22272b8e-1aa3-483b-9867-224fe02db4e8 eng utf8 dataset dataset NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom polardatacentre@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact 2023-01-13 ISO 19115 Geographic Information - Metadata ISO 19115:2003(E) European Petroleum Survey Group (EPSG) Geodetic Parameter Registry 2008-11-12 publication European Petroleum Survey Group EPSGadministrator@iogp.org https://www.epsg-registry.org/ EPSG Geodetic Parameter Dataset The EPSG Geodetic Parameter Dataset is a structured dataset of Coordinate Reference Systems and Coordinate Transformations, accessible through this online registry. information publisher urn:ogc:def:crs:EPSG::3031 6.18.3 Forecast regression model of the northern Super Dual Auroral Radar Network (SuperDARN) high-latitude ionospheric plasma motion built from data interval 1997-2008 inclusive 2023-01-13 creation 2023-01-13 revision 2023-01-13 publication 2023-01-13 released 1.0 https://doi.org/10.5285/22272b8e-1aa3-483b-9867-224fe02db4e8 doi GB/NERC/BAS/PDC/01706 https://data.bas.ac.uk/ NE/N01099X/1 award NE/T000937/1 award Please cite this item as: Lam, M., Shore, R., Chisham, G., & Freeman, M. (2023). Forecast regression model of the northern Super Dual Auroral Radar Network (SuperDARN) high-latitude ionospheric plasma motion built from data interval 1997-2008 inclusive (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/22272b8e-1aa3-483b-9867-224fe02db4e8 A forecast model of the northern high-latitude ionospheric plasma motion as observed by the SuperDARN radars. The model comprises a set of regression coefficients. The user needs to specify the day-of-year and the monthly mean of the solar radio flux at 10.7 cm/2800 MHz, often called the f10.7 index. They also need to provide the value of the interplanetary magnetic field (IMF) component By and the Sun-Earth component of the solar wind velocity Vx, both in geocentric solar magnetospheric (GSM) coordinates. The regression coefficients are provided as two files, one can be used to model the north-south (NS) component of the plasma motion and the other to model the east-west (EW) component of the motion. Funding was provided by NERC standard grant numbers: NE/V002732/1, NE/N01099X/1, NE/V00283X/1, NE/V002686/1 and NE/T000937/1. No credit. completed Lam, Mai Mai British Antarctic Survey Researcher author Shore, Robert British Antarctic Survey Researcher author Chisham, Gareth British Antarctic Survey Researcher author Freeman, Mervyn British Antarctic Survey Researcher author NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact asNeeded completed EARTH SCIENCE > Sun-earth Interactions > Ionosphere/Magnetosphere Dynamics > Electric Fields/Electric Currents EARTH SCIENCE > Sun-earth Interactions > Ionosphere/Magnetosphere Dynamics > Plasma Waves EARTH SCIENCE > Sun-earth Interactions > Ionosphere/Magnetosphere Dynamics > Solar Wind EARTH SCIENCE > Sun-earth Interactions > Ionosphere/Magnetosphere Dynamics theme Global Change Master Directory (GCMD) Science Keywords 2026-01-27 publication 23 Global Change Data Center, Science and Exploration Directorate, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA) Greenbelt MD United States of America https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords Global Change Master Directory (GCMD) Keywords The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords. information publisher Ionospheric electric field Solar wind effects on ionosphere SuperDARN Upper atmosphere dynamics onospheric plasma convection theme F-region Ionosphere place Atmospheric conditions theme GEMET - INSPIRE themes, version 1.0 2021-01-06 revision otherRestrictions no limitations to public access otherRestrictions no limitations license Open Government Licence v3.0 otherRestrictions Data released under Open Government Licence V3.0: otherRestrictions None url url dependency url url dependency doi doi crossReference doi doi crossReference url url largerWorkCitation url url largerWorkCitation url url crossReference doi doi crossReference textTable eng utf8 climatologyMeteorologyAtmosphere -180.0 180.0 60.9 90.0 1997-01-01 2008-12-31 250.0 400.0 urn:ogc:def:crs:EPSG::5714 MSL height Not specific to any location or epoch. Hydrography. It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk. NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information distributor text/plain bytes 274432 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=22272b8e-1aa3-483b-9867-224fe02db4e8 WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: Our data set was derived from a reanalysis of SuperDARN plasma velocity data: Shore, R., Freeman, M., Chisham, G., Lam, M. M., & Breen, P. (2022). Dominant spatial and temporal patterns of horizontal ionospheric plasma velocity variation covering the northern polar region, from 1997.0 to 2009.0 - VERSION 2.0 (Version 2.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/2b9f0e9f-34ec-4467-9e02-abc771070cd9. The Shore et al. (2022) reanalysis data covers the period 1997.0 to 2009.0 at 5-min resolution. The scientific motivation and details of the methodology of its production are described in Shore et al., 2021, https://doi.org/10.1029/2021JA029272. We performed a regression analysis on the Shore et al. (2022) reanalysis data, which resulted in the forecast model regression coefficients published here. The regression analysis occurred via two steps described in Section 3 of Lam et al. (see References below), submitted to the journal Space Weather in January 2023: Step A: see Section 3.2 of Lam et al. (2023). Regression of each component of the SuperDARN plasma velocity with respect to 5-min averages of the epsilon solar wind coupling function (Koskinen and Tanskanen, 2012 https://doi.org/10.1029/2002JA009283), IMF By, and a constant. This produced 3 regression coefficients (the slope in epsilon, the slope in By and the constant) for every location and month (3 step A coefficients x 559 locations x 144 months). Step B: see Section 3.3 of Lam et al. (2023). Regression of each set of regression coefficients (each of size 559 x 144) produced in Step A with respect to 4 variables: sin x, cos x, the monthly mean value of f10.7, and a constant, where x = 2pi (tj - 79)/365.25 and tj is the day-of-year in the middle of the 12 months of the year (j = 1 to 12). This produced 12 regression coefficients for each velocity component, so 24 in total (3 step A coefficients x 4 step B coefficients x 2 velocity components). Use of regression coefficients. The plasma velocity can be forecast (or hindcast) by reading in these 24 regression coefficients from two ACSII files and using them in Equations 6, and subsequently Equations 5 of Lam et al. (2023). An example of how this is done is given by the IDL programme 'read_BAS_convection.pro'. Please see Data structure and data format below for details.  Data collection: The authors gratefully acknowledge the use of SuperDARN data. The original plasma velocity observations were gathered using the northern hemisphere radars of the SuperDARN global array. SuperDARN is a collection of radars funded by the national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom, and the United States. The fitted Doppler velocities were processed from the original autocorrelation functions using version 4.5 of the radar software toolkit (RSTv4.5) and within that toolkit, fitting routine 'FitACF v2.5'. The fitted Doppler velocities were analysed using multiple data-interpolating empirical orthogonal function eigenanalyses for the period 1997.0 to 2009.0 at 5-min resolution, extending between the north magnetic pole and 30 degrees colatitude, as described in Shore et al., 2021 DOI: 10.1029/2021JA029272. Data quality: The SuperDARN radar observations were processed to remove ground scatter, and to eliminate measurements with too low power (lower than 3dB), or which had a poor-quality flag (identified in RSTv4.0). When binning the data, range gates below 11 and above 150 (where those values correspond to a multiple of the 45 km range distance from the radar array location) were not used, since these gave inaccurate locational estimates. The Shore et al. (2022) eigenanalyses of the radar data were performed on a spatial grid with 559 locations, so we keep the same grid for consistency. We recombined all 10 spatial and temporal modes for the 12-year interval. The resulting velocities have NaN (not a number) values for co-latitudes greater than 30 degrees, and for the single point exactly at the pole. For this reason, our forecast model regression coefficients also have NaN values for co-latitudes greater than 30 degrees and the pole. asNeeded completed