served from IRI/LDEO Climate Data Library
ECMWF GGA sphm climatology: specific humidity data
GGA sphm specific humidity from ECMWF: European Center for Medium Range Weather Forecasts.Independent Variables (Grids)
- Pressure
- grid: /P (mb) ordered [ (10.0) (30.0) (50.0) (70.0) (100.0) (150.0) (200.0) (250.0) (300.0) (400.0) (500.0) (700.0) (850.0) (1000.0)] :grid
- Time (time)
- grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 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
- CE
- null
- CS
- null
- datatype
- realarraytype
- units
- unitless
- history
- Averaged over T2[1985, 1992]
References
Trenberth1992Last updated: Mon, 12 Sep 2016 21:39:40 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| P | T | X | Y | |
 ECMWF GGA sphm climatology[ Y X P T |] | M | 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 Y X P T
- Differentiate along Y X P T
- Take differences along Y X P T
RMS (root mean square with mean *not* removed) over Y X P T | Y X Y P Y T X P X T P T | Y X P Y X T Y P T X P T | Y X P T |
RMSA (root mean square with mean removed) over Y X P T | Y X Y P Y T X P X T P T | Y X P Y X T Y P T X P T | Y X P T |
Maximum over Y X P T | Y X Y P Y T X P X T P T | Y X P Y X T Y P T X P T | Y X P T |
Minimum over Y X P T | Y X Y P Y T X P X T P T | Y X P Y X T Y P T X P T | Y X P T |
Detrend (best-fit-line) over Y X P T | Y X Y P Y T X P X T P T | Y X P Y X T Y P T X P T | Y X P T |
Note on units