Data Library ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast DomTerProb
X20.25E - 53.25E
Y13.75S - 24.75N
SFeb 2021 - Jun 2022
served from digilib.icpac.net

ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast DomTerProb: Probabilités du Tercile Dominant data

Probabilités du Tercile Dominant from ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast: Forecast and Error.

Independent Variables (Grids)

Forecast Issue Date (forecast_reference_time)
grid: /S (months since 1960-01-01) ordered (0000 1 Feb 2021) to (0000 1 Jul 2022) by 1.0 N= 18 pts :grid
Longitude (longitude)
grid: /X (degree_east) ordered (20.5E) to (53E) by 0.5 N= 66 pts :grid
Latitude (latitude)
grid: /Y (degree_north) ordered (13.5S) to (24.5N) by 0.5 N= 77 pts :grid

Other Info

Key
1.0<35 SN
2.035-40 SN
3.040-45 SN
4.045-50 SN
5.050-55 SN
6.055-60 SN
7.060-65 SN
8.065-70 SN
9.070-75 SN
10.075-80 SN
11.0>80 SN
12.0<35 PN
13.035-40 PN
14.040-45 PN
15.045-50 PN
16.050-55 PN
17.055-60 PN
18.060-65 PN
19.065-70 PN
20.070-75 PN
21.075-80 PN
22.0>80 PN
23.0<35 AN
24.035-40 AN
25.040-45 AN
26.045-50 AN
27.050-55 AN
28.055-60 AN
29.060-65 AN
30.065-70 AN
31.070-75 AN
32.075-80 AN
33.0>80 AN
bufferwordsize
4
CE
33
colorscalename
tercileclassesscale
CS
1
datatype
realarraytype
file_missing_value
0
fnname
maskle
maxncolor
254
missing_value
NaN
pointwidth
0
scale_max
33.0
scale_min
1.0
units
ids
history
[ masklt ( { [ dominant_class ( ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ) - 1. ] * 11. } , 22 ) + dominant_class ( ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Above ) ] + [ masknotrange ( { [ dominant_class ( ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ) - 1. ] * 11. } , 10 , 12 ) + dominant_class ( ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Normal ) ]
masklt [ ( { dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ] - 1. } * 11. ) , 22 ] + dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Above ]
masklt [ ( { dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ] - 1. } * 11. ) , 22 ]
dominant_class over C[Below, Above]
dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Above ]
dominant_class over Prob[<35, >80]
masknotrange [ ( { dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ] - 1. } * 11. ) , 10 , 12 ] + dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Normal ]
masknotrange [ ( { dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Below, Above]
dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Normal ]
dominant_class over Prob[<35, >80]
maskgt [ ( { dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ] - 1. } * 11. ) , 0 ] + dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Below ]
maskgt [ ( { dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob ] - 1. } * 11. ) , 0 ]
dominant_class over C[Below, Above]
dominant_class [ ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob Below ]
dominant_class over Prob[<35, >80]
colorscale

Last updated: Thu, 28 Jul 2022 20:33:36 GMT
Expires: Wed, 09 Jun 2021 00:00:00 GMT

Data Views

SXY
[ X Y | S]MMM


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. Average over X Y S | X Y X S Y S | X Y S |
RMS (root mean square with mean *not* removed) over X Y S | X Y X S Y S | X Y S |
RMSA (root mean square with mean removed) over X Y S | X Y X S Y S | X Y S |
Maximum over X Y S | X Y X S Y S | X Y S |
Minimum over X Y S | X Y X S Y S | X Y S |
Detrend (best-fit-line) over X Y S | X Y X S Y S | X Y S |
Convert units from ids to

Note on units