root mean sq root mean sq ∂T max ∫dIWMO [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] : ∂T percentile data
root mean sq root mean sq
∂T max
∫dIWMO [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] .
is
Independent Variables (Grids)
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- tercileclassesscale
- CS
- null
- datatype
- doublearraytype
- maxncolor
- 254
- missing_value
- NaN
- percentile
- Probability
- units
- percent ids /months
- 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
$partialdiff sub T$ max $integral dIWMO$ [ 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 prcp[dry, wet]
root mean sq $partialdiff sub T$ max $integral dIWMO$ [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] - Averaged over T[16 Nov - 15 Feb, 16 Aug - 15 Nov] IWMO[99900, 9885849] minimum 0.0% data present
root mean sq root mean sq $partialdiff sub T$ max $integral dIWMO$ [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] - Averaged over avOS[LaNina, ElNino] minimum 0.0% data present
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
- Differentiate along
- Take differences along
Average over
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units