conductivity
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Seawater conductivity refers to the ability of seawater to conduct electricity. The presence of ions in the seawater, such as salt, increases the electrical conducting ability of seawater. As such, conductivity can be used as a proxy for determining the quantity of salt in a sample of seawater. This is the unprocessed data that are output directly from the sensor which are then converted to salinity in S m-1. coordinates : time lat lon seawater_pressure data_product_identifier : CONDWAT_L0 long_name : Seawater Conductivity Measurement precision : 0 units : counts
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
ctd_tc_oxygen
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
ancillary_variables : oxygen comment : Dissolved Oxygen (DO) Concentration from the Stable Response Dissolved Oxygen Instrument is a measure of the concentration of gaseous oxygen mixed in seawater. coordinates : time lat lon seawater_pressure data_product_identifier : DOCONCS_L1 long_name : DO precision : 4 units : µmol L-1
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
ctd_tc_oxygen_qc_executed
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Executed
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
ctd_tc_oxygen_qc_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Results
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
density
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
ancillary_variables : pressure practical_salinity temperature comment : Seawater Density is defined as mass per unit volume and is calculated from the conductivity, temperature and depth of a seawater sample using the TEOS-10 equation. coordinates : time lat lon seawater_pressure data_product_identifier : DENSITY_L2 long_name : Seawater Density precision : 3 standard_name : sea_water_density units : kg m-3
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
density_qc_executed
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Executed
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
density_qc_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Results
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
deployment
(time)
int32
dask.array<chunksize=(10485760,), meta=np.ndarray>
long_name : Deployment Number name : deployment
Array Chunk
Bytes 348.62 MB 41.94 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type int32 numpy.ndarray
87155243
1
dissolved_oxygen
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
ancillary_variables : ctd_tc_oxygen practical_salinity pressure temperature comment : Dissolved Oxygen Concentration from the Stable Response Dissolved Oxygen Instrument is a measure of the concentration of gaseous oxygen mixed in seawater. This data product is corrected for salinity, temperature, and depth. coordinates : time lat lon seawater_pressure data_product_identifier : DOXYGEN_L2 long_name : DO - Pressure Temp Sal Corrected precision : 4 standard_name : moles_of_oxygen_per_unit_mass_in_sea_water units : µmol kg-1
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
dissolved_oxygen_qc_executed
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Executed
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
dissolved_oxygen_qc_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Results
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
driver_timestamp
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Driver timestamp, UTC long_name : Driver Timestamp, UTC units : seconds since 1900-01-01
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
ingestion_timestamp
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : The NTP Timestamp for when the granule was ingested long_name : Ingestion Timestamp, UTC units : seconds since 1900-01-01
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
internal_timestamp
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Internal timestamp, UTC long_name : Internal Timestamp, UTC units : seconds since 1900-01-01
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
oxy_calphase
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : Calibrated Phase precision : 0 units : counts
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
oxy_temp
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : DOSTA Temperature precision : 0 units : counts
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
oxygen
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Dissolved Oxygen (DO) unprocessed measurement from the Stable Response Dissolved Oxygen Instrument. coordinates : time lat lon seawater_pressure data_product_identifier : DOCONCS-CNT_L0 long_name : DO Measurement precision : 0 units : counts
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
port_timestamp
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Port timestamp, UTC long_name : Port Timestamp, UTC units : seconds since 1900-01-01
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
practical_salinity
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
ancillary_variables : practical_salinity_qartod_results practical_salinity_qartod_executed pressure conductivity temperature comment : Salinity is generally defined as the concentration of dissolved salt in a parcel of seawater. Practical Salinity is a more specific unitless quantity calculated from the conductivity of seawater and adjusted for temperature and pressure. It is approximately equivalent to Absolute Salinity (the mass fraction of dissolved salt in seawater) but they are not interchangeable. coordinates : time lat lon seawater_pressure data_product_identifier : PRACSAL_L2 long_name : Practical Salinity precision : 4 standard_name : sea_water_practical_salinity units : 1
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
practical_salinity_qartod_executed
(time)
|S1
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : time lat lon seawater_pressure long_name : Practical Salinity Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_practical_salinity status_flag tests_executed : gross_range_test
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type |S1 numpy.ndarray
87155243
1
practical_salinity_qartod_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : time lat lon seawater_pressure flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Practical Salinity QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_practical_salinity status_flag
