Energetic electron precipitation and their atmospheric effect

Energetic particle precipitation induces ionization of the atmosphere which initiates a chain of reaction cycles affecting atmospheric composition and dynamics potentially down to surface weather systems. Ionization rates are retrieved based on yield functions or pre-calculated monoenergetic electron flux and energy spectra of precipitated energetic particles. Usually, information about energy spectra is obtained from satellites, balloons, and various ground-based observations. In all cases, some assumptions about spectral distribution for the entire energy range have to be made. As ionization rates are widely used in chemistry-climate models to estimate the atmospheric response to particle forcing, evaluation of the energy spectra is a key task in the solar-terrestrial studies. In this paper, it is shown that possible uncertainties of the ionization rates retrieval based on different spectral functions can lead to large disagreements in the ionization rates, with implications for the modelled response of atmospheric composition and dynamics to electron precipitation

Model results of OH airglow considering four different wavelength regions to derive night-time atomic oxygen and atomic hydrogen in the mesopause region

Based on the zero-dimensional box model Module Efficiently Calculating the Chemistry of the Atmosphere/Chemistry As A Box model Application (CAABA/MECCA-3.72f), an OH airglow model was developed to derive night-time number densities of atomic oxygen ([O(3P)]) and atomic hydrogen ([H]) in the mesopause region ( ∼ 75–100 km). The profiles of [O(3P)] and [H] were calculated from OH airglow emissions measured at 2.0 µm by the Sounding of the Atmosphere using Broadband Emission Radiography (SABER) instrument on board NASA\u27s Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite. The two target species were used to initialize the OH airglow model, which was empirically adjusted to fit four different OH airglow emissions observed by the satellite/instrument configuration TIMED/SABER at 2.0 µm and at 1.6 µm as well as measurements by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument on board the Environmental Satellite (ENVISAT) of the transitions OH(6-2) and OH(3-1). Comparisons between the "best-fit model" obtained here and the satellite measurements suggest that deactivation of vibrationally excited OH(ν) via OH(ν ≥ 7)+O2 might favour relaxation to OH(ν′ ≤ 5)+O2 by multi-quantum quenching. It is further indicated that the deactivation pathway to OH(ν′ = ν − 5)+O2 dominates. The results also provide general support of the recently proposed mechanism OH(ν)+O(3P) → OH(0 ≤ ν′ ≤ ν − 5)+O(1D) but suggest slower rates of OH(ν = 8,7,6,5)+O(3P), partly disagreeing with laboratory experiments. Additionally, deactivation to OH(ν′ = ν − 5)+O(1D) might be preferred. The profiles of [O(3P)] and [H] derived here are plausible between 80 and 95 km but should be regarded as an upper limit. The values of [O(3P)] obtained in this study agree with the corresponding TIMED/SABER values between 80 and 85 km but are larger from 85 to 95 km due to different relaxation assumptions of OH(ν)+O(3P). The [H] profile found here is generally larger than TIMED/SABER [H] by about 50 % from 80 to 95 km, which is primarily attributed to our faster OH(ν = 8)+O2 rate

Retrieval of nitric oxide in the mesosphere from SCIAMACHY nominal limb spectra

We present a retrieval algorithm for nitric oxide (NO) number densities from measurements from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, on Envisat) nominal limb mode (0--91 km). The NO number densities are derived from atmospheric emissions in the gamma bands in the range 230--300 nm, measured by the SCIAMACHY ultra-violet (UV) channel 1. The retrieval is adapted from the mesosphere and lower thermosphere mode (MLT, 50--150 km) NO retrieval (Bender et al., 2013, arXiv:1808.02388), including the same 3-D ray tracing, 2-D retrieval grid, and regularisations with respect to altitude and latitude. Since the nominal mode limb scans extend only to about 91 km, we use NO densities in the lower thermosphere (above 92 km), derived from empirical models, as a priori input. The priors are the Nitric Oxide Empirical Model (NOEM; Marsh et al., 2004) and a regression model derived from the MLT NO data comparison (Bender et al., 2015). Our algorithm yields plausible NO number densities from 60 to 85 km from the SCIAMACHY nominal limb mode scans. Using a priori input substantially reduces the incorrect attribution of NO from the lower thermosphere, where no direct limb measurements are available. The vertical resolution lies between 5 and 10 km in the altitude range 65--80 km. Analysing all SCIAMACHY nominal limb scans provides almost 10 years (from August 2002 to April 2012) of daily NO measurements in this altitude range. This provides a unique data record of NO in the upper atmosphere and is invaluable for constraining NO in the mesosphere, in particular for testing and validating chemistry climate models during this period.Comment: 12 pages, 9 figures, published 201

