Articles | Volume 39, issue 5
https://doi.org/10.5194/angeo-39-899-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/angeo-39-899-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regular paper
| 
14 Oct 2021
Regular paper |
| 14 Oct 2021
| 14 Oct 2021
Validation of SSUSI-derived auroral electron densities: comparisons to EISCAT data
Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
Birkeland Centre for Space Science, Bergen, Norway
Patrick J. Espy
Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
Birkeland Centre for Space Science, Bergen, Norway
Larry J. Paxton
Applied Physics Laboratory, Johns Hopkins University, Laurel, Maryland, USA
Related authors
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
Short summary
Short summary
Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Stefan Bender, Miriam Sinnhuber, Patrick J. Espy, and John P. Burrows
Atmos. Chem. Phys., 19, 2135–2147, https://doi.org/10.5194/acp-19-2135-2019, https://doi.org/10.5194/acp-19-2135-2019, 2019
Short summary
Short summary
We present an empirical model for nitric oxide (NO) in the mesosphere (60–90 km) derived from SCIAMACHY limb scan data. Our model relates the daily (longitudinally) averaged NO number densities from SCIAMACHY as a function of geomagnetic latitude to the solar Lyman-alpha and the geomagnetic AE indices. We use a non-linear regression model, incorporating a finite and seasonally varying lifetime for the geomagnetically induced NO.
Amirmahdi Zarboo, Stefan Bender, John P. Burrows, Johannes Orphal, and Miriam Sinnhuber
Atmos. Meas. Tech., 11, 473–487, https://doi.org/10.5194/amt-11-473-2018, https://doi.org/10.5194/amt-11-473-2018, 2018
Short summary
Short summary
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). 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. These observations provide information about the chemistry and dynamics and can be used to infer ozone, solar heating rates, and temperature in the MLT.
Bernd Funke, William Ball, Stefan Bender, Angela Gardini, V. Lynn Harvey, Alyn Lambert, Manuel López-Puertas, Daniel R. Marsh, Katharina Meraner, Holger Nieder, Sanna-Mari Päivärinta, Kristell Pérot, Cora E. Randall, Thomas Reddmann, Eugene Rozanov, Hauke Schmidt, Annika Seppälä, Miriam Sinnhuber, Timofei Sukhodolov, Gabriele P. Stiller, Natalia D. Tsvetkova, Pekka T. Verronen, Stefan Versick, Thomas von Clarmann, Kaley A. Walker, and Vladimir Yushkov
Atmos. Chem. Phys., 17, 3573–3604, https://doi.org/10.5194/acp-17-3573-2017, https://doi.org/10.5194/acp-17-3573-2017, 2017
Short summary
Short summary
Simulations from eight atmospheric models have been compared to tracer and temperature observations from seven satellite instruments in order to evaluate the energetic particle indirect effect (EPP IE) during the perturbed northern hemispheric (NH) winter 2008/2009. Models are capable to reproduce the EPP IE in dynamically and geomagnetically quiescent NH winter conditions. The results emphasize the need for model improvements in the dynamical representation of elevated stratopause events.
Stefan Bender, Miriam Sinnhuber, Martin Langowski, and John P. Burrows
Atmos. Meas. Tech., 10, 209–220, https://doi.org/10.5194/amt-10-209-2017, https://doi.org/10.5194/amt-10-209-2017, 2017
Short summary
Short summary
We present the retrieval of NO number densities from 60 km to 85 km from measurements of SCIAMACHY/Envisat in its nominal limb mode (0–91 km). We derive the densities from the NO gamma bands (230–300 nm). Using prior input reduces the incorrect attribution of NO from the lower thermosphere. The SCIAMACHY nominal limb scans provide almost 10 years of daily NO data in this altitude range, a unique data record to constrain NO in the mesosphere for testing and validating chemistry climate models.
S. Bender, M. Sinnhuber, T. von Clarmann, G. Stiller, B. Funke, M. López-Puertas, J. Urban, K. Pérot, K. A. Walker, and J. P. Burrows
Atmos. Meas. Tech., 8, 4171–4195, https://doi.org/10.5194/amt-8-4171-2015, https://doi.org/10.5194/amt-8-4171-2015, 2015
Short summary
Short summary
We compare the nitric oxide (NO) daily zonal mean number density data sets in the mesosphere and lower thermosphere (MLT, 60km to 150km) from four instruments: ACE-FTS (2004--2010), MIPAS (2005--2012), SCIAMACHY (2008--2012), and SMR (2003--2012). We find that these data sets from different instruments consistently constrain NO in the MLT. Thus, they offer reliable forcing inputs for climate and chemistry climate models as an initial step to include solar and geomagnetic activity.
