data: root mean sq [ $integral dT$ ( NiMet ENACTS ENACTS_v1 ALL Rainfall monthly precip ) climatology ]

root mean sq [ ∫dT ( NiMet ENACTS ENACTS_v1 ALL Rainfall monthly precip ) climatology ]: Rainfall Amount data

ENACTS_v1 ALL Rainfall monthly precip int_dT int_dT Rainfall Amount from NiMet ENACTS: Enhancing National Climate Service Initiative.

Independent Variables (Grids)

Time: grid: /T (months since 01-Jan) periodic (0000 1 Jan) to (0000 1 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

CE

null

CS

null

datatype

doublearraytype

file_missing_value

-99.0

maxncolor

254

missing_value

NaN

units

8.33333333333333×10^-05 meter year

history

$integral dT$ [ NiMet ENACTS ENACTS_v1 ALL Rainfall monthly precip ] climatology

Boxes with less than 0.0% dropped
Averaged over T2[16 Dec 1980 - 15 Dec 1981, 16 Dec 2023 - 15 Dec 2024] minimum 0.0% data present

root mean sq [ $integral dT$ ( NiMet ENACTS ENACTS_v1 ALL Rainfall monthly precip ) climatology ]

Averaged over X[2.38125E, 14.94375E] minimum 0.0% data present

Last updated: Fri, 14 Feb 2025 14:55:22 GMT

Data Views

	T	Y
root mean sq [ $integral dT$ ( NiMet ENACTS ENACTS_v1 ALL Rainfall monthly precip ) 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

Average over Y T | 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