served from dlibrary.snia.gub.uy
root mean sq anom min root mean sq detrended-bfl ∫dX [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast PROBABILIDADESFORESCAST ] : Probabilidades - Precipitacion data
PROBABILIDADESFORESCAST int_dX adif adif min min Probabilidades - Precipitacion from IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast: Forecast and Error. isIndependent Variables (Grids)
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- halfgreyscale
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- 0
- fnname
- maskle
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 3.0
- units
- ids degree_east
- history
- [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Superior a lo Normal ) + masklt ( { [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Normal ) + masknotrange ( { [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ) - 1. ] * 11. } , 10 , 12 ) ]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Superior a lo Normal ] + masklt [ ( { dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ] - 1. } * 11. ) , 22 ]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Superior a lo Normal ]
dominant_class over ProbForecast[<35, >80]
- masklt [ ( { dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ] - 1. } * 11. ) , 22 ]
dominant_class over C[Debajo de lo Normal, Superior a lo Normal]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Superior a lo Normal ]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Normal ] + masknotrange [ ( { dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ] - 1. } * 11. ) , 10 , 12 ]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Normal ]
dominant_class over ProbForecast[<35, >80]
- masknotrange [ ( { dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Debajo de lo Normal, Superior a lo Normal]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Normal ]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Superior a lo Normal ] + masklt [ ( { dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ] - 1. } * 11. ) , 22 ]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Debajo de lo Normal ] + maskgt [ ( { dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ] - 1. } * 11. ) , 0 ]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Debajo de lo Normal ]
dominant_class over ProbForecast[<35, >80]
- maskgt [ ( { dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ] - 1. } * 11. ) , 0 ]
dominant_class over C[Debajo de lo Normal, Superior a lo Normal]
- dominant_class [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Debajo de lo Normal ]
- Averaged over S[0000 1 Jan 2000, 0000 1 Apr 2026] minimum 0.0% data present
min root mean sq detrended-bfl $integral dX$ [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast PROBABILIDADESFORESCAST ]- min over Y[29.5S, 35.5S] L[1.5 months, 3.5 months]
root mean sq anom min root mean sq detrended-bfl $integral dX$ [ IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast PROBABILIDADESFORESCAST ]- Averaged over X[59.5W, 52.5W] minimum 0.0% data present
- [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Superior a lo Normal ) + masklt ( { [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast Normal ) + masknotrange ( { [ dominant_class ( IRI Forecast GZ200_CFSV2-PRECIP_GPCC Forecast ProbForecast ) - 1. ] * 11. } , 10 , 12 ) ]
Last updated: Mon, 31 Jul 2017 15:25:55 GMT
Expires: Sat, 05 Aug 2017 00:00:00 GMT
Data Views
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
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units