Articles | Volume 11, issue 1
https://doi.org/10.5194/gi-11-149-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gi-11-149-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Swarm Langmuir probes' data quality validation and future improvements
Filomena Catapano
CORRESPONDING AUTHOR
Serco c/o ESA, ESRIN, Earth Observation Directorate, Frascati, Italy
Stephan Buchert
Swedish Institute of Space Physics, Uppsala, Sweden
Enkelejda Qamili
Serco c/o ESA, ESRIN, Earth Observation Directorate, Frascati, Italy
Thomas Nilsson
Swedish Institute of Space Physics, Uppsala, Sweden
Jerome Bouffard
European Space Agency (ESA), Earth Observation Directorate, Frascati, Italy
Christian Siemes
Delft University of Technology, Delft, the Netherlands
Igino Coco
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Rome, Italy
Raffaella D'Amicis
National Institute for Astrophysics, Institute for Space Astrophysics and Planetology, Rome, Italy
Lars Tøffner-Clausen
DTU Space, Technical University of Denmark, Kongens Lyngby, Denmark
Lorenzo Trenchi
Serco c/o ESA, ESRIN, Earth Observation Directorate, Frascati, Italy
Poul Erik Holmdahl Olsen
DTU Space, Technical University of Denmark, Kongens Lyngby, Denmark
Anja Stromme
European Space Agency (ESA), Earth Observation Directorate, Frascati, Italy
Related authors
Filomena Catapano, Gaetano Zimbardo, Silvia Perri, Antonella Greco, and Anton V. Artemyev
Ann. Geophys., 34, 917–926, https://doi.org/10.5194/angeo-34-917-2016, https://doi.org/10.5194/angeo-34-917-2016, 2016
Short summary
Short summary
Spacecraft observations show that energetic ions are found in the Earth’s magnetotail, with energies ranging from tens of keV to a few hundreds of keV. In this paper we carry out test particle simulations in which protons and other ion species are injected in the Vlasov magnetic field configurations obtained by Catapano et al. (2015). Three-dimensional time-dependent stochastic electromagnetic perturbations are included in the simulation box, so that the ion acceleration process is studied.
Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Richard Essery, Ghislain Picard, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Jérôme Bouffard, Alessandro Di Bella, and Michele Scagliola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1583, https://doi.org/10.5194/egusphere-2024-1583, 2024
Preprint archived
Short summary
Short summary
Sea ice thickness is essential for climate studies. Radar altimetry has provided sea ice thickness measurement, but uncertainty arises from interaction of the signal with the snow cover. Therefore, modelling the signal interaction with the snow is necessary to improve retrieval. A radar model was used to simulate the radar signal from the snow-covered sea ice. This work paved the way to improved physical algorithm to retrieve snow depth and sea ice thickness for radar altimeter missions.
Joachim Vogt, Octav Marghitu, Adrian Blagau, Leonie Pick, Nele Stachlys, Stephan Buchert, Theodoros Sarris, Stelios Tourgaidis, Thanasis Balafoutis, Dimitrios Baloukidis, and Panagiotis Pirnaris
Geosci. Instrum. Method. Data Syst., 12, 239–257, https://doi.org/10.5194/gi-12-239-2023, https://doi.org/10.5194/gi-12-239-2023, 2023
Short summary
Short summary
Motivated by recent community interest in a satellite mission to the atmospheric lower thermosphere and ionosphere (LTI) region (100–200 km altitude), the DIPCont project is concerned with the reconstruction quality of vertical profiles of key LTI variables using dual- and single-spacecraft observations. The report introduces the probabilistic DIPCont modeling framework, demonstrates its usage by means of a set of self-consistent parametric non-isothermal models, and discusses first results.
Florent Garnier, Sara Fleury, Gilles Garric, Jérôme Bouffard, Michel Tsamados, Antoine Laforge, Marion Bocquet, Renée Mie Fredensborg Hansen, and Frédérique Remy
The Cryosphere, 15, 5483–5512, https://doi.org/10.5194/tc-15-5483-2021, https://doi.org/10.5194/tc-15-5483-2021, 2021
Short summary
Short summary
Snow depth data are essential to monitor the impacts of climate change on sea ice volume variations and their impacts on the climate system. For that purpose, we present and assess the altimetric snow depth product, computed in both hemispheres from CryoSat-2 and SARAL satellite data. The use of these data instead of the common climatology reduces the sea ice thickness by about 30 cm over the 2013–2019 period. These data are also crucial to argue for the launch of the CRISTAL satellite mission.
Joshua Dreyer, Noora Partamies, Daniel Whiter, Pål G. Ellingsen, Lisa Baddeley, and Stephan C. Buchert
Ann. Geophys., 39, 277–288, https://doi.org/10.5194/angeo-39-277-2021, https://doi.org/10.5194/angeo-39-277-2021, 2021
Short summary
Short summary
Small-scale auroral features are still being discovered and are not well understood. Where aurorae are caused by particle precipitation, the newly reported fragmented aurora-like emissions (FAEs) seem to be locally generated in the ionosphere (hence,
aurora-like). We analyse data from multiple instruments located near Longyearbyen to derive their main characteristics. They seem to occur as two types in a narrow altitude region (individually or in regularly spaced groups).
