served from maproom.meteorwanda.gov.rw
∫dT ∂Y ∂X [ CIPH Rwanda CSMT_ENACT falciparum TempCondProb ] : ∂Y ∂X Percent Occurrence of Temperature Condition in Historical Record data
TempCondProb partial_X partial_Y ∂Y ∂X Percent Occurrence of Temperature Condition in Historical Record from CIPH Rwanda CSMT_ENACT falciparum: Climatic Suitability for a Malaria Transmission.Independent Variables (Grids)
- Time
- grid: /T (months since 1960-01-01) ordered (0000 1 Jan 1960) to (0000 1 Jan 1961) by 1.0 N= 13 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (28.55E) to (30.95E) by 0.05000003 N= 49 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
- 100.0
- CI
- 25.0
- CS
- 0.0
- datatype
- doublearraytype
- file_missing_value
- -9999
- fnname
- flagge
- maxncolor
- 254
- missing_value
- NaN
- units
- 273.567195834312 radian-2 east year
- history
- $integral dT$ $partialdiff sub Y$ $partialdiff sub X$ [ CIPH Rwanda CSMT_ENACT falciparum TempCondProb ]
- Boxes with less than 0.0% dropped
Averaged over T2[1981, 2010] minimum 0.0% data present
- Boxes with less than 0.0% dropped
- colorscale
References
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Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 CIPH Rwanda CSMT_ENACT falciparum[Annual_Sum
PcpnCondProb
TempCondProb
AllCondProb
RHCondProb
] | |||
| grid: /X (degree_east) ordered (28.525E) to (30.975E) by 0.05000002 N= 50 pts :grid | D | ||
|---|---|---|---|
| grid: /Y (degree_north) ordered (2.975S) to (1.025S) by 0.05 N= 40 pts :grid | O=0.0249999 | ||
| grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid | O=-0.5 | ||
 $integral dT$ $partialdiff sub Y$ $partialdiff sub X$ [ CIPH Rwanda CSMT_ENACT falciparum TempCondProb ] [ X Y T |] | M | 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 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