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NextGen CPT Estacional CHIRPS Guatemala NextGenL2 Forecast target_length: Length of forecast time data
target_length Length of forecast time from NextGen CPT Estacional CHIRPS Guatemala NextGenL2 Forecast: Forecast and Error.Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (3.5)] :grid
- S (forecast_reference_time)
- grid: /S (days since 1960-01-01) ordered [ (0000 1 Mar 2023) (0000 1 Apr 2023) (0000 1 May 2023) (0000 1 Jun 2023) (0000 1 Jul 2023) (0000 1 Aug 2023) (0000 1 Sep 2023) (0000 1 Oct 2023) (0000 1 Nov 2023) (0000 1 Dec 2023) (0000 1 Jan 2024) (0000 1 Feb 2024) (0000 1 Mar 2024) (0000 1 Apr 2024) (0000 1 May 2024) (0000 1 Jun 2024) (0000 1 Jul 2024) (0000 1 Aug 2024) (0000 1 Sep 2024) (0000 1 Oct 2024) (0000 1 Nov 2024)] :grid
Other Info
- calendar
- 360
- CE
- null
- CS
- null
- datatype
- realarraytype
- missing_value
- NaN
- pointwidth
- 1.0
- units
- days
- standard units*
- 86400 second
- history
- Averaged in T with overlapping interval 3
Last updated: Thu, 23 Mar 2023 19:50:42 GMT
Data Views
Views
line plots
color bars
scatter
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
- Differentiate along S
- Take differences along S
RMS (root mean square with mean *not* removed) over S |
RMSA (root mean square with mean removed) over S |
Maximum over S |
Minimum over S |
Detrend (best-fit-line) over S |
Note on units