S. Bender, M. Sinnhuber, J. P. Burrows, M. Langowski, B. Funke, and M. López-Puertas
Atmos. Meas. Tech., 6, 2521–2531, https://doi.org/10.5194/amt-6-2521-2013, https://doi.org/10.5194/amt-6-2521-2013, 2013
Sabine Wüst, Michael Bittner, Patrick J. Espy, W. John R. French, and Frank J. Mulligan
Atmos. Chem. Phys., 23, 1599–1618, https://doi.org/10.5194/acp-23-1599-2023, https://doi.org/10.5194/acp-23-1599-2023, 2023
Short summary
Short summary
Ground-based OH* airglow measurements have been carried out for almost 100 years. Advanced detector technology has greatly simplified the automatic operation of OH* airglow observing instruments and significantly improved the temporal and/or spatial resolution. Studies based on long-term measurements or including a network of instruments are reviewed, especially in the context of deriving gravity wave properties. Scientific and technical challenges for the next few years are described.
Gunter Stober, Alexander Kozlovsky, Alan Liu, Zishun Qiao, Masaki Tsutsumi, Chris Hall, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, Patrick J. Espy, Robert E. Hibbins, and Nicholas Mitchell
Atmos. Meas. Tech., 14, 6509–6532, https://doi.org/10.5194/amt-14-6509-2021, https://doi.org/10.5194/amt-14-6509-2021, 2021
Short summary
Short summary
Wind observations at the edge to space, 70–110 km altitude, are challenging. Meteor radars have become a widely used instrument to obtain mean wind profiles above an instrument for these heights. We describe an advanced mathematical concept and present a tomographic analysis using several meteor radars located in Finland, Sweden and Norway, as well as Chile, to derive the three-dimensional flow field. We show an example of a gravity wave decelerating the mean flow.
Ekaterina Vorobeva, Marine De Carlo, Alexis Le Pichon, Patrick Joseph Espy, and Sven Peter Näsholm
Ann. Geophys., 39, 515–531, https://doi.org/10.5194/angeo-39-515-2021, https://doi.org/10.5194/angeo-39-515-2021, 2021
Short summary
Short summary
Our approach compares infrasound data and simulated microbarom soundscapes in multiple directions. Data recorded during 2014–2019 at Infrasound Station 37 in Norway were processed and compared to model results in different aspects (directional distribution, signal amplitude, and ability to track atmospheric changes during extreme events). The results reveal good agreement between the model and data. The approach has potential for near-real-time atmospheric and microbarom diagnostics.
Willem E. van Caspel, Patrick J. Espy, Robert E. Hibbins, and John P. McCormack
Ann. Geophys., 38, 1257–1265, https://doi.org/10.5194/angeo-38-1257-2020, https://doi.org/10.5194/angeo-38-1257-2020, 2020
Short summary
Short summary
Global-scale wind measurements from the upper regions of the atmosphere are used to isolate those atmospheric waves that follow the apparent motion of the sun over the course of a day. We present 16 years of near-continuous measurements, demonstrating the unique capabilities of the array of high-latitude SuperDARN radars. The validation steps outlined in our work also provide a methodology for future studies using wind measurements from the (expanding) network of SuperDARN radars.
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
Short summary
Short summary
Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Christoph Franzen, Patrick Joseph Espy, and Robert Edward Hibbins
Atmos. Chem. Phys., 20, 333–343, https://doi.org/10.5194/acp-20-333-2020, https://doi.org/10.5194/acp-20-333-2020, 2020
Short summary
Short summary
Ground-based observations of the hydroxyl (OH) airglow have indicated that the rotational energy levels may not be in thermal equilibrium with the surrounding gas. Here we use simulations of the OH airglow to show that temperature changes across the extended airglow layer, either climatological or those temporarily caused by atmospheric waves, can mimic this effect for thermalized OH. Thus, these must be considered in order to quantify the non-thermal nature of the OH airglow.
Stefan Bender, Miriam Sinnhuber, Patrick J. Espy, and John P. Burrows
Atmos. Chem. Phys., 19, 2135–2147, https://doi.org/10.5194/acp-19-2135-2019, https://doi.org/10.5194/acp-19-2135-2019, 2019
Short summary
Short summary
We present an empirical model for nitric oxide (NO) in the mesosphere (60–90 km) derived from SCIAMACHY limb scan data. Our model relates the daily (longitudinally) averaged NO number densities from SCIAMACHY as a function of geomagnetic latitude to the solar Lyman-alpha and the geomagnetic AE indices. We use a non-linear regression model, incorporating a finite and seasonally varying lifetime for the geomagnetically induced NO.
Amirmahdi Zarboo, Stefan Bender, John P. Burrows, Johannes Orphal, and Miriam Sinnhuber
Atmos. Meas. Tech., 11, 473–487, https://doi.org/10.5194/amt-11-473-2018, https://doi.org/10.5194/amt-11-473-2018, 2018
Short summary
Short summary
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). 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. These observations provide information about the chemistry and dynamics and can be used to infer ozone, solar heating rates, and temperature in the MLT.
