served from 181.199.253.14
max ∫dC [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ] : Tercile Probabilities data
TercProb int_dC Tercile Probabilities from Hydromet Seasonal_Forecast Precipitation Forecast: Forecast, Error and Skill.Independent Variables (Grids)
- C
- grid: /C (ids) unordered [ (rmal) (mal) () (8“WX8“WX¥f ‘)] :grid
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- Forecast Issue Date (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (0000 1 Apr 2019) to (0000 1 Aug 2021) by 1.0 N= 29 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (1.025N) to (8.525N) by 0.05 N= 151 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- 100
- colorscalename
- tercileclassesscale
- CS
- 0
- datatype
- doublearraytype
- file_missing_value
- -1.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- units
- percent ids
- history
- max over X[61.525W, 56.475W]
- 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| C | L | S | Y | |
 max $integral dC$ [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ] 2.5 months[ Y C | S L] | 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 Y C S
- Differentiate along Y C S
- Take differences along Y C S
RMS (root mean square with mean *not* removed) over Y C S | Y C Y S C S | Y C S |
RMSA (root mean square with mean removed) over Y C S | Y C Y S C S | Y C S |
Maximum over Y C S | Y C Y S C S | Y C S |
Minimum over Y C S | Y C Y S C S | Y C S |
Detrend (best-fit-line) over Y C S | Y C Y S C S | Y C S |
Note on units