ancillary_surface_classification_flag
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : 7-state surface type classification computed from a mask built with MODIS and GlobCover data. flag_meanings : open_ocean land continental_water aquatic_vegetation continental_ice_snow floating_ice salted_basin flag_values : [0, 1, 2, 3, 4, 5, 6] institution : European Space Agency long_name : surface classification source : MODIS/GlobCover standard_name : status_flag valid_max : 6 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
cross_track_angle
(cycle_num, pass_num, num_lines)
float64
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : Angle with respect to true north of the cross-track direction to the right of the spacecraft velocity vector. long_name : cross-track angle from true north units : degrees valid_max : 359999999 valid_min : 0
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
9866 584 8
cross_track_distance
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Distance of sample from nadir. Negative values indicate the left side of the swath, and positive values indicate the right side of the swath. long_name : cross track distance units : m valid_max : 75000.0 valid_min : -75000.0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
dac
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Model estimate of the effect on sea surface topography due to high frequency air pressure and wind effects and the low-frequency height from inverted barometer effect (inv_bar_cor). This value is subtracted from the ssh_karin and ssh_karin_2 to compute ssha_karin and ssha_karin_2, respectively. Use only one of inv_bar_cor and dac. institution : LEGOS/CNES/CLS long_name : dynamic atmospheric correction source : MOG2D units : m valid_max : 12000 valid_min : -12000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
depth_or_elevation
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Ocean depth or land elevation above reference ellipsoid. Ocean depth (bathymetry) is given as negative values, and land elevation positive values. institution : European Space Agency long_name : ocean depth or land elevation source : Altimeter Corrected Elevations, version 2 units : m valid_max : 10000 valid_min : -12000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
distance_to_coast
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Approximate distance to the nearest coast point along the Earth surface. institution : European Space Agency long_name : distance to coast source : MODIS/GlobCover units : m valid_max : 21000 valid_min : -21000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
doppler_centroid
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Doppler centroid (in hertz or cycles per second) estimated by KaRIn. long_name : doppler centroid estimated by KaRIn units : 1/s valid_max : 30000 valid_min : -30000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
dynamic_ice_flag
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Dynamic ice flag for the location of the KaRIn measurement. flag_meanings : no_ice probable_ice ice no_data flag_values : [0, 1, 2, 3] institution : EUMETSAT long_name : dynamic ice flag source : EUMETSAT Ocean and Sea Ice Satellite Applications Facility standard_name : status_flag valid_max : 3 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
geoid
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Geoid height above the reference ellipsoid with a correction to refer the value to the mean tide system, i.e. includes the permanent tide (zero frequency). long_name : geoid height source : EGM2008 (Pavlis et al., 2012) standard_name : geoid_height_above_reference_ellipsoid units : m valid_max : 1500000 valid_min : -1500000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
heading_to_coast
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Approximate compass heading (0-360 degrees with respect to true north) to the nearest coast point. long_name : heading to coast units : degrees valid_max : 35999 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
height_cor_xover
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Height correction from crossover calibration. To apply this correction the value of height_cor_xover should be added to the value of ssh_karin, ssh_karin_2, ssha_karin, and ssha_karin_2. long_name : height correction from crossover calibration quality_flag : height_cor_xover_qual units : m valid_max : 100000 valid_min : -100000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
height_cor_xover_qual
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Flag indicating the quality of the height correction from crossover calibration. Values of 0, 1, and 2 indicate that the correction is good, suspect, and bad, respectively. flag_meanings : good suspect bad flag_values : [0, 1, 2] long_name : quality flag for height correction from crossover calibration standard_name : status_flag valid_max : 2 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
ice_conc
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Concentration of sea ice from model. institution : EUMETSAT long_name : concentration of sea ice source : EUMETSAT Ocean and Sea Ice Satellite Applications Facility standard_name : sea_ice_area_fraction units : % valid_max : 10000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
internal_tide_hret
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Coherent internal ocean tide. This value is subtracted from the ssh_karin and ssh_karin_2 to compute ssha_karin and ssha_karin_2, respectively. long_name : coherent internal tide (HRET) source : Zaron (2019) units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
internal_tide_sol2
