Toolkit for incoherent scatter radar experiment design and applications to EISCAT_3D Article Swipe
Spencer Hatch
,
Ilkka Virtanen
,
K. M. Laundal
,
Habtamu W. Tesfaw
,
Juha Vierinen
,
Devin Huyghebaert
,
Andres Spicher
,
Jens Christian Hessen
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-2025-1768
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-2025-1768
Modern phased array incoherent scatter radar (ISR) systems consist of several thousand phased-array antenna elements. Next-generation phased-array ISR systems are shifting towards multistatic setups consisting of three sites, such as EISCAT_3D with sites in Finland, Norway, and Sweden. The tremendous flexibility that these ISR systems afford also presents a challenge: Given a science question and an estimate of the the associated ionospheric conditions, how does one begin to design an ISR experiment? Here we present a method for performing observing system simulation experiments (OSSEs) with multistatic and monostatic ISRs. The method estimates the variance, or uncertainty, of measurements of three scalar quantities (plasma density, electron and ion temperature), and the covariance of one vector quantity (ion drift) in the case of multistatic systems. It is based on analytic first-order linearization of the incoherent scatter spectrum, as well as inverse and radar theory. Uncertainty estimation requires specification of the radar system as well as plasma density, electron and ion temperature, ion-neutral collision frequency, and the fractional density of O+. We validate this analytic uncertainty estimation method against uncertainty estimates derived directly from EISCAT incoherent scatter radar measurements made over Tromsø. We also present an open-source implementation of this method and additional tools written in R and Python that may be used to assess whether a candidate experiment is likely to achieve the temporal and spatial resolution needed to study a particular phenomenon. The user may vary parameters such as integration time, bit length, and duty cycle to understand their effect on experimental uncertainties. By default the EISCAT_3D radar configuration is used and these parameters are calculated automatically via two commonly used empirical models; it is nevertheless straightforward to manually specify alternative radar configurations, whether mono- or multistatic, and individual ionospheric and atmospheric parameters. We show how different beam patterns affect reconstruction of the ionospheric potential electric field, and present an example experiment optimized for reconstructing the electrodynamics around an auroral arc.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.5194/egusphere-2025-1768
- OA Status
- gold
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409814638
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409814638Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5194/egusphere-2025-1768Digital Object Identifier
- Title
-
Toolkit for incoherent scatter radar experiment design and applications to EISCAT_3DWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-25Full publication date if available
- Authors
-
Spencer Hatch, Ilkka Virtanen, K. M. Laundal, Habtamu W. Tesfaw, Juha Vierinen, Devin Huyghebaert, Andres Spicher, Jens Christian HessenList of authors in order
- Landing page
-
https://doi.org/10.5194/egusphere-2025-1768Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5194/egusphere-2025-1768Direct OA link when available
- Concepts
-
Incoherent scatter, Radar, Remote sensing, Computer science, Geology, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.present | 75, 192, 308 |
| abstract_inverted_index.scatter | 5, 134, 184 |
| abstract_inverted_index.science | 53 |
| abstract_inverted_index.several | 11 |
| abstract_inverted_index.spatial | 224 |
| abstract_inverted_index.specify | 279 |
| abstract_inverted_index.systems | 8, 19, 45 |
| abstract_inverted_index.theory. | 142 |
| abstract_inverted_index.towards | 22 |
| abstract_inverted_index.whether | 213, 283 |
| abstract_inverted_index.written | 202 |
| abstract_inverted_index.Finland, | 35 |
| abstract_inverted_index.Tromsø. | 189 |
