served from IRI/LDEO Climate Data Library
NOAA NCEP CPC CMORPH daily_calculated mean morphed [ cmorph * 24. ]: Estimated precipitation data
cmorph cmorph cmorph cmorph Estimated precipitation from NOAA NCEP CPC CMORPH daily_calculated mean morphed: Daily average derived from CMORPH V0px RAW 3-hourly appended to CMORPH 3-hourly orignames morphed.Independent Variables (Grids)
- Time
- grid: /T (days since 2002-12-07 00:00:00) ordered (7 Dec 2002) to (18 Sep 2024) by 1.0 N= 7957 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (19.875W) to (94.875E) by 0.25 N= 460 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (3.875S) to (39.875N) by 0.25 N= 176 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 150
- colorscalename
- cmorph_tool_colors
- CS
- 0
- datatype
- realarraytype
- file_missing_value
- -9999.0
- maxncolor
- 254
- missing_value
- NaN
- mm/hr
- mm
- pointwidth
- 0
- scale_max
- 150.0
- scale_min
- 0.0
- units
- mm /hr
- standard units*
- 2.77777777777778×10-07 meter second-1
- history
- NOAA NCEP CPC CMORPH daily_calculated mean morphed [ cmorph * 24. ]
- T: 2100-2400 27 Oct 2015 to 2100-2400 18 Sep 2024 appended from NOAA NCEP CPC CMORPH V0px RAW 3-hourly [ prcp / 3. ]
Boxes with less than 0.0% dropped
- T: 2100-2400 27 Oct 2015 to 2100-2400 18 Sep 2024 appended from NOAA NCEP CPC CMORPH V0px RAW 3-hourly [ prcp / 3. ]
- colorscale
References
Joyce, R.J., J.E. Janowiak, P. A. Arkin and P. Xie, 2004: CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution. J. Hydrometeorology, 5, 487-503.Last updated: Tue, 20 Jul 2021 19:46:33 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 NOAA NCEP CPC CMORPH daily_calculated mean morphed [ cmorph * 24. ][ 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