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root mean sq anom ∂T [ NiMet CIPH CSMT TempCondProb ] : ∂T Percent Occurrence of Temperature Condition in Historical Record data
TempCondProb partial_T partial_T ∂T Percent Occurrence of Temperature Condition in Historical Record from NiMet CIPH CSMT: 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
- -99.0
- fnname
- flagge
- maxncolor
- 254
- missing_value
- NaN
- units
- 12 year-1
- history
- $partialdiff sub T$ [ NiMet CIPH CSMT TempCondProb ]
- Boxes with less than 100.0% dropped
Averaged over T2[1981, 2024] minimum 0.0% data present
root mean sq anom $partialdiff sub T$ [ NiMet CIPH CSMT TempCondProb ]- Averaged over X[2.4E, 14.925E] Y[3.99375N, 14.08125N] T[16 Dec - 15 Jan, 16 Nov - 15 Dec] minimum 0.0% data present
- Boxes with less than 100.0% 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: Mon, 17 Feb 2025 14:29:37 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