Recent advances in upper atmospheric structure

A possible quantitative explanation of the semi-annual variation in thermospheric density has been obtained in terms of a semi-annual variation in the computed globally averaged vertical energy carried by propagating tides from the lower and middle atmosphere into the thermosphere. The effect is primarily due to seasonal changes in the distribution of water vapor and in the solar declination angle and Sun-Earth distance. An MSIS-83 empirical model of the thermosphere, representing a revision of the earlier MSIS models, has been prepared. The database used covers a wider range of solar activity than previous models and an improved magnetic storm representation is included. Atomic oxygen profiles in the 100 to 160 km altitude region of the auroral thermosphere have been recalculated from measured quenching of N₂(A³∑_u⁺) using the latest laboratory rates and the results are in good agreement with the mean CIRA 1972 profile. A new empirical model of thermospheric variations with geomagnetic activity has been developed incorporating variations with local magnetic time, latitude dependent terms which can vary with the magnitude of the geomagnetic disturbance, and an altitude dependent expression for the equatorial wave. A new index ML, derived from the AL index, has been developed that appears to have promise to represent the variations of thermospheric species with geomagnetic activity. Satellite measured values of solar UV flux, ground-based observations of CaK plages, sunspot numbers and 10.7 cm solar radio flux have been analyzed for temporal variations. Some differences have been identified and the significance to empirical and theoretical upper atmosphere models is discussed.     

Chapman函数在实际模式大气中的数值积分计算

本文对Chapman阳光掠射函数[Ch(z_p,χ)]进行了数值积分,求得了其在实际模式大气中随观测高度z_p及天顶角χ的变化.计算并讨论了低热层高温度梯度、分子与湍流扩散、重力场及太阳活动对 Ch(z_p,χ)的影响.结果表明,在150 km以下,Ch(z_p,χ)与前人用等标高模式及等标高梯度模式的计算结果差别较大.其中高温度梯度的影响起主导作用.特别是太阳活动对Chapman函数影响较显著,高年与低年之间可变化10—40％(在大天顶角时),这有可能推动热层大气中辐射-光化学-动力学耦合关系的变化.     

Properties of the mesosphere and thermosphere and comparison with CIRA 72

Exospheric temperatures of several reference atmosphere are reviewed and a recommendation is made for the exospheric temperature of a proposed mean CIRA. One of the deficiencies of CIRA 72 and other present thermospheric models is the representation of density changes with geomagnetic activity. This deficiency is illustrated with samples of data. The data show the effects of geomagnetic activity, particle precipitation, a solar proton event, and gravity waves. An empirical model developed from the unique AFGL satellite density data bank using multiple linear regression is reviewed. The present model is for low to moderate solar flux and quiet geomagnetic conditions, but it is planned to extend the model to active conditions. Good progress has been made since CIRA 72 was specified in our knowledge and understanding of the properties of the lower thermosphere, although there are still some unresolved problems. The biggest progress has been made in the theory of tidal effects and of particulate energy deposition and of electrojet heating. On the other hand, it is still not possible to define adequately the systematic variations of the lower boundary conditions of thermospheric models. This is due to lack of knowledge of the systematic variations of the structure properties in the 100 to 120 km altitude region and inadequate information on the mesospheric turbulence profile and variations in the turbopause altitude.     

一氧化氮冷却率的变化及其作用

利用最新的NO经验公式,计算了近两个太阳活动周期100-200km间NO的冷却率,研究了太阳和地磁活动对NO和O冷却率的影响。进一步证明了NO冷却是120km以上热层的主要冷却过程。      

Comparison of the observed and modeled low- to mid-latitude thermosphere response to magnetic activity: Effects of solar cycle and disturbance time delay

The performance of JB2008 and NRLMSISE-00 models, in describing the response of the thermosphere to magnetic activity are evaluated against total mass density retrieved from accelerometer measurements made onboard CHAMP satellite during 5 years. We show that the global low- to mid-latitude disturbance amplitude is correctly described by the JB2008 model for low solar activity conditions and by both the JB2008 and the NRLMSISE-00 models for high solar activity conditions. For low solar activity conditions, statistics based on almost 3 years of data confirm the large underestimation by the NRLMSISE-00 model quantified by Lathuillère et al. (2008) for the year 2004. We also found that the time delay between low- to mid-latitude global thermosphere disturbance and magnetic activity is statistically well estimated by the NRLMSISE-00 and JB2008 models for disturbed conditions. For moderately disturbed conditions however, the time delay estimated by the JB2008 model is too large by about 3 h. For very disturbed conditions, we found different time delays during day-time and night-time, using new geomagnetic proxies with a 30-min time resolution.     

