data: detrended-bfl $partialdiff sub X$ [ ENACTS version0 CIPH CSMT PcpnCondProb ]

detrended-bfl ∂_X [ ENACTS version0 CIPH CSMT PcpnCondProb ] : ∂_X Percent Occurrence of Precipitation Condition in Historical Record data

PcpnCondProb partial_X ∂_X Percent Occurrence of Precipitation Condition in Historical Record from ENACTS version0 CIPH CSMT: Climatic Suitability for a Malaria Transmission.

Independent Variables (Grids)

Month (time): grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (21.88E) to (51.43E) by 0.05 N= 592 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (11.775S) to (23.125N) by 0.05 N= 699 pts :grid

Other Info

bufferwordsize: 8
CE: null
CI: 25.0
colorscalename: precip_colors
CS: null
datatype: doublearraytype
fnname: flagge
maxncolor: 254
missing_value: NaN
pointwidth: 1.0
units: 57.2957795130823 radian^-1 east
history: Averaged over T2[1981, 2023] minimum 0.0% data present

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: Thu, 16 May 2024 08:16:46 GMT
Expires: Mon, 10 Jun 2024 00:00:00 GMT

Data Views

	T	X	Y
detrended-bfl $partialdiff sub X$ [ ENACTS version0 CIPH CSMT PcpnCondProb ] [ 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