served from maproom.meteorwanda.gov.rw
root mean sq ∫dY min [ CIPH Rwanda CSMT_ENACT falciparum TempCondProb ] : Percent Occurrence of Temperature Condition in Historical Record data
TempCondProb min int_dY Percent Occurrence of Temperature Condition in Historical Record from CIPH Rwanda CSMT_ENACT falciparum: Climatic Suitability for a Malaria Transmission. isIndependent Variables (Grids)
Other Info
- bufferwordsize
- 8
- CE
- null
- CI
- 25.0
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -9999
- fnname
- flagge
- maxncolor
- 254
- missing_value
- NaN
- units
- degree_north
- standard units*
- 0.0174532925199433 radian north
- history
- CIPH Rwanda CSMT_ENACT falciparum TempCondProb
- Boxes with less than 0.0% dropped
Averaged over T2[1981, 2010] minimum 0.0% data present
$integral dY$ min [ CIPH Rwanda CSMT_ENACT falciparum TempCondProb ]- min over X[28.525E, 30.975E] T[Jan, Dec]
root mean sq $integral dY$ min [ CIPH Rwanda CSMT_ENACT falciparum TempCondProb ]- Averaged over Y[3S, 1S] minimum 0.0% data present
- Boxes with less than 0.0% dropped
References
Grover-Kopec, E. K., M. B. Blumenthal, P. N. Ceccato, T. Dinku, J. Omumbo, S. J. Connor, 2006: Web-based climate information resources for malaria control in Africa. Malaria Journal, 5:38.
Last updated: Wed, 26 Jun 2024 17:08:06 GMT
Data Views
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
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units