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root mean sq anom min [ lat , root mean sq anom min ∂lon ( UY precipitacion ) ] : lat, ∂lon Precipitacion data
root mean sq anom min [ lat , root mean sq anom min ∂lon ( UY precipitacion ) ] . isIndependent Variables (Grids)
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- fnname
- min
- gridid
- 166962888
- missing_value
- NaN
- pointwidth
- 0.2826087
- scale_max
- null
- scale_min
- null
- units
- degree_north
- standard units*
- 0.0174532925199433 radian north
- history
- root mean sq anom min $partialdiff sub lon$ [ UY precipitacion ]
- min over lon[58.85526W, 53.64474W]
Averaged over time[Jan 1925, Dec 2009] minimum 0.0% data present
root mean sq anom min [ lat , root mean sq anom min $partialdiff sub lon$ ( UY precipitacion ) ]- Averaged over lat[29.5S, 36S] minimum 0.0% data present
- min over lon[58.85526W, 53.64474W]
Last updated: Sun, 02 Jun 2024 17:51:42 GMT
Data Views
 UY[precipitacion
prec
] |
| grid: /time (months since 1960-01-01) ordered (Jan 1925) to (Dec 2009) by 1.0 N= 1020 pts :grid |
 root mean sq anom min [ lat , root mean sq anom min $partialdiff sub lon$ ( UY precipitacion ) ] [ |] |
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