Mid-latitude thermospheric zonal winds during the equinoxes

The diurnal variation of the mid-latitude upper thermosphere zonal winds during equinoxes has been studied using data recently generated from CHAMP measurements from 2002 to 2004 using an iterative algorithm. The wind data was separated into two geomagnetic activity levels, representing high geomagnetic activity level (Ap > 8) and low geomagnetic activity level (Ap ? 8). The data were further separated into two solar flux levels; with F10.7 > 140 for high and F10.7 ? 140 for low. Geomagnetic activity is a correlator just as significant as solar activity. The response of mid-latitude thermospheric zonal winds to increases in geomagnetic disturbances and solar flux is evident. With increase in geomagnetic activity, midday to midnight winds are generally less eastward and generally more westward after the about midnight transitions. The results show that east west transitions generally occurred about midnight hours for all the situations analyzed. The west to east transition occurs from 1400–1500 MLT. Enhanced westward averaged zonal wind speeds going above 150 ms⁻¹ are observed in the north hemisphere mid-latitude about sunrise hours (∼0700–1100 MLT). Nighttime winds in the north hemisphere are in good agreement with previous single station ground observations over Millstone Hill. Improved ground observations and multi satellite observations from space will greatly improve temporal coverage of the Earth’s thermosphere.     

太阳活动突发过程对临近空间大气影响的模拟

空间天气对地球及近地空间具有重要影响,大的空间天气事件对中上层大气动力学和成分具有不同的影响。利用全大气耦合模式WACCM,针对太阳耀斑、太阳质子、地磁暴三类事件,以太阳活动平静期2015年5月10-14日的GEOS-5数据为模式背景场,通过F_10.7、离子产生率、Kp及Ap指数设置,分别模拟三类事件对临近空间大气温度、密度和臭氧的影响。结果表明耀斑事件在三类事件中对临近空间大气温度和密度的影响最为显著。平流层大气温度增加是由耀斑辐射增强引起平流层臭氧吸收紫外辐射发生的光化学反应所致,耀斑事件引起平流层和低热层温度增加约为2～3 K,低热层大气相对密度增加在6%以内;太阳质子事件及磁暴事件主要影响低热层,但太阳质子事件和磁暴事件对低热层温度扰动不大于1 K。     

强磁暴、能量粒子暴与热层大气密度涨落之间的相关关系

利用1997-2007年由GOES8, GOES11和GOES12星载高能粒子探测器在地球同步轨道高度上所探测到的高能质子和高能电子通量探测数据以及高度560km左右星载大气密度探测器所得的热层大气密度探测数据, 统计分析了强地磁扰动、高能粒子通量跃变和热层大气密度涨落之间的相关关系, 初步获得强地磁扰动期间, 地球同步轨道(外辐射带外环)均出现了增幅大于三个数量级的高能质子通量(尤其是E>1MeV)强增强现象, 随后热 层大气密度强烈上涨, 表明三者之间是正相关关系. 在时间上地球同步轨道高能质子通量强增强现象先于日均Ap值(地磁活动程度)上涨约一天左右, 而热层大气密度强涨落现象又明显滞后于强地磁扰动事件.      

太阳活动低年广州地区地磁扰动与电离层闪烁的统计特征分析

基于肇庆地磁台的地磁监测数据和广州气象卫星地面站建立的华南地区GPS电离层闪烁监测网的监测数据, 统计分析了2008年7月至2010年7月太阳活动低年期间广州地区地磁扰动与电离层闪烁的关系. 用肇庆台地磁水平分量H的变化量换算出肇庆地磁指数K, 以此来代表广州地区地磁扰动情况.分析结果表明, 磁暴/强地磁扰动对广州地区电离层闪烁的发生总体表现为抑制作用, 电离层闪烁主要发生在低K值期间, 而在K ≥ 4时电离层闪烁的发生呈下降趋势. 电离层闪烁发生率随季节和地磁活动的变化规律表现在, 春季的弱闪烁发生率、夜间中等以上闪烁发生率和夏季中等以上闪烁的发生率明显与地磁活动指数K相关, 即随$K$指数的增大而减小; 在秋季和冬季闪烁发生率与K指数变化无明显关系. 同时还综合分析了地磁与太阳活动的变化对电离层活动的影响, 广州地区闪烁主要发生在太阳活动较低的磁静日期间.      