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Coherent internal tide. This value is currently always defaulted. long_name : coherent internal tide (Model 2) source : None units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
inv_bar_cor
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Estimate of static effect of atmospheric pressure on sea surface height. Above average pressure lowers sea surface height. Computed by interpolating ECMWF pressure fields in space and time. The value is included in dac. To apply, add dac to ssha_karin and ssha_karin_2 and subtract inv_bar_cor. long_name : static inverse barometer effect on sea surface height units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
iono_cor_gim_ka
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Equivalent vertical correction due to ionosphere delay. The reported sea surface height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. institution : JPL long_name : ionosphere vertical correction quality_flag : ssh_karin_2_qual source : Global Ionosphere Maps units : m valid_max : 0 valid_min : -5000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
latitude_avg_ssh
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Latitude of measurement [-80,80]. Positive latitude is North latitude, negative latitude is South latitude. This value may be biased away from a nominal grid location if some of the native, unsmoothed samples were discarded during processing. long_name : weighted average latitude of samples used to compute SSH standard_name : latitude units : degrees_north valid_max : 80000000 valid_min : -80000000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
load_tide_fes
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Geocentric load tide height. The effect of the ocean tide loading of the Earth's crust. This value has already been added to the corresponding ocean tide height value (ocean_tide_fes). institution : LEGOS/CNES long_name : geocentric load tide height (FES) source : FES2014b (Carrere et al., 2016) units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
load_tide_got
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Geocentric load tide height. The effect of the ocean tide loading of the Earth's crust. This value has already been added to the corresponding ocean tide height value (ocean_tide_got). institution : GSFC long_name : geocentric load tide height (GOT) source : GOT4.10c (Ray, 2013) units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
longitude_avg_ssh
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Longitude of measurement. East longitude relative to Greenwich meridian. This value may be biased away from a nominal grid location if some of the native, unsmoothed samples were discarded during processing. long_name : weighted average longitude of samples used to compute SSH standard_name : longitude units : degrees_east valid_max : 359999999 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_dynamic_topography
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Mean dynamic topography above the geoid. institution : CNES/CLS long_name : mean dynamic topography source : CNES_CLS_2022 units : m valid_max : 30000 valid_min : -30000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_dynamic_topography_uncert
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Accuracy of the mean dynamic topography. institution : CNES/CLS long_name : mean dynamic topography accuracy source : CNES_CLS_2022 units : m valid_max : 10000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_sea_surface_cnescls
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Mean sea surface height above the reference ellipsoid. The value is referenced to the mean tide system, i.e. includes the permanent tide (zero frequency). institution : CNES/CLS long_name : mean sea surface height (CNES/CLS) source : CNES_CLS_2022 units : m valid_max : 1500000 valid_min : -1500000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_sea_surface_cnescls_uncert
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Accuracy of the mean sea surface height (mean_sea_surface_cnescls). institution : CNES/CLS long_name : mean sea surface height accuracy (CNES/CLS) source : CNES_CLS_2022 units : m valid_max : 10000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_sea_surface_dtu
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Mean sea surface height above the reference ellipsoid. The value is referenced to the mean tide system, i.e. includes the permanent tide (zero frequency). institution : DTU long_name : mean sea surface height (DTU) source : DTU18 units : m valid_max : 1500000 valid_min : -1500000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_sea_surface_dtu_uncert
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Accuracy of the mean sea surface height (mean_sea_surface_dtu) institution : DTU long_name : mean sea surface height accuracy (DTU) source : DTU18 units : m valid_max : 10000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_wave_direction
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Mean sea surface wave direction. institution : Meteo France long_name : mean sea surface wave direction source : Meteo France Wave Model (MF-WAM) units : degree valid_max : 36000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
mean_wave_period_t02
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Sea surface wind wave mean period from model spectral density second moment. institution : Meteo France long_name : t02 mean wave period source : Meteo France Wave Model (MF-WAM) standard_name : sea_surface_wind_wave_mean_period_from_variance_spectral_density_second_frequency_moment units : s valid_max : 10000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
model_dry_tropo_cor
