served from dlibrary.snia.gub.uy
root mean sq anom mean detrended-bfl ∂X ∂L detrended-bfl ∂S [ IRI Forecast_old SST_CFSV2-PRECIP_GPCC History InputObs ] : ∂X ∂L ∂S input observations data
InputObs partial_S adif partial_L partial_X adif adif adif ∂X ∂L ∂S input observations from IRI Forecast_old SST_CFSV2-PRECIP_GPCC History: Predicand, Hindcast and Skill.Independent Variables (Grids)
- Latitude (latitude)
- grid: /Y (degree_north) ordered (30S) to (35S) by 1.0 N= 6 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 3.0
- units
- 99.0071069986062 meter radian-1 east year-3
- history
- root mean sq anom mean detrended-bfl $partialdiff sub X$ $partialdiff sub L$ detrended-bfl $partialdiff sub S$ [ IRI Forecast_old SST_CFSV2-PRECIP_GPCC History InputObs ]
- Averaged over X[59.5W, 52.5W] L[1.5 months, 3.5 months] minimum 0.0% data present
Averaged over T2[1982, 2013] S[Jan 2015, Feb 2017] minimum 0.0% data present
- Averaged over X[59.5W, 52.5W] L[1.5 months, 3.5 months] minimum 0.0% data present
Last updated: Wed, 08 Mar 2017 14:24:39 GMT
Data Views
Views
line plots
color bars
scatter
Filters
Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.- Monthly Climatology calculates a monthly climatology by averaging over all years.
- anomalies calculates the difference between the (above) monthly climatology and the original data.
- Integrate along Y
- Differentiate along Y
- Take differences along Y
RMS (root mean square with mean *not* removed) over Y |
RMSA (root mean square with mean removed) over Y |
Maximum over Y |
Minimum over Y |
Detrend (best-fit-line) over Y |
Note on units