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| Global attributes (metadata) |
Variables (data) |
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Global Attributes
WOCE_version
Theses satellite mean wind fields are a part of the WOCE package, provided on two DVDs.
The current package version is "3.0".
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CONVENTIONS
The netCDF standard conventions to which the product refers. The convention is always
"COARDS/WOCE" which means that the data files comply to COARDS and WOCE standard
requirements. COARDS stands for Cooperative Ocean/Atmosphere Research Data Service. The
information on the COARDS standard can be found at http://ferret.wrc.noaa.gov/noaa_coop/coop_cdf_profile.html
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long_name
A complete descriptive name for the product. The long_name has the format
<satellite> <period> mean wind fields where period
is the time interval over which raw data are averaged (daily,
weekly, monthly).
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short_name
The official reference of the product. The format is MWF-<satellite>-<period_id>
where period_id is the identifier of the time interval over which raw data are
averaged (D for daily means, W for weekly means, M for
monthly means).
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producer_agency
The agency that provides the project funding. The nominal value is IFREMER.
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producer_institution
The institution (here department) that provides project management. The nominal value is
CERSAT.
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netcdf_version_id
A character string, which identifies the version of the netcdf (Network Common Data Form)
library, which was used to generate this data file. The netcdf libraries are developed by
Unidata Program Centre in Boulder, Colorado.
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product_version
A character string, which identifies the version of the software, used to generate this
data file. The format of this string is x.y where x.y the release
identification number.
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creation_time
The clock time when the data file was produced. The format of the date is YYYY-DDDTHH:MM:SS
where YYYY is the calendar year, DDD the day of the year, HH
represents the hour in twenty four hour time, MM the minutes and SS the
seconds.
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start_date
The UTC start date of the time interval over which the raw data are averaged on the grid.
The format of the date is YYYY-DDDTHH:MM:SS where YYYY
is the calendar year, DDD the day of the year, HH represents the hour in
twenty four hour time, MM the minutes and SS the seconds.
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stop_date
The UTC end date of the time interval over which the raw data are averaged on the grid.
The format of the date is YYYY-DDDTHH:MM:SS where YYYY
is the calendar year, DDD the day of the year, HH represents the hour in
twenty four hour time, MM the minutes and SS the seconds.
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time_resolution
The length of the time interval over which the raw data are averaged on the grid. The
nominal values are one day mean for the daily means, one week mean
for the weekly means and one month mean for the monthly means.
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spatial_resolution
The size -in latitude and longitude- of the cells of the product grids.
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platform_id
The identifier (name)of the satellite on which the wind sensor (scatterometer) is
embedded.
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instrument
The identifier (name) of the scatterometer collecting the raw wind values averaged on the
grids. The nominal value is SeaWinds.
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objective_method
The objective method used to average the raw wind values and fill the gaps on the grid.
The nominal value is kriging.
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north_latitude
The north latitude of the rectangular grid on which the wind values are averaged. The
latitude reference is the Equator : latitude is positive in the northern hemisphere, and
negative in the southern hemisphere. The nominal value is 80.00.
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south_latitude
The south latitude of the rectangular grid on which the wind values are averaged. The
latitude reference is the Equator : latitude is positive in the northern hemisphere, and
negative in the southern hemisphere. The nominal value is -80.00.
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west_longitude
The west longitude of the rectangular grid on which the wind values are averaged. The
longitude reference is the Greenwich meridian : longitude is positive eastward, negative
westward and ranges between [-180, 180[ (compatibility within the WOCE package).
The nominal value is -180.00.
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east_longitude
The east longitude of the rectangular grid on which the wind values are averaged. The
longitude reference is the Greenwich meridian : longitude is positive eastward, negative
westward and ranges between [-180, 180[ (compatibility within the WOCE
package). The nominal value is -180.00.
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Variables
time
This parameter indicates the time of the center of the averaged period. It is
provided as the number of hours passed since 1900-1-1 0:0:0.This parameter is included for
compatibility within the WOCE package.
| Conceptual type |
integer |
| Storage type |
Int32 |
| Number of bytes |
4 |
| Units |
hours |
| Minimum value |
First hour of this file period |
| Maximum value |
Last hour of this file period |
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depth
This parameter indicates the depth of the measurement. Scatterometer surface wind
are estimated at 10m height in neutral condition. Therefore the depth parameter is set to
+10 (the sea surface has the depth 0, and the positive depth are above the sea surface).
