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

SOURCES .IRI .Analyses .ICPAC .Models .Montreal .CMC2-CanCM4 .FORECAST .MONTHLY .tref S partial %5BL M S %5Ddetrend-bfl %5BY L S %5Ddetrend-bfl %5BY M L S %5Ddetrend-bfl S integral

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 S
• Differentiate along S
• Take differences along S

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

Convert units from 0.00694444444444444 (year above 2000) year to

Note on units