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NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic MSL pressure: Pressure data
NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic MSL pressure.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (Jan 1949) to (Dec 2021) by 1.0 N= 876 pts :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
- 4
- calendar
- standard
- center
- US Weather Service - National Met. Center
- datatype
- realarraytype
- grib_name
- PRES
- gribfield
- 1
- GRIBgridcode
- 2
- gribleveltype
- 102
- gribNumBits
- 13
- 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
- scale_max
- 108300.0
- scale_min
- 95947.0
- subcenter
- NCEP Ensemble Products
- units
- Pa
- standard units*
- kilogram meter-1 second-2
References
Kalnay_etal1996Last updated: Wed, 09 Mar 2022 20:30:18 GMT
Expires: Thu, 03 Feb 2022 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| P | T | X | Y | |
 NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic[PressureLevel
surface
MSL
total_air_column
] | ||||
| grid: /X (degree_east) periodic (0) to (2.5W) by 2.5 N= 144 pts :grid | M | |||
|---|---|---|---|---|
| grid: /Y (degree_north) ordered (90N) to (90S) by 2.5 N= 73 pts :grid | M | |||
| grid: /P (mb) ordered [ (1000) (925) (850) (700) (600) (500) (400) (300)] :grid | M | |||
| grid: /T (months since 1960-01-01) ordered (Jan 1949) to (Dec 2021) by 1.0 N= 876 pts :grid | M | |||
| NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel vtemp[ X Y | P T] | M | M | M | M |
 NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic MSL pressure[ 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