served from 197.155.140.164
mean [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ anomalies ]: Covar. v and specific hum data
mean [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ anomalies ].Independent Variables (Grids)
- Pressure
- grid: /P (mb) ordered [ (1000) (925) (850) (700) (600) (500) (400) (300)] :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
- 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
- m /s
- standard units*
- meter second-1
- history
- mean [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ anomalies ]
- Averaged over T2[1949, 2022]
Averaged over X[1.25W, 1.25W] T[1159 18 Nov 1948 - 1159 19 Nov 1948, 0002 18 Dec 2023]
- Averaged over T2[1949, 2022]
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
Views
data as colors
data as contours
line plots
color bars| P | Y | |
 NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic[surface
PressureLevel
MSL
total_air_column
] | ||
 mean [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBVQ anomalies ][ Y P |] | 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 Y P
- Differentiate along Y P
- Take differences along Y P
RMS (root mean square with mean *not* removed) over Y P | Y P |
RMSA (root mean square with mean removed) over Y P | Y P |
Maximum over Y P | Y P |
Minimum over Y P | Y P |
Detrend (best-fit-line) over Y P | Y P |
Note on units