served from 45.183.221.150
min [ NextGen CPT Estacional CPC Guatemala ExtraVars PoM ]: Porcentaje de Mediana data
min [ NextGen CPT Estacional CPC Guatemala ExtraVars PoM ].Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- percentile
- grid: /percentile (unitless) ordered [ (0.5)] :grid
- Longitud (longitude)
- grid: /X (degree_east) ordered (92W) to (88W) by 1.0 N= 5 pts :grid
- Latitud (latitude)
- grid: /Y (degree_north) ordered (13N) to (18N) by 1.0 N= 6 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 200
- colorscalename
- prcp_anomaly_25max500_colors2_percentmedian
- CS
- 0
- datatype
- realarraytype
- file_missing_value
- -999.0
- fnname
- maskge
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- scale_max
- 200.0
- scale_min
- 0.0
- units
- percent
- standard units*
- 0.01
- history
- min [ NextGen CPT Estacional CPC Guatemala ExtraVars PoM ]
- percentiles computed over S2:16 Dec 1982 - 15 Dec 2009 0% min data present
min over S[0000 1 Jan 2019, 0000 1 Jan 2021]
- percentiles computed over S2:16 Dec 1982 - 15 Dec 2009 0% min data present
- colorscale
Last updated: Fri, 05 Nov 2021 18:02:01 GMT
Expires: Sat, 09 May 2020 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts
line plots
color bars| L | percentile | X | Y | |
 grid: /X (degree_east) ordered (92W) to (88W) by 1.0 N= 5 pts :grid | M | |||
|---|---|---|---|---|
| grid: /Y (degree_north) ordered (13N) to (18N) by 1.0 N= 6 pts :grid | M | |||
| grid: /X (degree_east) ordered (92W) to (88W) by 1.0 N= 5 pts :grid | M | |||
| grid: /Y (degree_north) ordered (13N) to (18N) by 1.0 N= 6 pts :grid | M | |||
 min [ NextGen CPT Estacional CPC Guatemala ExtraVars PoM ] 0.5 2.5 months[ X Y | percentile L] | M | M | 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
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