| abstract_inverted_index.analytic | 128, 172 |
| abstract_inverted_index.commonly | 269 |
| abstract_inverted_index.density, | 104, 155 |
| abstract_inverted_index.directly | 180 |
| abstract_inverted_index.electric | 305 |
| abstract_inverted_index.electron | 105, 156 |
| abstract_inverted_index.estimate | 57 |
| abstract_inverted_index.manually | 278 |
| abstract_inverted_index.patterns | 298 |
| abstract_inverted_index.presents | 48 |
| abstract_inverted_index.quantity | 115 |
| abstract_inverted_index.question | 54 |
| abstract_inverted_index.requires | 145 |
| abstract_inverted_index.shifting | 21 |
| abstract_inverted_index.systems. | 123 |
| abstract_inverted_index.temporal | 222 |
| abstract_inverted_index.thousand | 12 |
| abstract_inverted_index.validate | 170 |
| abstract_inverted_index.Abstract. | 0 |
| abstract_inverted_index.EISCAT_3D | 31, 256 |
| abstract_inverted_index.candidate | 215 |
| abstract_inverted_index.collision | 161 |
| abstract_inverted_index.different | 296 |
| abstract_inverted_index.elements. | 15 |
| abstract_inverted_index.empirical | 271 |
| abstract_inverted_index.estimates | 92, 178 |
| abstract_inverted_index.observing | 80 |
| abstract_inverted_index.optimized | 312 |
| abstract_inverted_index.potential | 304 |
| abstract_inverted_index.spectrum, | 135 |
| abstract_inverted_index.variance, | 94 |
| abstract_inverted_index.additional | 200 |
| abstract_inverted_index.associated | 61 |
| abstract_inverted_index.calculated | 265 |
| abstract_inverted_index.challenge: | 50 |
| abstract_inverted_index.consisting | 25 |
| abstract_inverted_index.covariance | 111 |
| abstract_inverted_index.estimation | 144, 174 |
| abstract_inverted_index.experiment | 216, 311 |
| abstract_inverted_index.fractional | 165 |
| abstract_inverted_index.frequency, | 162 |
| abstract_inverted_index.incoherent | 4, 133, 183 |
| abstract_inverted_index.individual | 288 |
| abstract_inverted_index.monostatic | 88 |
| abstract_inverted_index.parameters | 236, 263 |
| abstract_inverted_index.particular | 230 |
| abstract_inverted_index.performing | 79 |
| abstract_inverted_index.quantities | 102 |
| abstract_inverted_index.resolution | 225 |
| abstract_inverted_index.simulation | 82 |
| abstract_inverted_index.tremendous | 40 |
| abstract_inverted_index.understand | 247 |
| abstract_inverted_index.Uncertainty | 143 |
| abstract_inverted_index.alternative | 280 |
| abstract_inverted_index.atmospheric | 291 |
| abstract_inverted_index.conditions, | 63 |
| abstract_inverted_index.experiment? | 72 |
| abstract_inverted_index.experiments | 83 |
| abstract_inverted_index.first-order | 129 |
| abstract_inverted_index.flexibility | 41 |
| abstract_inverted_index.integration | 239 |
| abstract_inverted_index.ion-neutral | 160 |
| abstract_inverted_index.ionospheric | 62, 289, 303 |
| abstract_inverted_index.multistatic | 23, 86, 122 |
| abstract_inverted_index.open-source | 194 |
| abstract_inverted_index.parameters. | 292 |
| abstract_inverted_index.phenomenon. | 231 |
| abstract_inverted_index.uncertainty | 173, 177 |
| abstract_inverted_index.experimental | 251 |
| abstract_inverted_index.measurements | 98, 186 |
| abstract_inverted_index.multistatic, | 286 |
| abstract_inverted_index.nevertheless | 275 |
| abstract_inverted_index.phased-array | 13, 17 |
| abstract_inverted_index.temperature, | 159 |
| abstract_inverted_index.uncertainty, | 96 |
| abstract_inverted_index.automatically | 266 |
| abstract_inverted_index.configuration | 258 |
| abstract_inverted_index.linearization | 130 |
| abstract_inverted_index.specification | 146 |
| abstract_inverted_index.temperature), | 108 |
| abstract_inverted_index.implementation | 195 |
| abstract_inverted_index.reconstructing | 314 |
| abstract_inverted_index.reconstruction | 300 |
| abstract_inverted_index.uncertainties. | 252 |
| abstract_inverted_index.Next-generation | 16 |
| abstract_inverted_index.configurations, | 282 |
| abstract_inverted_index.electrodynamics | 316 |
| abstract_inverted_index.straightforward | 276 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.92242777 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |