f4245a21-dee9-46cf-85b2-114798cb7ebc 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 2021-03-01 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 Dominant spatial and temporal patterns of horizontal ionospheric plasma velocity variation covering the northern polar region, for the month of February 2001 2021-03-01 creation 2021-03-01 revision 2021-03-01 publication 2021-03-01 released 1.0 https://doi.org/10.5285/f4245a21-dee9-46cf-85b2-114798cb7ebc doi GB/NERC/BAS/PDC/01473 https://data.bas.ac.uk/ NE/N01099X/1 award Please cite this item as: Shore, R., Freeman, M., & Chisham, G. (2021). Dominant spatial and temporal patterns of horizontal ionospheric plasma velocity variation covering the northern polar region, for the month of February 2001 (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/f4245a21-dee9-46cf-85b2-114798cb7ebc We present a reanalysis of SuperDARN plasma velocity measurements, using the method of data-interpolating Empirical Orthogonal Functions (EOFs). The northern polar region's radar-measured line of sight Doppler velocities are binned in an equal-area grid (areas of approximately 110,000km2) in quasi-dipole latitude and quasi-dipole magnetic local time (MLT). Within this spatial grid, which extends to 30 degrees colatitude, the plasma velocity is given in terms of cardinal north and east vector components (in the quasi-dipole coordinate frame), with the median of every SuperDARN measurement in the spatial bin taken every 5 minutes. These sparse binned data are infilled to provide a measurement at every spatial and temporal location via EOF analysis, ultimately comprising a reanalysis spanning the month of February 2001. This resource provides a convenient method of using SuperDARN data without its usual extreme sparseness, for studies of ionospheric electrodynamics. The reanalysis is provided in sets of orthogonal modes of variability (spatial and temporal patterns), along with the timestamps of each epoch, and the spatial coordinate information of all bin locations. We also provide the temporal mean of the data in each spatial bin, which is removed prior to the EOF analysis. Funding was provided by NERC standard grants NE/N01099X/1 (THeMES) and NE/V002732/1 (SWIMMR-T). No credit. completed Shore, Robert British Antarctic Survey Researcher author Freeman, Mervyn British Antarctic Survey Researcher author Chisham, Gareth 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 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 Data Interpolating Empirical Orthogonal Functions Ionospheric electrodynamics Plasma velocity SuperDARN reanalysis Upper atmosphere dynamics 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 This data is governed by the NERC Data Policy: https://www.ukri.org/who-we-are/nerc/our-policies-and-standards/nerc-data-policy/ otherRestrictions This data is governed by the NERC data policy and supplied under Open Government Licence v.3 url url crossReference url url largerWorkCitation doi doi crossReference textTable eng utf8 climatologyMeteorologyAtmosphere -180.0 180.0 60.0 90.0 2001-02-01 2001-02-28 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 application/x-hdf application/netcdf bytes 105906176 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=f4245a21-dee9-46cf-85b2-114798cb7ebc WWW:LINK-1.0-http--link Get Data Download data download bytes 105906176 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=f4245a21-dee9-46cf-85b2-114798cb7ebc WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: Following the data binning into an equal-area grid and 5-min medians as described in the abstract, the data gaps are infilled as follows. We initially infill the data gaps in the sparse binned data with zeros, and then we apply the method of data-interpolating Empirical Orthogonal Functions (EOFs). This allows global (i.e. the full extent of the binned data set) spatial and temporal basis vector patterns to be obtained. These basis vectors collectively describe the full variability of the dataset. The form (i.e. morphology/shape) of the basis vectors is controlled by the cross-correlations within the dataset. Since the ionospheric plasma velocity is strongly correlated in space and time, the spatial and temporal behaviour of the basis vectors with the largest eigenvalues (i.e. those which describe the majority of the variability in the dataset) are defined by the underlying physics of the ionospheric plasma. In contrast, since the missing data are relatively uncorrelated in space and time, the missing data contributes to lower-eigenvalue basis vectors. This provides us with a method to infill the missing values with the largest-eigenvalue basis vector, which is a better guess for the underlying plasma velocity field than the initial infill of zeros. Moreover, we have done this without any a priori specification of source geometry. The EOF-solution-and-infill process is repeated iteratively, until the amplitude of the infill converges with that of the data measurements, where both overlap. This infill only converges when it reinforces patterns present in the original data, thus providing a self-consistent description of the plasma velocity at the original temporal resolution of the SuperDARN data set. This gives complete spatial and temporal coverage without resorting to climatological averages, spatially smoothed models, or a priori relationships determined from solar wind drivers. Following this retrieval of the un-measured variability of the data, we fit a sinusoid model to translate the basis vectors from their line-of-sight (i.e. radar look direction) basis to a basis of cardinal north and east plasma velocity vector components. This method is described in full in a paper ('Data-Driven Basis Functions for SuperDARN Ionospheric Plasma Flow Characterisation and Prediction'), presently under review in JGR Space Physics (2021). Data collection: The data were gathered using the northern hemisphere radars of the SuperDARN global array, and the fitted Doppler velocities were processed from the original autocorrelation functions using version 4.0 of the radar software toolkit (RSTv4.0) and within that toolkit, fitting routine 'fitacfv2.5'. Data quality: The SuperDARN data 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 multiple of 45 km range distance from the radar array location) were not used, since these gave inaccurate locational estimates. asNeeded completed