Analysis of ionospheric TEC response to solar and geomagnetic activities at different solar activity stages

Studying the relationship of total electron content (TEC) to solar or geomagnetic activities at different solar activity stages can provide a reference for ionospheric modeling and prediction. On the basis of solar activity indices, geomagnetic activity parameters, and ionospheric TEC data at different solar activity stages, this study analyzes the overall variation relationships of solar and geomagnetic activities with ionospheric TEC, the characteristics of the quasi-27-day periodic oscillations of the three variables at different stages, and the delayed TEC response of solar activity by conducting correlation analysis, Butterworth band-pass filtering, Fourier transform, and time lag analysis. The following results are obtained. (1) TEC exhibits a significant linear relationship with solar activity at different solar activity stages. The correlation coefficients |R| are arranged as follows: |R|_EUV > |R|_F10.7 > |R|sunspot number. No significant linear relationship exists between TEC and geomagnetic activity parameters (|R| < 0.35). (2) TEC, solar activity indices, and geomagnetic activity parameters have a period of 10.5 years. The maximum amplitudes of the Fourier spectrum for TEC and solar activity indices are nearly 27 days and those of geomagnetic activity parameters are nearly 27 and 13.5 days. (3) The deviations of the quasi-27-day significant periodic oscillation of TEC and solar activity indices are consistent. (4) No evident relationship exists between the quasi-27-day periodic oscillation of TEC and geomagnetic activity parameters. (5) The delay time of TEC for the 10.7 cm solar radio flux and extreme ultraviolet is always consistent, whereas that for sunspot number varies at each stage.     

CHANGES OF THE THERMOSPHERE DENSITY IN THE SUNSHINE AND SHADE AREA OBSERVED BY "SZ-2" ATMOSPHERIC DENSITY DETECTOR

In this paper, thermosphere density data of "SZ-2" Atmospheric Density Detec tor From February to April 2001 are used to study the changes of the thermo sphere density in the sunshine and shaded area during solar and geomagnetic activity. The results show that in the sunshine area, the peak value of atmo spheric density changes as F10.7 varies; during geomagnetic activity, the peak value of atmospheric density in the shaded area increases as Ap increases, and start off with higher latitude, therefore move to lower latitude.     

Empirical models of the thermosphere and requirements for improvements

The different types of variation in the thermosphere are briefly examined and the solar-activity effect is singled out for special attention. To this day, empirical models have made use of the decimetric solar flux F_10.7 as an index of the variable XUV radiation from the sun. To account for the change in the relative intensity of the different types of emissions in the course of the solar cycle, F_10.7 is made to perform double duty: The daily values are used to represent the day-to-day and “27-day” variations, while its averages over several solar rotations are used to represent the variations with the 11-year cycle. The availability of direct solar XUV data should eventually eliminate the need for such a make-shift procedure. Accuracy and continuity requirements of XUV intensity measurements are discussed and a strategy is outlined for sorting out the relevant features from the observational material and putting them to practical use in thermospheric modeling. It is suggested that future models of the diurnal and the geomagnetic variation use as a guide theoretical models which have achieved considerable success in qualitatively representing the observed phenomena.     

广州地磁Z分量日变幅的谱特征

利用1972—1993年广州地磁资料，分析了Z分量日变幅的年平均、年变化和半年变化等低频成分的逐年变化，以及小于60天的短周期变化特征．同时对1972—1993年的F10.7日均值进行了谱分析．结果指出，广州地磁Z分量日变幅的年平均与太阳活动指数F10．7的年平均存在良好的线性相关；具有幅度大约5nT夏季极大的年变化，与太阳活动没有明显相关，是一种季节效应；存在春秋分极大的半年变化，幅度与太阳活动有关，高年的幅度明显大于低年；具有明显的与太阳自转相关的27天左右的变化和明显的与行星波有关的接近16日、10日、5日、2日等短周期变化．广州地磁Z分量日变幅的这些谱特征，有助于更深入地了解中低层大气对电离层影响的物理机制．     

低纬地磁Z分量的半年变化

利用武汉、广州、泉州和琼中等4个低纬地磁站连续多年的地磁资料，计算了各月5个磁静日Z分量日均值与中午1100---1300时段平均值之差(Dz)，对每年12个Dz采用多元回归分析方法，得到各年的半年变化幅度和相位．结果表明：4个站的Dz每年都有半年变化现象；半年变化幅度与太阳活动有关，一般来说，太阳活动高年Dz半年变化幅度明显大于太阳活动低年；太阳活动本身的半年变化，对Dz半年变化幅度有显著的调制作用；Dz半年变化的相位在3—4月(或9—10月)，即极大值出现在分季；低纬地区地磁Z分量存在显著的半年变化，能够反映赤道电急流也有明显的半年变化，这再一次证明，赤道电急流幅度的半年变化，通过“喷泉效应”使得电离层，f0F2产生半年变化，其是产生，f0F2半年变化的一个主要因素．     

On statistical relationship of solar, geomagnetic and human activities.

