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∂Y [ Ethiopia CPT NextGen FMAM_PRCP Models GFDL-CM2p5-FLOR-A06 Forecasts PredErrorVars ]: ∂Y prediction error variance data
PredErrorVars ∂Y prediction error variance from Ethiopia CPT NextGen FMAM_PRCP Models GFDL-CM2p5-FLOR-A06 Forecasts: Forecast and Error.Independent Variables (Grids)
- Start time (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (0000 1 Sep 2019) to (0000 1 Jan 2025) by 12.8 N= 6 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) periodic (33.125E) to (47.875E) by 0.25 N= 60 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (3.25N) to (14.75N) by 0.25 N= 47 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- null
- colorscalename
- rainbowcolorscale
- CS
- 0
- datatype
- realarraytype
- file_missing_value
- -999.0
- maxncolor
- 256
- missing_value
- NaN
- pointwidth
- 0
- units
- 7.67529625250267×10-15 meter2 radian-1 north second-2
Last updated: Wed, 01 Feb 2023 14:07:40 GMT
Expires: Thu, 01 Jan 2026 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| S | X | Y | |
 $partialdiff sub Y$ [ Ethiopia CPT NextGen FMAM_PRCP Models GFDL-CM2p5-FLOR-A06 Forecasts PredErrorVars ][ X Y | S] | 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 X Y S
- Differentiate along X Y S
- Take differences along X Y S
RMS (root mean square with mean *not* removed) over X Y S | X Y X S Y S | X Y S |
RMSA (root mean square with mean removed) over X Y S | X Y X S Y S | X Y S |
Maximum over X Y S | X Y X S Y S | X Y S |
Minimum over X Y S | X Y X S Y S | X Y S |
Detrend (best-fit-line) over X Y S | X Y X S Y S | X Y S |
Note on units