Retrieval of O₂(¹Σ) and O₂(¹Δ) volume emission rates in the mesosphere and lower thermosphere using SCIAMACHY MLT limb scans

We present the retrieved volume emission rates (VERs) from the airglow of both the daytime and twilight O2(1Σ) band and O2(1Δ) band emissions in the mesosphere and lower thermosphere (MLT). The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard the European Space Agency Envisat satellite observes upwelling radiances in limb-viewing geometry during its special MLT mode over the range 50–150 km. In this study we use the limb observations in the visible (595–811 nm) and near-infrared (1200–1360 nm) bands. We have investigated the daily mean latitudinal distributions and the time series of the retrieved VER in the altitude range from 53 to 149 km. The maximal observed VERs of O2(1Δ) during daytime are typically 1 to 2 orders of magnitude larger than those of O2(1Σ). The latter peaks at around 90 km, whereas the O2(1Δ) emissivity decreases with altitude, with the largest values at the lower edge of the observations (about 53 km). The VER values in the upper mesosphere (above 80 km) are found to depend on the position of the sun, with pronounced high values occurring during summer for O2(1Δ). O2(1Σ) emissions show additional high values at polar latitudes during winter and spring. These additional high values are presumably related to the downwelling of atomic oxygen after large sudden stratospheric warmings (SSWs). Accurate measurements of the O2(1Σ) and O2(1Δ) airglow, provided that the mechanism of their production is understood, yield valuable information about both the chemistry and dynamics in the MLT. For example, they can be used to infer the amounts and distribution of ozone, solar heating rates, and temperature in the MLT

The impact of an extreme solar event on the middle atmosphere: a case study

A possible impact of an extreme solar particle event (ESPE) on the middle atmosphere is studied for present-day climate and geomagnetic conditions. We consider an ESPE with an occurrence probability of about 1 per millennium. In addition, we assume that the ESPE is followed by an extreme geomagnetic storm (GMS), and we compare the contribution of the two extreme events. The strongest known and best-documented ESPE of 774/5 CE is taken as a reference example and established estimates of the corresponding ionization rates are applied. The ionization rates due to the energetic particle precipitation (EPP) during an extreme GMS are upscaled from analyzed distributions of electron energy spectra of observed GMSs. The consecutive buildup of NOx and HOx by ionization is modeled in the high-top 3D chemistry circulation model KArlsruhe SImulation Model of the middle Atmosphere (KASIMA), using specified dynamics from ERA-Interim analyses up to the stratopause. A specific dynamical situation was chosen that includes an elevated stratosphere event during January and maximizes the vertical coupling between the northern polar mesosphere–lower thermosphere region and the stratosphere; it therefore allows us to estimate a maximum possible impact. The particle event initially produces about 65 Gmol of NOy, with 25 Gmol of excess NOy even after 1 year. The related ozone loss reaches up to 50 % in the upper stratosphere during the first weeks after the event and slowly descends to the mid-stratosphere. After about 1 year, 20 % ozone loss is still observed in the northern stratosphere. The GMS causes strong ozone reduction in the mesosphere but plays only a minor role in the reduction in total ozone. In the Southern Hemisphere (SH), the long-lived NOy in the polar stratosphere, which is produced almost solely by the ESPE, is transported into the Antarctic polar vortex, where it experiences strong denitrification into the troposphere. For this special case, we estimate a NO3 washout that could produce a measurable signal in ice cores. The reduction in total ozone causes an increase of the UV erythema dose of less than 5 %, which maximizes in spring for northern latitudes of 30∘ and in summer for northern latitudes of about 60∘

Quantifying uncertainties of climate signals in chemistry climate models related to the 11-year solar cycle – Part 1: Annual mean response in heating rates, temperature, and ozone

