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∫dT2 ∫dL ∂T2 [ MGAP CPT hindcast_date ] : ∂T2 hindcast time data
MGAP CPT hindcast_date partial_T2 int_dL ∂T2 hindcast time from SOURCES: datos de MGAP SNIA prueba.Independent Variables (Grids)
- L
- grid: /L (months) ordered (2.0 months) to (5.0 months) by 1.0 N= 4 pts :grid
- Time (time)
- grid: /T (months since 01-Jan) ordered (Sep) to (Nov) by 1.0 N= 3 pts :grid
- Training period
- grid: /T2 (months since 1960-01-01) ordered (1980) to (2011) by 12.0 N= 32 pts :grid
Other Info
- bufferwordsize
- 8
- calendar
- 360
- CE
- null
- CS
- null
- datatype
- doublearraytype
- gridid
- 183231920
- pointwidth
- 3
- units
- 0.00694444444444444 year2
Last updated: Thu, 04 Feb 2016 15:18:08 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| L | T | T2 | |
 $integral dT2$ $integral dL$ $partialdiff sub T2$ [ MGAP CPT hindcast_date ] [ T2 T L |] | 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 T2 T L
- Differentiate along T2 T L
- Take differences along T2 T L
RMS (root mean square with mean *not* removed) over T2 T L | T2 T T2 L T L | T2 T L |
RMSA (root mean square with mean removed) over T2 T L | T2 T T2 L T L | T2 T L |
Maximum over T2 T L | T2 T T2 L T L | T2 T L |
Minimum over T2 T L | T2 T T2 L T L | T2 T L |
Detrend (best-fit-line) over T2 T L | T2 T T2 L T L | T2 T L |
Note on units