Christoph Franzen, Robert Edward Hibbins, Patrick Joseph Espy, and Anlaug Amanda Djupvik
Atmos. Meas. Tech., 10, 3093–3101, https://doi.org/10.5194/amt-10-3093-2017, https://doi.org/10.5194/amt-10-3093-2017, 2017
Short summary
Short summary
We discuss a technique to extract the hydroxyl (OH) airglow signal from routine astronomical spectroscopic observations from the Nordic Optical Telescope. Emission spectra from the vibrational manifold from v′ = 9 down to v′ = 3. The fitted rotational temperature distribution with v′ agrees with model conditions and the preponderance of previous work. We highlight the potential for archived and future observations with unprecedented spatial and temporal resolutions.
Stefan Lossow, Farahnaz Khosrawi, Gerald E. Nedoluha, Faiza Azam, Klaus Bramstedt, John. P. Burrows, Bianca M. Dinelli, Patrick Eriksson, Patrick J. Espy, Maya García-Comas, John C. Gille, Michael Kiefer, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Gabriele P. Stiller, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 10, 1111–1137, https://doi.org/10.5194/amt-10-1111-2017, https://doi.org/10.5194/amt-10-1111-2017, 2017
Bernd Funke, William Ball, Stefan Bender, Angela Gardini, V. Lynn Harvey, Alyn Lambert, Manuel López-Puertas, Daniel R. Marsh, Katharina Meraner, Holger Nieder, Sanna-Mari Päivärinta, Kristell Pérot, Cora E. Randall, Thomas Reddmann, Eugene Rozanov, Hauke Schmidt, Annika Seppälä, Miriam Sinnhuber, Timofei Sukhodolov, Gabriele P. Stiller, Natalia D. Tsvetkova, Pekka T. Verronen, Stefan Versick, Thomas von Clarmann, Kaley A. Walker, and Vladimir Yushkov
Atmos. Chem. Phys., 17, 3573–3604, https://doi.org/10.5194/acp-17-3573-2017, https://doi.org/10.5194/acp-17-3573-2017, 2017
Short summary
Short summary
Simulations from eight atmospheric models have been compared to tracer and temperature observations from seven satellite instruments in order to evaluate the energetic particle indirect effect (EPP IE) during the perturbed northern hemispheric (NH) winter 2008/2009. Models are capable to reproduce the EPP IE in dynamically and geomagnetically quiescent NH winter conditions. The results emphasize the need for model improvements in the dynamical representation of elevated stratopause events.
Stefan Bender, Miriam Sinnhuber, Martin Langowski, and John P. Burrows
Atmos. Meas. Tech., 10, 209–220, https://doi.org/10.5194/amt-10-209-2017, https://doi.org/10.5194/amt-10-209-2017, 2017
Short summary
Short summary
We present the retrieval of NO number densities from 60 km to 85 km from measurements of SCIAMACHY/Envisat in its nominal limb mode (0–91 km). We derive the densities from the NO gamma bands (230–300 nm). Using prior input reduces the incorrect attribution of NO from the lower thermosphere. The SCIAMACHY nominal limb scans provide almost 10 years of daily NO data in this altitude range, a unique data record to constrain NO in the mesosphere for testing and validating chemistry climate models.
S. Bender, M. Sinnhuber, T. von Clarmann, G. Stiller, B. Funke, M. López-Puertas, J. Urban, K. Pérot, K. A. Walker, and J. P. Burrows
Atmos. Meas. Tech., 8, 4171–4195, https://doi.org/10.5194/amt-8-4171-2015, https://doi.org/10.5194/amt-8-4171-2015, 2015
Short summary
Short summary
We compare the nitric oxide (NO) daily zonal mean number density data sets in the mesosphere and lower thermosphere (MLT, 60km to 150km) from four instruments: ACE-FTS (2004--2010), MIPAS (2005--2012), SCIAMACHY (2008--2012), and SMR (2003--2012). We find that these data sets from different instruments consistently constrain NO in the MLT. Thus, they offer reliable forcing inputs for climate and chemistry climate models as an initial step to include solar and geomagnetic activity.
N. H. Stray, Y. J. Orsolini, P. J. Espy, V. Limpasuvan, and R. E. Hibbins
Atmos. Chem. Phys., 15, 4997–5005, https://doi.org/10.5194/acp-15-4997-2015, https://doi.org/10.5194/acp-15-4997-2015, 2015
Short summary
Short summary
Planetary wave activity measured in the mesosphere to lower thermosphere is shown to increase drastically after strong stratospheric polar cap wind reversals associated with sudden stratospheric warmings. In addition, a moderate but significant correlation was found between planetary wave enhancement in the mesosphere to lower thermosphere and all stratospheric polar cap wind reversals, irrespective of the strength of the reversal.
