served from maproom.meteorwanda.gov.rw
∂Y ∫dS [ Rwanda CPT NextGen 0p25 GFDL-CM2p1-aer04 xValPred ] : ∂Y cross-validated data
Rwanda CPT NextGen 0p25 GFDL-CM2p1-aer04 xValPred int_dS ∂Y cross-validated from SOURCES: the IRI/LDEO collection of climate data.Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- S
- grid: /S (months since 1960-01-01) ordered (0000 16 Dec 1982) to (0000 16 Dec 2009) by 1.0 N= 325 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (28.125E) to (30.875E) by 0.25 N= 12 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (1.25S) to (2.75S) by 0.25 N= 7 pts :grid
Other Info
- CE
- null
- CS
- 0
- datatype
- realarraytype
- file_missing_value
- -999.0
- missing_value
- NaN
- pointwidth
- 0
- units
- 0.00477464829275686 meter radian-1 north year
- history
- Averaged in T with overlapping interval 3
Last updated: Thu, 12 Dec 2019 21:15:33 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | S | X | Y | |
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 $partialdiff sub Y$ $integral dS$ [ Rwanda CPT NextGen 0p25 GFDL-CM2p1-aer04 xValPred ] 2.5 months[ S | L X Y] | M | M | M | M |
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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 S X Y
- Differentiate along S X Y
- Take differences along S X Y
RMS (root mean square with mean *not* removed) over S X Y | S X S Y X Y | S X Y |
RMSA (root mean square with mean removed) over S X Y | S X S Y X Y | S X Y |
Maximum over S X Y | S X S Y X Y | S X Y |
Minimum over S X Y | S X S Y X Y | S X Y |
Detrend (best-fit-line) over S X Y | S X S Y X Y | S X Y |
Note on units