Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.5194/acp-19-2135-2019 |
Mesospheric nitric oxide model from SCIAMACHY data | |
Bender, Stefan1; Sinnhuber, Miriam2; Espy, Patrick J.1; Burrows, John P.3 | |
2019-02-18 | |
发表期刊 | ATMOSPHERIC CHEMISTRY AND PHYSICS
![]() |
ISSN | 1680-7316 |
EISSN | 1680-7324 |
出版年 | 2019 |
卷号 | 19期号:4页码:2135-2147 |
文章类型 | Article |
语种 | 英语 |
国家 | Norway; Germany |
英文摘要 | We present an empirical model for nitric oxide (NO) in the mesosphere (approximate to 60-90 km) derived from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartoghraphY) limb scan data. This work complements and extends the NOEM (Nitric Oxide Empirical Model; Marsh et al., 2004) and SANOMA (SMR Acquired Nitric Oxide Model Atmosphere; Kiviranta et al., 2018) empirical models in the lower thermosphere. The regression ansatz builds on the heritage of studies by Hendrickx et al. (2017) and the superposed epoch analysis by Sinnhuber et al. (2016) which estimate NO production from particle precipitation. Our model relates the daily (longitudinally) averaged NO number densities from SCIAMACHY (Bender et al., 2017b, a) as a function of geomagnetic latitude to the solar Lyman-alpha and the geomagnetic AE (auroral electrojet) indices. We use a non-linear regression model, incorporating a finite and seasonally varying lifetime for the geomagnetically induced NO. We estimate the parameters by finding the maximum posterior probability and calculate the parameter uncertainties using Markov chain Monte Carlo sampling. In addition to providing an estimate of the NO content in the mesosphere, the regression coefficients indicate regions where certain processes dominate. |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000459023300003 |
WOS关键词 | ENERGETIC PARTICLE-PRECIPITATION ; LOWER THERMOSPHERE ; CROSS-VALIDATION ; EMPIRICAL-MODEL ; RETRIEVAL ; NO ; ATMOSPHERE ; TRANSPORT ; NITROGEN ; ENVISAT |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/17298 |
专题 | 地球科学 |
作者单位 | 1.Norwegian Univ Sci & Technol, Dept Phys, Trondheim, Norway; 2.Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Karlsruhe, Germany; 3.Univ Bremen, Inst Environm Phys, Bremen, Germany |
推荐引用方式 GB/T 7714 | Bender, Stefan,Sinnhuber, Miriam,Espy, Patrick J.,et al. Mesospheric nitric oxide model from SCIAMACHY data[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2019,19(4):2135-2147. |
APA | Bender, Stefan,Sinnhuber, Miriam,Espy, Patrick J.,&Burrows, John P..(2019).Mesospheric nitric oxide model from SCIAMACHY data.ATMOSPHERIC CHEMISTRY AND PHYSICS,19(4),2135-2147. |
MLA | Bender, Stefan,et al."Mesospheric nitric oxide model from SCIAMACHY data".ATMOSPHERIC CHEMISTRY AND PHYSICS 19.4(2019):2135-2147. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论