served from IRI/LDEO Climate Data Library
ECMWF S2S CMA BCC-CPS-S2Sv1 forecast perturbed sfc_snow_ice rsn: Snow Density data
sfc_snow_ice Snow Density from ECMWF S2S CMA BCC-CPS-S2Sv1 forecast perturbed: Beijing Climate Center (BCC) Climate Prediction System version 1 for S2S.Independent Variables (Grids)
- Lead (forecast_period)
- grid: /LA (days) ordered (0.5 days) to (59.5 days) by 1.0 N= 60 pts :grid
- Ensemble Member (realization)
- grid: /M (ids) ordered (1) to (3) by 1.0 N= 3 pts :grid
- forecast start time (forecast_reference_time)
- grid: /S (days since 1960-01-01) ordered (0000 1 Jan 2016) to (0000 9 Nov 2019) by 1.0 N= 1409 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
- 04XXXX000B013D
- missing_value
- 9.99900026E20
- pointwidth
- 0.0
- standard_name
- snow_density
- units
- kg m-3
- standard units*
- kilogram meter-3
Last updated: Tue, 29 Aug 2023 13:33:38 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| LA | M | S | X | Y | |
 ECMWF S2S CMA BCC-CPS-S2Sv1 forecast perturbed sfc_snow_ice rsn[ X Y | M LA S] | M | M | M | M | M |
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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 M LA S
- Differentiate along X Y M LA S
- Take differences along X Y M LA S
RMS (root mean square with mean *not* removed) over X Y M LA S | X Y X M X LA X S Y M Y LA Y S M LA M S LA S | X Y M X Y LA X Y S X M LA X M S X LA S Y M LA Y M S Y LA S M LA S | X Y M LA X Y M S X Y LA S X M LA S Y M LA S | X Y M LA S |
RMSA (root mean square with mean removed) over X Y M LA S | X Y X M X LA X S Y M Y LA Y S M LA M S LA S | X Y M X Y LA X Y S X M LA X M S X LA S Y M LA Y M S Y LA S M LA S | X Y M LA X Y M S X Y LA S X M LA S Y M LA S | X Y M LA S |
Maximum over X Y M LA S | X Y X M X LA X S Y M Y LA Y S M LA M S LA S | X Y M X Y LA X Y S X M LA X M S X LA S Y M LA Y M S Y LA S M LA S | X Y M LA X Y M S X Y LA S X M LA S Y M LA S | X Y M LA S |
Minimum over X Y M LA S | X Y X M X LA X S Y M Y LA Y S M LA M S LA S | X Y M X Y LA X Y S X M LA X M S X LA S Y M LA Y M S Y LA S M LA S | X Y M LA X Y M S X Y LA S X M LA S Y M LA S | X Y M LA S |
Detrend (best-fit-line) over X Y M LA S | X Y X M X LA X S Y M Y LA Y S M LA M S LA S | X Y M X Y LA X Y S X M LA X M S X LA S Y M LA Y M S Y LA S M LA S | X Y M LA X Y M S X Y LA S X M LA S Y M LA S | X Y M LA S |
Note on units