This parameter is included for compatibility within the WOCE package.
| Conceptual type |
real |
| Storage type |
float |
| Number of bytes |
4 |
| Units |
meters |
| Minimum value |
10 |
| Maximum value |
10 |
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woce_date
This parameter indicates the date of the averaged period. The value refers to the
centre of this period, in UTC, using the YYYYMMDD format. The start_date and
stop_date attributes of the woce_date variable indicate the beginning and
the end of this period using the same format. The time_interval attribute indicates the
time resolution of the averaged period (one day, one week or
one month). This parameter is included for compatibility within the WOCE
package and is fully redundant with start_date and stop_date global
attributes.
| Conceptual type |
string |
| Storage type |
int32 |
| Number of bytes |
4 |
| Units |
UTC |
| Minimum value |
YYYYMMDD |
| Maximum value |
YYYYMMDD |
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woce_time
This parameter indicates the time of the averaged period. The value refers
to the centre of the time period, in UTC, using the hhmmss.dd format. The start_time
and stop_time attributes of the woce_time_of_day variable indicate the
beginning and the end of this period using the same format. This parameter is included for
compatibility within the WOCE package and is fully redundant with start_date and stop_date
global attributes.
| Conceptual type |
real |
| Storage type |
float |
| Number of bytes |
4 |
| Units |
UTC |
| Start time |
hhmmss.dd |
| Stop time |
hhmmss.dd |
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latitude
This parameter indicates the latitude corresponding to a given grid row. The
latitude value refers to the centre of the cells of this row. The latitude reference is
the Equator: latitude is positive in the northern hemisphere, and negative in the southern
hemisphere.
| Conceptual type |
real |
| Storage type |
float |
| Number of bytes |
4 |
| Units |
degree |
| Minimum value |
80 |
| Maximum value |
80 |
| Scale factor |
1. |
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longitude
This parameter indicates the longitude corresponding to a given grid column. The longitude
value refers to the centre of the cells of this column. The longitude reference is the
Greenwich meridian: longitude is positive eastward, negative westward and ranges between
[-180, 180[ (compatibility within the WOCE package).
| Conceptual type |
real |
| Storage type |
float |
| Number of bytes |
4 |
| Units |
degree |
| Minimum value |
180.00 |
| Maximum value |
179.99 |
| Scale factor |
1. |
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swath_count
This parameter indicates the number of averaged scatterometer swaths over a given
grid cell.
| Conceptual type |
integer |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
count |
| Minimum value |
0 |
| Maximum value |
32767 |
| Scale factor |
1 |
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quality_flag
This flag indicates the quality of the mean wind computation over a given grid cell. The
significance of each flag value is as follow:
Bit |
Definition |
| 0 |
Ice detection
0 : no ice detected
1 : sea ice detected within the grid cell. No mean wind was computed |
| 1 |
Land detection
0 : no land detected
1 : land detected within the grid cell. No mean wind was computed |
| 2 |
Mean wind retrieval
0 : mean wind was correctly retrieved
1 : mean wind was not computed because of too low sampling |
| 3 |
Mean stress retrieval
0 : mean stress was correctly retrieved
1 : mean stress was not computed because of too low sampling |
| 4 |
Mean wind in valid range
0 : mean wind was reported in valid range
1 : mean wind was out of valid range |
| 5 |
Mean stress in valid range
0 : mean stress was reported in valid range
1 : mean stress was out of valid range |
| Conceptual type |
enum |
| Storage type |
int8 |
| Number of bytes |
1 |
| Units |
n/a |
| Minimum value |
0 |
| Maximum value |
255 |
| Scale factor |
1 |
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wind_speed
The mean wind speed of the surface wind vector computed within a given grid cell,
using the kriging method.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
m/s |
| Minimum value |
0 |
| Maximum value |
60 |
| Scale factor |
0.01 |
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wind_speed_error
The wind speed error of the surface wind vector computed within a given grid
cell, using the kriging method. This parameter indicates the quality of the estimator; for
high values, which correspond to sampling problems, low wind speed or high variability,
the gridded data should be used carefully.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
m/s |
| Minimum value |
0 |
| Maximum value |
10. |
| Scale factor |
0.01 |
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zonal_wind_speed
The mean zonal wind vector component computed within a given grid cell, using the
kriging method. The zonal wind component is positive for eastward wind direction.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