Data of galactic cosmic rays, solar and geomagnetic activities and solar wind parameters on the one side and car accident events (CAE) in Poland on the other have been analyzed in order to reveal the statistical relationships among them for the period of 1990-2001. Cross correlation and cross spectrum of the galactic cosmic ray intensity, the solar wind (SW) velocity, Kp index of geomagnetic activity and CAE in Poland have been carried out. It is shown that in some epochs of the above-mentioned period there is found a reliable relationship between CAE and solar and geomagnetic activities parameters in the range of the different periodicities, especially, 7 days. The periodicity of 7 days revealed in the data of the CAE has the maximum on Friday without any exception for the minimum and maximum epochs of solar activity. However, the periodicity of 7 days is reliably revealed in other parameters characterizing galactic cosmic rays, SW, solar and geomagnetic activities, especially for the minimum epoch of solar activity. The periodicity of 3.5 days found in the series of CAE data more or less can be completely ascribed to the social effects, while the periodicity of 7 days can be ascribed to the social effect or/to the processes on the Sun, in the interplanetary space and in the Earth's magnetosphere and atmosphere.     

The geomagnetic variation in the upper atmosphere

A brief review is given of the development of models of the geomagnetic variation in the thermosphere and exosphere, including some recent models based mainly on satellite-borne gas analyzer measurements. One recent model, derived from ESRO4 data, is described in detail and compared with the model in CIRA72. The limitations of this model are discussed. The model in the MSIS comprehensive model is also examined briefly. There appears to be a serious error in the amplitude of the exospheric temperature increase predicted by the MSIS model.     

Variations of Thermosphere Density Based on Joint Analysis of In-Situ Measurement Data From Shenzhou Spacecrafts

Based on the measurements made by Atmospheric Density Detectors (ADDs) onboard Chinese spacecraft Shenzhou 2-4, the variations of thermosphere density are revealed. During the quiet period, the density at spacecraft altitude of 330～410km exhibited a dominant diurnal variation, with high value on dayside and low value on nightside. The ratio of the diurnal maximum density to the minimum ranged from 1.7 to 2.0. The ratio shows a positive correlation with the level of solar activity and a negative correlation with the level of geomagnetic activity. When a geomagnetic disturbance comes, the atmospheric density at the altitude of 330～410km displayed a global enhancement. For a strong geomagnetic disturbance, the atmospheric density increased by about 56%, and reached its maximum about 6～7 hours after the geomagnetic disturbance peak. The density asymmetry was also observed both in the southern and northern hemisphere during the geomagnetic disturbance peak.      

Storm-time atmospheric density modeling using neural networks and its application in orbit propagation

Upper atmospheric densities during geomagnetic storms are usually poorly estimated due to a lack of clear understanding of coupling mechanisms between the thermosphere and magnetosphere. Consequently, the orbit determination and propagation for low-Earth-orbit objects during geomagnetic storms have large uncertainties. Artificial neural networks are often used to identify nonlinear systems in the absence of rigorous theory. In the present study, an attempt has been made to model the storm-time atmospheric density using neural networks. Considering the debate over the representative of geomagnetic storm effect, i.e. the geomagnetic indices ap and Dst, three neural network models (NNM) are developed with ap, Dst and a combination of ap and Dst respectively. The density data used for training the NNMs are derived from the measurements of the satellites CHAMP and GRACE. The NNMs are evaluated by looking at: (a) the mean residuals and the standard deviations with respect to the density data that are not used in training process, and (b) the accuracy of reconstructing the orbits of selected objects during storms employing each model. This empirical modeling technique and the comparisons with the models NRLMSIS-00 and Jacchia-Bowman 2008 reveal (1) the capability of neural networks to model the relationship between solar and geomagnetic activities, and density variations; and (2) the merits and demerits of ap and Dst when it comes to characterizing density variations during storms.