served from 41.72.104.142
min [ S , min ∫dC ( ZMD CPT NCEP-CFSv2 Prob ) ]: Made of, Tercile Forecast data
min [ S , min ∫dC ( ZMD CPT NCEP-CFSv2 Prob ) ].Independent Variables (Grids)
- C
- grid: /C (ids) unordered [ (Below) () (nÅ nÅ èmÅ ) (Above¯)] :grid
- Made of (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (0000 1 Aug 2020) to (0000 1 Dec 2021) by 1.0 N= 17 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (20.22545E) to (33.77455E) by 0.2509091 N= 55 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (17.9S) to (8.1S) by 0.251282 N= 40 pts :grid
Other Info
- calendar
- 360
- datatype
- realarraytype
- fnname
- min
- gridid
- 163927360
- missing_value
- NaN
- pointwidth
- 0
- scale_max
- null
- scale_min
- null
- standard_name
- forecast_reference_time
- units
- months since 1960-01-01
- standard units*
- 0.0833333333333333 ( years since 1960-01-01 00:00.000000000 )
- history
- min over S[0000 1 Aug 2020, 0000 1 Dec 2021]
Last updated: Thu, 10 Feb 2022 00:03:57 GMT
Expires: Sat, 12 Mar 2022 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| C | S | X | Y | |
 ZMD CPT NCEP-CFSv2[xValPred
dof
hindcast_length
target_length
Var
Prob
hindcast_date
Obs
Mu
target_date
] | ||||
| grid: /X (degree_east) ordered (20.1E) to (33.9E) by 0.2509091 N= 56 pts :grid | O=-0.1254539 | |||
|---|---|---|---|---|
| grid: /Y (degree_north) ordered (17.9S) to (8.1S) by 0.251282 N= 40 pts :grid | M | |||
| grid: /C (ids) unordered [ (Below) (Normal) (Above)] :grid | D | |||
 min [ S , min $integral dC$ ( ZMD CPT NCEP-CFSv2 Prob ) ][ | S X Y C] | 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 S X Y C
- Differentiate along S X Y C
- Take differences along S X Y C
RMS (root mean square with mean *not* removed) over S X Y C | S X S Y S C X Y X C Y C | S X Y S X C S Y C X Y C | S X Y C |
RMSA (root mean square with mean removed) over S X Y C | S X S Y S C X Y X C Y C | S X Y S X C S Y C X Y C | S X Y C |
Maximum over S X Y C | S X S Y S C X Y X C Y C | S X Y S X C S Y C X Y C | S X Y C |
Minimum over S X Y C | S X S Y S C X Y X C Y C | S X Y S X C S Y C X Y C | S X Y C |
Detrend (best-fit-line) over S X Y C | S X S Y S C X Y X C Y C | S X Y S X C S Y C X Y C | S X Y C |
Note on units