Minna Palmroth, Maxime Grandin, Theodoros Sarris, Eelco Doornbos, Stelios Tourgaidis, Anita Aikio, Stephan Buchert, Mark A. Clilverd, Iannis Dandouras, Roderick Heelis, Alex Hoffmann, Nickolay Ivchenko, Guram Kervalishvili, David J. Knudsen, Anna Kotova, Han-Li Liu, David M. Malaspina, Günther March, Aurélie Marchaudon, Octav Marghitu, Tomoko Matsuo, Wojciech J. Miloch, Therese Moretto-Jørgensen, Dimitris Mpaloukidis, Nils Olsen, Konstantinos Papadakis, Robert Pfaff, Panagiotis Pirnaris, Christian Siemes, Claudia Stolle, Jonas Suni, Jose van den IJssel, Pekka T. Verronen, Pieter Visser, and Masatoshi Yamauchi
Ann. Geophys., 39, 189–237, https://doi.org/10.5194/angeo-39-189-2021, https://doi.org/10.5194/angeo-39-189-2021, 2021
Short summary
Short summary
This is a review paper that summarises the current understanding of the lower thermosphere–ionosphere (LTI) in terms of measurements and modelling. The LTI is the transition region between space and the atmosphere and as such of tremendous importance to both the domains of space and atmosphere. The paper also serves as the background for European Space Agency Earth Explorer 10 candidate mission Daedalus.
Sharon Aol, Stephan Buchert, Edward Jurua, and Marco Milla
Ann. Geophys., 38, 1063–1080, https://doi.org/10.5194/angeo-38-1063-2020, https://doi.org/10.5194/angeo-38-1063-2020, 2020
Short summary
Short summary
Ionospheric irregularities are a common phenomenon in the low-latitude ionosphere. In this paper, we compared simultaneous observations of plasma plumes by the JULIA radar, ionogram spread F generated from ionosonde observations installed at the Jicamarca Radio Observatory, and irregularities observed in situ by Swarm to determine whether Swarm in situ observations can be used as indicators of the presence of plasma plumes and spread F on the ground.
Stephan C. Buchert
Ann. Geophys., 38, 1019–1030, https://doi.org/10.5194/angeo-38-1019-2020, https://doi.org/10.5194/angeo-38-1019-2020, 2020
Short summary
Short summary
Winds in the Earth's upper atmosphere cause magnetic and electric variations both at the ground and in space all over the Earth. According to the model of entangled dynamos the true cause is wind differences between regions in the Northern and Southern Hemispheres that are connected by the Earth's dipole-like magnetic field. The power produced in the southern dynamo heats the northern upper atmosphere and vice versa. The dynamos exist owing to this entanglement, an analogy to quantum mechanics.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
Short summary
Short summary
The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Marco Meloni, Jerome Bouffard, Tommaso Parrinello, Geoffrey Dawson, Florent Garnier, Veit Helm, Alessandro Di Bella, Stefan Hendricks, Robert Ricker, Erica Webb, Ben Wright, Karina Nielsen, Sanggyun Lee, Marcello Passaro, Michele Scagliola, Sebastian Bjerregaard Simonsen, Louise Sandberg Sørensen, David Brockley, Steven Baker, Sara Fleury, Jonathan Bamber, Luca Maestri, Henriette Skourup, René Forsberg, and Loretta Mizzi
The Cryosphere, 14, 1889–1907, https://doi.org/10.5194/tc-14-1889-2020, https://doi.org/10.5194/tc-14-1889-2020, 2020
Short summary
Short summary
This manuscript aims to describe the evolutions which have been implemented in the new CryoSat Ice processing chain Baseline-D and the validation activities carried out in different domains such as sea ice, land ice and hydrology.
This new CryoSat processing Baseline-D will maximise the uptake and use of CryoSat data by scientific users since it offers improved capability for monitoring the complex and multiscale changes over the cryosphere.
Theodoros E. Sarris, Elsayed R. Talaat, Minna Palmroth, Iannis Dandouras, Errico Armandillo, Guram Kervalishvili, Stephan Buchert, Stylianos Tourgaidis, David M. Malaspina, Allison N. Jaynes, Nikolaos Paschalidis, John Sample, Jasper Halekas, Eelco Doornbos, Vaios Lappas, Therese Moretto Jørgensen, Claudia Stolle, Mark Clilverd, Qian Wu, Ingmar Sandberg, Panagiotis Pirnaris, and Anita Aikio
Geosci. Instrum. Method. Data Syst., 9, 153–191, https://doi.org/10.5194/gi-9-153-2020, https://doi.org/10.5194/gi-9-153-2020, 2020
Short summary
Short summary
Daedalus aims to measure the largely unexplored area between Eart's atmosphere and space, the Earth's
ignorosphere. Here, intriguing and complex processes govern the deposition and transport of energy. The aim is to quantify this energy by measuring effects caused by electrodynamic processes in this region. The concept is based on a mother satellite that carries a suite of instruments, along with smaller satellites carrying a subset of instruments that are released into the atmosphere.
