data: $integral dM$ M

Data Library ∫dM M

M[0.5 10.5]

served from IRI/LDEO Climate Data Library

∫dM M: Ensemble Member data

∫dM M.

Independent Variables (Grids)

M (realization): grid: /M (unitless) ordered (0.5) to (10.5) by 1.0 N= 11 pts :grid

Other Info

bufferwordsize: 8
datatype: doublearraytype
gridid: 188945080
pointwidth: 1.0
scale_max: null
scale_min: null
standard_name: realization
units: unitless

Last updated: Tue, 08 Dec 2020 21:54:43 GMT

Data Views

	L	M	S	X	Y
$partialdiff sub S$ [ IRI Analyses ICPAC Models Montreal CMC2-CanCM4 FORECAST MONTHLY tref ][ X Y \| L M S]	M	O=-0.5	M	M	M
grid: /M (unitless) ordered (1.0) to (10.0) by 1.0 N= 10 pts :grid		O=-0.5
grid: /S (months since 1960-01-01) ordered (Jan 2011) to (Jun 2019) by 1.0 N= 102 pts :grid			M
grid: /L (months) ordered (0.5 months) to (11.5 months) by 1.0 N= 12 pts :grid	M
grid: /S (months since 1960-01-01) ordered (Jan 2011) to (Jun 2019) by 1.0 N= 102 pts :grid			M
grid: /M (unitless) ordered (1.0) to (10.0) by 1.0 N= 10 pts :grid		O=-0.5
grid: /Y (degree_north) ordered (90S) to (90N) by 1.0 N= 181 pts :grid					M
grid: /L (months) ordered (0.5 months) to (11.5 months) by 1.0 N= 12 pts :grid	M
grid: /S (months since 1960-01-01) ordered (Jan 2011) to (Jun 2019) by 1.0 N= 102 pts :grid			M
$integral dM$ 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 M
Differentiate along M
Take differences along M

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

Note on units