Ground ice in the crust and soil may be one of the largest reservoirs of water on Mars. Near-surface ground ice is predicted to be stable at latitudes higher than 40 degrees (ref. 4), where a number of geomorphologic features indicative of viscous creep and hence ground ice have been observed. Mid-latitude soils have also been implicated as a water-ice reservoir, the capacity of which is predicted to vary on a 100,000-year timescale owing to orbitally driven variations in climate. It is uncertain, however, whether near-surface ground ice currently exists at these latitudes, and how it is changing with time. Here we report observational evidence for a mid-latitude reservoir of near-surface water ice occupying the pore space of soils. The thickness of the ice-occupied soil reservoir (1-10 m) and its distribution in the 30 degrees to 60 degrees latitude bands indicate a reservoir of (1.5-6.0) x 104 km3, equivalent to a global layer of water 10-40 cm thick. We infer that the reservoir was created during the last phase of high orbital obliquity less than 100,000 years ago, and is now being diminished.

The continuum theory applied to biomolecular electrostatics leads to an implicit-solvent model governed by the Poisson-Boltzmann equation. Solvers relying on a boundary integral representation typically do not consider features like solvent-filled cavities or ion-exclusion (Stern) layers, due to the added difficulty of treating multiple boundary surfaces. This has hindered meaningful comparisons with volume-based methods, and the effects on accuracy of including these features has remained unknown. This work presents a solver called PyGBe that uses a boundary-element formulation and can handle multiple interacting surfaces. It was used to study the effects of solvent-filled cavities and Stern layers on the accuracy of calculating solvation energy and binding energy of proteins, using the well-known apbs finite-difference code for comparison. The results suggest that if required accuracy for an application allows errors larger than about 2% in solvation energy, then the simpler, single-surface model can be used. When calculating binding energies, the need for a multi-surface model is problem-dependent, becoming more critical when ligand and receptor are of comparable size. Comparing with the apbs solver, the boundary-element solver is faster when the accuracy requirements are higher. The cross-over point for the PyGBe code is in the order of 1–2% error, when running on one gpu card (nvidia Tesla C2075), compared with apbs running on six Intel Xeon cpu cores. PyGBe achieves algorithmic acceleration of the boundary element method using a treecode, and hardware acceleration using gpus via PyCuda from a user-visible code that is all Python. The code is open-source under MIT license.

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