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Equivalent vertical correction due to dry troposphere delay. The reported sea surface height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. institution : ECMWF long_name : dry troposphere vertical correction quality_flag : ssh_karin_2_qual source : European Centre for Medium-Range Weather Forecasts units : m valid_max : -15000 valid_min : -30000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
model_wet_tropo_cor
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Equivalent vertical correction due to wet troposphere delay from weather model data. The reported pixel height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height (ssh_karin_2) results in the uncorrected sea surface height. institution : ECMWF long_name : wet troposphere vertical correction from weather model data quality_flag : ssh_karin_2_qual source : European Centre for Medium-Range Weather Forecasts units : m valid_max : 0 valid_min : -10000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
num_pt_avg
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Number of native unsmoothed, beam-combined KaRIn samples averaged. long_name : number of samples averaged units : 1 valid_max : 289 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
obp_ref_surface
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Height (relative to the reference ellipsoid) of the reference surface used by the KaRIn on-board processor. long_name : height of reference surface used by on-board-processor units : m valid_max : 150000000 valid_min : -15000000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ocean_tide_eq
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Equilibrium long-period ocean tide height. This value has already been added to the corresponding ocean tide height values (ocean_tide_fes and ocean_tide_got). long_name : equilibrium long-period ocean tide height units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ocean_tide_fes
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Geocentric ocean tide height. Includes the sum total of the ocean tide, the corresponding load tide (load_tide_fes) and equilibrium long-period ocean tide height (ocean_tide_eq). institution : LEGOS/CNES long_name : geocentric ocean tide height (FES) source : FES2014b (Carrere et al., 2016) units : m valid_max : 300000 valid_min : -300000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ocean_tide_got
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Geocentric ocean tide height. Includes the sum total of the ocean tide, the corresponding load tide (load_tide_got) and equilibrium long-period ocean tide height (ocean_tide_eq). institution : GSFC long_name : geocentric ocean tide height (GOT) source : GOT4.10c (Ray, 2013) units : m valid_max : 300000 valid_min : -300000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ocean_tide_non_eq
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Non-equilibrium long-period ocean tide height. This value is reported as a relative displacement with repsect to ocean_tide_eq. This value can be added to ocean_tide_eq, ocean_tide_fes, or ocean_tide_got, or subtracted from ssha_karin and ssha_karin_2, to account for the total long-period ocean tides from equilibrium and non-equilibrium contributions. institution : LEGOS/CNES long_name : non-equilibrium long-period ocean tide height source : FES2014b (Carrere et al., 2016) units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
orbit_alt_rate
(cycle_num, pass_num, num_lines)
float64
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : Orbital altitude rate with respect to the mean sea surface. long_name : orbital altitude rate with respect to mean sea surface units : m/s valid_max : 3500 valid_min : -3500
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
9866 584 8
orbit_qual
(cycle_num, pass_num, num_lines)
float32
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : Flag indicating the quality of the reconstructed attitude and orbit ephemeris. A value of 0 indicates the reconstructed attitude and orbit ephemeris are both good. Non-zero values less than 64 indicate that the reconstructed attitude is good but there are issues that degrade the quality of the orbit ephemeris. A value of 64 indicates that the reconstructed attitude is degraded or bad. flag_meanings : good orbit_estimated_during_a_maneuver orbit_interpolated_over_data_gap orbit_extrapolated_for_a_duration_less_than_1_day orbit_extrapolated_for_a_duration_between_1_to_2_days orbit_extrapolated_for_a_duration_greater_than_2_days bad_attitude flag_values : [0, 4, 5, 6, 7, 8, 64] long_name : orbit quality flag standard_name : status_flag valid_max : 64 valid_min : 0
Bytes
175.83 MiB
38.54 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
9866 584 8
phase_bias_ref_surface
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Height (relative to the reference ellipsoid) of the reference surface used for phase bias calculation during L1B processing. long_name : height of reference surface used for phase bias calculation units : m valid_max : 150000000 valid_min : -15000000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
polarization_karin
(cycle_num, pass_num, num_lines, num_sides)
object
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : H denotes co-polarized linear horizontal, V denotes co-polarized linear vertical. long_name : polarization for each side of the KaRIn swath
Bytes
703.34 MiB
154.16 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
object numpy.ndarray
8 1 2 9866 584
pole_tide
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Geocentric pole tide height. The total of the contribution from the solid-Earth (body) pole tide height, the ocean pole tide height, and the load pole tide height (i.e., the effect of the ocean pole tide loading of the Earth's crust). long_name : geocentric pole tide height source : Wahr (1985) and Desai et al. (2015) units : m valid_max : 2000 valid_min : -2000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
