That gives ESRL a very large improvement in resolution, 384x432 = 165,888 vs 360x120 = 43,200 is 3.84 times as many grid cells. This explains in part why Piomas graphics are so horrible.
Wip's excellent efforts (where are APL's?) can only put lipstick on a pig because the data is way off the mark: concentric rings of monotonically thinning ice on the 31 August are inconsistent with what we know (a lot) about ice age distribution classes and thickness. Their distribution is quite complex; they're in concentric bands off the CAA only to 0th order.
But we knew that much just from it being colder there. With a one-parameter fit (slope), the concentric rings can be generated and intersected with the ice pack shape from AMSR. Since a half meter error on two meter ice is acceptable on this forum, we're just about home with a photoshop hack.
If the Arctic Ocean proper is 8 million sq km, then ESRL cells are ~48 sq km or about 7 km on a side whereas Piomas cells are 185 sq km or about 24 km on a side. This matters relative to intrinsic scales of ice features such as floe size, ridging, ice edge and lead openings, dispersion, compaction, and localized interaction with air temperatures, melt, snow cover and rain.
It is a pity but the fact is, groups or individuals (like J Hansen after retirement) lacking adequate computer resources aren't going to be in the game, any more than they are in hurricane track prediction.
Equally unfortunate for Piomas is the unavoidable importance of graphics in effectively communicating results in climate science beyond a tiny clique of numerical analysts. See @zlabe to get an idea of what great graphics can do.
Along these lines, it's worth noting that ESRL is able to put out daily forecasts up to 10 days out in 6 hour increments (40 frame animations, REB.2017-09-05.nc bundles) whereas Piomas is hindcasting once a month several days after the fact, and only then because people here bug them. ESRL is thus readily integrable in near-real time in the GIS sense -- by anybody -- with many other independent .nc Arctic resources such as the 3.125 km UH AMSR2.
Panoply is not really "specialist software". It is a small, intuitive menu-driven bit of NASA freeware that's been available since Dec 2002 in everyone's operating system, updated regularly to the present. Nothing could be easier for viewing data arrays or exporting them (or subsets) as csv tables to excel. For people who do not want to look at command-line or big-endian (99% of forum members?), this is about the only option to unpack .nc files and get a quick map view of the data -- just double-click on any line labelled Geo2D. How hard is that -- and what is the alternative?
If it is so easy to get Piomas out of its funky coordinate system, why then do we have a separate 286-post forum explaining the intricate struggles to get it re-cast as something that can be compared to say Cryosat?
The PIOMAS grid is rendered on the 0.5km grid using polygons to approximate the curvilinear grid. This results in a maximum error of around 1km at the centre of the polygon faces. The result of this error is that each grid cell loses a small area to the grid cell in the row below and gains slightly less area from the grid cell in the row above. There is a similar error at the grid cell corners because the latitude & longitude co-ordinates for the PIOMAS grid are only provided to an accuracy of two decimal places.
There's free full text of Maslowski 2012 at ResearchGate, just google the doi:10.1029/2011JC007257. It's been cited subsequently 50 times. His academic papers overall have gotten a respectable 2,460 journal cites, about a third of mine.