Notes from the Climate Analysis group

precalculated diurnal cycle per month - T, P, cloud cover/fraction, sfc wind

• for 2D vars - 3h monthly average
• all table 2 & table 3 fields?

storm track metric: 500 mb variance, u' v', jet location

TC identification?

CAPE, CIN, shear, &/or other instability fields (moisture convergence/div, moisture flux) or other fields the RCMs should hndle better than GCMs (for regional detail)

monthly mean precomputed ensembles & ensemble variances

driving model data and if not, at least driving model data specifics (run #, etc.)

• -- at least monthly mean data, maybe daily (w/ diurnal cycle?) available from website
• --for sfc variables
• --precalc ENSO, MJO indices from drawing model to know if one was there ? or list of years w/ El Nino / la Nina to avoid download all years if not needed

list of parameterizations used & links on website to main paper

NARCCAP users & modelers reference list w/ link to manuscripts

one page summary &/or list of references per model

• parameterizations, internal nudging

recommended datasets (reanalysis) - links to them

other derived diagnostic fields from 3D fields

disaggregated levels - e.g., 500 mb heights, 240 mb wind

• need for reduced # 3D levels (standard heights)
• may want only 1 level (new esg system already does this?)

easy esg subsetting and suggested links

should decide & precalc some common vert. integrated & derived vars

info on caveats for users

how driving models fit into distribution of AR4 models

precalc histograms of the data downloaded

• or basic/preview stats
• what kind of distribution most useful
  • ways to reduce data needed for high freq. description
• 2d vars that describe extremes (short list) (e.g. Tebaldi vars)