served from maproom.metmalawi.gov.mw
mean ∫dT [ ∫dY ( UCSB CHIRPS v1p8 dekad prcp climatology ) anomalies ] : precipitation data
CHIRPS v1p8 dekad prcp prcp int_dY int_dY int_dT precipitation from UCSB: UC Santa Barbara.Independent Variables (Grids)
- Time
- grid: /T (months since 1960-01-01) ordered (0000 1 Jan 1960) to (0000 1 Jan 1961) by 0.3333335 N= 37 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (50N) to (50S) by 0.05 N= 2001 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- prcp_dekadrate_max600_smooth
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -9999.0
- maxncolor
- 254
- missing_value
- NaN
- standard_name
- lwe_precipitation_rate
- units
- 1.45444104332861×10-06 meter radian north year
- history
- $integral dY$ [ UCSB CHIRPS v1p8 dekad prcp climatology ]
Averaged over T2[1981, 2357 30 Dec 2023 - 2357 30 Dec 2024] minimum 0.0% data present
- $integral dY$ [ UCSB CHIRPS v1p8 dekad prcp climatology ] climatology
- Averaged over T2[1981, 2357 30 Dec 2023 - 2357 30 Dec 2024] minimum 0.0% data present
Averaged over T2=0000 1 Jan 1960 - 0000 1 Jan 1961 minimum 0.0% data present
- Averaged over T2[1981, 2357 30 Dec 2023 - 2357 30 Dec 2024] minimum 0.0% data present
- Averaged over X[180W, 180] minimum 0.0% data present
- $integral dY$ [ UCSB CHIRPS v1p8 dekad prcp climatology ]
References
Funk_etal2014Last updated: Thu, 02 Nov 2023 07:43:25 GMT
Expires: Tue, 01 Jul 2025 00:00:00 GMT
Data Views
Views
data as colors
data as contours| T | Y | |
 mean $integral dT$ [ $integral dY$ ( UCSB CHIRPS v1p8 dekad prcp climatology ) anomalies ] [ 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