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“Operation IceBridge, CryoSat-2, ICESat”

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Presentation on theme: "“Operation IceBridge, CryoSat-2, ICESat”"— Presentation transcript:

1 “Operation IceBridge, CryoSat-2, ICESat”
Nathan Kurtz, NASA/GSFC NSIDC DAAC UWG Meeting August 9-10 Boulder, CO

2 Science research area Science study area - Arctic and Antarctic sea ice Types of data used: laser and radar altimetry (ICESat, OIB, CryoSat-2), visible and infrared imagery (OIB), reanalysis/model data Overview of preprocessing/analysis steps: data ingestion, geolocation Recommendations: need easy download script for new data over sea ice only

3 Science study/research area
Science question(s) being addressed: How is the thickness of the global sea ice cover changing? Data are global extent Time series: 2003-present for ICESat, OIB, and CryoSat-2 Is data latency/download time critical: Yes, move towards near real-time products

4 Types of data being used
Observational (satellite, airborne, site-based) data being used Data types and formats needed/desired: netCDF, HDF5, text Combining data with other sources or models? Yes, sea ice freeboard data needs to be combined with snow depth data (from e.g. model, passive microwave) to get thickness Large data volumes: Typically no, though OIB imagery is quite large

5 Data Workflow Question driven or exploratory: Exploratory
Pull data once and work on it locally: Yes Continuous pull: Not currently doing, but would like to move towards this approach Overview of preprocessing/analysis steps: retracking of radar data, separation of ice and water, geophysical correction application, combine freeboard and snow depth data Challenges/friction points? Data formats: data are typically in multiple formats Computational limitations: work speed limited by number of processors Subsetting/Regridding/reprojection: needed for combining data, especially reanalysis data

6 Recommendations Improvements to DAAC tools/services
Shared tools and scripts Need to alert users to new data sets that may be of interest to their subject area Push data/computing/tools into the cloud: could be effective if code is parallelized and there are free processors available


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