Sharon Aol, Stephan Buchert, and Edward Jurua
Ann. Geophys., 38, 243–261, https://doi.org/10.5194/angeo-38-243-2020, https://doi.org/10.5194/angeo-38-243-2020, 2020
Short summary
Short summary
During the night, in the F region, equatorial ionospheric irregularities manifest as plasma depletions observed by satellites and may cause radio signals to fluctuate. We checked the distribution traits of ionospheric F-region irregularities in the low latitudes using 16 Hz electron density observations made by the faceplate onboard Swarm satellites. Using the high-resolution faceplate data, we were able to identify ionospheric irregularities of scales of only a few hundred metres.
Piero Diego, Igino Coco, Igor Bertello, Maurizio Candidi, and Pietro Ubertini
Ann. Geophys. Discuss., https://doi.org/10.5194/angeo-2019-136, https://doi.org/10.5194/angeo-2019-136, 2019
Manuscript not accepted for further review
Short summary
Short summary
In-situ measurements validation is always a delicate matter of study until data are collected by a single mission. In case of different missions operating almost in the same environment (i.e. latitude, altitude, local time) it is of fundamental importance the detection of instrumental setting and algorithms to provide the best accordance among measurements. The present work aims to validate both Swarm and CSES plasma density measures for the improvements of the ionospheric models development.
Filomena Catapano, Gaetano Zimbardo, Silvia Perri, Antonella Greco, and Anton V. Artemyev
Ann. Geophys., 34, 917–926, https://doi.org/10.5194/angeo-34-917-2016, https://doi.org/10.5194/angeo-34-917-2016, 2016
Short summary
Short summary
Spacecraft observations show that energetic ions are found in the Earth’s magnetotail, with energies ranging from tens of keV to a few hundreds of keV. In this paper we carry out test particle simulations in which protons and other ion species are injected in the Vlasov magnetic field configurations obtained by Catapano et al. (2015). Three-dimensional time-dependent stochastic electromagnetic perturbations are included in the simulation box, so that the ion acceleration process is studied.
J. Park, H. Lühr, C. Stolle, G. Malhotra, J. B. H. Baker, S. Buchert, and R. Gill
Ann. Geophys., 33, 829–835, https://doi.org/10.5194/angeo-33-829-2015, https://doi.org/10.5194/angeo-33-829-2015, 2015
Short summary
Short summary
Though high-latitude plasma convection has been monitored with a number of methods, more independent measurements are still warranted. In this study we introduce an automatic method to estimate along-track plasma drift velocity in the high-latitude ionosphere using the Swarm constellation. The obtained velocity is in qualitative agreement with Super Dual Auroral Radar Network (SuperDARN) data. The method can be generalized to any satellite constellations in pearls-on-a-string configurations.
T. Živković, S. Buchert, P. Ritter, L. Palin, and H. Opgenoorth
Ann. Geophys., 33, 623–635, https://doi.org/10.5194/angeo-33-623-2015, https://doi.org/10.5194/angeo-33-623-2015, 2015
Short summary
Short summary
In this paper we analyze 21 conjunctions between the Cluster and CHAMP satellites while they were passing magnetic cusp during relatively quiet solar activity. Only three of the conjunctions reveal field-aligned currents on both satellites as well as neutral density enhancement in the thermosphere. Poynting and electron energy fluxes (EEF) as well as Joule heating were computed and the conclusion is that for these weak events EEF has the strongest contribution to the observed density increase.
A. De Santis, E. Qamili, and L. Wu
Nat. Hazards Earth Syst. Sci., 13, 3395–3403, https://doi.org/10.5194/nhess-13-3395-2013, https://doi.org/10.5194/nhess-13-3395-2013, 2013
L. Trenchi, R. Bruno, R. D'Amicis, M. F. Marcucci, and D. Telloni
Ann. Geophys., 31, 1333–1341, https://doi.org/10.5194/angeo-31-1333-2013, https://doi.org/10.5194/angeo-31-1333-2013, 2013
Related subject area
Data quality
Airborne electromagnetic data levelling based on the structured variational method
Upgrade of LSA-SAF Meteosat Second Generation daily surface albedo (MDAL) retrieval algorithm incorporating aerosol correction and other improvements
Evaluating methods for reconstructing large gaps in historic snow depth time series
Production of definitive data from Indonesian geomagnetic observatories
Auroral classification ergonomics and the implications for machine learning
Artifacts from manganese reduction in rock samples prepared by focused ion beam (FIB) slicing for X-ray microspectroscopy
The influence of sample geometry on the permeability of a porous sandstone
The operator difference in absolute geomagnetic measurements
One second vector and scalar magnetic measurements at the low-latitude Choutuppal (CPL) magnetic observatory
Data quality control and tools in passive seismic experiments exemplified on the Czech broadband seismic pool MOBNET in the AlpArray collaborative project
Time-stamp correction of magnetic observatory data acquired during unavailability of time-synchronization services
Stability analysis of geomagnetic baseline data obtained at Cheongyang observatory in Korea
European UV DataBase (EUVDB) as a repository and quality analyser for solar spectral UV irradiance monitored in Sodankylä
Bed conduction impact on fiber optic distributed temperature sensing water temperature measurements
A framework for benchmarking of homogenisation algorithm performance on the global scale
New analysis software for Viking Lander meteorological data
Innovations and applications of the VERA quality control
Qiong Zhang, Xin Chen, Zhonghang Ji, Fei Yan, Zhengkun Jin, and Yunqing Liu
Geosci. Instrum. Method. Data Syst., 13, 193–203, https://doi.org/10.5194/gi-13-193-2024, https://doi.org/10.5194/gi-13-193-2024, 2024
Short summary
Short summary
In an airborne survey, dynamic flight conditions cause unequal data levels, which have a serious impact on airborne geophysical data analysis and interpretation. A new technique is proposed to level geophysical data, and we confirm the reliability of the method by applying it to magnetic data and apparent conductivity data. The method can automatically extract the levelling errors without the participation of staff members or tie line control.
