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∫dY min mean [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTW ] : Covar. T and omega data
NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTW CBTW CBTW min Covar. T and omega from NOAA: National Oceanic and Atmospheric Adminstration.Independent Variables (Grids)
- 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 (91.25N) to (91.25S) by 2.5 N= 74 pts :grid
Other Info
- bufferwordsize
- 8
- calendar
- standard
- CE
- null
- center
- US Weather Service - National Met. Center
- CS
- null
- datatype
- doublearraytype
- grib_name
- CBTW
- gribfield
- 1
- GRIBgridcode
- 2
- gribleveltype
- 100
- gribNumBits
- 16
- gribparam
- 194
- gribvariable
- 194
- 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
- 0.0174532925199433 ( degree_Kelvin above 0 ) kilogram meter-1 radian north second-3
- history
- $integral dY$ min mean [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBTW ]
- Averaged over T[Jan 1980, Aug 2014]
min over P[1000 mb, 100 mb]
- Averaged over T[Jan 1980, Aug 2014]
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: Wed, 10 Jan 2018 15:23:36 GMT
Expires: Fri, 03 Oct 2014 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts
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
- Differentiate along X Y
- Take differences along X Y
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |
Note on units