DOI: 10.5285/91523ff9-d621-46b3-87f7-ffb6efcd1847
title: BEDMAP3 - Ice thickness, bed and surface elevation for Antarctica - standardised data points

description: We present here the Bedmap3 ice thickness, bed and surface elevation standardised CSV data points that are used to create the Bedmap3 gridding products in addition to the previous data releases. The data consists of 50 million points acquired by 17 different data providers in Antarctica.
The associated datasets consist of: 
- Bedmap1 standardised CSV data points: https://doi.org/10.5285/f64815ec-4077-4432-9f55-0ce230f46029
- Bedmap2 standardised CSV data points: https://doi.org/10.5285/2fd95199-365e-4da1-ae26-3b6d48b3e6ac
- Bedmap3 statistically-summarised data points (shapefiles): https://doi.org/10.5285/a72a50c6-a829-4e12-9f9a-5a683a1acc4a
This work is supported by the SCAR Bedmap project and the British Antarctic Survey's core programme: National Capability - Polar Expertise Supporting UK Research
description: The primary source data consist of survey point measurements of ice thickness, bed elevation and surface elevation, which principally comes from airborne radar surveys and seismic soundings, and to a smaller extent from ground-based radar surveys. 
All the data have been standardised to a specific CSV format. The format consists of (i) an extended header section where (a) each line is introduced by a comment (#) character, (b) each line contains a single header item, (c) the colon character (:) is used as the key/value separator, (d) units are in parentheses, (e) attributes preferably use a common vocabulary such as the CF convention and includes attributes from the ACDD; (ii) a header row composed of the column name following the CF convention and units in parentheses; and finally (iii) the data using comma as the separator. The extended header consists of general information regarding each campaign such as the year, the name of the main investigator, funding and processing details.
The variable names are as follows: 
trajectory_id Line or Flight ID
trace_number Trace number from the specific line given in Line_ID
longitude Longitude (WGS84 EPSG: 4326) in decimal degrees
latitude Latitude (WGS84 EPSG: 4326) in decimal degrees
date Date following ISO 8601 format: YYYY: year, MM: month, DD: day
time_UTC UTC time following ISO 8601 format: HH: hours, MM: minutes, SS: seconds
surface_altitude Surface elevation or altitude (referenced to WGS84) in meters
land_ice_thickness Ice thickness in meters
bedrock_altitude Bed elevation or altitude (referenced to WGS84) in meters
two_way_travel_time Two-way travel time in seconds
aircraft_altitude Aircraft elevation or altitude when applicable (referenced to WGS84) in meters
along_track_distance Distance in the along-track direction in meters
description: All non-value data were converted to -9999, including any negative ice thickness values and any points with clear outliers. We checked the minimum and maximum values of each field to ensure the data are in a reasonable range and calculated mean and standard deviation on each dataset to identify potential issues. For example, if longitude/latitude values did not fall within the expected -180 to 180 or -50 to -90 degrees range respectively, the entire row was removed. When no ice thickness values were provided but surface and bed elevation values existed, we simply calculated ice thickness by subtracting the surface value from the bed value. At times, bed elevation was higher than surface elevation, likely due to issues with the semi-automatic picker used to extract the surface and bed reflector or a lack of distinctive reflectors in areas of shallow ice. To prevent this affecting the gridded product, we converted these values to -9999 for both the surface and the bed. Finally, we also conducted routine checks on the ice thickness data by comparing the given ice thickness value with the inferred ice thickness calculated from subtracting surface with bed. If these did not match, we placed -9999 on the ice thickness values.
 File naming conventions were also used throughout to easily identify a specific dataset as follows: DataProvider_Year_CampaignName_TypeofData_BM3. The type of data used was separated into three categories: Airborne Radar (AIR), Ground-based Radar (GRN), and Seismic (SEI) data. The 'BM3' abbreviation at the end identifies the datasets was part of the Bedmap3 compilation to differentiate from the Bedmap 1 and 2 (BM1 and BM2) compilations. For instance, the file named 'NASA_2019_ICEBRIDGE_AIR_BM3.csv' refers to the ICEBRIDGE airborne campaign led by NASA in 2019.