Ian Eisenman research group GitHub page

[See also: UCSD website]

Model of iceberg drift and decay including breakup: Python code, as well as ocean and atmosphere forcing datasets, for a Lagrangian iceberg model that includes a probabilistic breakup scheme for large tabular icebergs.
iceberg_model_EWE20.py
forcing datasets
England, Wagner, and Eisenman (2020). Modeling the breakup of tabular icebergs. Science Advances 6, eabd1273.

CESM simulations with specified sea ice motion: Model setup files and simulation results for runs with (i) the sea ice momentum equation replaced with relaxation to a specified observations-based ice motion field and (ii) the simulated surface wind field in the sea ice momentum equation replaced with a specified observations-based wind field.
CESM code modifications
Simulation output fields
Sun and Eisenman (2021). Observed Antarctic sea ice expansion reproduced in a climate model after correcting biases in sea ice drift velocity. Nature Communications 12, 1060.

Idealized model of sea ice and global climate with two ocean layers: Matlab code for a diffusive energy balance model (EBM) with seasonal variations, sea ice, and two ocean layers, including also code to run the model with the vertical heat flux locked.
sea_ice_EBM_deep_BEW20.m
plot_sea_ice_EBM_deep_BEW20.m
sea_ice_EBM_deep_locked_BEW20.m
Beer, Eisenman, and Wagner (2020). Polar amplification due to enhanced heat flux across the halocline. Geophysical Research Letters 47, e2019GL086706.

Model of iceberg drift and decay: Matlab code, as well as input forcing and seeding fields, for a Lagrangian iceberg model.
iceberg_model_WDE17.m
iceberg_model_WDE17.zip
Wagner, Dell, and Eisenman (2017). An analytical model of iceberg drift. Journal of Physical Oceanography 47, 1605-1616.

CMIP5 and CESM-LE sea ice and global temperature: NetCDF file containing processed GCM output from the CMIP5 and CESM-LE (aka LENS) archives: Arctic and Antarctic sea ice extent and sea ice area, as well global-mean surface air temperature.
CMIP5_processed_data_RE17.nc
CESMLE_processed_data_RE17.nc
E. Rosenblum and I. Eisenman (2017). Sea ice trends in climate models only accurate in runs with biased global warming. Journal of Climate 30, 6265-6278.

CMIP3 sea ice and global temperature: NetCDF file containing processed GCM output from the CMIP3 archive: Arctic and Antarctic sea ice extent and sea ice area, as well global-mean surface air temperature.
CMIP3_processed_data_RE16.nc
E. Rosenblum and I. Eisenman (2016). Faster Arctic sea ice retreat in CMIP5 than in CMIP3 due to volcanoes. Journal of Climate 29, 9179-9188.

CESM ocean-only simulations: Details related to CESM1 simulations in which only the ocean is active and the atmosphere, sea ice, and land runoff are specified from previous coupled simulations.
CESM-setup-notess_SES2016.pdf
PI-run-scriptss_SES2016.tgz
processed-simulation-outputs_SES2016.tgz
S. Sun, I. Eisenman, and A. Stewart (2016). The influence of Southern Ocean surface buoyancy forcing on glacial-interglacial changes in the global deep ocean stratification. Geophysical Research Letters 43, 8124-8132.
S. Sun, I. Eisenman, and A. Stewart (2018). Does Southern Ocean surface forcing shape the global ocean overturning circulation? Geophysical Research Letters 45, 2413-2423.

Idealized model of sea ice and global climate with weather noise: Matlab code for a diffusive energy balance model (EBM) with seasonal variations, sea ice, and stochastic weather noise.
sea_ice_EBM_WE15b.m [python version]
Wagner and Eisenman (2015). False alarms: How early warning signals falsely predict abrupt sea ice loss. Geophysical Research Letters 42, 10333-10341.

Idealized model of sea ice and global climate: Matlab code for a diffusive energy balance model (EBM) with seasonal variations and sea ice.
sea_ice_EBM_WE15.m [python version]
Model documentation: WE15_numerics.pdf
Wagner and Eisenman (2015). How climate model complexity influences sea ice stability. Journal of Climate 28, 3998-4014.

Energy balance model (EBM) of global climate: Matlab code for the standard annual-mean EBM discussed in Sec. 2b of the reference below. There is a relatively simple script and a faster but more complicated script.
EBM_simple_WE15.m [python version]
EBM_fast_WE15.m [python version]
Wagner and Eisenman (2015). How climate model complexity influences sea ice stability. Journal of Climate 28, 3998-4014.

Observed Antarctic sea ice cover: Monthly-mean quantities derived from Version 1 and Version 2 of the Bootstrap daily ice concentration dataset in the Southern Hemisphere: time series of ice extent and ice area, as well as ice concentration fields.
SH_sea_ice_area_Bootstrap_V1_V2.txt
SH_sea_ice_concentration_Bootstrap_V1_V2.nc
Eisenman, Meier, and Norris (2014). A spurious jump in the satellite record: has Antarctic sea ice expansion been overestimated? The Cryosphere 8, 1289-1296.

Toy model of sea ice and climate: Matlab code for a simplified dimensionless single-column sea ice model.
sea_ice_model_E12.m [dimensional version]
Eisenman (2012). Factors controlling the bifurcation structure of sea ice retreat. Journal of Geophysical Research—Atmospheres 117, D01111.

Observed Arctic sea ice edge: Zonal-mean sea ice edge latitude, sea ice extent, and sea ice equivalent extent (defined as total surface area, including land, north of the zonal-mean sea ice edge latitude) from 1978-2010 daily satellite-derived Northern Hemisphere sea ice concentration.
NH_observed_ice_edge_lat_and_extent.txt
Eisenman (2010). Geographic muting of changes in the Arctic sea ice cover. Geophysical Research Letters 37, L16501.

CCSM3 simulations with large and medium glacial ice sheets: This webpage has details regarding our NCAR CCSM3 T31x3 large ice sheet (Last Glacial Maximum) and medium ice sheet (12kya) simulations, including model setup description, setup files, and simulation results.
CCSM-LGM-and-12k
Eisenman, Bitz, and Tziperman (2009). Rain driven by receding ice sheets as a cause of past climate change. Paleoceanography 24, PA4209.

Single-column Arctic sea ice and climate model: Matlab code for an idealized model of the coupled Arctic sea ice-ocean-atmosphere climate system.
sea_ice_model_EW09.m
Eisenman and Wettlaufer (2009). Nonlinear threshold behavior during the loss of Arctic sea ice. Proceedings of the National Academy of Sciences 106, 28-32.

Paleo insolation: Matlab script to compute daily average insolation (sunlight at the top of the atmosphere) as a function of day and latitude at any point during the past 5 million years.
daily_insolation.m
Huybers and Eisenman (2006). Integrated summer insolation calculations. NOAA/NCDC Paleoclimatology Program Data Contribution #2006-079.

Miscellaneous Matlab scripts: Toolbox of various Matlab functions.
matlab-toolbox