data: $integral dY$ $partialdiff sub X$ [ $integral dY$ ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic surface pressure ) anomalies ]

∫dY ∂_X [ ∫dY ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic surface pressure ) anomalies ] : ∂_X Pressure data

∫dY ∂_X [ ∫dY ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic surface pressure ) anomalies ] .

Independent Variables (Grids)

Time (time): grid: /T (months since 1960-01-01) ordered (Jan 1949) to (Feb 2023) by 1.0 N= 890 pts :grid
Longitude (longitude): grid: /X (degree_east) periodic (1.25W) to (3.75W) by 2.5 N= 144 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (92.5N) to (92.5S) by 2.5 N= 75 pts :grid

Other Info

bufferwordsize: 8
calendar: standard
CE: null
center: US Weather Service - National Met. Center
CS: null
datatype: doublearraytype
grib_name: PRES
gribfield: 1
GRIBgridcode: 2
gribleveltype: 1
gribNumBits: 16
gribparam: 1
gribvariable: 1
PDS_TimeRange: 113
pointwidth: 1.0
process: 62 wave triangular, 28 layer Spectral model from "Medium Range Forecast" run
PTVersion: 2
subcenter: NCEP Ensemble Products
units: 0.0174532925199433 kilogram meter^-1 radian north second^-2
history: Averaged over T2[1949, 2022]

References

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Last updated: Mon, 27 Mar 2023 13:29:42 GMT

Data Views

	T	X	Y
$integral dY$ $partialdiff sub X$ [ $integral dY$ ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic surface pressure ) anomalies ] [ X Y \| T]	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 X Y T
Differentiate along X Y T
Take differences along X Y T