root mean sq ∫dY ∂Y ∂M detrended-bfl ∫dX [ IRI Analyses ICPAC Models Montreal CMC2-CanCM4 FORECAST MONTHLY tref ] : ∂Y ∂M Reference Temperature at 2 Meters data
Analyses ICPAC Models Montreal CMC2-CanCM4 FORECAST MONTHLY tref int_dX adif partial_M partial_Y int_dY
∂Y ∂M Reference Temperature at 2 Meters from IRI: International Research Institute for Climate and Society.
Independent Variables (Grids)
- M (realization)
- grid: /M (unitless) ordered (1.5) to (9.5) by 1.0 N= 9 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- center
- Montreal (RSMC)
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- 9.99900026E20
- grib_name
- TMP
- gribcenter
- 54
- gribfield
- 1
- gribleveltype
- 105
- gribNumBits
- 16
- gribparam
- 11
- missing_value
- NaN
- PDS_TimeRange
- 10
- pointwidth
- 0
- standard_name
- air_temperature
- units
- 0.0174532925199433 degree_Kelvin radian north
- history
- root mean sq $integral dY$ $partialdiff sub Y$ $partialdiff sub M$ detrended-bfl $integral dX$ [ IRI Analyses ICPAC Models Montreal CMC2-CanCM4 FORECAST MONTHLY tref ]
- S: 0000 1 Dec 2015 to 0000 1 Jul 2019 appended from Models NMME Cansips FORECAST MONTHLY tref
Averaged over X[0.5W, 0.5W] Y[90.5S, 90.5N] L[0.0 months, 12.0 months] S[0000 1 Jan 2011, 0000 1 Jul 2019] minimum 0.0% data present
References
Kirtman_etal2014
Last updated: Tue, 08 Dec 2020 21:54:43 GMT
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