Daniel Juncu, Xavier Ceamanos, Isabel F. Trigo, Sandra Gomes, and Sandra C. Freitas
Geosci. Instrum. Method. Data Syst., 11, 389–412, https://doi.org/10.5194/gi-11-389-2022, https://doi.org/10.5194/gi-11-389-2022, 2022
Short summary
Short summary
MDAL is a near real-time, satellite-based surface albedo product based on the geostationary Meteosat Second Generation mission. We propose an update to the processing algorithm that generates MDAL and evaluate the results of these changes through comparison with the pre-update, currently operational MDAL product as well as reference data using different satellite-based albedo products and in situ measurements. We find that the update provides a valuable improvement.
Johannes Aschauer and Christoph Marty
Geosci. Instrum. Method. Data Syst., 10, 297–312, https://doi.org/10.5194/gi-10-297-2021, https://doi.org/10.5194/gi-10-297-2021, 2021
Short summary
Short summary
Methods for reconstruction of winter long data gaps in snow depth time series are compared. The methods use snow depth data from neighboring stations or calculate snow depth from temperature and precipitation data. All methods except one are able to reproduce the average snow depth and maximum snow depth in a winter reasonably well. For reconstructing the number of snow days with snow depth ≥ 1 cm, results suggest using a snow model instead of relying on data from neighboring stations.
Relly Margiono, Christopher W. Turbitt, Ciarán D. Beggan, and Kathryn A. Whaler
Geosci. Instrum. Method. Data Syst., 10, 169–182, https://doi.org/10.5194/gi-10-169-2021, https://doi.org/10.5194/gi-10-169-2021, 2021
Short summary
Short summary
We have produced a standardised high-quality set of measurements to create definitive data for four Indonesian Geomagnetic Observatories for 2010–2018. We explain the steps taken to update the existing data collection and processing protocols and suggest improvements to further enhance the quality of the magnetic time series at each observatory. The new data will fill the gap in the western Pacific region and provide input into geomagnetic field modeling and secular variation studies.
Derek McKay and Andreas Kvammen
Geosci. Instrum. Method. Data Syst., 9, 267–273, https://doi.org/10.5194/gi-9-267-2020, https://doi.org/10.5194/gi-9-267-2020, 2020
Short summary
Short summary
Researchers are making increasing use of machine learning to improve accuracy, efficiency and consistency. During such a study of the aurora, it was noted that biases or distortions had crept into the data because of the conditions (or ergonomics) of the human trainers. As using machine-learning techniques in auroral research is relatively new, it is critical that such biases are brought to the attention of the academic and citizen science communities.
Dorothea S. Macholdt, Jan-David Förster, Maren Müller, Bettina Weber, Michael Kappl, A. L. David Kilcoyne, Markus Weigand, Jan Leitner, Klaus Peter Jochum, Christopher Pöhlker, and Meinrat O. Andreae
Geosci. Instrum. Method. Data Syst., 8, 97–111, https://doi.org/10.5194/gi-8-97-2019, https://doi.org/10.5194/gi-8-97-2019, 2019
Short summary
Short summary
Focused ion beam (FIB) slicing is a widely used technique to prepare ultrathin slices for the microanalysis of geological and environmental samples. During our investigations of the manganese oxidation states in rock varnish slices, we found an FIB-related reduction of manganese(IV) to manganese(II) at the samples’ surfaces. This study characterizes the observed reduction artifacts and emphasizes that caution is needed in the analysis of transition metal oxidation states upon FIB preparation.
Michael J. Heap
Geosci. Instrum. Method. Data Syst., 8, 55–61, https://doi.org/10.5194/gi-8-55-2019, https://doi.org/10.5194/gi-8-55-2019, 2019
Short summary
Short summary
To better understand the influence of sample geometry on laboratory measurements of permeability, the permeabilities of sandstone samples with different lengths and diameters were measured. Despite the large range in length, aspect ratio, and volume, the permeabilities of the samples are near identical. This is due to a homogeneous porosity structure and the small grain/pore size with respect to the minimum tested diameter and length. More tests are now needed to help develop such guidelines.