rad_cloud_liquid_water
(cycle_num, pass_num, num_lines, num_sides)
float64
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : Integrated cloud liquid water content from radiometer measurements. long_name : liquid water content from radiometer source : Advanced Microwave Radiometer standard_name : atmosphere_cloud_liquid_water_content units : kg/m^2 valid_max : 2000 valid_min : 0
Bytes
703.34 MiB
154.16 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 2 9866 584
rad_surface_type_flag
(cycle_num, pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : Flag indicating the validity and type of processing applied to generate the wet troposphere correction (rad_wet_tropo_cor). A value of 0 indicates that open ocean processing is used, a value of 1 indicates coastal processing, and a value of 2 indicates that rad_wet_tropo_cor is invalid due to land contamination. flag_meanings : open_ocean coastal_ocean land flag_values : [0, 1, 2] long_name : radiometer surface type flag source : Advanced Microwave Radiometer standard_name : status_flag valid_max : 2 valid_min : 0
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 2 9866 584
rad_tmb_187
(cycle_num, pass_num, num_lines, num_sides)
float64
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : Main beam brightness temperature measurement at 18.7 GHz. Value is unsmoothed (along-track averaging has not been performed). long_name : radiometer main beam brightness temperature at 18.7 GHz source : Advanced Microwave Radiometer standard_name : toa_brightness_temperature units : K valid_max : 25000 valid_min : 13000
Bytes
703.34 MiB
154.16 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 2 9866 584
rad_tmb_238
(cycle_num, pass_num, num_lines, num_sides)
float64
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : Main beam brightness temperature measurement at 23.8 GHz. Value is unsmoothed (along-track averaging has not been performed). long_name : radiometer main beam brightness temperature at 23.8 GHz source : Advanced Microwave Radiometer standard_name : toa_brightness_temperature units : K valid_max : 25000 valid_min : 13000
Bytes
703.34 MiB
154.16 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 2 9866 584
rad_tmb_340
(cycle_num, pass_num, num_lines, num_sides)
float64
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : Main beam brightness temperature measurement at 34.0 GHz. Value is unsmoothed (along-track averaging has not been performed). long_name : radiometer main beam brightness temperature at 34.0 GHz source : Advanced Microwave Radiometer standard_name : toa_brightness_temperature units : K valid_max : 28000 valid_min : 15000
Bytes
703.34 MiB
154.16 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 2 9866 584
rad_water_vapor
(cycle_num, pass_num, num_lines, num_sides)
float64
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : Integrated water vapor content from radiometer measurements. long_name : water vapor content from radiometer source : Advanced Microwave Radiometer standard_name : atmosphere_water_vapor_content units : kg/m^2 valid_max : 15000 valid_min : 0
Bytes
703.34 MiB
154.16 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 2 9866 584
rad_wet_tropo_cor
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Equivalent vertical correction due to wet troposphere delay from radiometer measurements. The reported pixel height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height (ssh_karin) results in the uncorrected sea surface height. long_name : wet troposphere vertical correction from radiometer data quality_flag : ssh_karin_qual source : Advanced Microwave Radiometer units : m valid_max : 0 valid_min : -10000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
rain_flag
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Flag indicates that signal is attenuated, probably from rain. flag_meanings : no_rain probable_rain rain no_data flag_values : [0, 1, 2, 3] long_name : rain flag standard_name : status_flag valid_max : 3 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
rain_rate
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Rain rate from weather model. institution : ECMWF long_name : rain rate from weather model source : European Centre for Medium-Range Weather Forecasts units : mm/hr valid_max : 200 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
sc_altitude
(cycle_num, pass_num, num_lines)
float64
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : Altitude of the KMSF origin. long_name : altitude of KMSF origin quality_flag : orbit_qual standard_name : height_above_reference_ellipsoid units : m valid_max : 2000000000 valid_min : 0
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
9866 584 8
sc_pitch
(cycle_num, pass_num, num_lines)
float64
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : KMSF attitude pitch angle; positive values move the KMSF +x axis up. long_name : pitch of the spacecraft quality_flag : orbit_qual standard_name : platform_pitch_angle units : degrees valid_max : 1800000 valid_min : -1799999
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
9866 584 8
sc_roll
(cycle_num, pass_num, num_lines)
float64
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : KMSF attitude roll angle; positive values move the +y antenna down. long_name : roll of the spacecraft quality_flag : orbit_qual standard_name : platform_roll_angle units : degrees valid_max : 1800000 valid_min : -1799999
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
9866 584 8
sc_yaw
(cycle_num, pass_num, num_lines)
float64
