event_period
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event period (instrument(s) mean) units : min \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_start
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event start time offset from midnight (instrument(s) mean) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_end
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event end time offset from midnight (instrument(s) mean) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_mean_rate
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event mean precipitation rate (instrument(s) mean) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_max_rate
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event max precipitation rate (instrument(s) mean) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_total
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event total accumulated (instrument(s) mean) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_rate_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event precipitation rate standard deviation (instrument(s) mean) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
num_instruments_per_event
(time)
float32
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : The number of instruments incorporated in the processing of the given event units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 44 B \n",
+ " 8 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float32 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
single_instrument_flag
(time)
float32
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Valid data from only a single instrument were available for the given event (use with caution) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 44 B \n",
+ " 8 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float32 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
instrument_Incorrect_dqr_flag
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : (Bitwise) instrument DQR Incorrect flag during part or all of the given event units : 1 comment : Value of 0 indicates Incorrect DQRs do not exist for the given event flag_masks : [ 1 2 4 8 16 32 64 128 256 512 1024] flag_meanings : pwd_Incorrect_dqr_exists aosmet_Incorrect_dqr_exists disdrometer_Incorrect_dqr_exists marinemet_Incorrect_dqr_exists abmmet_Incorrect_dqr_exists metwxt_Incorrect_dqr_exists pws_Incorrect_dqr_exists vdisquants_Incorrect_dqr_exists ldquants_Incorrect_dqr_exists wbpluvio2_Incorrect_dqr_exists tbrg_Incorrect_dqr_exists bit_1_description : pwd_Incorrect_dqr_exists bit_2_description : aosmet_Incorrect_dqr_exists bit_3_description : disdrometer_Incorrect_dqr_exists bit_4_description : marinemet_Incorrect_dqr_exists bit_5_description : abmmet_Incorrect_dqr_exists bit_6_description : metwxt_Incorrect_dqr_exists bit_7_description : pws_Incorrect_dqr_exists bit_8_description : vdisquants_Incorrect_dqr_exists bit_9_description : ldquants_Incorrect_dqr_exists bit_10_description : wbpluvio2_Incorrect_dqr_exists bit_11_description : tbrg_Incorrect_dqr_exists \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
instrument_Suspect_dqr_flag
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : (Bitwise) instrument DQR Suspect flag during part or all of the given event units : 1 comment : Value of 0 indicates Suspect DQRs do not exist for the given event flag_masks : [ 1 2 4 8 16 32 64 128 256 512 1024] flag_meanings : pwd_Suspect_dqr_exists aosmet_Suspect_dqr_exists disdrometer_Suspect_dqr_exists marinemet_Suspect_dqr_exists abmmet_Suspect_dqr_exists metwxt_Suspect_dqr_exists pws_Suspect_dqr_exists vdisquants_Suspect_dqr_exists ldquants_Suspect_dqr_exists wbpluvio2_Suspect_dqr_exists tbrg_Suspect_dqr_exists bit_1_description : pwd_Suspect_dqr_exists bit_2_description : aosmet_Suspect_dqr_exists bit_3_description : disdrometer_Suspect_dqr_exists bit_4_description : marinemet_Suspect_dqr_exists bit_5_description : abmmet_Suspect_dqr_exists bit_6_description : metwxt_Suspect_dqr_exists bit_7_description : pws_Suspect_dqr_exists bit_8_description : vdisquants_Suspect_dqr_exists bit_9_description : ldquants_Suspect_dqr_exists bit_10_description : wbpluvio2_Suspect_dqr_exists bit_11_description : tbrg_Suspect_dqr_exists \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
instrument_invalid_samples_flag
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : (Bitwise) instrument(s) with invalid sample(s) during the given event units : 1 comment : Value of 0 indicates all available instrument samples for the given event are within the valid range flag_masks : [ 1 2 4 8 16 32 64 128 256 512 1024] flag_meanings : invalid_pwd_samples invalid_aosmet_samples invalid_disdrometer_samples invalid_marinemet_samples invalid_abmmet_samples invalid_metwxt_samples invalid_pws_samples invalid_vdisquants_samples invalid_ldquants_samples invalid_wbpluvio2_samples invalid_tbrg_samples bit_1_description : invalid_pwd_samples bit_2_description : invalid_aosmet_samples bit_3_description : invalid_disdrometer_samples bit_4_description : invalid_marinemet_samples bit_5_description : invalid_abmmet_samples bit_6_description : invalid_metwxt_samples bit_7_description : invalid_pws_samples bit_8_description : invalid_vdisquants_samples bit_9_description : invalid_ldquants_samples bit_10_description : invalid_wbpluvio2_samples bit_11_description : invalid_tbrg_samples \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
instruments_included_per_event
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : (Bitwise) instrument(s) with valid samples throughout the given event units : 1 comment : Value of 0 indicates that there are no valid instrument events associated with the given event flag_masks : [ 1 2 4 8 16 32 64 128 256 512 1024] flag_meanings : valid_pwd_data valid_aosmet_data valid_disdrometer_data valid_marinemet_data valid_abmmet_data valid_metwxt_data valid_pws_data valid_vdisquants_data valid_ldquants_data valid_wbpluvio2_data valid_tbrg_data bit_1_description : valid_pwd_data bit_2_description : valid_aosmet_data bit_3_description : valid_disdrometer_data bit_4_description : valid_marinemet_data bit_5_description : valid_abmmet_data bit_6_description : valid_metwxt_data bit_7_description : valid_pws_data bit_8_description : valid_vdisquants_data bit_9_description : valid_ldquants_data bit_10_description : valid_wbpluvio2_data bit_11_description : valid_tbrg_data \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
min_instrument_for_event_period
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the min value of event period units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
