min root mean sq ∫dY ∂Y [ ENACTS version0 daily rainfall0p25 rfe ] : ∂Y precipitation data
daily rainfall0p25 rfe partial_Y int_dY int_dY
∂Y precipitation from ENACTS version0: version 0: CHIRPS-BLENDED and CRU.
Independent Variables (Grids)
- Latitude
- grid: /Y (degree_north) ordered (12.02175S) to (22.22611N) by 0.2499844 N= 138 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
- $integral dY$ $partialdiff sub Y$ [ ENACTS version0 daily rainfall0p25 rfe ]
- X regridded on ENACTS version0 daily rainfall rfe
Y regridded on ENACTS version0 daily rainfall rfe
root mean sq $integral dY$ $partialdiff sub Y$ [ ENACTS version0 daily rainfall0p25 rfe ] 31 Dec 2020- Averaged over X[20.8498E, 52.1502E] minimum 0.0% data present
min root mean sq $integral dY$ $partialdiff sub Y$ [ ENACTS version0 daily rainfall0p25 rfe ] - min over T[1 Jan 1981, 31 Dec 2020]
Last updated: Mon, 22 Feb 2021 09:33:15 GMT
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
Average over
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