Variations in the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry–climate model (CCM) formulation. In this study CCM simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1)–Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature, and ozone. The solar response is derived from climatological differences of time slice simulations prescribing SSI for the solar maximum in 1989 and near the solar minimum in 1994. The SSI values for the solar maximum of each SSI data set are created by adding the SSI differences between November 1994 and November 1989 to a common SSI reference spectrum for near-solar-minimum conditions based on ATLAS-3 (Atmospheric Laboratory of Applications and Science-3). The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar response in shortwave heating rates in the upper mesosphere and in the upper stratosphere–lower mesosphere. The strongest influence on the variability of the solar response in ozone and temperature is identified in the upper stratosphere–lower mesosphere. However, in the region of the largest ozone mixing ratio, in the stratosphere from 50 to 10 hPa, the SSI data sets do not contribute much to the variability of the solar response when the Spectral And Total Irradiance REconstructions-T (SATIRE-T) SSI data set is omitted. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid-latitudes, where the model dynamics modulate the solar responses. Apart from the upper mesosphere, there are also regions where the largest fraction of the variability of the solar response is explained by randomness, especially for the solar response in temperature

Mesospheric nitric oxide model from SCIAMACHY data

We present an empirical model for nitric oxide (NO) in the mesosphere (≈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-α 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

Exceptional middle latitude electron precipitation detected by balloon observations: implications for atmospheric composition

Energetic particle precipitation leads to ionization in the Earth\u27s atmosphere, initiating the formation of active chemical species which destroy ozone and have the potential to impact atmospheric composition and dynamics down to the troposphere. We report on one exceptionally strong high-energy electron precipitation event detected by balloon measurements in middle latitudes on 14 December 2009 with ionization rates locally comparable to strong solar proton events. This electron precipitation was likely caused by wave-particle interactions in the slot region between the inner and outer radiation belts, connected with still not well understood natural phenomena in the magnetosphere. Satellite observations of odd nitrogen and nitric acid are consistent with wide-spread electron precipitation into magnetic midlatitudes. Simulations with a 3D chemistry-climate model indicate almost complete destruction of ozone in the upper mesosphere over the region where high-energy electron precipitation occurred. Such an extraordinary type of energetic particle precipitation can have major implications for the atmosphere, and their frequency and strength should be carefully studied

NOy_{y} production, ozone loss and changes in net radiative heating due to energetic particle precipitation in 2002–2010

We analyze the impact of energetic particle precipitation on the stratospheric nitrogen budget, ozone abundances and net radiative heating using results from three global chemistry-climate models considering solar protons and geomagnetic forcing due to auroral or radiation belt electrons. Two of the models cover the atmosphere up to the lower thermosphere, the source region of auroral NO production. Geomagnetic forcing in these models is included by prescribed ionization rates. One model reaches up to about 80 km, and geomagnetic forcing is included by applying an upper boundary condition of auroral NO mixing ratios parameterized as a function of geomagnetic activity. Despite the differences in the implementation of the particle effect, the resulting modeled NOy in the upper mesosphere agrees well between all three models, demonstrating that geomagnetic forcing is represented in a consistent way either by prescribing ionization rates or by prescribing NOy at the model top. Compared with observations of stratospheric and mesospheric NOy from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument for the years 2002–2010, the model simulations reproduce the spatial pattern and temporal evolution well. However, after strong sudden stratospheric warmings, particle-induced NOy is underestimated by both high-top models, and after the solar proton event in October 2003, NOy is overestimated by all three models. Model results indicate that the large solar proton event in October 2003 contributed about 1–2 Gmol (10⁹ mol) NOy per hemisphere to the stratospheric NOy budget, while downwelling of auroral NOx from the upper mesosphere and lower thermosphere contributes up to 4 Gmol NOy . Accumulation over time leads to a constant particle-induced background of about 0.5–1 Gmol per hemisphere during solar minimum, and up to 2 Gmol per hemisphere during solar maximum. Related negative anomalies of ozone are predicted by the models in nearly every polar winter, ranging from 10–50% during solar maximum to 2–10% during solar minimum. Ozone loss continues throughout polar summer after strong solar proton events in the Southern Hemisphere and after large sudden stratospheric warmings in the Northern Hemisphere. During mid-winter, the ozone loss causes a reduction of the infrared radiative cooling, i.e., a positive change of the net radiative heating (effective warming), in agreement with analyses of geomagnetic forcing in stratospheric temperatures which show a warming in the late winter upper stratosphere. In late winter and spring, the sign of the net radiative heating change turns to negative (effective cooling). This spring-time cooling lasts well into summer and continues until the following autumn after large solar proton events in the Southern Hemisphere, and after sudden stratospheric warmings in the Northern Hemisphere