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

root mean sq ∂_T ∂_T [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel reld ] : ∂_T ∂_T Relative divergence data

root mean sq ∂_T ∂_T [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel reld ] .

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 (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: RELD
gribfield: 1
GRIBgridcode: 2
gribleveltype: 100
gribNumBits: 13
gribparam: 44
gribvariable: 44
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: 144 second^-1 year^-2
history: Averaged over T[16 Feb 1949 - 15 Mar 1949, 16 Dec 2022 - 15 Jan 2023]

References

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

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

Data Views

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