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NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic surface pressure anomalies: Pressure data
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic surface pressure anomalies.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (Jan 1949) to (Aug 2014) by 1.0 N= 788 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) periodic (1.25E) to (1.25W) 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
Other Info
- bufferwordsize
- 4
- calendar
- standard
- CE
- null
- center
- US Weather Service - National Met. Center
- CS
- null
- datatype
- realarraytype
- grib_name
- PRES
- gribfield
- 1
- GRIBgridcode
- 2
- gribleveltype
- 1
- gribNumBits
- 16
- gribparam
- 1
- gribvariable
- 1
- 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
- Pa
- standard units*
- kilogram meter-1 second-2
- history
- Averaged over T2[1949, 2013]
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, 29 May 2024 07:29:02 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic surface pressure anomalies[ 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
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units