Simulations of Antarctic Ice Sheet sensitivity to climate and ocean forcing for a suite of Antarctic palaeotopographies

We present steady-state ice thickness, bed elevation, and ice surface elevation output from simulations of the Antarctic Ice Sheet (AIS) on a suite of reconstructed Antarctic palaeotopographies using the DeConto and Pollard (DP16) ice sheet model. Ice surface mass balance inputs were provided using the GENESIS v3.0 global atmosphere general circulation model coupled to a 50 m slab ocean model, which provides boundary meteorology for the RegCM3 regional climate model. Three climate/ocean scenarios were simulated: (1) cold climate orbital parameters, preindustrial CO2 levels (280 ppm) and modern ocean temperatures, (2) a subsequent shift to warm climate orbital parameters, an increase in CO2 levels to 500 ppm, and a 5 deg C ocean temperature rise, and (3) as for (2), but with CO2 levels increased to 840 ppm. The steady-state simulations were performed on a suite of reconstructed Antarctic palaeotopographies pertaining to the following four time slices: (1) the Eocene-Oligocene boundary (EOB; ca. 34 Ma), (2) the Oligocene-Miocene boundary (OMB, ca. 23 Ma), (3) the mid-Miocene (MM; ca. 14 Ma), and (4) the mid-Pliocene (MP; ca. 3.5 Ma). Simulations were performed for minimum, median, and maximum end-member topographies, and equivalent simulations were run on the modern (ice-free) Antarctic bed topography for comparison. Further details are given in the accompanying publication. For more information, please contact G. Paxman. Funding was provided by NERC Ph.D. studentship NE/L002590/1

Ice flow model output for Pine Island Glacier (West Antarctica), from numerical inversions of ice surface velocities observed in 1996 and 2014

This data contains the model output of three numerical inversions of Pine Island Glacier ice surface velocities performed with the Community Ice Sheet Model (CISM2.0). The first and second simulations are inversions of the 1996 and 2014 velocity, respectively. The third simulation is a sensitivity experiment on the 2014 inversion. The gridded data consists of the ice surface velocity, basal velocity, basal stress, basal melt rates, and basal water fluxes, calculated for Pine Island Glacier catchment area

Occurrence records of ten Southern Ocean myctophid species with associated sea surface and depth-specific environmental conditions

This dataset contains occurrence records for ten Southern Ocean myctophid fish species that have been downloaded and cleaned from the online biodiversity repository GBIF. As well as providing GBIF documented metadata for each occurrence record, this dataset provides environmental conditions - specifically bathymetry, temperature, salinity, dissolved oxygen and net primary productivity - for each record. Both sea-surface and depth-specific values for the temperature, salinity and oxygen variables are given in separate data files. A third data file of corresponding background points and their associated environmental conditions is also provided. Together these data were used as input files for the MaxEnt ecological niche models within the peer reviewed article: Freer JJ, Tarling GA, Collins MA, Partridge JC, Genner MJ (2020) Estimating circumpolar distributions of lanternfish using 2D and 3D ecological niche models, Marine Ecology Progress Series

Ice flow model output for Pine Island Glacier (West Antarctica), from numerical inversions of ice surface velocities observed in 1996 and 2014

This data contains the model output of three numerical inversions of Pine Island Glacier ice surface velocities performed with the Community Ice Sheet Model (CISM2.0). The first and second simulations are inversions of the 1996 and 2014 velocity, respectively. The third simulation is a sensitivity experiment on the 2014 inversion. The gridded data consists of the ice surface velocity, basal velocity, basal stress, basal melt rates, and basal water fluxes, calculated for Pine Island Glacier catchment area

Data supplement: Regional disparities and seasonal differences in climate risk to rice labour

Data supplement to "Regional disparities and seasonal differences in climate risk to rice labour". The 880 million agricultural workers of the world are especially vulnerable to increasing heat stress due to climate change, affecting the health and income of individuals, while also decreasing global economic productivity. In this study, we focus on rice harvests across Asia and estimate the future impact on labour productivity by considering changes in climate at the time of the annual harvest. During these specific times of the year, heat stress is often higher compared to the rest of the year. Examining climate simulations of the Coupled Model Intercomparison Project 6 (CMIP6), we identified that labour productivity metrics for the rice harvest, based on wet-bulb globe temperature, are strongly correlated with global mean surface temperature in the long term (p<<0.01, R2>0.98 in all models). Limiting global warming to 1.5 °C rather than 2.0 °C prevents a clear reduction in labour capacity of 1% across all Asia and 2% across Southeast Asia, affecting the livelihoods of around 100 million people. Due to differences in mechanization between and within countries, we find that rice labour is especially vulnerable in Indonesia, the Philippines, Bangladesh, and the Indian states of West Bengal and Kerala.  Our results highlight the regional disparities and importance in considering seasonal differences in the estimation of the effect of climate change on labour productivity and occupational heat-stress.