R. J. de Wit, R. E. Hibbins, P. J. Espy, and E. A. Hennum
Ann. Geophys., 33, 309–319, https://doi.org/10.5194/angeo-33-309-2015, https://doi.org/10.5194/angeo-33-309-2015, 2015
Short summary
Short summary
Sudden stratospheric warmings (SSWs) are a natural laboratory to study vertical and horizontal coupling throughout the whole atmosphere. This study presents MLS derived pole-to-pole temperature anomalies associated with the 2013 major SSW. The results provide observational evidence for interhemispheric coupling, and the wave-mean flow interactions thought to be responsible for the formation of temperature anomalies in the summer hemisphere.
T. D. Demissie, P. J. Espy, N. H. Kleinknecht, M. Hatlen, N. Kaifler, and G. Baumgarten
Atmos. Chem. Phys., 14, 12133–12142, https://doi.org/10.5194/acp-14-12133-2014, https://doi.org/10.5194/acp-14-12133-2014, 2014
Short summary
Short summary
Summertime gravity waves detected in noctilucent clouds (NLCs) between 64◦ and 74◦N are found to have a similar climatology to those observed between 60◦ and 64◦N, and their direction of propagation is to the north and northeast as observed south of 64◦N. However, a unique population of fast, short wavelength waves propagating towards the SW is observed in the NLC. The sources of the prominent wave structures observed in the NLC are likely to be from waves propagating from near the tropopause.
M. Daae, C. Straub, P. J. Espy, and D. A. Newnham
Earth Syst. Sci. Data, 6, 105–115, https://doi.org/10.5194/essd-6-105-2014, https://doi.org/10.5194/essd-6-105-2014, 2014
S. Bender, M. Sinnhuber, J. P. Burrows, M. Langowski, B. Funke, and M. López-Puertas
Atmos. Meas. Tech., 6, 2521–2531, https://doi.org/10.5194/amt-6-2521-2013, https://doi.org/10.5194/amt-6-2521-2013, 2013
T. D. Demissie, N. H. Kleinknecht, R. E. Hibbins, P. J. Espy, and C. Straub
Ann. Geophys., 31, 1279–1284, https://doi.org/10.5194/angeo-31-1279-2013, https://doi.org/10.5194/angeo-31-1279-2013, 2013
C. Straub, P. J. Espy, R. E. Hibbins, and D. A. Newnham
Earth Syst. Sci. Data, 5, 199–208, https://doi.org/10.5194/essd-5-199-2013, https://doi.org/10.5194/essd-5-199-2013, 2013
Related subject area
Subject: Earth's ionosphere & aeronomy | Keywords: Auroral ionosphere
The altitude of green OI 557.7 nm and blue N2+ 427.8 nm aurora
Reconstruction of precipitating electrons and three-dimensional structure of a pulsating auroral patch from monochromatic auroral images obtained from multiple observation points
Spatio-temporal development of large-scale auroral electrojet currents relative to substorm onsets
Observations of sunlit N2+ aurora at high altitudes during the RENU2 flight
Daniel K. Whiter, Noora Partamies, Björn Gustavsson, and Kirsti Kauristie
Ann. Geophys., 41, 1–12, https://doi.org/10.5194/angeo-41-1-2023, https://doi.org/10.5194/angeo-41-1-2023, 2023
Short summary
Short summary
We measured the height of green and blue aurorae using thousands of camera images recorded over a 7-year period. Both colours are typically brightest at about 114 km altitude. When they peak at higher altitudes the blue aurora is usually higher than the green aurora. This information will help other studies which need an estimate of the auroral height. We used a computer model to explain our observations and to investigate how the green aurora is produced.
Mizuki Fukizawa, Takeshi Sakanoi, Yoshimasa Tanaka, Yasunobu Ogawa, Keisuke Hosokawa, Björn Gustavsson, Kirsti Kauristie, Alexander Kozlovsky, Tero Raita, Urban Brändström, and Tima Sergienko
Ann. Geophys., 40, 475–484, https://doi.org/10.5194/angeo-40-475-2022, https://doi.org/10.5194/angeo-40-475-2022, 2022
Short summary
Short summary
The pulsating auroral generation mechanism has been investigated by observing precipitating electrons using rockets or satellites. However, it is difficult for such observations to distinguish temporal changes from spatial ones. In this study, we reconstructed the horizontal 2-D distribution of precipitating electrons using only auroral images. The 3-D aurora structure was also reconstructed. We found that there were both spatial and temporal changes in the precipitating electron energy.
Sebastian Käki, Ari Viljanen, Liisa Juusola, and Kirsti Kauristie
Ann. Geophys., 40, 107–119, https://doi.org/10.5194/angeo-40-107-2022, https://doi.org/10.5194/angeo-40-107-2022, 2022
Short summary
Short summary
During auroral substorms, the ionospheric electric currents change rapidly, and a large amount of energy is dissipated. We combine ionospheric current data derived from the Swarm satellite mission with the substorm database from the SuperMAG ground magnetometer network. We obtain statistics of the strength and location of the currents relative to the substorm onset. Our results show that low-earth orbit satellites give a coherent picture of the main features in the substorm current system.
