served from maproom.meteorwanda.gov.rw
root mean sq ∂T ∂T ∫dT [ Rwanda Monthly climatologies temp ] : ∂T ∂T Temperature average data
Rwanda Monthly climatologies temp temp int_dT partial_T partial_T ∂T ∂T Temperature average from SOURCES: the IRI/LDEO collection of climate data.Independent Variables (Grids)
- Time
- grid: /T (months since 1960-01-01) ordered (Feb 1960) to (Dec 1960) by 1.0 N= 11 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (2.975S) to (1.025S) by 0.05 N= 40 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -9999
- missing_value
- NaN
- units
- DegC months /months /months
- history
- $partialdiff sub T$ $partialdiff sub T$ $integral dT$ [ Rwanda Monthly climatologies temp ]
- Boxes with less than 0.0% dropped
Averaged over T2[1983, 2014] minimum 0.0% data present
root mean sq $partialdiff sub T$ $partialdiff sub T$ $integral dT$ [ Rwanda Monthly climatologies temp ]- Averaged over X[28.5E, 31E] minimum 0.0% data present
- Boxes with less than 0.0% dropped
Last updated: Wed, 26 Jun 2024 17:19:20 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| T | Y | |
 root mean sq $partialdiff sub T$ $partialdiff sub T$ $integral dT$ [ Rwanda Monthly climatologies temp ] [ 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