data: $integral dX$ [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]

served from 181.199.253.14

∫dX [ 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
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
Longitude (longitude): grid: /X (degree_east) ordered (61.55W) to (56.45W) by 0.05000006 N= 103 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: 0.000174532925199433 radian east
colorscale

Last updated: Fri, 12 Jan 2024 14:16:35 GMT
Expires: Fri, 09 Feb 2024 00:00:00 GMT

Data Views

	C	L	S	X	Y
$integral dX$ [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ] 2.5 months[ X Y C \| S L]	M	M	M	M	M

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 C S
Differentiate along X Y C S
Take differences along X Y C S