m/s |
| Minimum value |
-60 |
| Maximum value |
60 |
| Scale factor |
0.01 |
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zonal_wind_speed_error
The mean zonal wind vector component error computed within a given grid cell,
using the kriging method. This parameter indicates the quality of the estimator; for high
values, which correspond to sampling problems, low wind speed or high variability, the
gridded data should be used carefully.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
m/s |
| Minimum value |
0 |
| Maximum value |
10. |
| Scale factor |
0.01 |
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meridional_wind_speed
The mean meridional wind vector component computed within a given grid cell,
using the kriging method. The meridional wind component is positive for northward wind
direction.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
m/s |
| Minimum value |
-60. |
| Maximum value |
60 |
| Scale factor |
0.01 |
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meridional_wind_speed_error
The mean meridional wind vector component error computed within a given grid
cell, using the kriging method. This parameter indicates the quality of the estimator; for
high values, which correspond to sampling problems, low wind speed or high variability,
the gridded data should be used carefully.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
m/s |
| Minimum value |
0 |
| Maximum value |
10. |
| Scale factor |
0.01 |
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wind_speed_divergence
The divergence of the wind vector, computed from the mean wind vector grids using
the second order finite difference scheme.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
s-1 |
| Minimum value |
-10-3 |
| Maximum value |
10-3 |
| Scale factor |
10-7 |
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wind_stress
The mean surface wind stress magnitude, computed within a given grid cell, uses
the kriging method. The wind stress individual measurements used in averaging were
calculated from the raw wind values using the Smith (1988) bulk formulation.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
Pa |
| Minimum value |
0.0 |
| Maximum value |
2.5 |
| Scale factor |
0.001 |
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wind_stress_error
The mean error of the surface wind stress magnitude, computed within a given grid
cell, using the kriging method. This parameter indicates the quality of the estimator; for
high values, which correspond to sampling problems, low wind stress or high variability,
the gridded data should be used carefully.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
Pa |
| Minimum value |
0.0 |
| Maximum value |
1.0 |
| Scale factor |
0.001 |
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zonal_wind_stress
The mean zonal surface wind stress component, computed within a given grid cell,
uses the kriging method. The wind stress individual measurements used in averaging were
calculated from the raw wind values using the Smith (1988) bulk formulation.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
Pa |
| Minimum value |
-2.5 |
| Maximum value |
2.5 |
| Scale factor |
0.001 |
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zonal_wind_stress_error
The mean error of the zonal surface wind stress component, computed within a
given grid cell, using the kriging method. This parameter indicates the quality of the
estimator; for high values, which correspond to sampling problems, low wind stress or high
variability, the gridded data should be used carefully.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
Pa |
| Minimum value |
0.0 |
| Maximum value |
1.0 |
| Scale factor |
0.001 |
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meridional_wind_stress
The mean meridional surface wind stress component, computed within a given grid
cell, uses the kriging method. The wind stress individual measurements used in averaging
were calculated from the raw wind values using the Smith (1988) bulk formulation.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
Pa |
| Minimum value |
-2.5 |
| Maximum value |
2.5 |
| Scale factor |
0.001 |
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meridional_wind_stress_error
The mean error of the meridional surface wind stress component, computed within a
given grid cell, using the kriging method. This parameter indicates the quality of the
estimator; for high values, which correspond to sampling problems, low wind stress or high
variability, the gridded data should be used carefully.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
Pa |
| Minimum value |
0.0 |
| Maximum value |
1.0 |
| Scale factor |
0.001 |
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wind_stress_curl
The curl of the wind stress vector, computed from the mean wind stress vector
grids using the second order finite difference scheme.
| Conceptual type |
real |
| Storage type |
int16 |
| Number of bytes |
2 |
| Units |
Pa/m |
| Minimum value |
-2.10-5 |
| Maximum value |
2.10-5 |
| Scale factor |
10-9 |
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