Pål Gunnar Ellingsen, Dag Lorentzen, David Kenward, James H. Hecht, J. Scott Evans, Fred Sigernes, and Marc Lessard
Ann. Geophys., 39, 849–859, https://doi.org/10.5194/angeo-39-849-2021, https://doi.org/10.5194/angeo-39-849-2021, 2021
Short summary
Short summary
Using the RENU2 rocket and ground-based instruments, we show that significant parts of the blue aurora above Svalbard at the time of launch were sunlit aurora. A sunlit aurora occurs when nitrogen molecules are ionised by extreme UV sunlight and subsequently hit by electrons from the Sun, resulting in blue and violet emissions. Understanding the source of an auroral emission gives insight into the interaction between the Sun and the Earth's upper atmosphere.
Cited articles
Ajello, J. M., Evans, J. S., Veibell, V., Malone, C. P., Holsclaw, G. M., Hoskins, A. C., Lee, R. A., McClintock, W. E., Aryal, S., Eastes, R. W., and Schneider, N.: The UV Spectrum of the Lyman–Birge–Hopfield Band System of N2 Induced by Cascading from Electron Impact, J. Geophys. Res.-Space, 125, e2019JA027546, https://doi.org/10.1029/2019ja027546, 2020. a
Aksnes, A., Stadsnes, J., Østgaard, N., Germany, G. A., Oksavik, K., Vondrak, R. R., Brekke, A., and Løvhaug, U. P.: Height profiles of the ionospheric electron density derived using space-based remote sensing of UV and X ray emissions and EISCAT radar data: A ground-truth experiment, J. Geophys. Res.-Space, 111, A02 301, https://doi.org/10.1029/2005ja011331, 2006. a, b, c, d, e, f, g
Banks, P. M., Chappell, C. R., and Nagy, A. F.: A new model for the interaction of auroral electrons with the atmosphere: Spectral degradation, backscatter, optical emission, and ionization, J. Geophys. Res., 79, 1459–1470, https://doi.org/10.1029/ja079i010p01459, 1974. a, b, c
Bender, S.: st-bender/pyeppaurora: Version 0.0.5, Zenodo [code], https://doi.org/10.5281/zenodo.4298137, 2020. a
Brasseur, G. P. and Solomon, S.: Aeronomy of the Middle Atmosphere, Atmospheric and Oceanographic Sciences Library, 32, Springer-Verlag, Dordrecht, the Netherlands, https://doi.org/10.1007/1-4020-3824-0, 2005. a
Dupuy, E., Walker, K. A., Kar, J., Boone, C. D., McElroy, C. T., Bernath, P. F., Drummond, J. R., Skelton, R., McLeod, S. D., Hughes, R. C., Nowlan, C. R., Dufour, D. G., Zou, J., Nichitiu, F., Strong, K., Baron, P., Bevilacqua, R. M., Blumenstock, T., Bodeker, G. E., Borsdorff, T., Bourassa, A. E., Bovensmann, H., Boyd, I. S., Bracher, A., Brogniez, C., Burrows, J. P., Catoire, V., Ceccherini, S., Chabrillat, S., Christensen, T., Coffey, M. T., Cortesi, U., Davies, J., De Clercq, C., Degenstein, D. A., De Mazière, M., Demoulin, P., Dodion, J., Firanski, B., Fischer, H., Forbes, G., Froidevaux, L., Fussen, D., Gerard, P., Godin-Beekmann, S., Goutail, F., Granville, J., Griffith, D., Haley, C. S., Hannigan, J. W., Höpfner, M., Jin, J. J., Jones, A., Jones, N. B., Jucks, K., Kagawa, A., Kasai, Y., Kerzenmacher, T. E., Kleinböhl, A., Klekociuk, A. R., Kramer, I., Küllmann, H., Kuttippurath, J., Kyrölä, E., Lambert, J.-C., Livesey, N. J., Llewellyn, E. J., Lloyd, N. D., Mahieu, E., Manney, G. L., Marshall, B. T., McConnell, J. C., McCormick, M. P., McDermid, I. S., McHugh, M., McLinden, C. A., Mellqvist, J., Mizutani, K., Murayama, Y., Murtagh, D. P., Oelhaf, H., Parrish, A., Petelina, S. V., Piccolo, C., Pommereau, J.-P., Randall, C. E., Robert, C., Roth, C., Schneider, M., Senten, C., Steck, T., Strandberg, A., Strawbridge, K. B., Sussmann, R., Swart, D. P. J., Tarasick, D. W., Taylor, J. R., Tétard, C., Thomason, L. W., Thompson, A. M., Tully, M. B., Urban, J., Vanhellemont, F., Vigouroux, C., von Clarmann, T., von der Gathen, P., von Savigny, C., Waters, J. W., Witte, J. C., Wolff, M., and Zawodny, J. M.: Validation of ozone measurements from the Atmospheric Chemistry Experiment (ACE), Atmos. Chem. Phys., 9, 287–343, https://doi.org/10.5194/acp-9-287-2009, 2009. a, b