min_instrument_for_event_mean_rate
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the min value of event mean rate units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
min_instrument_for_event_max_rate
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the min value of event max rate units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
min_instrument_for_event_total
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the min value of event total units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
max_instrument_for_event_period
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the max value of event period units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
max_instrument_for_event_mean_rate
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the max value of event mean rate units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
max_instrument_for_event_max_rate
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the max value of event max rate units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
max_instrument_for_event_total
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Instrument corresponding to the max value of event total units : 1 flag_values : [ 1 2 3 4 5 6 7 8 9 10 11] flag_meanings : pwd aosmet disdrometer marinemet abmmet metwxt pws vdisquants ldquants wbpluvio2 tbrg flag_1_description : pwd flag_2_description : aosmet flag_3_description : disdrometer flag_4_description : marinemet flag_5_description : abmmet flag_6_description : metwxt flag_7_description : pws flag_8_description : vdisquants flag_9_description : ldquants flag_10_description : wbpluvio2 flag_11_description : tbrg \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_period_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event period (instrument(s) min) units : min \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_period_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event period (instrument(s) max) units : min \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_period_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event period (instrument(s) standard deviation) units : min \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_start_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event start time offset from midnight (instrument(s) min) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_start_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event start time offset from midnight (instrument(s) max) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_start_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event start time offset from midnight (instrument(s) standard deviation) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_end_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event end time offset from midnight (instrument(s) min) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_end_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event end time offset from midnight (instrument(s) max) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_end_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event end time offset from midnight (instrument(s) standard deviation) units : s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_mean_rate_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event mean precipitation rate (instrument(s) min) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_mean_rate_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event mean precipitation rate (instrument(s) max) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_mean_rate_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event mean precipitation rate (instrument(s) standard deviation) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_max_rate_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event max precipitation rate (instrument(s) min) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_max_rate_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event max precipitation rate (instrument(s) max) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_max_rate_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event max precipitation rate (instrument(s) standard deviation) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_total_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event total accumulated (instrument(s) min) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_total_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event total accumulated (instrument(s) max) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_total_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event total accumulated (instrument(s) standard deviation) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_rate_std_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event precipitation rate standard deviation (instrument(s) min) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_rate_std_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event precipitation rate standard deviation (instrument(s) max) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
event_rate_std_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Event precipitation rate standard deviation (instrument(s) standard deviation) units : mm/hr \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
atmospheric_state_variables_source
(time)
float32
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Source (instrument or VAP) used for atmospheric state variables statistics units : 1 flag_values : [0 1 2 3 4] flag_meanings : no_data_available met maws aosmet metwxt flag_0_description : no_data_available flag_1_description : met flag_2_description : maws flag_3_description : aosmet flag_4_description : metwxt \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 44 B \n",
+ " 8 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float32 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
pres_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Atmospheric pressure (event mean) units : hPa \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
pres_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Atmospheric pressure (event min) units : hPa \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
pres_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Atmospheric pressure (event max) units : hPa \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
pres_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Atmospheric pressure (event standard deviation) units : hPa \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
