data: ECMWF S2S CMA BCC-CPS-S2Sv2 forecast control pressure_level

served from IRI/LDEO Climate Data Library

ECMWF S2S CMA BCC-CPS-S2Sv2 forecast control pressure_level_1 q: Specific Humidity data

forecast control pressure_level_1 Specific Humidity from ECMWF S2S CMA BCC-CPS-S2Sv2: Beijing Climate Center (BCC) Climate Prediction System version 2 for S2S.

Independent Variables (Grids)

Lead (forecast_period): grid: /L (days) ordered (0.0 days) to (60.0 days) by 1.0 N= 61 pts :grid
Pressure Level (air_pressure): grid: /P2 (hPa) ordered [ (200) (300) (500) (700) (850) (925) (1000)] :grid
forecast start time (forecast_reference_time): grid: /S (days since 1960-01-01) ordered (0000 11 Nov 2019) to (0000 1 Apr 2024) by 1.0 N= 1604 pts :grid
longitude (longitude): grid: /X (degree_east) periodic (0) to (1.5W) by 1.5 N= 240 pts :grid
latitude (latitude): grid: /Y (degree_north) ordered (90N) to (90S) by 1.5 N= 121 pts :grid

Other Info

bufferwordsize: 4
datatype: realarraytype
gribPDSpattern: 04XXXX00010100
missing_value: 9.99900026E20
pointwidth: 0.0
standard_name: specific_humidity
units: kg /kg
standard units*

Last updated: Tue, 23 Apr 2024 07:11:20 GMT

Data Views

	L	P2	S	X	Y
ECMWF S2S CMA BCC-CPS-S2Sv2 forecast control pressure_level_1 q[ X Y \| P2 L S]	M	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 X Y P2 L S
Differentiate along X Y P2 L S
Take differences along X Y P2 L S