**General****Modeling****Ice Sheet System Model**: Large-scale, 3D finite element ice flow model developed at JPL and the University of California Irvine.**Outreach****Iceland****IMO**: Icelandic Meteorological Office**Safetravel.is**: Crevasse maps for Iceland**Glacier outlines**: World glacier inventory**Antarctica****Velocity fields****Mosaics****MOA**: MODIS mosaic and snow grain size estimates.**LIMA**: Landsat mosaic**RAMP**: RADARSAT synthetic aperture radar backscatter amplitude mosaic**Topography****Bedmap2**: Bedrock, surface topography, grounding lines and coastline data from British Antarctic Survey**1-km DEM**: 1-km DEM from ERS-1 InSAR and ICESat laser altimetry**Grounding lines****Bedmap2**: Grounding lines and coastline data from combined DInSAR and MOA GLs**InSAR**: DInSAR-derived grounding lines**ICESat**: Grounding and hydrostatic lines derived from lazar altimeter onboard ICESat**MOA**: MODIS-derived grounding line and coastline files**ASAID**: Grounding and hydrostatic lines from Antarctic Surface Accumulation and Ice Discharge (ASAID) project**Drainage****NASA**: Radar altimeter derived drainage system boundaries and masks**Tidal models****Extras****Global ocean circulation**: "Perpetual Ocean" is an amazing video of global ocean surface currents**Ice/ocean**: Video of ocean circulation and ice shelf thickness

**Coding**:**Python**: A versitile high-level programming language that is easy to learn and can be augmented by a number of open-source libraries that cover the basic needs of nearly all scientific users. The Python community is very active and enthusiastic, so the number of available libraries continues to grow. Python is easily extensible with modules, which can written in low-level languages, like Fortran and C/C++, for improved performance and/or to recycle existing code. In short, if a scientist were to learn only one programming language, that language should be Python.**NumPy**: Numerical library, and much more, for Python.**SciPy**: Extensive scientific library for Python.**matplotlib**: Plotting library for Python.**matplotlib-basemap**: Geospatial plotting with matplotlib and Python. Basemap provides a pythonic interface for making maps, but has fewer tools than and, in my opinion, produces inferior results compared to**GMT**(see below).**mpi4py**: Python wrapper for MPI.**petsc4py**: Python wrapper for PETSc.**pyproj**: Python wrapper for PROJ.4.**GDAL**: Python wrapper for GDAL.**netcdf4-python**: Python wrapper for NetCDF4.**h5py**: Python wrapper for HDF5 library.**pyresample**: Geospatial resampling toolbox for Python.**PIL**: Python Imaging Library, which contains a number of useful tools for image io and manipulation.**f2py**: Fortran to Python interface generator for wrapping Fortran subroutines with Python. f2py is included with all current NumPy distributions, so the link is for the f2py documentation.**Fortran**: Fortran is a widely used, low-level language that is easy to learn. Many legacy codes are written in Fortran and though it may lack the versitility of newer languages like C++, the speed and ease of use make Fortran a great tool for anyone who writes a lot of code.**BLAS**: Basic Linear Algebra Subprograms.**LAPACK**: Linear Algebra Package is an indespensible library that contains a wealth of linear algebra tools.**OpenBLAS**: Optimized and (optionally) threaded BLAS.**C++**: Resources for C++, a commonly used, low-level, object-oriented language that builds upon (possibly enhances, depending on your point of view) C. C++ is one of the more difficult languages to master, but learning it may be worth the effort, depending on your particular applications and the existing tools relevant to those applications.**Geospatial**:**GMT**: Generic Mapping Tools is a toolbox for virtually any kind of plotting. GMT excels at geospatial plots. A number of useful tools, such as filters, for manipulating data are also included. The interface takes some getting used to, but the resulting plots are second to none.**CPT-City**: A good plot goes a long way. CPT-City has a wealth of colormaps in multiple formats to enhance plotting.**GDAL**: Geospatial data abstraction library (GDAL) contains a variety of tools for working with geospatial data. Basic and useful tools include format conversion routines and coordinate system transformation tools.**PROJ.4**: Cartographic projections library.**Parallelization**:**pthreads**: Documentation for POSIX threads (pthreads), open-source implementation of shared-memory parallelization.**OpenMP**: Open-source library for shared-memory parallelization.**OpenMPI**: An open-source message passing interface (MPI) library for distributed-memory parallelization.**MPICH**: Another open-source MPI library.**PETSc**: Portable Extensible Toolkit for Scientific Computation, for all your parallel PDE solver needs.**Finite element**:**Ice Sheet System Model**: Large-scale, 3D finite element ice flow model developed at JPL and the University of California Irvine.**FEniCS Project**: Generalized solutions of differential equations. (Mac users might need to install Ubuntu on a virtual machine)**Miscellaneous**:**SuiteSparse**: Extensive library of sparse-matrix tools. Probably the easiest and most straightforward way to get AMD and UMFPack, both of which*can*be used by SciPy (see above) to speedup scipy.sparse library.**FFTW**: Fastest Fourier Transform in the West

**Training****Mustache Man Training**: "Keep on doin'"**Running****Hal Higdon Training**: An assortment of training methods described by an accomplished marathoner.**No Meat Athlete**: An excellent blog (even for those of us who do not run exclusively on plants) on running, nutrition, gear, and a variety of other useful and interesting topics.**iRunFar.com**: Trail running resources.**Arctic Running**: Resources and races in Iceland**Trail Porn**: Apt slogan: "It won't get you fired, even if you want it to!"