ALBERT

Description: Context. The first opportunity to detect indications for life outside of the Solar System may be provided already within the next decade with upcoming missions such as the James Webb Space Telescope (JWST), the European Extremely Large Telescope (E-ELT) and the Atmospheric Remote-sensing Infrared Exoplanet Large-survey (ARIEL) mission, searching for atmospheric biosignatures on planets in the habitable zone of cool K- and M-stars. Nevertheless, their harsh stellar radiation and particle environment could lead to photochemical loss of atmospheric biosignatures. Aims. We aim to study the influence of cosmic rays on exoplanetary atmospheric biosignatures and the radiation environment considering feedbacks between energetic particle precipitation, climate, atmospheric ionization, neutral and ion chemistry, and secondary particle generation. Methods. We describe newly combined state-of-the-art modeling tools to study the impact of the radiation and particle environment, in particular of cosmic rays, on atmospheric particle interaction, atmospheric chemistry, and the climate-chemistry coupling in a self-consistent model suite. To this end, models like the Atmospheric Radiation Interaction Simulator (AtRIS), the Exoplanetary Terrestrial Ion Chemistry model (ExoTIC), and the updated coupled climate-chemistry model are combined. Results. In addition to comparing our results to Earth-bound measurements, we investigate the ozone production and -loss cycles as well as the atmospheric radiation dose profiles during quiescent solar periods and during the strong solar energetic particle event of February 23, 1956. Further, the scenario-dependent terrestrial transit spectra, as seen by the NIR-Spec infrared spectrometer onboard the JWST, are modeled. Amongst others, we find that the comparatively weak solar event drastically increases the spectral signal of HNO3, while significantly suppressing the spectral feature of ozone. Because of the slow recovery after such events, the latter indicates that ozone might not be a good biomarker for planets orbiting stars with high flaring rates.

Description: 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.

Description: 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.

Description: We compare simulations from three high-top (with upper lid above 120 km) and five medium-top (with upper lid around 80 km) atmospheric models with observations of odd nitrogen (NOx  =  NO + NO2), temperature, and carbon monoxide from seven satellite instruments (ACE-FTS on SciSat, GOMOS, MIPAS, and SCIAMACHY on Envisat, MLS on Aura, SABER on TIMED, and SMR on Odin) during the Northern Hemisphere (NH) polar winter 2008/2009. The models included in the comparison are the 3-D chemistry transport model 3dCTM, the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model, FinROSE, the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA), the modelling tools for SOlar Climate Ozone Links studies (SOCOL and CAO-SOCOL), and the Whole Atmosphere Community Climate Model (WACCM4). The comparison focuses on the energetic particle precipitation (EPP) indirect effect, that is, the polar winter descent of NOx largely produced by EPP in the mesosphere and lower thermosphere. A particular emphasis is given to the impact of the sudden stratospheric warming (SSW) in January 2009 and the subsequent elevated stratopause (ES) event associated with enhanced descent of mesospheric air. The chemistry climate model simulations have been nudged toward reanalysis data in the troposphere and stratosphere while being unconstrained above. An odd nitrogen upper boundary condition obtained from MIPAS observations has further been applied to medium-top models. Most models provide a good representation of the mesospheric tracer descent in general, and the EPP indirect effect in particular, during the unperturbed (pre-SSW) period of the NH winter 2008/2009. The observed NOx descent into the lower mesosphere and stratosphere is generally reproduced within 20 %. Larger discrepancies of a few model simulations could be traced back either to the impact of the models' gravity wave drag scheme on the polar wintertime meridional circulation or to a combination of prescribed NOx mixing ratio at the uppermost model layer and low vertical resolution. In March–April, after the ES event, however, modelled mesospheric and stratospheric NOx distributions deviate significantly from the observations. The too-fast and early downward propagation of the NOx tongue, encountered in most simulations, coincides with a temperature high bias in the lower mesosphere (0.2–0.05 hPa), likely caused by an overestimation of descent velocities. In contrast, upper-mesospheric temperatures (at 0.05–0.001 hPa) are generally underestimated by the high-top models after the onset of the ES event, being indicative for too-slow descent and hence too-low NOx fluxes. As a consequence, the magnitude of the simulated NOx tongue is generally underestimated by these models. Descending NOx amounts simulated with medium-top models are on average closer to the observations but show a large spread of up to several hundred percent. This is primarily attributed to the different vertical model domains in which the NOx upper boundary condition is applied. In general, the intercomparison demonstrates the ability of state-of-the-art atmospheric models to reproduce the EPP indirect effect in dynamically and geomagnetically quiescent NH winter conditions. The encountered differences between observed and simulated NOx, CO, and temperature distributions during the perturbed phase of the 2009 NH winter, however, emphasize the need for model improvements in the dynamical representation of elevated stratopause events in order to allow for a better description of the EPP indirect effect under these particular conditions.

Description: 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), 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.

Description: 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.

Description: 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's 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.

Description: 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.

Description: This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with respect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spectral irradiance (SSI), and the F10.7 index as well as particle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, electrons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850–2014), and future (2015–2300) simulations. For the preindustrial control simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunder-minimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models.For the historical simulations, the TSI and SSI time series are defined as the average of two solar irradiance models that are adapted to CMIP6 needs: an empirical one (NRLTSI2–NRLSSI2) and a semi-empirical one (SATIRE). A new and lower TSI value is recommended: the contemporary solar-cycle average is now 1361.0 W m−2. The slight negative trend in TSI over the three most recent solar cycles in the CMIP6 dataset leads to only a small global radiative forcing of −0.04 W m−2. In the 200–400 nm wavelength range, which is important for ozone photochemistry, the CMIP6 solar forcing dataset shows a larger solar-cycle variability contribution to TSI than in CMIP5 (50 % compared to 35 %).We compare the climatic effects of the CMIP6 solar forcing dataset to its CMIP5 predecessor by using time-slice experiments of two chemistry–climate models and a reference radiative transfer model. The differences in the long-term mean SSI in the CMIP6 dataset, compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave heating rates of −0.35 K day−1 at the stratopause), cooler stratospheric temperatures (−1.5 K in the upper stratosphere), lower ozone abundances in the lower stratosphere (−3 %), and higher ozone abundances (+1.5 % in the upper stratosphere and lower mesosphere). Between the maximum and minimum phases of the 11-year solar cycle, there is an increase in shortwave heating rates (+0.2 K day−1 at the stratopause), temperatures ( ∼  1 K at the stratopause), and ozone (+2.5 % in the upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset. This solar-cycle response is slightly larger, but not statistically significantly different from that for the CMIP5 forcing dataset.CMIP6 models with a well-resolved shortwave radiation scheme are encouraged to prescribe SSI changes and include solar-induced stratospheric ozone variations, in order to better represent solar climate variability compared to models that only prescribe TSI and/or exclude the solar-ozone response. We show that monthly-mean solar-induced ozone variations are implicitly included in the SPARC/CCMI CMIP6 Ozone Database for historical simulations, which is derived from transient chemistry–climate model simulations and has been developed for climate models that do not calculate ozone interactively. CMIP6 models without chemistry that perform a preindustrial control simulation with time-varying solar forcing will need to use a modified version of the SPARC/CCMI Ozone Database that includes solar variability. CMIP6 models with interactive chemistry are also encouraged to use the particle forcing datasets, which will allow the potential long-term effects of particles to be addressed for the first time. The consideration of particle forcing has been shown to significantly improve the representation of reactive nitrogen and ozone variability in the polar middle atmosphere, eventually resulting in further improvements in the representation of solar climate variability in global models.