Data Library ZMD CPT NextGen Forecast Dom_Terc
percentile
X19.97455E - 34.02546E
Y18.02564S - 7.97436S
SAug 2020 - Nov 2021
served from 41.72.104.142

ZMD CPT NextGen Forecast Dom_Terc: Dominant Tercile Probabilities data

Dominant Tercile Probabilities from ZMD CPT NextGen Forecast: Forecast and Error.

Independent Variables (Grids)

Made of (forecast_reference_time)
grid: /S (months since 1960-01-01) ordered (0000 1 Aug 2020) to (0000 1 Dec 2021) by 1.0 N= 17 pts :grid
Longitude (longitude)
grid: /X (degree_east) ordered (20.1E) to (33.9E) by 0.2509091 N= 56 pts :grid
Latitude (latitude)
grid: /Y (degree_north) ordered (17.9S) to (8.1S) by 0.251282 N= 40 pts :grid

Other Info

Key
1.0≤35 Below
2.035-40 Below
3.040-45 Below
4.045-50 Below
5.050-55 Below
6.055-60 Below
7.060-65 Below
8.065-70 Below
9.070-75 Below
10.075-80 Below
11.0≥80 Below
12.0≤35 Normal
13.035-40 Normal
14.040-45 Normal
15.045-50 Normal
16.050-55 Normal
17.055-60 Normal
18.060-65 Normal
19.065-70 Normal
20.070-75 Normal
21.075-80 Normal
22.0≥80 Normal
23.0≤35 Above
24.035-40 Above
25.040-45 Above
26.045-50 Above
27.050-55 Above
28.055-60 Above
29.060-65 Above
30.065-70 Above
31.070-75 Above
32.075-80 Above
33.0≥80 Above
bufferwordsize
4
CE
33
colorscalename
halfgreyscale
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
[ dominant_class ( ZMD CPT NextGen Forecast Prob Above ) + masklt ( { [ dominant_class ( ZMD CPT NextGen Forecast Prob ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( ZMD CPT NextGen Forecast Prob Normal ) + masknotrange ( { [ dominant_class ( ZMD CPT NextGen Forecast Prob ) - 1. ] * 11. } , 10 , 12 ) ]
dominant_class [ ZMD CPT NextGen Forecast Prob Above ] + masklt [ ( { dominant_class [ ZMD CPT NextGen Forecast Prob ] - 1. } * 11. ) , 22 ]
dominant_class [ ZMD CPT NextGen Forecast Prob Above ]
dominant_class over Prob[≤35, ≥80]
masklt [ ( { dominant_class [ ZMD CPT NextGen Forecast Prob ] - 1. } * 11. ) , 22 ]
dominant_class over C[Below, Above]
dominant_class [ ZMD CPT NextGen Forecast Prob Normal ] + masknotrange [ ( { dominant_class [ ZMD CPT NextGen Forecast Prob ] - 1. } * 11. ) , 10 , 12 ]
dominant_class [ ZMD CPT NextGen Forecast Prob Normal ]
dominant_class over Prob[≤35, ≥80]
masknotrange [ ( { dominant_class [ ZMD CPT NextGen Forecast Prob ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Below, Above]
dominant_class [ ZMD CPT NextGen Forecast Prob Below ] + maskgt [ ( { dominant_class [ ZMD CPT NextGen Forecast Prob ] - 1. } * 11. ) , 0 ]
dominant_class [ ZMD CPT NextGen Forecast Prob Below ]
dominant_class over Prob[≤35, ≥80]
maskgt [ ( { dominant_class [ ZMD CPT NextGen Forecast Prob ] - 1. } * 11. ) , 0 ]
dominant_class over C[Below, Above]
colorscale

Last updated: Thu, 10 Feb 2022 00:03:57 GMT
Expires: Sat, 12 Mar 2022 00:00:00 GMT

Data Views

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[ 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 |
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