served from kmddl.meteo.go.ke
mean ∂X [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBQW ] : ∂X Covar. spec. hum and omega data
mean ∂X [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBQW ] .Independent Variables (Grids)
- Longitude (longitude)
- grid: /X (degree_east) periodic (1.25W) to (3.75W) 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
- CBQW
- gribfield
- 1
- GRIBgridcode
- 2
- gribleveltype
- 100
- gribNumBits
- 16
- gribparam
- 195
- gribvariable
- 195
- 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
- 57.2957795130823 kilogram meter-1 radian-1 east second-3
- history
- Averaged over P[250.0 mb, 1050.0 mb] T[Jan 1949, Aug 2014]
References
Kalnay_etal1996Last 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| X | Y | |
 NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel[vpot
relv
CBTW
CBMZW
u
phi
CBUQ
qa
CBTZW
CBQW
psi
reld
v
vvel
CBVW
vtemp
temp
rhum
CBVQ
CBTMW
CBUW
] | ||
| grid: /X (degree_east) periodic (0) to (2.5W) by 2.5 N= 144 pts :grid | O=-1.25 | |
|---|---|---|
| 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 | ||
| grid: /T (months since 1960-01-01) ordered (Jan 1949) to (Aug 2014) by 1.0 N= 788 pts :grid | ||
 mean $partialdiff sub X$ [ NOAA NCEP-NCAR CDAS-1 MONTHLY Intrinsic PressureLevel CBQW ] [ X Y |] | 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
- 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