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root mean sq anom root mean sq ∫dX ∂Y [ ENACTS version0 daily rainfall0p25 rfe ] : ∂Y precipitation data
daily rainfall0p25 rfe partial_Y int_dX int_dX ∂Y precipitation from ENACTS version0: version 0: CHIRPS-BLENDED and CRU.Independent Variables (Grids)
- Latitude
- grid: /Y (degree_north) ordered (11.89676S) to (22.10112N) by 0.2499844 N= 137 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- prcp_dailyrate_max100_smooth
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -9999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 1.0
- standard_name
- lwe_precipitation_rate
- units
- mm /day
- standard units*
- 1.15740740740741×10-08 meter second-1
- history
- $integral dX$ $partialdiff sub Y$ [ ENACTS version0 daily rainfall0p25 rfe ]
- X regridded on ENACTS version0 daily rainfall rfe
Y regridded on ENACTS version0 daily rainfall rfe
root mean sq $integral dX$ $partialdiff sub Y$ [ ENACTS version0 daily rainfall0p25 rfe ] 31 Dec 2020- Averaged over X[20.8498E, 52.1502E] minimum 0.0% data present
root mean sq anom root mean sq $integral dX$ $partialdiff sub Y$ [ ENACTS version0 daily rainfall0p25 rfe ]- Averaged over T[1 Jan 1981, 31 Dec 2020] minimum 0.0% data present
- X regridded on ENACTS version0 daily rainfall rfe
Last updated: Mon, 22 Feb 2021 09:33:15 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