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : KMSF attitude yaw angle relative to the nadir track. The yaw angle is a right-handed rotation about the nadir (downward) direction. A yaw value of 0 deg indicates that the KMSF +x axis is aligned with the horizontal component of the Earth-relative velocity vector. A yaw value of 180 deg indicates that the spacecraft is in a yaw-flipped state, with the KMSF -x axis aligned with the horizontal component of the Earth-relative velocity vector. long_name : yaw of the spacecraft quality_flag : orbit_qual standard_name : platform_yaw_angle units : degrees valid_max : 1800000 valid_min : -1799999
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
9866 584 8
sea_state_bias_cor
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Sea state bias correction used to compute ssh_karin. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. The wind_speed_karin value is used to compute this quantity. long_name : sea state bias correction source : CNES units : m valid_max : 0 valid_min : -6000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
sea_state_bias_cor_2
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Sea state bias correction used to compute ssh_karin_2. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. The wind_speed_karin_2 value is used to compute this quantity. long_name : sea state bias correction source : CNES units : m valid_max : 0 valid_min : -6000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
sig0_cor_atmos_model
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Atmospheric correction to sigma0 from weather model data as a linear power multiplier (not decibels). sig0_cor_atmos_model is already applied in computing sig0_karin_2. institution : ECMWF long_name : two-way atmospheric correction to sigma0 from model quality_flag : sig0_karin_2_qual source : European Centre for Medium-Range Weather Forecasts units : 1 valid_max : 10.0 valid_min : 1.0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
sig0_cor_atmos_rad
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Atmospheric correction to sigma0 from radiometer data as a linear power multiplier (not decibels). sig0_cor_atmos_rad is already applied in computing sig0_karin. long_name : two-way atmospheric correction to sigma0 from radiometer data quality_flag : sig0_karin_qual source : Advanced Microwave Radiometer units : 1 valid_max : 10.0 valid_min : 1.0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
sig0_karin
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Normalized radar cross section (sigma0) from KaRIn in real, linear units (not decibels). The value may be negative due to noise subtraction. The value is corrected for instrument calibration and atmospheric attenuation. Radiometer measurements provide the atmospheric attenuation (sig0_cor_atmos_rad). long_name : normalized radar cross section (sigma0) from KaRIn quality_flag : sig0_karin_qual standard_name : surface_backwards_scattering_coefficient_of_radar_wave units : 1 valid_max : 10000000.0 valid_min : -1000.0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
sig0_karin_2
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Normalized radar cross section (sigma0) from KaRIn in real, linear units (not decibels). The value may be negative due to noise subtraction. The value is corrected for instrument calibration and atmospheric attenuation. A meteorological model provides the atmospheric attenuation (sig0_cor_atmos_model). long_name : normalized radar cross section (sigma0) from KaRIn quality_flag : sig0_karin_2_qual standard_name : surface_backwards_scattering_coefficient_of_radar_wave units : 1 valid_max : 10000000.0 valid_min : -1000.0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
sig0_karin_2_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for sigma0 from KaRIn in sig0_karin_2 variable. flag_masks : [1, 2, 4, 8, 16, 128, 256, 512, 1024, 2048, 4096, 8192, 65536, 131072, 262144, 524288, 16777216, 33554432, 536870912, 1073741824, 2147483648] flag_meanings : suspect_large_nrcs_delta suspect_large_nrcs_std suspect_large_nrcs_window_std suspect_beam_used suspect_less_than_nine_beams suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_media_attenuation_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_outside_of_range degraded bad_not_usable long_name : quality flag for sigma0 from KaRIn. standard_name : status_flag valid_max : 3809427359 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
sig0_karin_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for sigma0 from KaRIn in sig0_karin_qual variable. flag_masks : [1, 2, 4, 8, 16, 128, 256, 512, 1024, 2048, 4096, 8192, 65536, 131072, 262144, 524288, 16777216, 33554432, 268435456, 536870912, 1073741824, 2147483648] flag_meanings : suspect_large_nrcs_delta suspect_large_nrcs_std suspect_large_nrcs_window_std suspect_beam_used suspect_less_than_nine_beams suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_media_attenuation_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_radiometer_media_attenuation_missing bad_outside_of_range degraded bad_not_usable long_name : quality flag for sigma0 from KaRIn. standard_name : status_flag valid_max : 4077862815 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
sig0_karin_uncert
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : 1-sigma uncertainty on sigma0 from KaRIn. long_name : 1-sigma uncertainty on sigma0 from KaRIn units : 1 valid_max : 1000.0 valid_min : 0.0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
solid_earth_tide
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Solid-Earth (body) tide height. The zero-frequency permanent tide component is not included. long_name : solid Earth tide height source : Cartwright and Taylor (1971) and Cartwright and Edden (1973) units : m valid_max : 10000 valid_min : -10000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssh_karin
