data: max [ IRI CPT SONDv5 total_rainfall Forecast TercProb Near

max [ IRI CPT SONDv5 total_rainfall Forecast TercProb Near_Normal ]: Tercile Probabilities data

TercProb TercProb TercProb weights Tercile Probabilities from IRI CPT SONDv5 total_rainfall Forecast: Forecast and Error.

Variables Independientes (Grillas)

Longitude (longitude): grid: /X (degree_east) ordered (28.5375E) to (30.975E) by 0.0375 N= 66 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (2.9625S) to (1.05S) by 0.0375 N= 52 pts :grid

Otra Info

CE

colorscalename

halfgreyscale

CS

datatype

realarraytype

file_missing_value

-999.0

maxncolor

254

missing_value

NaN

pointwidth

scale_max

1.0

scale_min

units

unitless

valid_max

1.0

valid_min

history

max [ IRI CPT SONDv5 total_rainfall Forecast TercProb Near_Normal ]

percentiles computed over S:Aug 1982 - Jul 2017 0% min data present
max over TercProb[<35, >80] S[0000 1 Aug 2015, 0000 1 Aug 2018]

colorscale

Última Actualización: Wed, 11 Dec 2019 13:31:54 GMT
Expira: Sat, 01 Aug 2020 00:00:00 GMT

Data Views

	X	Y
max [ IRI CPT SONDv5 total_rainfall Forecast TercProb Near_Normal ][ X Y \|]	M	M

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 X Y
Differentiate along X Y
Take differences along X Y

Average over X Y | X Y |
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |

Note on units