served from maproom.meteorwanda.gov.rw
∫dT ∂Y [ Rwanda ENACTS temperatures temp ] anomalies: ∂Y Gridded Average Temperature data
Rwanda ENACTS temperatures temp temp partial_Y int_dT ∂Y Gridded Average Temperature from SOURCES: the IRI/LDEO collection of climate data.Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) (360) ordered [ (0800-1600 2 Feb 1961) (0800-1600 1 Apr 1961) (0800-1559 10 Nov 1962) ... (0800-1601 1 Dec 2024)] N= 226 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (28.525E) to (30.975E) by 0.05000002 N= 50 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (2.95S) to (1.05S) by 0.05 N= 39 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -9999
- missing_value
- NaN
- units
- DegC /degree_north days
- history
- Averaged over T2[1961, 2357 30 Dec 2022 - 2357 30 Dec 2023] minimum 0.0% data present
Last updated: Wed, 26 Jun 2024 17:08:06 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
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 $integral dT$ $partialdiff sub Y$ [ Rwanda ENACTS temperatures temp ] anomalies[ X Y | T] | M | M | M |
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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 X Y T
- Differentiate along X Y T
- Take differences along X Y T
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units