Articles | Volume 32, issue 4
https://doi.org/10.5194/angeo-32-367-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/angeo-32-367-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr – Part 3: Improved representation of solar cycle 11
M. Lockwood
Meteorology Department, University of Reading, Reading, Berkshire, UK
H. Nevanlinna
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
M. Vokhmyanin
St. Petersburg University, St. Petersburg, 198504, Russia
D. Ponyavin
St. Petersburg University, St. Petersburg, 198504, Russia
S. Sokolov
IZMIRAN, St. Petersburg, Russia
L. Barnard
Meteorology Department, University of Reading, Reading, Berkshire, UK
M. J. Owens
Meteorology Department, University of Reading, Reading, Berkshire, UK
R. G. Harrison
Meteorology Department, University of Reading, Reading, Berkshire, UK
A. P. Rouillard
Institut de Recherche en Astrophysique et Planétologie, 9 Ave. du Colonel Roche, BP 44 346, 31028 Toulouse Cedex 4, France
C. J. Scott
Meteorology Department, University of Reading, Reading, Berkshire, UK
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Long-term change in the ionosphere are expected due to increases in greenhouse gases in the lower atmosphere. Empirical formulae are used to estimate height. Through comparison with independent data we show that there are seasonal and long-term biases introduced by the empirical model. We conclude that estimates of long-term changes in ionospheric height need to account for these biases.
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A network of Rayleigh lidars have been used to infer the middle atmosphere temperature bias in ECMWF ERA-5 and ERA-interim reanalyses during 1990–2017. Results show that ERA-interim exhibits a cold bias of −3 to −4 K between 10 and 1 hPa. Comparisons with ERA-5 found a smaller bias of 1 K which varies between cold and warm between 10 and 3 hPa, indicating a good thermal representation of the atmosphere to 3 hPa. These biases must be accounted for in stratospheric studies using these reanalyses.
Darielle Dexheimer, Martin Airey, Erika Roesler, Casey Longbottom, Keri Nicoll, Stefan Kneifel, Fan Mei, R. Giles Harrison, Graeme Marlton, and Paul D. Williams
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A tethered-balloon system deployed supercooled liquid water content sondes and fiber optic distributed temperature sensing to collect in situ atmospheric measurements within mixed-phase Arctic clouds. These data were validated against collocated surface-based and remote sensing datasets. From these measurements and sensor evaluations, tethered-balloon flights are shown to offer an effective method of collecting data to inform numerical models and calibrate remote sensing instrumentation.
Christopher J. Scott and Patrick Major
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The variability of the Earth's ionosphere (the electrified region of the Earth's upper atmosphere) results from external forcing from above (through solar activity and space weather effects) and from below (via natural sources such as lightning storms and tectonics). Bombing raids over Europe during World War II were used to determine the quantitative impact of explosions on the ionosphere. It was found that raids using more than 300 tonnes of explosives weakened the ionosphere for up to 5 h.
Simon Thomas, Mathew Owens, Mike Lockwood, and Chris Owen
Ann. Geophys., 35, 825–838, https://doi.org/10.5194/angeo-35-825-2017, https://doi.org/10.5194/angeo-35-825-2017, 2017
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Galactic cosmic rays are high-energy particles from outside of the solar system. The products of their interaction with the atmosphere are counted by a network of neutron monitors. The number of cosmic rays reaching Earth is affected by the magnetic field embedded in the solar wind. The result is a number of regular variations in the neutron monitor data, including a diurnal variation. We have found that this variation is influenced by 1–2 h by the polarity of the Sun's magnetic field.
Katja Matthes, Bernd Funke, Monika E. Andersson, Luke Barnard, Jürg Beer, Paul Charbonneau, Mark A. Clilverd, Thierry Dudok de Wit, Margit Haberreiter, Aaron Hendry, Charles H. Jackman, Matthieu Kretzschmar, Tim Kruschke, Markus Kunze, Ulrike Langematz, Daniel R. Marsh, Amanda C. Maycock, Stergios Misios, Craig J. Rodger, Adam A. Scaife, Annika Seppälä, Ming Shangguan, Miriam Sinnhuber, Kleareti Tourpali, Ilya Usoskin, Max van de Kamp, Pekka T. Verronen, and Stefan Versick
Geosci. Model Dev., 10, 2247–2302, https://doi.org/10.5194/gmd-10-2247-2017, https://doi.org/10.5194/gmd-10-2247-2017, 2017
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The solar forcing dataset for climate model experiments performed for the upcoming IPCC report is described. This dataset provides the radiative and particle input of solar variability on a daily basis from 1850 through to 2300. With this dataset a better representation of natural climate variability with respect to the output of the Sun is provided which provides the most sophisticated and comprehensive respresentation of solar variability that has been used in climate model simulations so far.
C. J. Scott and R. Stamper
Ann. Geophys., 33, 449–455, https://doi.org/10.5194/angeo-33-449-2015, https://doi.org/10.5194/angeo-33-449-2015, 2015
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We use a novel technique to infer long-term compositional changes to the thermosphere from the annual variation of the ionospheric F2 region. A global analysis of these data reveal that long-term changes differ between geographic locations in a way that is very similar to the observed variation in the ionospheric response to increased atmospheric CO2 levels. In the absence of long-term measurements of thermospheric composition, further, detailed, modelling work is required.
M. Lockwood, H. Nevanlinna, L. Barnard, M. J. Owens, R. G. Harrison, A. P. Rouillard, and C. J. Scott
Ann. Geophys., 32, 383–399, https://doi.org/10.5194/angeo-32-383-2014, https://doi.org/10.5194/angeo-32-383-2014, 2014
H. Nevanlinna
Hist. Geo Space. Sci., 5, 75–80, https://doi.org/10.5194/hgss-5-75-2014, https://doi.org/10.5194/hgss-5-75-2014, 2014
C. J. Scott, R. Stamper, and H. Rishbeth
Ann. Geophys., 32, 113–119, https://doi.org/10.5194/angeo-32-113-2014, https://doi.org/10.5194/angeo-32-113-2014, 2014
J.-B. Renard, S. N. Tripathi, M. Michael, A. Rawal, G. Berthet, M. Fullekrug, R. G. Harrison, C. Robert, M. Tagger, and B. Gaubicher
Atmos. Chem. Phys., 13, 11187–11194, https://doi.org/10.5194/acp-13-11187-2013, https://doi.org/10.5194/acp-13-11187-2013, 2013
M. Lockwood, L. Barnard, H. Nevanlinna, M. J. Owens, R. G. Harrison, A. P. Rouillard, and C. J. Davis
Ann. Geophys., 31, 1957–1977, https://doi.org/10.5194/angeo-31-1957-2013, https://doi.org/10.5194/angeo-31-1957-2013, 2013
M. Lockwood, L. Barnard, H. Nevanlinna, M. J. Owens, R. G. Harrison, A. P. Rouillard, and C. J. Davis
Ann. Geophys., 31, 1979–1992, https://doi.org/10.5194/angeo-31-1979-2013, https://doi.org/10.5194/angeo-31-1979-2013, 2013