temp_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Temperature (event mean) units : degC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
temp_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Temperature (event min) units : degC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
temp_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Temperature (event max) units : degC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
temp_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Temperature (event standard deviation) units : degC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
rh_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Relative humidity (event mean) units : % \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
rh_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Relative humidity (event min) units : % \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
rh_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Relative humidity (event max) units : % \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
rh_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Relative humidity (event standard deviation) units : % \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wspd_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind speed (event mean) units : m/s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wspd_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind speed (event min) units : m/s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wspd_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind speed (event max) units : m/s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wspd_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind speed (event standard deviation) units : m/s \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wdir_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind direction (event mean) units : degree \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wdir_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind direction (event min) units : degree \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wdir_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind direction (event max) units : degree \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
wdir_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Wind direction (event standard deviation) units : degree \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
low_temperature_flag
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Low temperature flag units : 1 input_variable_units : degC comment : Logical expressions: le - less equal; lt - less than; gt - greater than; ge - greater equal flag_values : [0 1 2] flag_meanings : no_flag 0.0_le_T_lt_3.0 T_lt_0.0 flag_0_description : no_flag flag_1_description : 0.0_le_T_lt_3.0 flag_2_description : T_lt_0.0 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
strong_wind_flag
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Strong wind flag units : 1 input_variable_units : m/s comment : Logical expressions: le - less equal; lt - less than; gt - greater than; ge - greater equal flag_values : [0 1 2] flag_meanings : no_flag 10.0_le_V_lt_15.0 V_ge_15.0 flag_0_description : no_flag flag_1_description : 10.0_le_V_lt_15.0 flag_2_description : V_ge_15.0 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
high_relative_humidity_flag
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : High relative humidity flag units : 1 input_variable_units : % comment : Logical expressions: le - less equal; lt - less than; gt - greater than; ge - greater equal flag_values : [0 1 2] flag_meanings : no_flag 95.0_le_RH_lt_99.0 RH_ge_99.0 flag_0_description : no_flag flag_1_description : 95.0_le_RH_lt_99.0 flag_2_description : RH_ge_99.0 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
drop_moment_variables_source
(time)
float32
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Source (instrument or VAP) used for drop moment variables statistics units : 1 flag_values : [0 1 2] flag_meanings : no_data_available vdisquants ldquants flag_0_description : no_data_available flag_1_description : vdisquants flag_2_description : ldquants \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 44 B \n",
+ " 8 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float32 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
reflectivity_factor_kaband20c_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Equivalent_reflectivity_factor (Ka-Band at 20 degC) (event mean) units : dB \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
reflectivity_factor_kaband20c_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Equivalent_reflectivity_factor (Ka-Band at 20 degC) (event min) units : dB \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
reflectivity_factor_kaband20c_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Equivalent_reflectivity_factor (Ka-Band at 20 degC) (event max) units : dB \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
reflectivity_factor_kaband20c_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Equivalent_reflectivity_factor (Ka-Band at 20 degC) (event standard deviation) units : dB \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
differential_reflectivity_kaband20c_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Estimated Differential Radar Reflectivity (H, V) from Drop Size Distribution (Ka-Band at 20 degC) (event mean) units : dBZ \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
differential_reflectivity_kaband20c_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Estimated Differential Radar Reflectivity (H, V) from Drop Size Distribution (Ka-Band at 20 degC) (event min) units : dBZ \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
differential_reflectivity_kaband20c_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Estimated Differential Radar Reflectivity (H, V) from Drop Size Distribution (Ka-Band at 20 degC) (event max) units : dBZ \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
