data: $integral dX$ root mean sq anom $partialdiff sub T$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel vtemp ]

∫dX root mean sq anom ∂_T [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel vtemp ] : ∂_T Virtual temperature data

NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel vtemp partial_T partial_T ∂_T Virtual temperature from NOAA: National Oceanic and Atmospheric Adminstration.

Independent Variables (Grids)

Time (time): grid: /T (months since 1960-01-01) ordered (16 Jan 1980 - 15 Feb 1980) to (16 Jul 2014 - 15 Aug 2014) by 1.0 N= 415 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (1.25W) to (1.25W) by 2.5 N= 145 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: VTMP
gribfield: 1
GRIBgridcode: 2
gribleveltype: 100
gribNumBits: 13
gribparam: 12
gribvariable: 12
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: 0.20943951023932 degree_Kelvin radian east year^-1
history: Averaged over P[1000 mb, 300 mb]

References

Kalnay_etal1996

Last updated: Wed, 10 Jan 2018 15:23:36 GMT
Expires: Fri, 03 Oct 2014 00:00:00 GMT

Data Views

	T	X	Y
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic[surface PressureLevel MSL total_air_column ]
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel[CBTMW CBTW relv CBTZW CBUW CBQW v CBMZW CBVQ rhum temp qa reld vpot vtemp psi vvel phi CBUQ u CBVW ]
$integral dX$ root mean sq anom $partialdiff sub T$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel vtemp ] [ 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