Dataset

Cape Bowling Green Automated Marine Weather And Oceanographic Station

Australian Institute of Marine Science
Australian Institute of Marine Science (AIMS)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://data.aims.gov.au/metadataviewer/faces/view.xhtml?uuid=5f30a190-4ade-11dc-8f56-00008a07204e&rft.title=Cape Bowling Green Automated Marine Weather And Oceanographic Station&rft.identifier=http://data.aims.gov.au/metadataviewer/faces/view.xhtml?uuid=5f30a190-4ade-11dc-8f56-00008a07204e&rft.publisher=Australian Institute of Marine Science (AIMS)&rft.description=This dataset contains meteorological data from the weather station located on Cape Bowling Green in North Queensland which has been collected since 31 July 1987. \n \n Historical records for the period 9-7-1983 to 4-10-1985 have been retrospectively added to the dataset from a former Cape Bowling Green outstation (at the same location) after conversion from the original Fortran files. Note that there is a break in this middle of this data series as the outstation source was moved to Cape Ferguson (AIMS Wharf) and collected data there for the period 1-11-1983 to 30-5-1984. These historic data were collected using telemetery to send binary data daily to a computer controlled base station. Data were verified by comparing three sets of the same data, received over three days. The base station passed data to the central computing facility at AIMS for processing. Lightning destroyed this system in 1985. \n \n Data recorded: Barometric Pressure, Air Temperature, Solar Radiation (PAR), Wind Direction True (vector averaged), Wind Speed True (30 min average).\n These data are collected to support scientific research at AIMS. Data are made available on request to other researchers and to the public.\n The current weather station is an AIMS Mk3 System. \n \n 1. Operation and Weather Sensors \n \n The weather stations collect and store data in electronic memory every half-hour. A central base station calls each remote station regularly using HF radio or telephone lines. The data is transmitted over the radio as a frequency shift keyed signal, organised as packets of information. Errors are detected using parity and check sum methods. Invalid packets are identified by the Base Station, which requests they be sent again. This concept allows recovery of a very high percentage of the data despite poor communications. Remote stations store data for 21 days. Features such as automatic operation, remote control, remote time setting, built in diagnostics, have been developed and incorporated. \n \n The sensors are a key part of a weather station. The following are chosen considering the cost, reliability and accuracy. \n * R.M.Young manufactures the wind sensor, a model number 05103. It is a propeller type with the advantages of being highly linear, highly interchangeable and having a low threshold. Wind direction is measured as the direction the wind is coming from. \n * The solar radiation sensor is an Under Water Quantum Sensor made by Licor. It measures light in terms of its Photosynthetically Active Radiation (PAR). The spectral response is defined and weighted. Drift due to aging of the filters has proven to be a problem, but this applies to similar units too. \n * Temperature sensors are all Omega Interchangeable Thermistors. These