data: Hydromet Seasonal_Forecast Precipitation Forecast PearsonR

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Hydromet Seasonal_Forecast Precipitation Forecast PearsonR: Pearson correlation skill values data

Pearson correlation skill values from Hydromet Seasonal_Forecast Precipitation Forecast: Forecast, Error and Skill.

Independent Variables (Grids)

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 (61.525W) to (56.475W) by 0.05000003 N= 102 pts :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: 1
colorscalename: correlationcolorscale
CS: -1
datatype: realarraytype
maxncolor: 254
missing_value: -999.0
pointwidth: 0
scale_max: 1.0
scale_min: -1.0
units: unitless
colorscale

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

Data Views

	L	S	X	Y
Hydromet Seasonal_Forecast Precipitation Forecast PearsonR 2.5 months[ X Y \| S L]	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 S
Differentiate along X Y S
Take differences along X Y S