天周期(太阳自转周期);在2004年除了存在27天周期以外,还存在一个显著的54.4天周期(太阳自转周期的两倍)。但是软X-ray和FUV在2004并没有显著的54天周期,尽管它们与密度之间的相关性很好。Ap指数在2004也显示出54天周期,这样一来,地磁活动和太阳活动一起影响密度变化中的54天周期。我们比较了CHAMP观测密度与NRLMSISE00,DTM-2000和JB2006模式的预测值,结果表明这些模式都低估了热层密度对太阳自转活动的响应。
其次,本文分析了2002-2005期间太阳辐射流量变化对赤道顶部电离层总离子密度Ni的影响。分析结果表明,Ni与不同波段的太阳辐射之间的相关性显著不同。对长期变化而言,XUV (0-35 nm)和EUV (115-130 nm)与Ni之间的相关性较好;但是对短期变化而言,EUV (35-115 nm)与Ni之间的相关性更好。进一步的偏相关分析结果表明,Ni的长期变化主要受XUV (0-35 nm)和EUV (35-115 nm)的影响,其中受XUV (0-35 nm)的影响更大一些;短期变化主要受EUV (35-115 nm)的影响。此外,在2003年太阳辐射和Ni变化中都存在一个显著的27天周期;在2004除了存在27天周期以外,还存在一个显著的54天周期。
最后,考虑到太阳辐射能量输入是引起热层密度“半年变化”的一个重要驱动源。本文分析了2002-2005年期间400公里高度的热层密度的年内变化。这里的年内变化,通常指半年变化,其主要特征包括显著的纬度结构、半球不对称性、年际变化。年最大值与年最小值之间差值的年际变化为60%;年最大值与年最小值出现的时间的年际变化大概是20-40天。年内变化的年谐波成份,也就是年变化,半年变化,三分之一年变化,四分之一年变化,从2002年到2005年呈现出下降趋势,即与太阳活动的下降趋势是相关的。此外,这些年谐波的变化也与地磁活动相关。可见,太阳EUV辐射与焦耳加热是导致了热层大气密度的年内变化的主要因素。最近的热层经验模式并不能预测观测数据中显示出来的年谐波成份的纬度依赖性。此外,谐波成份中存在的纬度变化和年际变化并不能很好地用太阳活动和地磁活动指数拟合。这可能与其它一些影响因素有关,比如说在匀质层顶高度的季节-纬度变化,电离层藕合过程等都可能影响这里描述的年内变化,我们的研究结果提供了新的数据,这将挑战和验证热层-电离层大气环流模型中给出的热层年内变化,同时也有助于我们理解各种影响因素对年内变化的相对贡献。而且,我们建议用“年内变化”(“intra-annual variation”)一词来描述热层和电离层参数中可以用年变化,半年变化,三分之一年变化,四分之一年变化来表征的各种变化;“半年变化”一词仅限于描述周期为6个月的正弦变化。另外,我们还建议用“季节内变化”(“intra-seasonal variation”)来描述更短周期的各种变化,也就是比四分之一年周期更短的各种变化。
Solar ultraviolet (UV) radiation at wavelengths less than 400 nm is an important source of energy for aeronomic processes throughout the solar system. Solar UV photons are absorbed in planetary atmospheres, as well as throughout the heliosphere, via photodissociation of molecules, photoionization of molecules and atoms, and photoexcitation toexcitation including resonance scattering. In this paper, the solar irradiances data measured by TIMED SEE, as well as the solar proxies such as F10.7 and Mg II, thermosphere neutral density of CHAMP measurements and topside ionospheric plasmas densities from DMSP, are used to analyze solar irradiance effects on the variabilities of the thermosphere and the ionosphere.
