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max [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]: Tercile Probabilities data
TercProb Tercile Probabilities from Hydromet Seasonal_Forecast Precipitation Forecast: Forecast, Error and Skill.Independent Variables (Grids)
- Tercile Categories
- grid: /C (ids) unordered [ (Below_Normal) (Near_Normal) (Above_Normal)] :grid
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (1.025N) to (8.525N) by 0.05 N= 151 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 100
- colorscalename
- tercileclassesscale
- CS
- 0
- datatype
- realarraytype
- file_missing_value
- -1.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- scale_max
- 100.0
- scale_min
- 0.0
- units
- percent
- standard units*
- 0.01
- history
- max over X[61.525W, 56.475W] S[0000 1 Apr 2019, 0000 1 Aug 2021]
- colorscale
Last updated: Fri, 12 Jan 2024 14:16:35 GMT
Expires: Fri, 09 Feb 2024 00:00:00 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars
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 Y C
- Differentiate along Y C
- Take differences along Y C
RMS (root mean square with mean *not* removed) over Y C | Y C |
RMSA (root mean square with mean removed) over Y C | Y C |
Maximum over Y C | Y C |
Minimum over Y C | Y C |
Detrend (best-fit-line) over Y C | Y C |
Note on units