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

served from IRI/LDEO Climate Data Library

ECMWF S2S CMA BCC-CPS-S2Sv2 forecast control sfc_heat_flux sshf: Daily Accumulated Surface Sensible Heat Net Flux data

forecast control sfc_heat_flux Daily Accumulated Surface Sensible Heat Net Flux 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: /L1 (days) ordered (1.0 days) to (60.0 days) by 1.0 N= 60 pts :grid
forecast start time (forecast_reference_time): grid: /S (days since 1960-01-01) ordered (0000 11 Nov 2019) to (0000 11 Apr 2024) by 1.0 N= 1614 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: 04XXXX000B000B
missing_value: 9.99900026E20
pointwidth: 0.0
units: W m^-2 s
standard units*: kilogram second^-2

Last updated: Fri, 03 May 2024 07:12:07 GMT

Data Views

	L1	S	X	Y
ECMWF S2S CMA BCC-CPS-S2Sv2 forecast control sfc_heat_flux sshf[ X Y \| L1 S]	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 L1 S
Differentiate along X Y L1 S
Take differences along X Y L1 S