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∂T [ NiMet CIPH CSMT TempCondProb ]: ∂T Percent Occurrence of Temperature Condition in Historical Record data
TempCondProb TempCondProb TempCondProb TempCondProb ∂T Percent Occurrence of Temperature Condition in Historical Record from NiMet CIPH CSMT: Climatic Suitability for a Malaria Transmission.Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) ordered [ (1200 1 Feb - 2400 1 Mar) (0000 2 Mar - 1200 31 Mar) (1200 31 Mar - 2400 30 Apr) (0000 1 May - 1200 31 May) (1200 31 May - 2400 30 Jun) (0000 1 Jul - 1200 31 Jul) (1200 31 Jul - 1200 31 Aug) (1200 31 Aug - 2400 30 Sep) (0000 1 Oct - 1200 31 Oct) (1200 31 Oct - 2400 30 Nov) (0000 1 Dec - 1200 31 Dec)] :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (2.4E) to (14.925E) by 0.03750001 N= 335 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (3.99375N) to (14.08125N) by 0.0375 N= 270 pts :grid
Other Info
- CE
- 100.0
- CI
- 25.0
- Conventions
- COARDS
- CS
- 0.0
- datatype
- realarraytype
- file_missing_value
- -99.0
- fnname
- flagge
- maxncolor
- 254
- missing_value
- NaN
- units
- 1.15740740740741×10-05 second-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
- Boxes with less than 100.0% dropped
- colorscale
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
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $partialdiff sub T$ [ NiMet CIPH CSMT 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