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root mean sq [ ∫dX ( ∂Y { ICPAC CHIRP-BLENDED monthly rainfall precipitation } anomalies ) climatology ]: ∂Y Precipitation data
root mean sq [ ∫dX ( ∂Y { ICPAC CHIRP-BLENDED monthly rainfall precipitation } anomalies ) climatology ].Independent Variables (Grids)
- Time (time)
- grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (11.75S) to (23.1N) by 0.05 N= 698 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 1.0
- units
- mm /month
- standard units*
- 0.012 meter year-1
- history
- $integral dX$ [ $partialdiff sub Y$ ( ICPAC CHIRP-BLENDED monthly rainfall precipitation ) anomalies ] climatology
- Averaged over T2[1981, 2016] minimum 0.0% data present
Averaged over T2[1981, 2016] minimum 0.0% data present
root mean sq [ $integral dX$ ( $partialdiff sub Y$ { ICPAC CHIRP-BLENDED monthly rainfall precipitation } anomalies ) climatology ]- Averaged over X[21.83E, 51.48E] minimum 0.0% data present
- Averaged over T2[1981, 2016] minimum 0.0% data present
Last updated: Thu, 17 Dec 2020 09:38:54 GMT
Expires: Wed, 10 May 2017 00:00:00 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars
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 T
- Differentiate along Y T
- Take differences along Y T
RMS (root mean square with mean *not* removed) over Y T | Y T |
RMSA (root mean square with mean removed) over Y T | Y T |
Maximum over Y T | Y T |
Minimum over Y T | Y T |
Detrend (best-fit-line) over Y T | Y T |
Note on units