Explore projects

Example notebook testing waveform interpolation in the frequency domain with zero-padding and comparing the results to the current TFMRA implementation in pysiral.

EU project OCEAN:ICE Deliverable: D1.4 Gridded European circumpolar sea ice production fluxes

This deliverable is a new dataset of sea ice production (SIP) in Antarctic coastal polynyas, critical regions for sea ice formation and dense water formation. Using Earth Observation data and atmospheric reanalysis, we use a heat budget method to estimate the SIP. We use sea ice concentration (SIC) from passive microwave sensors and ECMWF ERA5 reanalysis for near-surface wind speed and surface air temperature. Comparison against previous literature shows broad consistency in spatial patterns and magnitude of ice production, with notable variations across larger polynyas. Despite simplifications and thereby increased uncertainties in the absolute ice production values, the data set provides valuable insights into the dynamics and variability of Antarctic polynya SIP for the period 1992-2023.

Citation: Kaleschke, L. (2024). EU project OCEAN:ICE Deliverable: D1.4 Gridded European circumpolar sea ice production fluxes [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11652686

scripts for pre- and postprocessing

Calculate time series of distance to open water or ice edge for a set of locations using SSMI sea ice concentration data.

SMOS-derived Antarctic thin sea-ice thickness from 2010 to 2020: data description and validation in the Weddell Sea

Code and data for figures and statistics used in the ESSD paper with the same title.

Python module of Uwe Zenker (WERUM Software & Systems AG) to connect to and query AWI Datapool (Hadoop system) on behalf of the AWI Data Centre. Access near realtime data, DSHIP data and PANGAEA data warehouse in one go!

Generation of AWI-ESM Boundary Conditions from various reconstructions

Investigation of trend sensitivity in SPARC (and other) borehole sites via numerical modeling.

Scripts and configuration files to process ALS data from MOSAiC both with als_level1b_seaice (IDL Level-1b processor) and awi-als-toolbox (python code for high level data products)

Python implementation of a live data read from the Velodyne-HDL-32E LiDAR sensor. The program is capable to read from pcap files and translate to txt files, and point cloud format. Furthermore it provides a live data read out in XYZ coordinates.