EISCAT: CEDAR Madrigal Database, available at: http://cedar.openmadrigal.org, last access: 21 September 2020. a
Fang, X., Randall, C. E., Lummerzheim, D., Solomon, S. C., Mills, M. J., Marsh, D. R., Jackman, C. H., Wang, W., and Lu, G.: Electron impact ionization: A new parameterization for 100 eV to 1 MeV electrons, J. Geophys. Res.-Space, 113, A09311, https://doi.org/10.1029/2008ja013384, 2008. a, b, c, d
Funke, B., López-Puertas, M., Gil-López, S., von Clarmann, T., Stiller, G. P., Fischer, H., and Kellmann, S.: Downward transport of upper atmospheric NOx into the polar stratosphere and lower mesosphere during the Antarctic 2003 and Arctic 2002/2003 winters, J. Geophys. Res.-Atmos., 110, D24 308, https://doi.org/10.1029/2005JD006463, 2005. a
Funke, B., Ball, W., Bender, S., Gardini, A., Harvey, V. L., Lambert, A., López-Puertas, M., Marsh, D. R., Meraner, K., Nieder, H., Päivärinta, S.-M., Pérot, K., Randall, C. E., Reddmann, T., Rozanov, E., Schmidt, H., Seppälä, A., Sinnhuber, M., Sukhodolov, T., Stiller, G. P., Tsvetkova, N. D., Verronen, P. T., Versick, S., von Clarmann, T., Walker, K. A., and Yushkov, V.: HEPPA-II model–measurement intercomparison project: EPP indirect effects during the dynamically perturbed NH winter 2008–2009, Atmos. Chem. Phys., 17, 3573–3604, https://doi.org/10.5194/acp-17-3573-2017, 2017. a
Germany, G. A., Torr, M. R., Richards, P. G., and Torr, D. G.: The dependence of modeled OI 1356 and N2 Lyman Birge Hopfield auroral emissions on the neutral atmosphere, J. Geophys. Res.-Space, 95, 7725, https://doi.org/10.1029/ja095ia06p07725, 1990. a, b
Khazanov, G. V. and Chen, M. W.: Why Atmospheric Backscatter Is Important in the Formation of Electron Precipitation in the Diffuse Aurora, J. Geophys. Res.-Space, 126, e2021JA029211, https://doi.org/10.1029/2021ja029211, 2021. a, b, c
Knight, H. K.: Auroral ionospheric E region parameters obtained from satellite- based far-ultraviolet and ground-based ionosonde observations – effects of proton precipitation, Ann. Geophys., 39, 105–118, https://doi.org/10.5194/angeo-39-105-2021, 2021. a
Knight, H. K., Galkin, I. A., Reinisch, B. W., and Zhang, Y.: Auroral Ionospheric E Region Parameters Obtained From Satellite-Based Far Ultraviolet and Ground-Based Ionosonde Observations: Data, Methods, and Comparisons, J. Geophys. Res.-Space, 123, 6065–6089, https://doi.org/10.1029/2017ja024822, https://doi.org/10.1029/2017JA024822, 2018. a, b, c, d
Lehtinen, M. S. and Huuskonen, A.: General incoherent scatter analysis and GUISDAP, J. Atmos. Terr. Phys., 58, 435–452, https://doi.org/10.1016/0021-9169(95)00047-x, 1996. a
Lossow, S., Khosrawi, F., Kiefer, M., Walker, K. A., Bertaux, J.-L., Blanot, L., Russell, J. M., Remsberg, E. E., Gille, J. C., Sugita, T., Sioris, C. E., Dinelli, B. M., Papandrea, E., Raspollini, P., García-Comas, M., Stiller, G. P., von Clarmann, T., Dudhia, A., Read, W. G., Nedoluha, G. E., Damadeo, R. P., Zawodny, J. M., Weigel, K., Rozanov, A., Azam, F., Bramstedt, K., Noël, S., Burrows, J. P., Sagawa, H., Kasai, Y., Urban, J., Eriksson, P., Murtagh, D. P., Hervig, M. E., Högberg, C., Hurst, D. F., and Rosenlof, K. H.: The SPARC water vapour assessment II: profile-to-profile comparisons of stratospheric and lower mesospheric water vapour data sets obtained from satellites, Atmos. Meas. Tech., 12, 2693–2732, https://doi.org/10.5194/amt-12-2693-2019, 2019. a, b
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and Versick, S.: Solar forcing for CMIP6 (v3.2), Geosci. Model Dev., 10, 2247–2302, https://doi.org/10.5194/gmd-10-2247-2017, 2017. a
Paxton, L. J. and Zhang, Y.: Space Weather Fundamentals, chap. Far ultraviolet imaging of the aurora, 213–244, CRC Press Laurel, MD, USA, 2016. a
Paxton, L. J., Meng, C.-I., Fountain, G. H., Ogorzalek, B. S., Darlington, E. H., Gary, S. A., Goldsten, J. O., Kusnierkiewicz, D. Y., Lee, S. C., Linstrom, L. A., Maynard, J. J., Peacock, K., Persons, D. F., and Smith, B. E.: Special sensor ultraviolet spectrographic imager: an instrument description, in: Instrumentation for Planetary and Terrestrial Atmospheric Remote Sensing, edited by: Chakrabarti, S. and Christensen, A. B., SPIE, https://doi.org/10.1117/12.60595, 1992. a, b, c, d
