Articles | Volume 23, issue 4
https://doi.org/10.5194/npg-23-215-2016
https://doi.org/10.5194/npg-23-215-2016
Research article
 | 
02 Aug 2016
Research article |  | 02 Aug 2016

Spectral characteristics of high-latitude raw 40 MHz cosmic noise signals

Chris M. Hall

Related authors

Atmospheric tomography using the Nordic Meteor Radar Cluster and Chilean Observation Network De Meteor Radars: network details and 3D-Var retrieval
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
Meteor radar observations of polar mesospheric summer echoes over Svalbard
Joel P. Younger, Iain M. Reid, Chris L. Adami, Chris M. Hall, and Masaki Tsutsumi
Atmos. Meas. Tech., 14, 5015–5027, https://doi.org/10.5194/amt-14-5015-2021,https://doi.org/10.5194/amt-14-5015-2021, 2021
Short summary
Climatology of the mesopause relative density using a global distribution of meteor radars
Wen Yi, Xianghui Xue, Iain M. Reid, Damian J. Murphy, Chris M. Hall, Masaki Tsutsumi, Baiqi Ning, Guozhu Li, Robert A. Vincent, Jinsong Chen, Jianfei Wu, Tingdi Chen, and Xiankang Dou
Atmos. Chem. Phys., 19, 7567–7581, https://doi.org/10.5194/acp-19-7567-2019,https://doi.org/10.5194/acp-19-7567-2019, 2019
Short summary
Neutral atmosphere temperature trends and variability at 90 km, 70 °N, 19 °E, 2003–2014
Silje Eriksen Holmen, Chris M. Hall, and Masaki Tsutsumi
Atmos. Chem. Phys., 16, 7853–7866, https://doi.org/10.5194/acp-16-7853-2016,https://doi.org/10.5194/acp-16-7853-2016, 2016
Short summary
Change in turbopause altitude at 52 and 70° N
Chris M. Hall, Silje E. Holmen, Chris E. Meek, Alan H. Manson, and Satonori Nozawa
Atmos. Chem. Phys., 16, 2299–2308, https://doi.org/10.5194/acp-16-2299-2016,https://doi.org/10.5194/acp-16-2299-2016, 2016
Short summary

Related subject area

Subject: Time series, machine learning, networks, stochastic processes, extreme events | Topic: Ionosphere, magnetosphere, planetary science, solar science
Quantification of magnetosphere–ionosphere coupling timescales using mutual information: response of terrestrial radio emissions and ionospheric–magnetospheric currents
Alexandra Ruth Fogg, Caitríona M. Jackman, Sandra C. Chapman, James E. Waters, Aisling Bergin, Laurent Lamy, Karine Issautier, Baptiste Cecconi, and Xavier Bonnin
Nonlin. Processes Geophys., 31, 195–206, https://doi.org/10.5194/npg-31-195-2024,https://doi.org/10.5194/npg-31-195-2024, 2024
Short summary
Nonlinear vortex solution for perturbations in the Earth's ionosphere
Miroslava Vukcevic and Luka Č. Popović
Nonlin. Processes Geophys., 27, 295–306, https://doi.org/10.5194/npg-27-295-2020,https://doi.org/10.5194/npg-27-295-2020, 2020
Short summary
The physics of space weather/solar-terrestrial physics (STP): what we know now and what the current and future challenges are
Bruce T. Tsurutani, Gurbax S. Lakhina, and Rajkumar Hajra
Nonlin. Processes Geophys., 27, 75–119, https://doi.org/10.5194/npg-27-75-2020,https://doi.org/10.5194/npg-27-75-2020, 2020
Short summary
Complex network description of the ionosphere
Shikun Lu, Hao Zhang, Xihai Li, Yihong Li, Chao Niu, Xiaoyun Yang, and Daizhi Liu
Nonlin. Processes Geophys., 25, 233–240, https://doi.org/10.5194/npg-25-233-2018,https://doi.org/10.5194/npg-25-233-2018, 2018
Evolution of fractality in space plasmas of interest to geomagnetic activity
Víctor Muñoz, Macarena Domínguez, Juan Alejandro Valdivia, Simon Good, Giuseppina Nigro, and Vincenzo Carbone
Nonlin. Processes Geophys., 25, 207–216, https://doi.org/10.5194/npg-25-207-2018,https://doi.org/10.5194/npg-25-207-2018, 2018
Short summary

Cited articles

Balasis, G., Daglis, I. A., Kapiris, P., Mandea, M., Vassiliadis, D., and Eftaxias, K.: From pre-storm activity to magnetic storms: a transition described in terms of fractal dynamics, Ann. Geophys., 24, 3557–3567, https://doi.org/10.5194/angeo-24-3557-2006, 2006.
Behera, J. K., Sinha, A. K., Singh A. K., Rawat, R., Vichare, G., Dhar, A., Pathan, B. M., Nair, K. U., Selvaraj, C., and Elango, P.: First results from imaging riometer installed at Indian Antarctic station Maitri, J. Earth Syst. Sci., 123, 593–602, 2014.
Chambers, J. M., Cleveland, W. S., Kleiner, B., and Tukey, P. A.: Graphical Methods for Data Analysis, 395 pp., Duxbury Press, Boston, Massachusetts, 1963.
Canal, C. A. G., Hojvat, C., and Tarutina, T.: Scaler mode of the Auger Observatory and sunspots, Astrophys. J. Suppl., 202, 16–22, https://doi.org/10.1088/0067-0049/202/2/16, 2012.
Delignieres, D., Ramdani, S., Lemoine, L., Torre, K., Fortes, M., and Ninot, G.: Fractal analyses for `short' time series: A re-assessment of classical methods, J. Math. Psychol., 50, 525–544, 2006.
Download
Short summary
The relative ionospheric opacity meter ("riometer") is a traditional instrument for measuring the degree to which cosmic noise is absorbed by the ionosphere and therefore how energetic the particles – electrons, protons etc. – are that cause the ionisation. We identify the same signatures in the "hour-to-days" timescale variability as reported in solar and geomagnetic disturbances. The result demonstrates the relationship between riometer data and the underlying physics for different timescales.