data: root mean sq $integral dP$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel qa ]

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root mean sq ∫dP [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel qa ] : Specific humidity data

root mean sq ∫dP [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel qa ] .

Independent Variables (Grids)

Time (time): grid: /T (months since 1960-01-01) ordered (Jan 1949) to (Aug 2014) by 1.0 N= 788 pts :grid
Longitude (longitude): grid: /X (degree_east) periodic (0) to (2.5W) by 2.5 N= 144 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (90N) to (90S) by 2.5 N= 73 pts :grid

Other Info

bufferwordsize: 8
calendar: standard
CE: null
center: US Weather Service - National Met. Center
CS: null
datatype: doublearraytype
grib_name: SPFH
gribfield: 1
GRIBgridcode: 2
gribleveltype: 100
gribNumBits: 15
gribparam: 51
gribvariable: 51
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: mb
standard units*: 100 kilogram meter^-1 second^-2
history: Averaged over P[250.0 mb, 1037.5 mb]

References

Kalnay_etal1996

Last updated: Wed, 29 May 2024 07:29:02 GMT

Data Views

	T	X	Y
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic[MSL total_air_column PressureLevel surface ]
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel[vpot relv CBTW CBMZW u phi CBUQ qa CBTZW CBQW psi reld v vvel CBVW vtemp temp rhum CBVQ CBTMW CBUW ]
grid: /X (degree_east) periodic (0) to (2.5W) by 2.5 N= 144 pts :grid		M
grid: /Y (degree_north) ordered (90N) to (90S) by 2.5 N= 73 pts :grid			M
grid: /P (mb) ordered [ (1000) (925) (850) (700) (600) (500) (400) (300)] :grid
grid: /T (months since 1960-01-01) ordered (Jan 1949) to (Aug 2014) by 1.0 N= 788 pts :grid	M
root mean sq $integral dP$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel qa ] [ 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