Yufei He, Xudong Zhao, Jianjun Wang, Fuxi Yang, Xijing Li, Changjiang Xin, Wansheng Yan, and Wentong Tian
Geosci. Instrum. Method. Data Syst., 8, 21–27, https://doi.org/10.5194/gi-8-21-2019, https://doi.org/10.5194/gi-8-21-2019, 2019
Nelapatla Phani Chandrasekhar, Sai Vijay Kumar Potharaju, Kusumita Arora, Chandra Shakar Rao Kasuba, Leonid Rakhlin, Sergey Tymoshyn, Laszlo Merenyi, Anusha Chilukuri, Jayashree Bulusu, and Sergey Khomutov
Geosci. Instrum. Method. Data Syst., 6, 547–560, https://doi.org/10.5194/gi-6-547-2017, https://doi.org/10.5194/gi-6-547-2017, 2017
Short summary
Short summary
This work presents the progressive steps which led to the successful setup of such measurements at the new magnetic observatory in Choutuppal (CPL) of CSIR-NGRI, Hyderabad, India. Iterative tuning of the setup led to the generation of good quality data from 2016 onward. The processes of commissioning this setup in low-latitude conditions, with the aim of producing 1 s definitive data, and the characteristics of the data from this new instrument are presented here.
Luděk Vecsey, Jaroslava Plomerová, Petr Jedlička, Helena Munzarová, Vladislav Babuška, and the AlpArray working group
Geosci. Instrum. Method. Data Syst., 6, 505–521, https://doi.org/10.5194/gi-6-505-2017, https://doi.org/10.5194/gi-6-505-2017, 2017
Short summary
Short summary
This paper focuses on major issues related to data reliability and MOBNET network performance in the AlpArray seismic experiments. We present both new hardware and software tools that help to assure the high-quality standard of broadband seismic data. Special attention is paid to issues like a detection of sensor misorientation, timing problems, exchange of record components and/or their polarity reversal, sensor mass centring, or anomalous channel amplitudes due to imperfect gain.
Pierdavide Coïsson, Kader Telali, Benoit Heumez, Vincent Lesur, Xavier Lalanne, and Chang Jiang Xin
Geosci. Instrum. Method. Data Syst., 6, 311–317, https://doi.org/10.5194/gi-6-311-2017, https://doi.org/10.5194/gi-6-311-2017, 2017
Short summary
Short summary
Data loggers of magnetic observatories use GPS receivers to provide accurate time stamping of recorded data. Typical sampling rate is 1 s. A failure of the GPS receiver can result in erroneous time stamps. The observatory of Lanzhou, China, accumulated a lag of 28 s over 1 year. Using magnetic data recorded at other locations in a radius of 3000 km it was possible to estimate the diurnal lag and correct the time tamps to produce reliable 1 min averages of magnetic data.
Shakirah M. Amran, Wan-Seop Kim, Heh Ree Cho, and Po Gyu Park
Geosci. Instrum. Method. Data Syst., 6, 231–238, https://doi.org/10.5194/gi-6-231-2017, https://doi.org/10.5194/gi-6-231-2017, 2017
Short summary
Short summary
In this work, we analysed the Cheongyang geomagnetic baseline data from 2014 to 2016. We observed a step of more than 5 nT in the H and Z baseline in 2014 and 2015 due to artificial magnetic noise in the absolute hut. The baseline also shows a periodic modulation due to temperature variations in the fluxgate magnetometer hut. The quality of the baselines was improved by correcting the discontinuity in the H and Z baselines.
Anu Heikkilä, Jussi Kaurola, Kaisa Lakkala, Juha Matti Karhu, Esko Kyrö, Tapani Koskela, Ola Engelsen, Harry Slaper, and Gunther Seckmeyer
Geosci. Instrum. Method. Data Syst., 5, 333–345, https://doi.org/10.5194/gi-5-333-2016, https://doi.org/10.5194/gi-5-333-2016, 2016
Short summary
Short summary
Solar spectral UV irradiance data measured by the Brewer #037 spectroradiometer in Sodankylä, Finland, in 1990–2014 were examined for their quality flags given by the quality assurance (QA) tools of the European UV DataBase (EUVDB). Statistical analysis on the flags was performed, and five cases were investigated in detail. The results can be used in further development of the quality control/QA tools and selection of cases of exceptional atmospheric conditions for process studies.
