Show/Hide data repr

xarray.Dataset

Dimensions:
- time: 32

Coordinates: (1)

time

(time)

float64

3.632e+09 3.644e+09 ... 3.77e+09

axis :: T
calendar :: gregorian
long_name :: time
standard_name :: time
units :: seconds since 1900-01-01 0:0:0

array([3.631749e+09, 3.643769e+09, 3.644136e+09, 3.647535e+09, 3.674912e+09,
       3.674915e+09, 3.675010e+09, 3.675010e+09, 3.675182e+09, 3.675183e+09,
       3.677264e+09, 3.677265e+09, 3.677265e+09, 3.677267e+09, 3.677267e+09,
       3.677268e+09, 3.677268e+09, 3.677269e+09, 3.677270e+09, 3.677270e+09,
       3.677271e+09, 3.677271e+09, 3.677271e+09, 3.678463e+09, 3.704224e+09,
       3.714343e+09, 3.717706e+09, 3.744382e+09, 3.746722e+09, 3.751704e+09,
       3.757864e+09, 3.770253e+09])

Data variables: (49)

deployment

(time)

int32

dask.array<chunksize=(32,), meta=np.ndarray>

long_name :: Deployment Number
name :: deployment





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  int32  numpy.ndarray

driver_id_device1

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Driver Id Device1
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

driver_id_device2

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Driver Id Device2
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

driver_id_device3

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Driver Id Device3
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

driver_id_prestart

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Driver Id Prestart
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

driver_id_sami

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Driver Id SAMI
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

driver_timestamp

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

comment :: Driver timestamp, UTC
long_name :: Driver Timestamp, UTC
units :: seconds since 1900-01-01





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

extend_global_config

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Extend Global Config
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

ingestion_timestamp

(time)

float64

dask.array<chunksize=(32,), 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  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

internal_timestamp

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

comment :: Internal timestamp, UTC
long_name :: Internal Timestamp, UTC
units :: seconds since 1900-01-01





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

launch_time

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

comment :: Launch time recorded in seconds since January 1, 1904
coordinates :: time lat lon
long_name :: Launch Time, UTC
precision :: 0
units :: seconds since 1904-01-01





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

measure_to_pump_on

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Measure to Pump-On
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

number_blanks

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Blanks
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

number_flushes

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Flushes
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

number_measurements

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Measurements
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

number_reagent_pumps

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Reagent Pumps
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

number_samples_averaged

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Samples
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

parameter_pointer_device1

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Parameter Pointer Device1
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

parameter_pointer_device2

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Parameter Pointer Device2
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

parameter_pointer_device3

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Parameter Pointer Device3
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

parameter_pointer_prestart

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Parameter Pointer Prestart
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

parameter_pointer_sami

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Parameter Pointer SAMI
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

pmi_sample_schedule

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: PMI Sample Schedule
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

port_timestamp

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

comment :: Port timestamp, UTC
long_name :: Port Timestamp, UTC
units :: seconds since 1900-01-01





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

pump_measure_t

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Pump Measure
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

pump_off_flush

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Pump-Off Flush
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

pump_off_to_measure

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Pump-Off to Measure
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

pump_on_flush

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Pump-On Flush
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

pump_on_ind

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Pump-On Ind
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

pv_off_ind

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: PV-Off Ind
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

recording_time

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

comment :: Elapsed time between start and stop, in seconds.
coordinates :: time lat lon
long_name :: Recording Time
precision :: 0
units :: s





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

salinity_delay

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Salinity Delay
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

sami_sample_schedule

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: SAMI Sample Schedule
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

send_live_records

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Send Live Records
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

send_record_type

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Send Record Type Early
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

slot1_follows_sami_sample

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Slot1 Follows SAMI Sample
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

slot1_independent_schedule

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Slot1 Independent Schedule
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

slot2_follows_sami_sample

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Slot2 Follows SAMI Sample
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

slot2_independent_schedule

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Slot2 Independent Schedule
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

slot3_follows_sami_sample

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Slot3 Follows SAMI Sample
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

slot3_independent_schedule

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Slot3 Independent Schedule
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

start_time_offset

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

comment :: Elapsed time between launch and start, in seconds.
coordinates :: time lat lon
long_name :: Start Time Offset
precision :: 0
units :: s