First, thermosphere densities near 410 km altitude are analyzed for solar irradiance variability effects during the period 2002-2004. Correlations between the densities and the solar irradiances for different spectral lines and wavelength ranges reveal significantly different characteristics. The density correlates remarkably well with all the selected solar irradiances except the lower chromospheric O I (130.4 nm) emission. Among the chosen solar proxies, the Mg II core-to-wing ratio index, EUV (30-120 nm) and F10.7 show the highest correlations with the density for short-term (< ~27 days) variations. For both long- (> ~27 days) and short-term variations, linear correlation coefficients exhibit a decreasing trend from low latitudes towards high latitudes. The density variability can be effectively modeled (capturing 71% of the variance) using multiple solar irradiance indices, including F10.7, SEUV (the EUV 30-120 nm index), and SFUV (the FUV 120-193 nm index), in which a lag time of 1 day was used for both F10.7 and SEUV, and 5 days for SFUV. In our regression formulation SEUV has the largest contribution to the density variation (40%), with the F10.7 having the next largest contribution (32%) and SFUV accounting for the rest (28%). Furthermore, a pronounced period of about 27.2 days (mean period of the Sun's rotation) is present in both density and solar irradiance data of 2003 and 2004, and a pronounced period of about 54.4 days (doubled period of the solar rotation) is also revealed in 2004. However, soft X-ray and FUV irradiances did not present a pronounced 54.4 day period in 2004, in spite of their high correlation with the densities. The Ap index also shows 54-day periodicities in 2004, and magnetic activity, together with solar irradiance, affects the 54-day variation in density significantly. In addition, NRLMSISE00, DTM-2000 and JB2006 model predictions are compared with density measurements from CHAMP to assess their accuracy, and the results show that these models underestimate the response of the thermosphere to variations induced by solar rotation.
Next, the equatorial topside ionospheric plasmas densities Ni are analyzed for solar irradiance variability effects during the period 2002-2005. Linear correlations between Ni and the solar irradiances for different wavelength ranges reveal significantly different characteristics. XUV (0-35 nm) and EUV (115-130 nm) show higher correlation with Ni for the long-term variations, whereas EUV (35-115 nm) show higher correlation for the short-term variations. Moreover, partial correlation analysis shows that the long-term variations of Ni are affected by both XUV (0-35 nm) and EUV (35-115 nm), whereas XUV (0-35 nm) play a more important role; the short-term variations of Ni are mostly affected by EUV (35-115 nm). Furthermore, a pronounced period of about 27 days is present in both Ni and solar irradiance data of 2003 and 2004, and a pronounced period of about 54 days is also revealed in 2004.
Finally, prompted by previous studies that have suggested solar EUV radiation as a means of driving the semiannual variation, we investigate the intra-annual variation in thermosphere neutral density near 400 km during 2002-2005. The intra-annual variation, commonly referred to as the‘semiannual variation’, is characterized by significant latitude structure, hemispheric asymmetries, and inter-annual variability. The magnitude of the maximum yearly difference, from the yearly minimum to the yearly maximum, varies by as much as 60% from year to year, and the phases of the minima and maxima also change by 20-40 days from year to year. Each annual harmonic of the intra-annual variation, namely, annual, semiannual, ter-annual and quatra-annual, exhibits a decreasing trend from 2002 through 2005 that is correlated with the decline in solar activity. In addition, some variations in these harmonics are correlated with geomagnetic activity, as represented by the daily mean value of Kp. Recent empirical models of the thermosphere are found to be deficient in capturing most of the latitude dependencies discovered in our data. In addition, the solar flux and geomagnetic activity proxies that we have employed do not capture some latitude and inter-annual variations detected in our data. It is possible that these variations are partly due to other effects, such as seasonal-latitudinal variations in turbopause altitude (and hence O/N2 composition) and ionosphere coupling processes that remain to be discovered in the context of influencing the intra-annual variations depicted here. Our results provide a new dataset to challenge and validate thermosphere-ionosphere general circulation models that seek to delineate the thermosphere intra-annual variation and to understand the various competing mechanisms that may contribute to its existence and variability. We furthermore suggest that the term“intra-annual”variation be adopted to describe the variability in thermosphere and ionosphere parameters that is well-captured through a superposition of annual, semiannual, ter-annual, and quatra-annual harmonic terms, and that“semiannual’be used strictly in reference to a pure 6-monthly sinusoidal variation. Moreover, we propose the term“intra-seasonal”to refer to those shorter-term variations that arise as residuals from the above Fourier representation.
引文
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