served from IRI/LDEO Climate Data Library
∂T detrended-bfl ∫dT [ IRI Analyses CSMT TempCondProb ] : ∂T Percent Occurrence of Temperature Condition in Historical Record data
TempCondProb int_dT adif ∂T Percent Occurrence of Temperature Condition in Historical Record from IRI Analyses CSMT: Climatic Suitability for Malaria Transmission.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (Jan 1960) to (Dec 1960) by 1.0 N= 12 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (20.25W) to (55.25E) by 0.5 N= 152 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (40.25S) to (40.25N) by 0.5 N= 162 pts :grid
Other Info
- CE
- null
- CI
- 25.0
- CS
- null
- datatype
- realarraytype
- file_missing_value
- -99.900002
- fnname
- flagge
- maxncolor
- 254
- missing_value
- NaN
- units
- unitless
- history
- Averaged over T2[1951, 2000] minimum 0.0% data present
References
Grover-Kopec_etal2006Last updated: Mon, 12 Sep 2016 21:33:48 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $partialdiff sub T$ detrended-bfl $integral dT$ [ IRI Analyses 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