T. O'Donnell Meininger and J. S. Selker
Geosci. Instrum. Method. Data Syst., 4, 19–22, https://doi.org/10.5194/gi-4-19-2015, https://doi.org/10.5194/gi-4-19-2015, 2015
K. Willett, C. Williams, I. T. Jolliffe, R. Lund, L. V. Alexander, S. Brönnimann, L. A. Vincent, S. Easterbrook, V. K. C. Venema, D. Berry, R. E. Warren, G. Lopardo, R. Auchmann, E. Aguilar, M. J. Menne, C. Gallagher, Z. Hausfather, T. Thorarinsdottir, and P. W. Thorne
Geosci. Instrum. Method. Data Syst., 3, 187–200, https://doi.org/10.5194/gi-3-187-2014, https://doi.org/10.5194/gi-3-187-2014, 2014
O. Kemppinen, J. E. Tillman, W. Schmidt, and A.-M. Harri
Geosci. Instrum. Method. Data Syst., 2, 61–69, https://doi.org/10.5194/gi-2-61-2013, https://doi.org/10.5194/gi-2-61-2013, 2013
D. Mayer, A. Steiner, and R. Steinacker
Geosci. Instrum. Method. Data Syst., 1, 135–149, https://doi.org/10.5194/gi-1-135-2012, https://doi.org/10.5194/gi-1-135-2012, 2012
Cited articles
Abe, T. and Oyama, K.-i.:
Langmuir Probe,
in: An Introduction to Space Instrumentation,
edited by: Oyama, K. and Cheng, C. Z.,
TERRAPUB, Japan, 63–75, https://doi.org/10.5047/aisi.010, 2013. a
Archer, W. E., Gallardo-Lacourt, B., Perry, G. W., St.-Maurice, J. P., Buchert, S. C., and Donovan, E.:
Steve: The Optical Signature of Intense Subauroral Ion Drifts,
Geophys. Res. Lett.,
46, 6279–6286, https://doi.org/10.1029/2019GL082687, 2019. a, b, c, d
Bilitza, D.: IRI the International Standard for the Ionosphere, Adv. Radio Sci., 16, 1–11, https://doi.org/10.5194/ars-16-1-2018, 2018. a
Boyd, R. L. F.:
An Introduction to Langmuir Probes for Space Research,
in: Introduction to Solar Terrestrial Relations,
edited by: Ortner, J. and Maseland, H.,
Astrophysics and Space Science Library,
Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-94-010-3590-3_39, pp. 455–465, 1965. a
Buchert, S. and Nilsson, T.:
Swarm level 1b Plasma processor algorithm, ESA,
https://earth.esa.int/eogateway/documents/20142/37627/swarm-level-1b-plasma-processor-algorithm.pdf/bae64759-b901-d961-4d18-0a5b317f8c12 (last access: 31 July 2021),
, 2018. a
Coffey, V. N., Wright, K. H., Minow, J. I., Schneider, T. A., Vaughn, J. A., Craven, P. D., Chandler, M. O., Koontz, S. L., Parker, L. N., and Bui, T. H.:
Validation of the Plasma Densities and Temperatures From the ISS Floating Potential Measurement Unit,
IEEE T. Plasma Sci.,
36, 2301–2308, https://doi.org/10.1109/TPS.2008.2004271, 2008. a
Covington, A.:
Micro-Wave Solar Noise Observations During the Partial Eclipse of November 23, 1946,
Nature,
159, 405–406, https://doi.org/10.1038/159405a0, 1947. a
Covington, A. E.:
Solar Noise Observations on 10.7 Centimeters,
Proceedings of the IRE,
36, 454–457, https://doi.org/10.1109/JRPROC.1948.234598, 1948. a
De Michelis, P., Consolini, G., Pignalberi, A., Tozzi, R., Coco, I., Giannattasio, F., Pezzopane, M., and Balasis, G.:
Looking for a proxy of the ionospheric turbulence with Swarm data,
Sci. Rep.-UK,
11, 2045–2322, https://doi.org/10.1038/s41598-021-84985-1, 2021. a, b
DTU:
Swarm L1B processor algorithms,
https://earth.esa.int/eogateway/documents/20142/37627/swarm-level-1b-processor-algorithms.pdf/e0606842-41ca-fa48-0a40-05a0d4824501?version=1.0 (last access: 31 July 2021),
National Space Institute, Technical University of Denmark (DTU), 2019a. a
ENS-Technology:
On Titanium Plating, ENS Technology,
https://www.enstechnology.com/specialty-plating/exotic-metal/titanium-plating (last access: 31 July 2021),
2022. a
Eriksson, A. I., Boström, R., Gill, R., Åhlén, L., Jansson, S.-E., Wahlund, J.-E., André, M., Mälkki, A., Holtet, J. A., Lybekk, B., Pedersen, A., Blomberg, L. G., and The LAP Team:
RPC-LAP: The Rosetta Langmuir Probe Instrument,
Space Sci. Rev.,
128, 729–744, https://doi.org/10.1007/s11214-006-9003-3, 2007. a, b
European Space Agency:
Swarm Publications, ESA,
https://earth.esa.int/eogateway/missions/swarm/publications (last access: 31 July 2021),
2021b. a
ESA:
Swarm preliminary plasma dataset user note, ESA,
https://earth.esa.int/eogateway/documents/20142/37627/swarm-preliminary-plasma-dataset-user-note.pdf/6e8c356f-16d9-5145-1cc9-a9c5736653ab (last access: 31 July 2021), 2015. a