differential_reflectivity_kaband20c_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Estimated Differential Radar Reflectivity (H, V) from Drop Size Distribution (Ka-Band at 20 degC) (event standard deviation) units : dBZ \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_differential_phase_kaband20c_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Differential Phase from Drop Size Distribution (Ka-Band at 20 degC) (event mean) units : degree/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_differential_phase_kaband20c_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Differential Phase from Drop Size Distribution (Ka-Band at 20 degC) (event min) units : degree/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_differential_phase_kaband20c_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Differential Phase from Drop Size Distribution (Ka-Band at 20 degC) (event max) units : degree/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_differential_phase_kaband20c_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Differential Phase from Drop Size Distribution (Ka-Band at 20 degC) (event standard deviation) units : degree/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_attenuation_kaband20c_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Attenuation (Ka-Band at 20 degC) (event mean) units : dB/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_attenuation_kaband20c_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Attenuation (Ka-Band at 20 degC) (event min) units : dB/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_attenuation_kaband20c_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Attenuation (Ka-Band at 20 degC) (event max) units : dB/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
specific_attenuation_kaband20c_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Specific Attenuation (Ka-Band at 20 degC) (event standard deviation) units : dB/km \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
mass_weighted_mean_diameter_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Mean Drop Diameter (event mean) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
mass_weighted_mean_diameter_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Mean Drop Diameter (event min) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
mass_weighted_mean_diameter_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Mean Drop Diameter (event max) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
mass_weighted_mean_diameter_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Mean Drop Diameter (event standard deviation) units : mm \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_shape_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Shape Parameter of Modeled Drop Gamma Size Distribution (event mean) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_shape_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Shape Parameter of Modeled Drop Gamma Size Distribution (event min) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_shape_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Shape Parameter of Modeled Drop Gamma Size Distribution (event max) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_shape_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Shape Parameter of Modeled Drop Gamma Size Distribution (event standard deviation) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_slope_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Slope Parameter of Modeled Drop Gamma Size Distribution (event mean) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_slope_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Slope Parameter of Modeled Drop Gamma Size Distribution (event min) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_slope_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Slope Parameter of Modeled Drop Gamma Size Distribution (event max) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
gammapsd_slope_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Slope Parameter of Modeled Drop Gamma Size Distribution (event standard deviation) units : 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
lwc_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Liquid Water Content (event mean) units : g/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
lwc_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Liquid Water Content (event min) units : g/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
lwc_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Liquid Water Content (event max) units : g/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
lwc_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Liquid Water Content (event standard deviation) units : g/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
total_droplet_concentration_mean
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Total Droplet Concentration (event mean) units : 1/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
total_droplet_concentration_min
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Total Droplet Concentration (event min) units : 1/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
total_droplet_concentration_max
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Total Droplet Concentration (event max) units : 1/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
total_droplet_concentration_std
(time)
float64
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Total Droplet Concentration (event standard deviation) units : 1/m^3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
time_offset
(time)
datetime64[ns]
dask.array<chunksize=(1,), meta=np.ndarray>
long_name : Time offset from base_time \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 88 B \n",
+ " 16 B \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (11,) \n",
+ " (2,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 19 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " datetime64[ns] numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 11 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
base_time
(time)
datetime64[ns]
2022-04-04 ... 2022-04-30
long_name : Base time in Epoch array(['2022-04-04T00:00:00.000000000', '2022-04-05T00:00:00.000000000',\n",
+ " '2022-04-05T00:00:00.000000000', '2022-04-11T00:00:00.000000000',\n",
+ " '2022-04-11T00:00:00.000000000', '2022-04-12T00:00:00.000000000',\n",
+ " '2022-04-14T00:00:00.000000000', '2022-04-24T00:00:00.000000000',\n",
+ " '2022-04-25T00:00:00.000000000', '2022-04-28T00:00:00.000000000',\n",
+ " '2022-04-30T00:00:00.000000000'], dtype='datetime64[ns]') lat
(time)
float64
29.67 29.67 29.67 ... 29.67 29.67
long_name : latitude units : degree_N array([29.67, 29.67, 29.67, 29.67, 29.67, 29.67, 29.67, 29.67, 29.67,\n",
+ " 29.67, 29.67]) lon
(time)
float64
-95.06 -95.06 ... -95.06 -95.06
long_name : longitude units : degree_E array([-95.059, -95.059, -95.059, -95.059, -95.059, -95.059, -95.059,\n",
+ " -95.059, -95.059, -95.059, -95.059]) alt
(time)
float64
8.0 8.0 8.0 8.0 ... 8.0 8.0 8.0 8.0
long_name : Altitude above mean sea level units : m array([8., 8., 8., 8., 8., 8., 8., 8., 8., 8., 8.])