served from IRI/LDEO Climate Data Library

*prcp*- grid: /prcp (ids) unordered [ (dry) (normal) (wet)] :grid
*Time*(time)- grid: /T (months since 01-Jan) periodic (Jan-Mar) to (Oct-Dec) by 3.0 N= 4 pts :grid

*bufferwordsize*- 8
*CE*- 100
*colorscalename*- tercileclassesscale
*CS*- 0
*datatype*- doublearraytype
*maxncolor*- 254
*missing_value*- NaN
*percentile*- Probability
*scale_max*- 100.0
*scale_min*- 0.0
*units*- percent
*standard units**- 0.01
*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

max [ mean ( { percentile_over [ T2 75% min ] [ NOAA NCDC GCPS MONTHLY STATION mean prcp ] } * masklt { [ percentile_over ( T ) ( KAPLAN Indices NINO3 avOS ) ] , 1 } ) * unnamed ] 9885100- max over avOS[LaNina, ElNino]

max max [ 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 IWMO[100100, 9885100]

- Boxes with less than 0.0% dropped
- colorscale

Last updated: *Wed, 13 Feb 2019 20:27:28 GMT*

- 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 T
- Differentiate along prcp T
- Take differences along prcp T

RMS (root mean square with mean *not* removed) over prcp T | prcp T |

RMSA (root mean square with mean removed) over prcp T | prcp T |

Maximum over prcp T | prcp T |

Minimum over prcp T | prcp T |

Detrend (best-fit-line) over prcp T | prcp T |

Note on units