are interchangeable and have high accuracy, but reliability has proven a problem. We are considering alternatives. \n * The barometric sensor was a modified Aanderaa type on earlier stations. The Mk2 stations were fitted with a Weathertronics Unit. Now all stations are Mk3 stations fitted with a Vaisala barometer which is more interchangeable and more accurate. \n \n 2. System Accuracy \n \n System accuracy is calculated as the sum of errors caused by: \n * Calibration \n * Interchanging sensors \n * Drift with time \n * Effects of an ambient temperature range from 0-40 degrees C. \n \n The following are the specifications of the sensors used with Mk3 stations. A new sensor suite will be used with Mk5 stations, partly based on the Vaisala WXT510 weather sensor. \n \n Both the temperature and wind sensors are interchangeable, and not individually calibrated, though some individual sensors have been checked against standards. \n \n * Air Temperature: Interchangeable thermistor and electronics is within +/- 0.4 deg. C, with a 30 seconds settling time in air. There are additional errors due to the aspiration of the temperature screen at low wind speeds. \n * Solar radiation (PAR): +/- 5% of reading. Sensor drift is approximately -4% per year initially. \n * Barometric pressure: +/- 1 hecto Pascal. \n * Wind speed: 2% of reading +/- 0.1% FSD. \n * Wind direction: 2% of reading +/- 0.1% FSD. \n \n Electrical settling time for solar radiation and wind parameters is 7 seconds. This is necessary for anti-aliasing filters. Mk1 and Mk2 stations averaged 16 samples over the 16 seconds before logging. Mk3 stations use a continuously averaging software system. The wind readings are vector averaged, so direction is accounted for properly. \n \n Calibration procedures and routines are detailed on the Engineering website. \n \n 3. Wind Sensor Specification \n \n The following are additional specifications of the wind sensors used with Mk3 stations. A new sensor will be used with Mk5 stations. Wind sensors are mounted at a nominal 10 meters above water. \n \n The R.M. Young sensor has the following characteristics: \n * Wind Speed \n Range: 0-60 m/s \n Pitch: 29.4 cm air passes per rev. \n Distance constant: 2.7 m for 63% recovery \n * Wind Direction \n Range: 360 deg, with 5 deg electrically open at north \n Damping ratio: 0.25 \n Delay distance: 1.5 m for 50% recovery \n Threshold: 1.0 m/s @ 10 deg. \n Displacement: 1.5 m/s @ 5 deg. displacement \n Damped w/length: 7.4 m \n Undamped w/length: 7.2 m\n&rft.creator=Australian Institute of Marine Science (AIMS) &rft.date=2021&rft.relation=http://data.aims.gov.au/extpubs/do/viewPub.do?articleId=2205&rft.coverage=northlimit=-19.3; southlimit=-19.3; westlimit=147.4; eastLimit=147.4&rft.coverage=northlimit=-19.3; southlimit=-19.3; westlimit=147.4; eastLimit=147.4&rft_rights=Use Limitation: All AIMS data, products and services are provided as is and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.&rft_rights=Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: Australian Institute of Marine Science (AIMS). (2020). Northern Australia Automated Marine Weather and Oceanographic Stations, Sites: [Cape Bowling Green]. https://doi.org/10.25845/5c09bf93f315d, accessed[date-of-access].&rft_subject=oceans&rft.type=dataset&rft.language=English Access the data