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Fully corrected sea surface height measured by KaRIn. The height is relative to the reference ellipsoid defined in the global attributes. This value is computed using radiometer measurements for wet troposphere effects on the KaRIn measurement (e.g., rad_wet_tropo_cor and sea_state_bias_cor). long_name : sea surface height quality_flag : ssh_karin_qual standard_name : sea surface height above reference ellipsoid units : m valid_max : 150000000 valid_min : -15000000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssh_karin_2
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Fully corrected sea surface height measured by KaRIn. The height is relative to the reference ellipsoid defined in the global attributes. This value is computed using model-based estimates for wet troposphere effects on the KaRIn measurement (e.g., model_wet_tropo_cor and sea_state_bias_cor_2). long_name : sea surface height quality_flag : ssh_karin_2_qual standard_name : sea surface height above reference ellipsoid units : m valid_max : 150000000 valid_min : -15000000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssh_karin_2_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for sea surface height from KaRIn in ssh_karin_2 variable. flag_masks : [1, 2, 4, 8, 16, 64, 128, 256, 512, 1024, 2048, 4096, 8192, 32768, 65536, 131072, 262144, 524288, 16777216, 33554432, 536870912, 1073741824, 2147483648] flag_meanings : suspect_large_ssh_delta suspect_large_ssh_std suspect_large_ssh_window_std suspect_beam_used suspect_less_than_nine_beams suspect_ssb_out_of_range suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_ssb_not_computable degraded_media_delays_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_outside_of_range degraded bad_not_usable long_name : quality flag for sea surface height from KaRIn standard_name : status_flag valid_max : 3809460191 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssh_karin_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for sea surface height from KaRIn in ssh_karin variable. flag_masks : [1, 2, 4, 8, 16, 64, 128, 256, 512, 1024, 2048, 4096, 8192, 32768, 65536, 131072, 262144, 524288, 16777216, 33554432, 134217728, 268435456, 536870912, 1073741824, 2147483648] flag_meanings : suspect_large_ssh_delta suspect_large_ssh_std suspect_large_ssh_window_std suspect_beam_used suspect_less_than_nine_beams suspect_ssb_out_of_range suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_ssb_not_computable degraded_media_delays_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_ssb_missing bad_radiometer_corr_missing bad_outside_of_range degraded bad_not_usable long_name : quality flag for sea surface height from KaRIn standard_name : status_flag valid_max : 4212113375 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssh_karin_uncert
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : 1-sigma uncertainty on the sea surface height from the KaRIn measurement. long_name : sea surface height anomaly uncertainty units : m valid_max : 60000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssha_karin
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Sea surface height anomaly from the KaRIn measurement = ssh_karin - mean_sea_surface_cnescls - solid_earth_tide - ocean_tide_fes – internal_tide_hret - pole_tide - dac. long_name : sea surface height anomaly quality_flag : ssha_karin_qual units : m valid_max : 1000000 valid_min : -1000000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssha_karin_2
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Sea surface height anomaly from the KaRIn measurement = ssh_karin_2 - mean_sea_surface_cnescls - solid_earth_tide - ocean_tide_fes – internal_tide_hret - pole_tide - dac. long_name : sea surface height anomaly quality_flag : ssha_karin_2_qual units : m valid_max : 1000000 valid_min : -1000000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssha_karin_2_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for the SSHA from KaRIn in the ssha_karin_2 variable flag_masks : [1, 2, 4, 8, 16, 64, 128, 256, 512, 1024, 2048, 4096, 8192, 32768, 65536, 131072, 262144, 524288, 16777216, 33554432, 67108864, 536870912, 1073741824, 2147483648] flag_meanings : suspect_large_ssh_delta suspect_large_ssh_std suspect_large_ssh_window_std suspect_beam_used suspect_less_than_nine_beams suspect_ssb_out_of_range suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_ssb_not_computable degraded_media_delays_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_tide_corrections_missing bad_outside_of_range degraded bad_not_usable long_name : sea surface height anomaly quality flag standard_name : status_flag valid_max : 3876569055 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
ssha_karin_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for the SSHA from KaRIn in the ssha_karin variable. flag_masks : [1, 2, 4, 8, 16, 64, 128, 256, 512, 1024, 2048, 4096, 8192, 32768, 65536, 131072, 262144, 524288, 16777216, 33554432, 67108864, 134217728, 268435456, 536870912, 1073741824, 2147483648] flag_meanings : suspect_large_ssh_delta suspect_large_ssh_std suspect_large_ssh_window_std suspect_beam_used suspect_less_than_nine_beams suspect_ssb_out_of_range suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_ssb_not_computable degraded_media_delays_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_tide_corrections_missing bad_ssb_missing bad_radiometer_corr_missing bad_outside_of_range degraded bad_not_usable long_name : sea surface height anomaly quality flag standard_name : status_flag valid_max : 4279222239 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
