served from IRI/LDEO Climate Data Library
max min ∂T min ∂T ∂prcp detrended-bfl [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] : ∂T ∂T ∂prcp percentile data
max min ∂T min ∂T ∂prcp detrended-bfl [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] . isIndependent Variables (Grids)
Other Info
- CE
- null
- colorscalename
- tercileclassesscale
- CS
- null
- datatype
- realarraytype
- maxncolor
- 254
- missing_value
- NaN
- percentile
- Probability
- units
- percent /ids /months /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
$partialdiff sub T$ min $partialdiff sub T$ $partialdiff sub prcp$ detrended-bfl [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ]- min over IWMO[100100, 9885100]
min $partialdiff sub T$ min $partialdiff sub T$ $partialdiff sub prcp$ detrended-bfl [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] Jul-Sep- min over prcp[, Ðöã ] avOS[LaNina, ElNino]
max min $partialdiff sub T$ min $partialdiff sub T$ $partialdiff sub prcp$ detrended-bfl [ 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[Oct-Dec, Jul-Sep]
- Boxes with less than 0.0% dropped
Last updated: Wed, 13 Feb 2019 20:27:28 GMT
Data Views
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
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