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root mean sq ∂T [ NiMet ENACTS ENACTS_v1 ALL Temperature monthly tmax climatology ] : ∂T Maximum Temperature data
ENACTS_v1 ALL Temperature monthly tmax tmax partial_T ∂T Maximum Temperature from NiMet ENACTS: Enhancing National Climate Service Initiative.Independent Variables (Grids)
- Time
- grid: /T (months since 01-Jan) periodic (16 Dec - 15 Jan) to (16 Nov - 15 Dec) by 1.0 N= 12 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (3.975N) to (14.1N) by 0.0375 N= 271 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -99.0
- missing_value
- NaN
- units
- 12 degree_Kelvin year-1
- history
- $partialdiff sub T$ [ NiMet ENACTS ENACTS_v1 ALL Temperature monthly tmax climatology ]
- Boxes with less than 100.0% dropped
Averaged over T2[1981, 2024] minimum 0.0% data present
root mean sq $partialdiff sub T$ [ NiMet ENACTS ENACTS_v1 ALL Temperature monthly tmax climatology ]- Averaged over X[2.38125E, 14.94375E] minimum 0.0% data present
- Boxes with less than 100.0% dropped
Last updated: Mon, 17 Feb 2025 14:29:37 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| T | Y | |
 root mean sq $partialdiff sub T$ [ NiMet ENACTS ENACTS_v1 ALL Temperature monthly tmax climatology ] [ Y T |] | M | M |
|---|
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