served from 129.236.110.25
mean ∂S ∫dS root mean sq ∂C [ OLE2 CPT ESCENARIO2 ODDSWETDAYS ] : ∂S ∂C ODDS Días Lluviosos data
mean ∂S ∫dS root mean sq ∂C [ OLE2 CPT ESCENARIO2 ODDSWETDAYS ] .Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- S (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (16 Dec 1999 - 15 Jan 2000) to (16 Nov 2025 - 15 Dec 2025) by 1.0 N= 312 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (32.5N) to (62.5S) by 0.5 N= 191 pts :grid
Other Info
- CE
- null
- CS
- null
- datatype
- realarraytype
- file_missing_value
- -999.0
- missing_value
- NaN
- pointwidth
- 0
- units
- percent /ids months /months
- history
- mean $partialdiff sub S$ $integral dS$ root mean sq $partialdiff sub C$ [ OLE2 CPT ESCENARIO2 ODDSWETDAYS ]
- Averaged over X[118W, 28W] minimum 0.0% data present
Averaged over C[, ] minimum 0.0% data present
- Averaged over X[118W, 28W] minimum 0.0% data present
Last updated: Sat, 06 Dec 2025 07:30:02 GMT
Expires: Mon, 05 Jan 2026 00:00:00 GMT
Data Views
Views
data as colors
data as contours| L | S | Y | |
 mean $partialdiff sub S$ $integral dS$ root mean sq $partialdiff sub C$ [ OLE2 CPT ESCENARIO2 ODDSWETDAYS ] 2.5 months[ Y | S L] | M | M | M |
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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 S
- Differentiate along Y S
- Take differences along Y S
RMS (root mean square with mean *not* removed) over Y S | Y S |
RMSA (root mean square with mean removed) over Y S | Y S |
Maximum over Y S | Y S |
Minimum over Y S | Y S |
Detrend (best-fit-line) over Y S | Y S |
Note on units