swh_karin
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Significant wave height from KaRIn volumetric correlation. long_name : significant wave height from KaRIn quality_flag : swh_karin_qual standard_name : sea_surface_wave_significant_height units : m valid_max : 15000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
swh_karin_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for significant wave height from KaRIn in swh_karin_qual variable. flag_masks : [8, 16, 32, 128, 256, 512, 1024, 2048, 4096, 8192, 131072, 262144, 524288, 16777216, 33554432, 536870912, 1073741824, 2147483648] flag_meanings : suspect_beam_used suspect_less_than_nine_beams suspect_rain_likely suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_outside_of_range degraded bad_not_usable long_name : quality flag for significant wave height from KaRIn. standard_name : status_flag valid_max : 3809361848 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
swh_karin_uncert
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : 1-sigma uncertainty on significant wave height from KaRIn. long_name : 1-sigma uncertainty on significant wave height from KaRIn units : m valid_max : 25000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
swh_model
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Significant wave height from model. institution : ECMWF long_name : significant wave height from wave model source : European Centre for Medium-Range Weather Forecasts standard_name : sea_surface_wave_significant_height units : m valid_max : 15000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
swh_nadir_altimeter
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Significant wave height from nadir altimeter. long_name : significant wave height from nadir altimeter standard_name : sea_surface_wave_significant_height units : m valid_max : 15000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
swh_ssb_cor_source
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Bit flag that indicates the source of significant wave height information that was used to compute the sea state bias correction in sea_state_bias_cor. flag_masks : [1, 2, 4] flag_meanings : nadir_altimeter karin model long_name : source flag for significant wave height information used to compute sea state bias correction standard_name : status_flag valid_max : 7 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
swh_ssb_cor_source_2
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Bit flag that indicates the source of significant wave height information that was used to compute the sea state bias correction in sea_state_bias_cor_2. flag_masks : [1, 2, 4] flag_meanings : nadir_altimeter karin model long_name : source flag for significant wave height information used to compute sea state bias correction standard_name : status_flag valid_max : 7 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
swh_wind_speed_karin_source
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Bit flag that indicates the source of significant wave height information that was used to compute the wind speed estimate from KaRIn data in wind_speed_karin. flag_masks : [1, 2, 4] flag_meanings : nadir_altimeter karin model long_name : source flag for significant wave height information used to compute wind speed from KaRIn standard_name : status_flag valid_max : 7 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
swh_wind_speed_karin_source_2
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Bit flag that indicates the source of significant wave height information that was used to compute the wind speed estimate from KaRIn data in wind_speed_karin_2. flag_masks : [1, 2, 4] flag_meanings : nadir_altimeter karin model long_name : source flag for significant wave height information used to compute wind speed from KaRIn standard_name : status_flag valid_max : 7 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
time
(cycle_num, pass_num, num_lines)
datetime64[ns]
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : Time of measurement in seconds in the UTC time scale since 1 Jan 2000 00:00:00 UTC. [tai_utc_difference] is the difference between TAI and UTC reference time (seconds) for the first measurement of the data set. If a leap second occurs within the data set, the attribute leap_second is set to the UTC time at which the leap second occurs. leap_second : 0000-00-00T00:00:00Z long_name : time in UTC standard_name : time tai_utc_difference : 37.0
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
datetime64[ns] numpy.ndarray
9866 584 8
time_tai
(cycle_num, pass_num, num_lines)
datetime64[ns]
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : Time of measurement in seconds in the TAI time scale since 1 Jan 2000 00:00:00 TAI. This time scale contains no leap seconds. The difference (in seconds) with time in UTC is given by the attribute [time:tai_utc_difference]. long_name : time in TAI standard_name : time tai_utc_difference : 37.0
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
datetime64[ns] numpy.ndarray
9866 584 8
velocity_heading
(cycle_num, pass_num, num_lines)
float64
dask.array<chunksize=(1, 1, 9866), meta=np.ndarray>
comment : Angle with respect to true north of the horizontal component of the spacecraft Earth-relative velocity vector. A value of 90 deg indicates that the spacecraft velocity vector pointed due east. Values between 0 and 90 deg indicate that the velocity vector has a northward component, and values between 90 and 180 deg indicate that the velocity vector has a southward component. long_name : heading of the spacecraft Earth-relative velocity vector quality_flag : orbit_qual units : degrees valid_max : 359999999 valid_min : 0
Bytes
351.67 MiB
77.08 kiB
Shape
(8, 584, 9866)