Ambient Seismic Recordings and Distributed Acoustic Sensing (DAS): Imaging the firn layer on Rutford Ice Stream, Antarctica

This dataset contains the following files: 1. 7 hours of continuous DAS data (100 Hz sampling): 2020-01-14T00:00:19.598000Zoffset_****.mseed, with offset referring to the distance from the DAS channel to the interrogator. 2. Corresponding 7 hours of vertical component continuous geophone (A000, located at DAS channel offset 550 m) data

Seismic noise interferometry and Distributed Acoustic Sensing (DAS): measuring the firn layer S-velocity structure on Rutford Ice Stream, Antarctica

This dataset contains files including continuous DAS and geophone data and a refracted P wave travel time data collected on Rutford Ice Stream, Antarctica. The seismic data is used to perform seismic noise interferometry. The travel time data is used to perform refraction inversion to get the P wave velocity profile. 1. 7 hours of continuous DAS data (100 Hz sampling): 2020-01-14T00:00:19.598000Zoffset_****.mseed, with offset referring to the distance from the DAS channel to the interrogator. 2. Corresponding 7 hours of vertical component continuous geophone (A000, located at DAS channel offset 570 m) data. 3. Refraction P wave travel time from a geophone array refraction survey

Rutford Ice Stream Distributed Acoustic Sensing Dataset associated with the publication: Distributed Acoustic Sensing (DAS) for natural microseismicity studies: A case study from Antarctica

This dataset contains the following files: DAS_line_channels_info.txt - File containing DAS line geometry spatial coordinates. DAS_triangle_channels_info.txt - File containing DAS triangle geometry spatial coordinates. geophones_info.txt - File containing geophone network geometry spatial coordinates. buried_das_noise_period.m - MSEED file containing the DAS seismic data associated with the buried fibre. unburied_das_noise_period.m - MSEED file containing the DAS seismic data associated with the unburied fibre. icequakes_line_run_DAS_geophones_combined.txt - File containing icequake event catalogue for the line geometry deployment using both DAS and geophones for detection. icequakes_line_run_DAS_only.txt - File containing icequake event catalogue for the line geometry deployment using only DAS for detection. icequakes_line_run_geophones_only.txt - File containing icequake event catalogue for the line geometry deployment using only geophones for detection. icequakes_triangle_run_DAS_geophones_combined.txt - File containing icequake event catalogue for the triangle geometry deployment using both DAS and geophones for detection. icequakes_triangle_run_DAS_only.txt - File containing icequake event catalogue for the triangle geometry deployment using only DAS for detection. icequakes_triangle_run_geophones_only.txt - File containing icequake event catalogue for the line geometry deployment using only geophones for detection. Also includes the following event files, containing DAS observations +/- 10 seconds around the event (named by approx. event origin time): das_event_20200114040143.m das_event_20200114040226.m das_event_20200114050208.m das_event_20200117010211.m das_event_20200117010915.m das_event_20200117041807.

Processed bed elevation picks from airborne radar depth sounding across the region of three tributaries of Slessor Glacier, Coats Land, East Antarctica (2001/02 season)

During the austral summer of 2001/02 five thousand line kilometres of airborne radio echo sounding and aeromagnetic data were collected in the region of three tributaries of Slessor Glacier, East Antarctica, which drains into the Filchner Ice Shelf. We present here the processed bed elevation picks from airborne radar depth sounding acquired using the BAS aerogeophysicaly equipped Twin Otter aircraft. Data are provided as XYZ ASCII line data. Data were collected as part of UK Natural Environment Research Council (NERC) grant GR3/AFI2/6

Processed bed elevation picks from airborne radar depth sounding across the region of three tributaries of Slessor Glacier, Coats Land, East Antarctica (2001/02 season)

During the austral summer of 2001/02 five thousand line kilometres of airborne radio echo sounding and aeromagnetic data were collected in the region of three tributaries of Slessor Glacier, East Antarctica, which drains into the Filchner Ice Shelf. We present here the processed bed elevation picks from airborne radar depth sounding acquired using the BAS aerogeophysicaly equipped Twin Otter aircraft. Data are provided as XYZ ASCII line data. Data were collected as part of UK Natural Environment Research Council (NERC) grant GR3/AFI2/6