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

timer_interval_device1

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Timer Interval Device1
precision :: 0
units :: s





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

timer_interval_device2

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Timer Interval Device2
precision :: 0
units :: s





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

timer_interval_device3

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Timer Interval Device3
precision :: 0
units :: s





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

timer_interval_prestart

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Timer Interval Prestart
precision :: 0
units :: s





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

timer_interval_sami

(time)

float64

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Timer Interval SAMI
precision :: 0
units :: s





  
      Array  Chunk 
  
  
     Bytes  256 B   256 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

use_baud_rate_57600

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Use Baud Rate 9600
precision :: 0
units :: 1





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

valve_delay

(time)

float32

dask.array<chunksize=(32,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Valve Delay
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  128 B   128 B 
     Shape  (32,)   (32,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

Attributes: (53)
Conventions :
CF-1.6
Metadata_Conventions :
Unidata Dataset Discovery v1.0
Notes :
This netCDF product is a copy of the data on the University of Washington AWS Cloud Infrastructure.
Owner :
University of Washington Cabled Array Value Add Team.
cdm_data_type :
Point
collection_method :
streamed
comment :
Some of the metadata of this dataset has been modified to be CF-1.6 compliant.
creator_name :
Ocean Observatories Initiative
creator_url :
http://oceanobservatories.org/
date_created :
2020-08-11T00:19:18.095293
date_downloaded :
2020-09-22T23:13:16.722329
date_modified :
2020-08-11T00:19:18.095300
date_processed :
2020-09-22T23:14:23.136615
featureType :
point
geospatial_lat_max :
44.637
geospatial_lat_min :
44.637
geospatial_lat_resolution :
0.1
geospatial_lat_units :
degrees_north
geospatial_lon_max :
-124.30587
geospatial_lon_min :
-124.30587
geospatial_lon_resolution :
0.1
geospatial_lon_units :
degrees_east
geospatial_vertical_positive :
down
geospatial_vertical_resolution :
0.1
geospatial_vertical_units :
meters
history :
2020-08-11T00:19:18.095218 generated from Stream Engine
id :
CE02SHBP-LJ01D-10-PHSEND103-streamed-phsen_configuration
infoUrl :
http://oceanobservatories.org/
institution :
Ocean Observatories Initiative
keywords :
keywords_vocabulary :
lat :
44.637
license :
lon :
-124.30587
naming_authority :
org.oceanobservatories
nodc_template_version :
NODC_NetCDF_TimeSeries_Orthogonal_Template_v1.1
node :
LJ01D
processing_level :
L2
project :
Ocean Observatories Initiative
publisher_email :
publisher_name :
Ocean Observatories Initiative
publisher_url :
http://oceanobservatories.org/
references :
More information can be found at http://oceanobservatories.org/
sensor :
10-PHSEND103
source :
CE02SHBP-LJ01D-10-PHSEND103-streamed-phsen_configuration
sourceUrl :
http://oceanobservatories.org/
standard_name_vocabulary :
NetCDF Climate and Forecast (CF) Metadata Convention Standard Name Table 29
stream :
phsen_configuration
subsite :
CE02SHBP
summary :
Dataset Generated by Stream Engine from Ocean Observatories Initiative
time_coverage_end :
2015-06-24T12:04:14.678165
time_coverage_start :
2015-02-01T03:02:45.680267
title :
Data produced by Stream Engine version 1.15.0 for CE02SHBP-LJ01D-10-PHSEND103-streamed-phsen_configuration