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∂T ∂Region [ MGAP IPA PPNA promedio ] climatology: ∂T ∂Region Promedio data
promedio promedio partial_Region partial_T ∂T ∂Region Promedio from MGAP IPA PPNA: PPNA mensual.Independent Variables (Grids)
- Region
- grid: /Region (ids) ordered (2) to (10) by 1.0 N= 9 pts :grid
- Time (time)
- grid: /T (months since 01-Jan) periodic (16 Mar - 15 Apr) to (16 Feb - 15 Mar) by 1.0 N= 12 pts :grid
Other Info
- CE
- null
- CS
- null
- datatype
- realarraytype
- file_missing_value
- -9999.0
- missing_value
- NaN
- units
- unitless /ids /months
- history
- Averaged over T2[16 Mar 2000 - 15 Mar 2001, 16 Mar 2016 - 15 Mar 2017] minimum 0.0% data present
Last updated: Tue, 27 Jun 2017 15:51:03 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| Region | T | |
 doc[] | ||
| MGAP IPA PPNA[minimo
nombre
the_geom
promedio
label
maximo
desvio
] | ||
 $partialdiff sub T$ $partialdiff sub Region$ [ MGAP IPA PPNA promedio ] climatology[ T Region |] | 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 T Region
- Differentiate along T Region
- Take differences along T Region
RMS (root mean square with mean *not* removed) over T Region | T Region |
RMSA (root mean square with mean removed) over T Region | T Region |
Maximum over T Region | T Region |
Minimum over T Region | T Region |
Detrend (best-fit-line) over T Region | T Region |
Note on units