Paxton, L. J., Meng, C.-I., Fountain, G. H., Ogorzalek, B. S., Darlington, E. H., Gary, S. A., Goldsten, J. O., Kusnierkiewicz, D. Y., Lee, S. C., Linstrom, L. A., Maynard, J. J., Peacock, K., Persons, D. F., Smith, B. E., Strickland, D. J., and Daniell Jr., R. E.: SSUSI – Horizon-to-horizon and limb-viewing spectrographic imager for remote sensing of environmental parameters, in: Ultraviolet Technology IV, edited by: Huffman, R. E., SPIE, https://doi.org/10.1117/12.140846, 1993. a, b, c, d
Paxton, L. J., Morrison, D., Zhang, Y., Kil, H., Wolven, B., Ogorzalek, B. S., Humm, D. C., and Meng, C.-I.: Validation of remote sensing products produced by the Special Sensor Ultraviolet Scanning Imager (SSUSI): a far UV-imaging spectrograph on DMSP F-16, in: Optical Spectroscopic Techniques, Remote Sensing, and Instrumentation for Atmospheric and Space Research IV, edited by: Larar, A. M. and Mlynczak, M. G., SPIE, https://doi.org/10.1117/12.454268, 2002. a
Paxton, L. J., Schaefer, R. K., Zhang, Y., and Kil, H.: Far ultraviolet instrument technology, J. Geophys. Res.-Space, 122, 2706–2733, https://doi.org/10.1002/2016ja023578, 2017. a, b, c, d
Paxton, L. J., Schaefer, R. K., Zhang, Y., Kil, H., and Hicks, J. E.: SSUSI and SSUSI-Lite: Providing Space Situational Awareness and Support for Over 25 Years, Johns Hopkins APL Tech. D., 34, 388–400, 2018. a
Picone, J. M., Hedin, A. E., Drob, D. P., and Aikin, A. C.: NRLMSISE-00 empirical model of the atmosphere: Statistical comparisons and scientific issues, J. Geophys. Res.-Space, 107, 1468, https://doi.org/10.1029/2002JA009430, 2002. a
Porter, H. S., Jackman, C. H., and Green, A. E. S.: Efficiencies for production of atomic nitrogen and oxygen by relativistic proton impact in air, J. Chem. Phys., 65, 154–167, https://doi.org/10.1063/1.432812, 1976. a
Randall, C. E.: Validation of POAM III ozone: Comparisons with ozonesonde and satellite data, J. Geophys. Res.-Atmos., 108, 4367, https://doi.org/10.1029/2002jd002944, 2003. a
Randall, C. E.: Stratospheric effects of energetic particle precipitation in 2003–2004, Geophys. Res. Lett., 32, L05 802, https://doi.org/10.1029/2004gl022003, 2005. a
Randall, C. E., Siskind, D. E., and Bevilacqua, R. M.: Stratospheric NOx enhancements in the Southern Hemisphere Vortex in winter/spring of 2000, Geophys. Res. Lett., 28, 2385–2388, https://doi.org/10.1029/2000gl012746, 2001. a
Randall, C. E., Harvey, V. L., Siskind, D. E., France, J., Bernath, P. F., Boone, C. D., and Walker, K. A.: NOx descent in the Arctic middle atmosphere in early 2009, Geophys. Res. Lett., 36, L18811, https://doi.org/10.1029/2009GL039706, 2009. a, b, c
Rees, M.: Auroral electrons, Space Sci. Rev., 10, 413–441, https://doi.org/10.1007/bf00203621, 1969. a
Rees, M. H.: Auroral ionization and excitation by incident energetic electrons, Planet. Space Sci., 11, 1209–1218, https://doi.org/10.1016/0032-0633(63)90252-6, 1963. a, b, c
Robinson, R. M. and Vondrak, R. R.: Validation of techniques for space based remote sensing of auroral precipitation and its ionospheric effects, Space Sci. Rev., 69, 331–407, https://doi.org/10.1007/bf02101699, 1994. a, b, c
Schröter, J., Heber, B., Steinhilber, F., and Kallenrode, M.: Energetic particles in the atmosphere: A Monte-carlo simulation, Adv. Space Res., 37, 1597–1601, https://doi.org/10.1016/j.asr.2005.05.085, 2006. a
Smith-Johnsen, C., Marsh, D. R., Orsolini, Y., Tyssøy, H. N., Hendrickx, K., Sandanger, M. I., Ødegaard, L.-K. G., and Stordal, F.: Nitric Oxide Response to the April 2010 Electron Precipitation Event: Using WACCM and WACCM-D With and Without Medium-Energy Electrons, J. Geophys. Res.-Space, 123, 5232–5245, https://doi.org/10.1029/2018ja025418, 2018. a, b