(1, 1, 9866)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
9866 584 8
volumetric_correlation
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Volumetric correlation. long_name : volumetric correlation quality_flag : ssh_karin_2_qual units : 1 valid_max : 20000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
volumetric_correlation_uncert
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : 1-sigma uncertainty computed analytically using observed correlation and effective number of looks. Two-sided error bars (volumetric_correlation-volumetric_correlation_uncert, volumetric_correlation+volumetric_correlation_uncert) include 68% of probability distribution. long_name : volumetric correlation standard deviation quality_flag : ssh_karin_2_qual units : 1 valid_max : 10000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
wind_speed_karin
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Wind speed from KaRIn computed from sig0_karin. long_name : wind speed from KaRIn quality_flag : wind_speed_karin_qual standard_name : wind_speed units : m/s valid_max : 65000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
wind_speed_karin_2
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Wind speed from KaRIn computed from sig0_karin_2. long_name : wind speed from KaRIn quality_flag : wind_speed_karin_2_qual standard_name : wind_speed units : m/s valid_max : 65000 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
wind_speed_karin_2_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for wind speed from KaRIn in wind_speed_karin_2 variable. flag_masks : [8, 16, 128, 256, 512, 1024, 2048, 4096, 8192, 65536, 131072, 262144, 524288, 16777216, 33554432, 536870912, 1073741824, 2147483648] flag_meanings : suspect_beam_used suspect_less_than_nine_beams suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_media_attenuation_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_outside_of_range degraded bad_not_usable long_name : quality flag for wind speed from KaRIn. standard_name : status_flag valid_max : 3809427352 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
wind_speed_karin_qual
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Quality flag for wind speed from KaRIn in wind_speed_karin variable. flag_masks : [8, 16, 128, 256, 512, 1024, 2048, 4096, 8192, 65536, 131072, 262144, 524288, 16777216, 33554432, 268435456, 536870912, 1073741824, 2147483648] flag_meanings : suspect_beam_used suspect_less_than_nine_beams suspect_pixel_used suspect_num_pt_avg suspect_karin_telem suspect_orbit_control suspect_sc_event_flag suspect_tvp_qual suspect_volumetric_corr degraded_media_attenuation_missing degraded_beam_used degraded_large_attitude degraded_karin_ifft_overflow bad_karin_telem bad_very_large_attitude bad_radiometer_media_attenuation_missing bad_outside_of_range degraded bad_not_usable long_name : quality flag for wind speed from KaRIn. standard_name : status_flag valid_max : 4077862808 valid_min : 0
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
wind_speed_model_u
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Eastward component of the atmospheric model wind vector at 10 meters. institution : ECMWF long_name : u component of model wind source : European Centre for Medium-Range Weather Forecasts standard_name : eastward_wind units : m/s valid_max : 30000 valid_min : -30000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
wind_speed_model_v
(cycle_num, pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Northward component of the atmospheric model wind vector at 10 meters. institution : ECMWF long_name : v component of model wind source : European Centre for Medium-Range Weather Forecasts standard_name : northward_wind units : m/s valid_max : 30000 valid_min : -30000
Bytes
23.70 GiB
5.19 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 69 9866 584
wind_speed_rad
(cycle_num, pass_num, num_lines, num_sides)
float64
dask.array<chunksize=(1, 1, 9866, 2), meta=np.ndarray>
comment : Wind speed from radiometer measurements. long_name : wind speed from radiometer source : Advanced Microwave Radiometer standard_name : wind_speed units : m/s valid_max : 65000 valid_min : 0
Bytes
703.34 MiB
154.16 kiB
Shape
(8, 584, 9866, 2)
(1, 1, 9866, 2)
Dask graph
4672 chunks in 2 graph layers
Data type
float64 numpy.ndarray
8 1 2 9866 584
wind_speed_ssb_cor_source
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Bit flag that indicates the source of wind speed information that was used to compute the sea state bias correction in sea_state_bias_cor. flag_masks : [1, 2, 4] flag_meanings : nadir_altimeter karin model long_name : source flag for wind speed information used to compute sea state bias correction standard_name : status_flag valid_max : 7 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
wind_speed_ssb_cor_source_2
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Bit flag that indicates the source of wind speed information that was used to compute the sea state bias correction in sea_state_bias_cor_2. flag_masks : [1, 2, 4] flag_meanings : nadir_altimeter karin model long_name : source flag for wind speed information used to compute sea state bias correction standard_name : status_flag valid_max : 7 valid_min : 0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584
x_factor
(cycle_num, pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 1, 9866, 69), meta=np.ndarray>
comment : Radiometric calibration X factor as a linear power ratio. long_name : radiometric calibration X factor as a composite value for the X factors of the +y and -y channels units : 1 valid_max : 1.0000000200408773e+20 valid_min : 0.0
Bytes
11.85 GiB
2.60 MiB
Shape
(8, 584, 9866, 69)
(1, 1, 9866, 69)
Dask graph
4672 chunks in 2 graph layers
Data type
float32 numpy.ndarray
8 1 69 9866 584