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Use Limitation: All AIMS data, products and services are provided "as is" and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.

Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: "Australian Institute of Marine Science (AIMS). (2020). Northern Australia Automated Marine Weather and Oceanographic Stations, Sites: [Cape Bowling Green]. https://doi.org/10.25845/5c09bf93f315d, accessed[date-of-access]".

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Brief description

This dataset contains meteorological data from the weather station located on Cape Bowling Green in North Queensland which has been collected since 31 July 1987. \n \n Historical records for the period 9-7-1983 to 4-10-1985 have been retrospectively added to the dataset from a former Cape Bowling Green outstation (at the same location) after conversion from the original Fortran files. Note that there is a break in this middle of this data series as the outstation source was moved to Cape Ferguson (AIMS Wharf) and collected data there for the period 1-11-1983 to 30-5-1984. These historic data were collected using telemetery to send binary data daily to a computer controlled base station. Data were verified by comparing three sets of the same data, received over three days. The base station passed data to the central computing facility at AIMS for processing. Lightning destroyed this system in 1985. \n \n Data recorded: Barometric Pressure, Air Temperature, Solar Radiation (PAR), Wind Direction True (vector averaged), Wind Speed True (30 min average).\n These data are collected to support scientific research at AIMS. Data are made available on request to other researchers and to the public.\n The current weather station is an AIMS Mk3 System. \n \n 1. Operation and Weather Sensors \n \n The weather stations collect and store data in electronic memory every half-hour. A central base station calls each remote station regularly using HF radio or telephone lines. The data is transmitted over the radio as a frequency shift keyed signal, organised as packets of information. Errors are detected using parity and check sum methods. Invalid packets are identified by the Base Station, which requests they be sent again. This concept allows recovery of a very high percentage of the data despite poor communications. Remote stations store data for 21 days. Features such as automatic operation, remote control, remote time setting, built in diagnostics, have been developed and incorporated. \n \n The sensors are a key part of a weather station. The following are chosen considering the cost, reliability and accuracy. \n * R.M.Young manufactures the wind sensor, a model number 05103. It is a propeller type with the advantages of being highly linear, highly interchangeable and having a low threshold. Wind direction is measured as the direction the wind is coming from. \n * The solar radiation sensor is an Under Water Quantum Sensor made by Licor. It measures light in terms of its "Photosynthetically Active Radiation" (PAR). The spectral response is defined and weighted. Drift due to aging of the filters has proven to be a problem, but this applies to similar units too. \n * Temperature sensors are all Omega Interchangeable Thermistors. These are interchangeable and have high accuracy, but reliability has proven a problem. We are considering alternatives. \n * The barometric sensor was a modified Aanderaa type on earlier stations. The Mk2 stations were fitted with a Weathertronics Unit. Now all stations are Mk3 stations fitted with a Vaisala barometer which is more interchangeable and more accurate. \n \n 2. System Accuracy \n \n System accuracy is calculated as the sum of errors caused by: \n * Calibration \n * Interchanging sensors \n * Drift with time \n * Effects of an ambient temperature range from 0-40 degrees C. \n \n The following are the specifications of the sensors used with Mk3 stations. A new sensor suite will be used with Mk5 stations, partly based on the Vaisala WXT510 weather sensor. \n \n Both the temperature and wind sensors are interchangeable, and not individually calibrated, though some individual sensors have been checked against standards. \n \n * Air Temperature: Interchangeable thermistor and electronics is within +/- 0.4 deg. C, with a 30 seconds settling time in air. There are additional errors due to the aspiration of the temperature screen at low wind speeds. \n * Solar radiation (PAR): +/- 5% of reading. Sensor drift is approximately -4% per year initially. \n * Barometric pressure: +/- 1 hecto Pascal. \n * Wind speed: 2% of reading +/- 0.1% FSD. \n * Wind direction: 2% of reading +/- 0.1% FSD. \n \n Electrical settling time for solar radiation and wind parameters is 7 seconds. This is necessary for anti-aliasing filters. Mk1 and Mk2 stations averaged 16 samples over the 16 seconds before logging. Mk3 stations use a continuously averaging software system. The wind readings are vector averaged, so direction is accounted for properly. \n \n Calibration procedures and routines are detailed on the Engineering website. \n \n 3. Wind Sensor Specification \n \n The following are additional specifications of the wind sensors used with Mk3 stations. A new sensor will be used with Mk5 stations. Wind sensors are mounted at a nominal 10 meters above water. \n \n The R.M. Young sensor has the following characteristics: \n * Wind Speed \n Range: 0-60 m/s \n Pitch: 29.4 cm air passes per rev. \n Distance constant: 2.7 m for 63% recovery \n * Wind Direction \n Range: 360 deg, with 5 deg electrically open at north \n Damping ratio: 0.25 \n Delay distance: 1.5 m for 50% recovery \n Threshold: 1.0 m/s @ 10 deg. \n Displacement: 1.5 m/s @ 5 deg. displacement \n Damped w/length: 7.4 m \n Undamped w/length: 7.2 m\n

Notes

Bainbridge, Scott, Mr (Custodian)

Modified: 12 05 2021

This dataset is part of a larger collection

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147.4,-19.3

147.4,-19.3

text: northlimit=-19.3; southlimit=-19.3; westlimit=147.4; eastLimit=147.4

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Identifiers
  • Local : 5f30a190-4ade-11dc-8f56-00008a07204e
  • global : 5f30a190-4ade-11dc-8f56-00008a07204e