SSUSI: Data Products, available at: https://ssusi.jhuapl.edu/data_products, last access: 21 September 2020. a
Strickland, D., Bishop, J., Evans, J., Majeed, T., Shen, P., Cox, R., Link, R., and Huffman, R.: Atmospheric Ultraviolet Radiance Integrated Code (AURIC): theory, software architecture, inputs, and selected results, J. Quant. Spectrosc. Ra., 62, 689–742, https://doi.org/10.1016/s0022-4073(98)00098-3, 1999. a, b, c
Strickland, D. J., Jasperse, J. R., and Whalen, J. A.: Dependence of auroral FUV emissions on the incident electron spectrum and neutral atmosphere, J. Geophys. Res.-Space, 88, 8051, https://doi.org/10.1029/ja088ia10p08051, 1983. a, b, c
Strong, K., Wolff, M. A., Kerzenmacher, T. E., Walker, K. A., Bernath, P. F., Blumenstock, T., Boone, C., Catoire, V., Coffey, M., De Mazière, M., Demoulin, P., Duchatelet, P., Dupuy, E., Hannigan, J., Höpfner, M., Glatthor, N., Griffith, D. W. T., Jin, J. J., Jones, N., Jucks, K., Kuellmann, H., Kuttippurath, J., Lambert, A., Mahieu, E., McConnell, J. C., Mellqvist, J., Mikuteit, S., Murtagh, D. P., Notholt, J., Piccolo, C., Raspollini, P., Ridolfi, M., Robert, C., Schneider, M., Schrems, O., Semeniuk, K., Senten, C., Stiller, G. P., Strandberg, A., Taylor, J., Tétard, C., Toohey, M., Urban, J., Warneke, T., and Wood, S.: Validation of ACE-FTS N2O measurements, Atmos. Chem. Phys., 8, 4759–4786, https://doi.org/10.5194/acp-8-4759-2008, 2008. a
Torr, M. R., Torr, D. G., Zukic, M., Johnson, R. B., Ajello, J., Banks, P., Clark, K., Cole, K., Keffer, C., Parks, G., Tsurutani, B., and Spann, J.: A far ultraviolet imager for the International Solar-Terrestrial Physics Mission, Space Sci. Rev., 71, 329–383, https://doi.org/10.1007/bf00751335, 1995. a
Turunen, E., Verronen, P. T., Seppälä, A., Rodger, C. J., Clilverd, M. A., Tamminen, J., Enell, C.-F., and Ulich, T.: Impact of different energies of precipitating particles on NOx generation in the middle and upper atmosphere during geomagnetic storms, J. Atmos. Sol.-Terr. Phy., 71, 1176–1189, https://doi.org/10.1016/j.jastp.2008.07.005, 2009. a
van de Kamp, M., Seppälä, A., Clilverd, M. A., Rodger, C. J., Verronen, P. T., and Whittaker, I. C.: A model providing long-term data sets of energetic electron precipitation during geomagnetic storms, J. Geophys. Res.-Atmos., 121, 12520–12540, https://doi.org/10.1002/2015jd024212, 2016.
a
Verronen, P. T., Seppälä, A., Clilverd, M. A., Rodger, C. J., Kyrölä, E., Enell, C.-F., Ulich, T., and Turunen, E.: Diurnal variation of ozone depletion during the October–November 2003 solar proton events, J. Geophys. Res.-Space, 110, A09S32, https://doi.org/10.1029/2004ja010932, 2005. a
Vickrey, J. F., Vondrak, R. R., and Matthews, S. J.: Energy deposition by precipitating particles and Joule dissipation in the auroral ionosphere, J. Geophys. Res.-Space, 87, 5184–5196, https://doi.org/10.1029/ja087ia07p05184, 1982. a, b, c
Vondrak, R. R. and Baron, M. J.: Radar measurements of the latitudinal variation of auroral ionization, Radio Sci., 11, 939–946, https://doi.org/10.1029/rs011i011p00939, 1976. a, b, c, d
Wissing, J. M. and Kallenrode, M.-B.: Atmospheric Ionization Module Osnabrück (AIMOS): A 3-D model to determine atmospheric ionization by energetic charged particles from different populations, J. Geophys. Res.-Space, 114, A06 104, https://doi.org/10.1029/2008ja013884, 2009. a, b, c
Short summary
The coupling of the atmosphere to the space environment has become recognized as an important driver of atmospheric chemistry and dynamics. We have validated the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) products for average electron energy and electron energy flux by comparison to EISCAT electron density profiles. The good agreement shows that SSUSI far-UV observations can be used to provide ionization rate profiles throughout the auroral region.
The coupling of the atmosphere to the space environment has become recognized as an important...
