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KMD Forecast CPT Rainfall Seasonal History PearsonR: Pearson correlation skill values data
Pearson correlation skill values from KMD Forecast CPT Rainfall Seasonal History: Predictand, Hindcast and Skill.Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- Hindcast Issue Date
- grid: /S (months since 01-Jan) periodic (0000 1 Jan) to (0000 1 Dec) by 1.0 N= 12 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (22E) to (51.25E) by 0.25 N= 118 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (11.5S) to (23N) by 0.25 N= 139 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- 1
- colorscalename
- correlationcolorscale
- CS
- -1
- datatype
- doublearraytype
- maxncolor
- 254
- missing_value
- -999.0
- scale_max
- 1.0
- scale_min
- -1.0
- units
- unitless
- colorscale
Last updated: Wed, 29 May 2024 07:29:02 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | S | X | Y | |
 KMD Forecast CPT Rainfall Seasonal History[PearsonR
final_season
InputObs
hindcast_date
CrossValHind
hindcast_length
] | ||||
| grid: /X (degree_east) ordered (22E) to (51.25E) by 0.25 N= 118 pts :grid | M | |||
|---|---|---|---|---|
| grid: /Y (degree_north) ordered (11.5S) to (23N) by 0.25 N= 139 pts :grid | M | |||
| grid: /S (months since 01-Jan) periodic (0000 1 Jan) to (0000 1 Dec) by 1.0 N= 12 pts :grid | M | |||
| KMD Forecast CPT Rainfall Seasonal History PearsonR 2.5 months[ X Y | S L] | M | M | M | M |
 KMD Forecast CPT Rainfall Seasonal History 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
RMS (root mean square with mean *not* removed) over X Y S | X Y X S Y S | X Y S |
RMSA (root mean square with mean removed) over X Y S | X Y X S Y S | X Y S |
Maximum over X Y S | X Y X S Y S | X Y S |
Minimum over X Y S | X Y X S Y S | X Y S |
Detrend (best-fit-line) over X Y S | X Y X S Y S | X Y S |
Note on units