served from IRI/LDEO Climate Data Library
∂T max root mean sq min ∫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
∂T max root mean sq min ∫dIWMO [ 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)
- Time (time)
- grid: /T (months since 01-Jan) periodic (Jan-Mar) to (Oct-Dec) by 3.0 N= 4 pts :grid
Other Info
- CE
- null
- colorscalename
- tercileclassesscale
- CS
- null
- datatype
- realarraytype
- 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
min $integral dIWMO$ [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ]- min over prcp[dry, wet]
root mean sq min $integral dIWMO$ [ 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 IWMO[99900, 9885849] minimum 0.0% data present
$partialdiff sub T$ max root mean sq min $integral dIWMO$ [ 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 avOS[LaNina, ElNino]
- Boxes with less than 0.0% dropped
Last updated: Wed, 13 Feb 2019 20:27:28 GMT
Data Views
Views
line plots
color bars
scatter
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
- Differentiate along T
- Take differences along T
RMS (root mean square with mean *not* removed) over T |
RMSA (root mean square with mean removed) over T |
Maximum over T |
Minimum over T |
Detrend (best-fit-line) over T |
Note on units