data: mean [ $partialdiff sub Y$ ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTZW anomalies ) climatology ]

served from 197.155.140.164

mean [ ∂_Y ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTZW anomalies ) climatology ]: ∂_Y Covar. u and T data

mean [ ∂_Y ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTZW anomalies ) climatology ].

Independent Variables (Grids)

Pressure: grid: /P (mb) ordered [ (1000) (925) (850) (700) (600) (500) (400) (300) (250) (200) (150) (100) (70) (50) (30) (20) (10)] :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 (88.75N) to (88.75S) by 2.5 N= 72 pts :grid

Other Info

bufferwordsize

calendar

standard

CE

null

center

US Weather Service - National Met. Center

CS

null

datatype

doublearraytype

grib_name

CBTZW

gribfield

GRIBgridcode

gribleveltype

100

gribNumBits

gribparam

197

gribvariable

197

PDS_TimeRange

113

pointwidth

1.0

process

62 wave triangular, 28 layer Spectral model from "Medium Range Forecast" run

PTVersion

subcenter

NCEP Ensemble Products

units

57.2957795130823 degree_Kelvin meter radian^-1 north second^-1

history

$partialdiff sub Y$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTZW anomalies ] climatology

Averaged over T2[1949, 2022]
Averaged over T2[1949, 2022]

mean [ $partialdiff sub Y$ ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTZW anomalies ) climatology ]

Averaged over T[Jan, Dec]

References

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

Data Views

	P	X	Y
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic[MSL total_air_column surface PressureLevel ]
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel[CBMZW relv qa vpot CBTW CBVQ vvel CBTMW CBQW u CBTZW phi rhum temp v psi CBVW reld CBUW vtemp CBUQ ]
mean [ $partialdiff sub Y$ ( NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTZW anomalies ) climatology ][ X Y P \|]	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 P
Differentiate along X Y P
Take differences along X Y P