data: dominant_class weights

served from IRI/LDEO Climate Data Library

dominant_class weights: Date data

dominant_class weights.

Independent Variables (Grids)

Time (time): grid: /T (julian_day) ordered (1 May 2017) to (21 May 2017) by 1.0 N= 21 pts :grid

Other Info

Key
1.0	1 May 2017
2.0	2 May 2017
3.0	3 May 2017
4.0	4 May 2017
5.0	5 May 2017
6.0	6 May 2017
7.0	7 May 2017
8.0	8 May 2017
9.0	9 May 2017
10.0	10 May 2017
11.0	11 May 2017
12.0	12 May 2017
13.0	13 May 2017
14.0	14 May 2017
15.0	15 May 2017
16.0	16 May 2017
17.0	17 May 2017
18.0	18 May 2017
19.0	19 May 2017
20.0	20 May 2017
21.0	21 May 2017

bufferwordsize: 4
CE: 21
CLISTu: julian_day
colorscalename: rainbowcolorscale
CS: 1
datatype: integerarraytype
gridid: 195770632
maxncolor: 256
missing_value: 0
pointwidth: 1.0
scale_max: 21.0
scale_min: 1.0
standard_name: time
units: ids
valid_max: 21
valid_min: 1
history: dominant_class over Date[1 May 2017, 21 May 2017]
colorscale

Last updated: Fri, 03 May 2024 19:55:02 GMT
Expires: Mon, 26 Feb 2024 00:00:00 GMT

Data Views

	T
BoM MJO RMM[amplitude RMM1 phase RMM2 ]
BoM MJO RMM RMM1[ T \|]	M
BoM MJO RMM RMM2[ T \|]	M
BoM MJO RMM RMM1[ T \|]	M
BoM MJO RMM RMM2[ T \|]	M
dominant_class weights[ T \|]	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 T
Differentiate along T
Take differences along T

	T
BoM MJO RMM[amplitude RMM1 phase RMM2 ]
BoM MJO RMM RMM1[ T \|]	M
BoM MJO RMM RMM2[ T \|]	M
BoM MJO RMM RMM1[ T \|]	M
BoM MJO RMM RMM2[ T \|]	M
dominant_class weights[ T \|]	M