max ∂prcp ∫dIWMO ∫dprcp ∂prcp min [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] : ∂prcp ∂prcp percentile data
max
∂prcp ∫dIWMO ∫dprcp ∂prcp min [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] .
Independent Variables (Grids)
- prcp
- grid: /prcp (ids) unordered [ (0Ѿ) (Ðöã
)] :grid
Other Info
- CE
- null
- colorscalename
- tercileclassesscale
- CS
- null
- datatype
- realarraytype
- maxncolor
- 254
- missing_value
- NaN
- percentile
- Probability
- units
- percent /ids ids ids /ids
- history
- mean [ ( percentile_over { T2 75% min } { NOAA NCDC GCPS MONTHLY STATION mean prcp } ) * masklt ( { percentile_over [ T ] [ KAPLAN Indices NINO3 avOS ] } , 1 ) ]
- Boxes with less than 0.0% dropped
Averaged over T2[1901, 1990] minimum 0.0% data present
$partialdiff sub prcp$ $integral dIWMO$ $integral dprcp$ $partialdiff sub prcp$ min [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] 16 Nov - 15 Feb 9885849- min over avOS[, ]
max $partialdiff sub prcp$ $integral dIWMO$ $integral dprcp$ $partialdiff sub prcp$ min [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] - max over T[16 Feb - 15 May, 16 Nov - 15 Feb] IWMO[99900, 9885849]
Last updated: Wed, 13 Feb 2019 20:27:28 GMT
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 prcp
- Differentiate along prcp
- Take differences along prcp
Average over
prcp
|
RMS (root mean square with mean *not* removed) over
prcp
|
RMSA (root mean square with mean removed) over
prcp
|
Maximum over
prcp
|
Minimum over
prcp
|
Detrend (best-fit-line) over
prcp
|
Note on units