This page is under construction...explanation and links will be added in the coming days and weeks...feedback welcome!
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1. ACME adopted flawed FV (regular in latitude, except at the poles) grids gridfiles that omitted a small strip of longitude to the east of Greenwich. This problem was identified independently by Charles Doutriaux and myself. For FV 129x256, this amounted to 0.2% of global area, that might appear as a gap or blank strip when plotted. Maps based on the flawed grids somehow reapportion area so that total area is conserved (4*pi sr), yet this necessarily redistributes weights from their true positions. This causes a mismatch between "area"- and "gw"- weighted statistics. The solution is to generate grids that center Greenwich in the first zonal gridcell, and to base maps on those grids. With these grids, the gap disappears and "area"- and "gw"-weighted statistics agree to double-precision.
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3. All SCRIP and CESM-maintained Gaussian grids that I have examined (T42, T62, and T85) infer gridcell interfaces as midpoints between Gaussian quadrature points/angles. Software then infers the gridcell areas from gridcell interfaces. The problem is that interfaces defined by the midpoint rule will always produce areas inconsistent with those implied by the quadrature weights. This causes a mismatch between "area"- and "gw"- weighted statistics. NCO now uses Newton-Raphson iteration (instead of the quadrature midpoints) to determine the gridcell interface location that exactly matches areas determined by the (now double-precision) Gaussian weights. The Newton-Raphson iteration moves interfaces by, typically, a few tenths of a degree (for moderate resolution Gaussian grids) from their previous locations as quadrature midpoints. With these grids, "area"- and "gw"-weighted statistics are consistent and agree to double-precision.
4. Some regular equi-angular lat/lon grids historically produced and used in the CESM community utilize the continuous form of the weighting function (i.e., cosine(lat)) evaluated on the discretized grid, rather than the exact discretized weight function (i.e., the difference of the sine of the latitudes bounding the zone). And some of these regular equi-angular lat/lon grids are used as staggered/offset grids for FV dynamics variables (e.g., U, V). All regular equi-angular lat/lon grids must have the same functional form for weights as the FV grid itself, since they are simply offsets of eachother. Without this correction, statistics of variables computed on the FV dynamics grid may be misdiagnosed (fxm: last sentence not yet verified). Users of all regular equi-angular grids, including staggered FV grids, should ensure their grids were produced with the correct weighting function. One way to do this is to verify the "area" variable, if present, exactly matches the area between the gridcell interfaces. If unsure, consider generating a new regular grid with the instructions below, or ask me and I will be happy to generate one for you and keep it in a standard location where others may access it.
5. For historical reasons, mapfiles generated by ESMF_RegridWeightGen (up to and including version 6.3.0rp1) using bilinear interpolation do not include complete output grid information. In particular, they lack gridcell area, because the ESMF team thought area would not be desired by users employing non-conservative mapping. However, it is helpful to include area so long as users understand that interpolative maps are non-conservative. The new mapfiles include gridcell area for bilinear interpolation maps.
6. Great circle arcs vs. lat/lon arcs, latitude-weights, and --user_areas...fxm.
Why Migrate?
The new grids and mapfiles address these problems, which have always existed in ACME and its predecessors (CESM, CCSM, CCM), and therefore cannot be too severe. The numerical flaws explained above can be thought of as fuzziness at the level of a few tenths of a degree in geo-referencing regridded data to the native model grid. These location errors produce only small (<< 1%) errors in regional or global statistics. So, why migrate? One aim is that diagnostics and observational evaluations with regridded data (often much more intuitive to visually evaluate than native SE grids) produce the same answers (to double precision whenever possible) as statistics computed on the native model grid. Without migration, agreement between native and regridded statistics beyond single precision is a matter of luck and coincidence, not determinism and reproducibility. As ACME grids shift to ~1/4 degree and finer, it becomes even more important to exploit the full double precision accuracy that software can guarantee when supplied with accurate grids.
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