data: root mean sq anom [ Hydromet CIPH CSMT RHCondProb ]

root mean sq anom [ Hydromet CIPH CSMT RHCondProb ]: Percent Occurrence of Relative Humidity Condition in Historical Record data

RHCondProb Percent Occurrence of Relative Humidity Condition in Historical Record from Hydromet 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

Other Info

bufferwordsize

calendar

standard

CE

null

center

US Weather Service - National Met. Center

CI

25.0

CS

null

datatype

doublearraytype

fnname

flagge

grib_name

SPFH

gribfield

GRIBgridcode

gribleveltype

100

gribNumBits

gribparam

gribvariable

maxncolor

254

PDS_TimeRange

113

pointwidth

1.0

process

62 wave triangular, 28 layer Spectral model from "Medium Range Forecast" run

PTVersion

subcenter

NCEP Ensemble Products

units

unitless

history

Hydromet CIPH CSMT RH

X regridded on Hydromet CIPH CSMT RH
Y regridded on Hydromet CIPH CSMT RH

Hydromet CIPH CSMT RHCondProb

Averaged over T2[1991, 2020]

root mean sq anom [ Hydromet CIPH CSMT RHCondProb ]

Averaged over X[61.525W, 56.475W] Y[0.975N, 8.525N]

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: Fri, 03 Oct 2025 15:15:25 GMT

Data Views

	T	X	Y
Hydromet CIPH CSMT[RHCondProb PcpnCondProb Annual_Sum TempCondProb AllCondProb ]
grid: /X (degree_east) ordered (61.525W) to (56.475W) by 0.05000003 N= 102 pts :grid		M
grid: /Y (degree_north) ordered (0.975N) to (8.525N) by 0.05 N= 152 pts :grid			M
grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid	M
Hydromet CIPH CSMT TempCondProb[ X Y T \|]	M	M	M
Hydromet CIPH CSMT RHCondProb[ X Y T \|]	M	M	M
root mean sq anom [ Hydromet CIPH CSMT RHCondProb ][ T \|]	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 T
Differentiate along T
Take differences along T