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
practical_salinity_qc_executed
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Executed
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
practical_salinity_qc_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Results
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
pressure
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor. This is the unprocessed data that are output directly from the sensor which are then converted to pressure in dbar. data_product_identifier : PRESWAT_L0 long_name : Seawater Pressure Measurement precision : 0 units : counts
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
pressure_temp
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor. This is the unprocessed data that are output directly from the sensor which are then converted to pressure in dbar. coordinates : time lat lon seawater_pressure long_name : Seawater Pressure Measurement precision : 0 units : counts
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
seawater_conductivity
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
ancillary_variables : seawater_conductivity_qartod_results seawater_conductivity_qartod_executed pressure seawater_temperature conductivity comment : Seawater conductivity refers to the ability of seawater to conduct electricity. The presence of ions in the seawater, such as salt, increases the electrical conducting ability of seawater. As such, conductivity can be used as a proxy for determining the quantity of salt in a sample of seawater. coordinates : time lat lon seawater_pressure data_product_identifier : CONDWAT_L1 long_name : Seawater Conductivity precision : 6 standard_name : sea_water_electrical_conductivity units : S m-1
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
seawater_conductivity_qartod_executed
(time)
|S1
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : time lat lon seawater_pressure long_name : Seawater Conductivity Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_electrical_conductivity status_flag tests_executed : gross_range_test
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type |S1 numpy.ndarray
87155243
1
seawater_conductivity_qartod_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : time lat lon seawater_pressure flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Seawater Conductivity QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_electrical_conductivity status_flag
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_conductivity_qc_executed
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Executed
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_conductivity_qc_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Results
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_pressure
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
ancillary_variables : seawater_pressure_qartod_results seawater_pressure_qartod_executed pressure pressure_temp axis : Z comment : Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor. data_product_identifier : PRESWAT_L1 long_name : Seawater Pressure precision : 3 standard_name : sea_water_pressure units : dbar
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
seawater_pressure_qartod_executed
(time)
|S1
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : time lat lon seawater_pressure long_name : Seawater Pressure Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_pressure status_flag tests_executed : gross_range_test
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type |S1 numpy.ndarray
87155243
1
seawater_pressure_qartod_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : time lat lon seawater_pressure flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Seawater Pressure QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_pressure status_flag
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_pressure_qc_executed
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Executed
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_pressure_qc_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Results
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_temperature
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
ancillary_variables : seawater_temperature_qartod_results seawater_temperature_qartod_executed temperature comment : Seawater temperature near the sensor. coordinates : time lat lon seawater_pressure data_product_identifier : TEMPWAT_L1 long_name : Seawater Temperature precision : 4 standard_name : sea_water_temperature units : degree_C
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1
seawater_temperature_qartod_executed
(time)
|S1
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : time lat lon seawater_pressure long_name : Seawater Temperature Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_temperature status_flag tests_executed : gross_range_test
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type |S1 numpy.ndarray
87155243
1
seawater_temperature_qartod_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : time lat lon seawater_pressure flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Seawater Temperature QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_temperature status_flag
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_temperature_qc_executed
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Executed
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
seawater_temperature_qc_results
(time)
uint8
dask.array<chunksize=(10485760,), meta=np.ndarray>
coordinates : time lat lon seawater_pressure long_name : QC Checks Results
Array Chunk
Bytes 87.16 MB 10.49 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type uint8 numpy.ndarray
87155243
1
temperature
(time)
float64
dask.array<chunksize=(10485760,), meta=np.ndarray>
comment : Seawater temperature unprocessed measurement near the sensor. coordinates : time lat lon seawater_pressure data_product_identifier : TEMPWAT_L0 long_name : Seawater Temperature Measurement precision : 0 units : counts
Array Chunk
Bytes 697.24 MB 83.89 MB
Shape (87155243,) (10485760,)
Count 10 Tasks 9 Chunks
Type float64 numpy.ndarray
87155243
1