A mathematical model (Bennetts and Meylan, 2021, doi.org/10.1137/20M13851) has been used to make predictions of ocean wave transfer to Ross Ice Shelf flexure. The transfer is considered along transects of the Ross Ice Shelf and adjoining open ocean, where the ice shelf thickness and seabed profiles along the transects are sampled from the Bedmap2 dataset (Fretwell et al, 2013, doi.org/10.5194/tc-7-375-2013). Our dataset consists of MAT-files, where each file is for a particular transect and holds two structures: 'data_I' as input data and 'data_o' for the model output data. The input data are the profiles from Bedmap2: 'thick' is the shelf thickness, 'draft' is the shelf draught; and 'bed' is the seabed elevation. They are all in vector form with 2001 sample points along the shelf, which was found to give model outputs accurate to 95%. The input data also contains: a 1x2 vector 'L_vec', for which the first entry is the shelf length, and the second entry is the length of the adjoining open ocean, where both values are in metres; and a 1x2 vector 'Int_vec', for which the first entry is the total number of sample points (ocean + shelf) and the second entry is the number of points in the shelf only. The output date are the three matrices where the rows correspond to different wave period and columns are distances along the transect: 'eta_w' is the water displacement (dimensionless); 'eta_s' is the shelf displacement (dimensionless); and 'str' is the flexural shelf strain (1/metres). All three outputs are normalised by the incident amplitude, noting that the model is linear. The output data also contains: a 1x300 vector containing the wave periods 'T', which are log-spaced between 10s and 1000s. The data are divided into two folders: validation/ and transects/. The first group (validation/) are used to validate the model predictions against the observations of Chen et al (Geophysical Research Letters, 2019, doi.org/10.1029/2019GL084123) close to 2 km away from the shelf front, where the results of Chen et al (2019) have been digitised and are contained in 'Chen_paper.mat'. The second group (transects/) can be used to study transfer over a 500km wide region of the Ross Ice Shelf. There are 101 transects with 5 km spacing. We also analysed the shelf displacement and strain over different wave periods at 10 km away from shelf front for all transects to investigate the relations between strain and wave period, these data have stored in 'Transfer_function_x_10km.mat'. Three MATLAB scripts (Fig1.m, Fig2.m, Fig3.m) are included to recreate results from Bennetts et al (submitted). Fig1.m produces plots from observation (Chen et al) and our models. Fig2.m performs strain transfer function analysis for different profiles and Fig3.m generate the strain map and selected region of Ross Ice Shelf for given incident ocean wave. For Fig1.m, it requires “Bedmap2 Toolbox for Matlab” to access the bedmap2 for producing Ross Ice Shelf on the Antarctica map. A link to download this software will be stated in the MATLAB scripts. An updated dataset was provided on 2022-10-25.

The data are from our Nature Article from June 2018: "Antarctic ice shelf disintegration triggered by sea ice loss and ocean swell". The abstract is: "Understanding the causes of recent catastrophic ice shelf disintegrations is a crucial step towards improving coupled models of the Antarctic Ice Sheet and predicting its future state and contribution to sea-level rise. An overlooked climate-related causal factor is regional sea ice loss. Here we show that for the disintegration events observed (the collapse of the Larsen A and B and Wilkins ice shelves), the increased seasonal absence of a protective sea ice buffer enabled increased flexure of vulnerable outer ice shelf margins by ocean swells that probably weakened them to the point of calving. This outer-margin calving triggered wider-scale disintegration of ice shelves compromised by multiple factors in preceding years, with key prerequisites being extensive flooding and outer-margin fracturing. Wave-induced flexure is particularly effective in outermost ice shelf regions thinned by bottom crevassing. Our analysis of satellite and ocean-wave data and modelling of combined ice shelf, sea ice and wave properties highlights the need for ice sheet models to account for sea ice and ocean waves." Details of the analyses and data used, and the data generated by this study, are given in the paper: https://www.nature.com/articles/s41586-018-0212-1. Code availability: Analytical scripts used in this study are freely available from the authors via the corresponding author upon reasonable request. Data availability: The datasets and products generated during the current study are available from the corresponding author on reasonable request. The datasets forming the basis of the study are available as follows: (1) Sea ice: Daily estimates of satellite-derived sea ice concentration (gridded at a spatial resolution of 25 x 25 km) derived by the NASA Bootstrap algorithm for the period 1979-2010 were obtained from the US National Snow and Ice Data Center (NSIDC) dataset at: http://nsidc.org/data/NSIDC-0079. Accessed August 2015. (2) Waves: Ocean wave-field data were obtained from the CAWCR (Collaboration for Australian Weather and Climate Research) Wave Hindcast 1979–2010 dataset run on a 0.4 x 0.4° global grid: https://doi.org/10.4225/08/523168703DCC5. Accessed September 2017. (3) Satellite visible and thermal infrared imagery of ice shelves and disintegration events: The NOAA AVHRR image of the Larsen1995 disintegration used in Figure 2 was obtained from the British Antarctic Survey: http://www.nerc-bas.ac.uk/icd/bas_publ.html. Accessed June 2015. MODIS visible and 839 thermal infrared imagery from the US NSIDC archive at: http://nsidc.org/data/iceshelves_images/. Accessed June 2012. The study involved 2 model components, and model output is described below. The 2 models are: (i) a model of ocean swell attenuation by sea ice; and (ii) an ice shelf-ocean wave interaction model. Descriptions of both are given in the Nature paper (Methods section). DESCRIPTIONS OF THE 13 INDIVIDUAL DATA FILES PROVIDED (NB DESCRIPTIONS OF DATASETS GENERATED RELATIVE TO THE FIGURES) ARE GIVEN IN THE FILES: (1) Source data for Figures 4 (parts a-d), 5 and 6a are given in Excel spreadsheet files "Source-Data_2017-07-09041A_Figure.....xlsx". (2) Source data for Extended Data Figures 1 (parts a-b), 3 (parts b,d and parts a,c), 4 (parts b,d and a,c) and 6 are given in Excel spreadsheet files "Source-Data_2017-07-09041A_EDFig.....xlsx".