ESA:
Swarm L1B baseline evolution, ESA,
https://earth.esa.int/documents/10174/1514862/Swarm-Level-1B-baseline-evolutions (last access: 31 July 2021), 2018. a
ESA:
Summary and recommendations report, ESA,
https://earth.esa.int/eogateway/documents/20142/1479677/Swarm-DQW9-Summary-Recommendations-Report.pdf (last access: 31 July 2021), 2019. a
ESA:
Swarm data gaps recovered, ESA,
https://earth.esa.int/documents/10174/1583357/Swarm-data-gaps-recovered.pdf (last access: 31 July 2021), 2020a. a
ESA:
Swarm L1B and L2 operational processors, ESA,
https://earth.esa.int/documents/10174/1514862/Swarm-L1B-and-L2-operational-processors.pdf (last access: 31 July 2021), 2020b. a
Flury, J., Rummel, R., Reigber, C., Rothacher, M., Boedecker, G., and Schreiber, U.:
CHAMP Mission 5 Years in Orbit,
Springer, Berlin, Heidelberg, 2006. a
Hatch, S. M., Haaland, S., Laundal, K. M., Moretto, T., Yau, A. W., Bjoland, L., Reistad, J. P., Ohma, A., and Oksavik, K.:
Seasonal and Hemispheric Asymmetries of F Region Polar Cap Plasma Density: Swarm and CHAMP Observations,
J. Geophys. Res.-Space,
125, e2020JA028084, https://doi.org/10.1029/2020JA028084, 2020. a
Heelis, R. A. and Maute, A.:
Challenges to Understanding the Earth's Ionosphere and Thermosphere,
J. Geophys. Res.-Space,
125, e2019JA027497, https://doi.org/10.1029/2019JA027497, 2020. a, b
IRF:
Faceplate plasma density, ESA,
https://swarm-diss.eo.esa.int/#swarm%2FAdvanced%2FPlasma_Data%2F16_Hz_Faceplate_plasma_density (last access: 31 July 2021), 2017. a
Jin, Y. and Xiong, C.:
Interhemispheric Asymmetry of Large-Scale Electron Density Gradients in the Polar Cap Ionosphere: UT and Seasonal Variations,
J. Geophys. Res.-Space,
125, e2019JA027601, https://doi.org/10.1029/2019JA027601, 2020. a, b
Jin, Y., Xiong, C., Clausen, L., Spicher, A., Kotova, D., Brask, S., Kervalishvili, G., Stolle, C., and Miloch, W.:
Ionospheric Plasma Irregularities Based on In Situ Measurements From the Swarm Satellites,
J. Geophys. Res.-Space,
125, e2020JA028103, https://doi.org/10.1029/2020JA028103, 2020. a
Knudsen, D. J., Burchill, J. K., Buchert, S. C., Eriksson, A. I., Gill, R., Wahlund, J.-E., Åhlen, L., Smith, M., and Moffat, B.:
Thermal ion imagers and Langmuir probes in the Swarm electric field instruments,
J. Geophys. Res.-Space,
122, 2655–2673, https://doi.org/10.1002/2016JA022571, 2017. a, b, c, d, e
Lebreton, J. P., Stverak, S., Travnicek, P., Maksimovic, M., Klinge, D., Merikallio, S., Lagoutte, D., Poirier, B., Blelly, P. L., Kozacek, Z., and Salaquarda, M.:
The ISL Langmuir Probe Experiment Processing Onboard DEMETER: Scientific Objectives, Description and First Results,
Planet. Space Sci.,
54, 472–486, https://doi.org/10.1016/j.pss.2005.10.017, 2006. a, b
Liu, J., Guan, Y., Zhang, X., and Shen, X.:
The data comparison of electron density between CSES and DEMETER satellite, Swarm constellation and IRI model,
Earth and Space Science,
8, e2020EA001475, https://doi.org/10.1029/2020EA001475, 2020. a
Liu, L. and Chen, Y.:
Statistical analysis of solar activity variations of total electron content derived at Jet Propulsion Laboratory from GPS observations,
J. Geophys. Res.-Space,
114, https://doi.org/10.1029/2009JA014533, 2009. a
Lomidze, L., Knudsen, D. J., Burchill, J., Kouznetsov, A., and Buchert, S. C.:
Calibration and Validation of Swarm Plasma Densities and Electron Temperatures Using Ground-Based Radars and Satellite Radio Occultation Measurements,
Radio Sci.,
53, 15–36, https://doi.org/10.1002/2017RS006415, 2018. a, b, c, d
MacDonald, E. A., Donovan, E., Nishimura, Y., Case, N. A., Gillies, D. M., Gallardo-Lacourt, B., Archer, W. E., Spanswick, E. L., Bourassa, N., Connors, M., Heavner, M., Jackel, B., Kosar, B., Knudsen, D. J., Ratzlaff, C., and Schofield, I.:
New science in plain sight: Citizen scientists lead to the discovery of optical structure in the upper atmosphere,
Science Advances,
4, 3, https://doi.org/10.1126/sciadv.aaq0030, 2018. a
Noja, M., Stolle, C., Park, J., and Lühr, H.:
Long-term analysis of ionospheric polar patches based on CHAMP TEC data,
