data: root mean sq $partialdiff sub Y$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ ]

root mean sq ∂_Y [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ ] : ∂_Y Covar. v and specific hum data

NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ partial_Y ∂_Y Covar. v and specific hum from NOAA: National Oceanic and Atmospheric Adminstration.

Variables Independientes (Grillas)

Pressure: grid: /P (mb) ordered [ (1000) (925) (850) (700) (600) (500) (400) (300)] :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

Otra Info

bufferwordsize: 8
calendar: standard
CE: null
center: US Weather Service - National Met. Center
CS: null
datatype: doublearraytype
grib_name: CBVQ
gribfield: 1
GRIBgridcode: 2
gribleveltype: 100
gribNumBits: 16
gribparam: 193
gribvariable: 193
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: 57.2957795130823 meter radian^-1 north second^-1
history: Averaged over T[Jan 1980, Aug 2014]

Referencias

Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, A. Leetmaa, B. Reynolds, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, R. Jenne, and D. Joseph. The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of the American Meteorological Society, March, 1996

Última Actualización: Wed, 10 Jan 2018 15:23:36 GMT
Expira: Fri, 03 Oct 2014 00:00:00 GMT

Data Views

	P	X	Y
root mean sq $partialdiff sub Y$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ ] [ 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