摘要
中间层顶-低热层区域是地球大气中重要的空间区域。基于剥洋葱算法及氧分子气辉光谱理论,利用迈克耳孙全球高分辨率热层成像干涉仪(MIGHTI)测量的O2-A波段气辉辐射强度图像,反演得到海拔为92~140 km的大气温度廓线。首先,根据氧分子气辉光谱理论,结合MIGHTI仪器参数,计算了其各光谱通道信号强度随温度的变化关系;然后,利用剥洋葱算法提取各光谱通道的目标层信号强度,并结合信号强度与温度的函数关系,反演得到大气温度廓线;最后,通过与SABER卫星的观测结果及NRLMSIS-00大气模型的仿真数据的对比,验证了MIGHTI温度反演的可靠性与合理性。误差分析结果表明,MIGHTI的温度探测误差随高度增加而增大,在92 km处为1 K,在140 km处为13 K。
Objective The mesosphere-lower thermosphere(MLT)region is an important space region in the earth's atmosphere.As a significant parameter of atmospheric thermodynamics in the MLT region,the temperature is of great academic significance and application value.Since it is not affected by weather and geographical conditions,satelliteborne temperature detection can perform allweather and longterm observation on a global scale.Thus,it becomes an important detection method to obtain the threedimensional distribution and spatiotemporal evolution in the midupper atmospheric temperature.Previous satellite payloads,such as the wind imaging interferometer(WINDII)and the highresolution Doppler interferometer(HRDI)on the UARS satellite,and the sounding of the atmosphere using broadband emission radiometry(SABER)on the TIMED satellite,have made contributions to the distribution detection of the midupper atmospheric temperature field.However,the MLT region still suffers from problems including incomplete space coverage or low detection accuracy.In October 2019,the Michelson interferometer for global highresolution thermospheric imaging(MIGHTI)on NASA's ionospheric connection(ICON)explorer measured the radiation intensity of the O_(2)-A band through five discrete wavelength channels and obtained three years of continuous observation data.Based on the onion peeling algorithm and the theory of the O_(2)-A band airglow spectrum,this paper retrieves the atmospheric temperature profile in the 92-140 km area via the O_(2)-A band airglow radiation intensity measured by MIGHTI.In addition,comparisons with the observation results of the SABER satellite,the simulation data of the NRLMSIS00 atmospheric model,and the temperature product of MIGHTI obtained by the ICON team using an optimization algorithm are conducted systematically to verify the rationality of MIGHTI temperature retrieval.Methods The relative radiation intensity of each spectral line in O_(2)-A band airglow which follows the Boltzmann distribution is affected by temperature.MIGHTI samples the O_(2)-A band signal through five channels,and the strength of signals in the B and D channels increases with the rising temperature,whereas the strength of the signal in channel C is just the opposite.The ratio of signal channels with different temperature responses is independent of the emission rate,and also changes monotonously with the temperature.Therefore,the atmospheric temperature can be accurately retrieved by measuring the ratio of channel signal strengths.The relative radiance of O_(2)-A band on the line of sight obtained from the limbviewing observation of MIGHTI is stripped by the onion peeling algorithm to obtain the relative intensity of the target layer.Then,according to the relative intensity of the target layer of channels B,C,and D,the atmospheric temperature profile information is retrieved through combining the functional relationship between the channel strength ratio calculated by the MIGHTI instrument parameters and the temperature.Results and Discussions To evaluate the rationality and reliability of the MIGHTI temperature retrieval results obtained by the onion peeling algorithm,this paper verifies the MIGHTI retrieval results by comparing the measured data of SABER and simulation data of atmospheric model NRLMSIS00.The results show that MIGHTI temperature retrieval is in good agreement with SABER at 92-100 km,and the temperature distribution of MIGHTI is basically consistent with that of the empirical model in the altitude range below 130 km,which shows the overall retrieval reliability of MIGHTI on a global scale.According to the characteristics of annual midupper atmospheric temperature changes,the detected temperature ratio of MIGHTI and SABER to the model temperature is calculated in one day of four seasons respectively.In the altitude range of 92-100 km,the temperature ratio profiles of MIGHTI and SABER are similar and very close to 1,which proves that MIGHTI has a strong temperature retrieval rationality in this altitude range.It is also compared with the temperature profile obtained by the optimization algorithm adopted by the ICON team to further evaluate the rationality of the onion peeling algorithm for retrieving MIGHTI temperature.Within the height range that can be retrieved by the optimization algorithm,the difference between the temperature values retrieved by the two algorithms differs slightly within±5%,which further verifies the rationality of the temperature retrieval by the onion peeling algorithm.Conclusions The O_(2)-A band airglow measured by MIGHTI is retrieved and the atmospheric temperature distribution in this region is calculated by the onion peeling algorithm.By comparing the observation results of the SABER satellite,the NRLMSIS00 atmospheric model data,and the MIGHTI temperature products obtained by the ICON team using the optimization method,the paper verifies the reliability and rationality of MIGHTI temperature retrieval.By measuring the shape of the O_(2)-A band airglow radiation spectrum,MIGHTI can detect the atmospheric temperature profile between 92-140 km,which covers the MLT area effectively.The minimum temperature error is 1 K at 90 km,and the maximum temperature retrieval error is 13 K at 140 km.
作者
胡向瑞
李发泉
王后茂
张子豪
郭建军
武魁军
何微微
Hu Xiangrui;Li Faquan;Wang Houmao;Zhang Zihao;Guo Jianjun;Wu Kuijun;He Weiwei(School of Physics and Electronic Information,Yantai University,Yantai 264005,Shandong,China;Innovation Academy for Precision Measurement Science and Technology,Chinese Academy of Sciences,Wuhan 430071,Hubei,China;National Space Science Center,Chinese Academy of Sciences,Beijing 100190,China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2023年第12期55-63,共9页
Acta Optica Sinica
基金
国家自然科学基金(41975039,61705253)
山东省自然科学基金(ZR2021QD088)
山东省高校青年创新技术项目(2021KJ008)。
关键词
大气光学
温度反演
气辉辐射
临边观测
剥洋葱算法
atmospheric optics
temperature retrieval
airglow radiation
limbviewing
onion peeling algorithm