IRI FD SubX SubX_Tercile_Forecast Subx_weekly_Temperature MMEv21_Temperature_ELR dominant: Dominant Tercile Probability data

Dominant Tercile Probability from IRI FD SubX SubX_Tercile_Forecast Subx_weekly_Temperature MMEv21_Temperature_ELR: SubX MMEv21 global weekly probability forecasts of below-normal, above-normal, and near-normal temperature for Saturday-Friday target. MMEv21 forecast starts from May 7 2021.

Independent Variables (Grids)

Forecast_period
grid: /L (days) ordered (4.5 days) to (25.5 days) by 7.0 N= 4 pts :grid
forecast start time (forecast_reference_time)
grid: /S (days since 1960-01-01) ordered (0000 2 Oct 2020) to (0000 26 Jul 2024) by 7.0 N= 200 pts :grid
Longitude (longitude)
grid: /X (degree_east) periodic (0) to (1W) by 1.0 N= 360 pts :grid
Latitude (latitude)
grid: /Y (degree_north) ordered (90S) to (90N) by 1.0 N= 181 pts :grid

Other Info

CE
99.601593
colorscalename
tercileclassesscale
CS
-99.601593
datatype
realarraytype
fnname
masklt
maxncolor
254
missing_value
NaN
pointwidth
0.0
scale_max
99.601593
scale_min
-99.601593
units
percent
standard units*
0.01
colorscale

Last updated: Thu, 25 Jul 2024 15:18:14 GMT
Expires: Thu, 01 Aug 2024 00:00:00 GMT

Data Views

LSXY
[ X Y | L S]MMMM


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. Average over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
RMS (root mean square with mean *not* removed) over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
RMSA (root mean square with mean removed) over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Maximum over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Minimum over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Detrend (best-fit-line) over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Convert units from percent to

Note on units