Radio Sci.,
48, 289–301, https://doi.org/10.1002/rds.20033, 2013. a
Olsen, N., Friis-Christensen, E., Floberghagen, R., Alken, P., Beggan, C. D., Chulliat, A., Doornbos, E., da Encarnação, J. T., Hamilton, B., Hulot, G., van den IJssel, J., Kuvshinov, A., Lesur, V., Lühr, H., Macmillan, S., Maus, S., Noja, M., Olsen, P. E. H., Park, J., Plank, G., Püthe, C., Rauberg, J., Ritter, P., Rother, M., Sabaka, T. J., Schachtschneider, R., Sirol, O., Stolle, C., Thébault, E., Thomson, A. W. P., Tøffner-Clausen, L., Velímský, J., Vigneron, P., and Visser, P. N.:
The Swarm Satellite Constellation Application and Research Facility (SCARF) and Swarm data products,
Earth Planets Space,
65, 1880–5981, https://doi.org/10.5047/eps.2013.07.001, 2013. a
Oyama, K.:
DC Langmuir Probe for Measurement of Space Plasma: A Brief Review,
Journal of Astronomy and Space Sciences,
32, 2, https://doi.org/10.5140/JASS.2015.32.3.167, 2015. a
Pezzopane, M. and Pignalberi, A.:
The ESA Swarm mission to help ionospheric modeling: a new NeQuick topside formulation for mid-latitude regions,
Sci. Rep.-UK,
9, 12253, https://doi.org/10.1038/s41598-019-48440-6, 2019.
a
Pignalberi, A., Pezzopane, M., Tozzi, R., De Michelis, P., and Coco, I.:
Comparison between IRI and preliminary Swarm Langmuir probe measurements during the St. Patrick storm period,
Earth Planets Space,
68, 93, https://doi.org/10.1186/s40623-016-0466-5, 2016. a
Prölss, G.:
Physics of the Earth's Space Environment,
Springer, Berlin, Heidelberg, 2004. a
Singh, A. K., Haralambous, H., Oikonomou, C., and Leontiou, T.:
A topside investigation over a mid-latitude digisonde station in Cyprus,
Adv. Space Res.,
67, 739–748, https://doi.org/10.1016/j.asr.2020.10.009, 2021. a
Smirnov, A., Shprits, Y., Zhelavskaya, I., Lühr, H., Xiong, C., Goss, A., Prol, F. S., Schmidt, M., Hoque, M., Pedatella, N., and Szabó-Roberts, M.:
Intercalibration of the Plasma Density Measurements in Earth's Topside Ionosphere,
J. Geophys. Res.-Space,
126, e2021JA029334, https://doi.org/10.1029/2021JA029334, 2021. a
Tapping, K. F.:
The 10.7 cm solar radio flux (F10.7),
Space Weather,
11, 394–406, https://doi.org/10.1002/swe.20064, 2013. a
Vaishnav, R., Jacobi, C., and Berdermann, J.: Long-term trends in the ionospheric response to solar extreme-ultraviolet variations, Ann. Geophys., 37, 1141–1159, https://doi.org/10.5194/angeo-37-1141-2019, 2019. a
Wang, X., Hsu, H.-W., and Horányi, M.:
Identification of when a Langmuir probe is in the sheath of a spacecraft: The effects of secondary electron emission from the probe,
J. Geophys. Res.-Space,
120, 2428–2437, https://doi.org/10.1002/2014JA020624, 2015. a
Xiong, C., Park, J., Lühr, H., Stolle, C., and Ma, S. Y.: Comparing plasma bubble occurrence rates at CHAMP and GRACE altitudes during high and low solar activity, Ann. Geophys., 28, 1647–1658, https://doi.org/10.5194/angeo-28-1647-2010, 2010. a
Xiong, C., Xu, J.-S., Stolle, C., van den Ijssel, J., Yin, F., Kervalishvili, G. N., and Zangerl, F.:
On the Occurrence of GPS Signal Amplitude Degradation for Receivers on Board LEO Satellites,
Space Weather,
18, e2019SW002398, https://doi.org/10.1029/2019SW002398, 2020. a
Yang, T.-Y., Park, J., Kwak, Y.-S., Oyama, K.-I., Minow, J. I., and Lee, J.:
Morning Overshoot of Electron Temperature as Observed by the Swarm Constellation and the International Space Station,
J. Geophys. Res.-Space,
125, e2019JA027299, https://doi.org/10.1029/2019JA027299, 2020. a
Short summary
The quality control and validation activities performed by the Swarm data quality team reveal the good-quality LPs. The analysis demonstrated that the current baseline plasma data products are improved with respect to previous baseline. The LPs have captured the ionospheric plasma variability over more than half of a solar cycle, revealing the data quality dependence on the solar activity. The quality of the LP data will further improve promotion of their application to a broad range of studies.
The quality control and validation activities performed by the Swarm data quality team reveal...