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Automation of National Observing System

Automation of National Observing System. RA VI Seminar on Capacity Building and New technologies in Meteorology: Challenges and Opportunities for the Balkan Countries Sofia, Bulgaria, 11-13 October 2001 Dr. Miroslav Ondráš, Dr. Igor Zahumenský. STRUCTURE (1). PART I Why automation?

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Automation of National Observing System

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  1. Automation of National Observing System RA VI Seminar on Capacity Building and New technologies in Meteorology: Challenges and Opportunities for the Balkan Countries Sofia, Bulgaria, 11-13 October 2001 Dr. Miroslav Ondráš, Dr. Igor Zahumenský

  2. STRUCTURE (1) PART I • Why automation? • Limitation and differences • Consequences of automation • Strategy of automation • Associated activities

  3. STRUCTURE (2) PART II • Basic requirements for aws • Basic functions of aws

  4. PART I • Why automation? • Limitation and differences • Consequences of automation • Strategy of automation • Associated activities

  5. WHY AUTOMATION ? (1) • Continuous increase of demands for regular, timely and on-line data with the increased time resolution is the main driving force for automation and restructuring of National Observing System. • Increased time resolution (10 min) becomes a basic requirement to cope with the severe weather forecasting and warnings.

  6. WHY AUTOMATION ? (2) • AWS may be configured to provide information for synoptic purposes as well as for aviation or climatological or other purposes. • AWS can work in different modes depending on user requirements, automatically switching between modes depending on weather.

  7. WHY AUTOMATION ? (3)Advantages (1) • The observation consistency (site-to-site and day-to-night); • Objective and uniform measurements; • High frequency of data provision; • Higher accuracy and quality of data; • Better timeliness and data availability; • More frequent special observations;

  8. WHY AUTOMATION ? (4)Advantages (2) • Higher density of observations available in real time; • Continuous measurement of the atmosphere (each minute up-to-date observations); • Data from AWS can be integrated more effectively with the data from other systems; • AWS’ data can be more effectively archived; • Lesser cost per data piece.

  9. LIMITATIONS & DIFFERENCES (1) • AWS does not provide a horizon-to-horizon evaluation of the weather, only of weather that has passed through the sampling volume of the sensor array (measurements made at a fixed location); • Some elements are difficult to automate; • Compatibility between AWS and observer outputs (visibility,clouds,present weather,etc) ; • AWS requires initial capital investment.

  10. LIMITATIONS & DIFFERENCES (2) AWS and observer differ in their methods of sampling and processing the various weather elements: • A human observer estimates weather phenomena at a fixed location by integrating in space. • An automatic system estimates weather phenomena at a fixed location by integrating in time.

  11. LIMITATIONS & DIFFERENCES (3) • AWS applies procedures and algorithms to the collected data in order to extrapolate the weather over a wider area. • AWS provides objective and consistent information while human observations show significant subjectivity and uncertainty.

  12. AWS Fixed location (time-averaged); Representation for 3-5km of sensor site; Continuous observation; Consistent observation; Report everything detected by sensors. HUMAN Fixed time (spatial-averaged); Representation horizon-to-horizon; Time constraints; Affected by lights, building, human perception; Intelligent filtering. LIMITATIONS & DIFFERENCES (4)

  13. CONSEQUENCES OF AUTOMATION Automation: • Introduces more technological complexity to the observation process; • Influences all phases of data flow (measurement-transmission-processing-archiving); • Introduces data inhomogeneity (comparing to old data series); • Influences maintenance system (replaces observers by technicians for maintenance); • Requires refreshment courses at all levels.

  14. STRATEGY OF AUTOMATION (1) • Automation should be seen as a tool to build integrated NOS that fits well in the regional and world-wide composite observing system. • Automation should be done very carefully with respect to present and future limitations and contradictory tendencies (e.g., requirement for conservative approach from Climatology).

  15. STRATEGY OF AUTOMATION (2) • Start with the combination of automatic and semi-automatic stations. • Design your AWS to be effective and multipurpose (serving for weather, hydrology and environment monitoring).

  16. STRATEGY OF AUTOMATION (3) • Implement only those AWSs, which are sufficiently well documented so as to provide adequate knowledge and understanding of their capabilities, characteristics and any procedures and algorithms used.

  17. STRATEGY OF AUTOMATION (4) • Before full implementation of automation thorough analysis of the functionality and comparison of AWS’ data with manual measurements is required (1 to 2 years of comparison measurements is necessary). • Before full implementation address the differences in instrumentation type, measurement methods, data processing, data control, calibration and maintenance of both types of monitoring networks.

  18. ASSOCIATED ACTIVITIES (1)Monitoring • Detailed performance monitoring of the functionality of the whole system is a precondition of the successful automated weather monitoring network; • It should allow for prompt remedial actions (pulling the data from AWS, filling the gaps, correction of errors); • It should go deep enough into the AWS so that long-term drift of sensors can be detected.

  19. ASSOCIATED ACTIVITIES (2) Calibration To guarantee data quality and validity there is a need to enhance all levels: • Initial calibration • Field calibration • Laboratory calibration It involves comparison against a known standard to determine how closely instrument output matches the standard over the expected range of operation.

  20. ASSOCIATED ACTIVITIES (3)MAINTENANCE • Preventive (cleaning); • Corrective (AWS component failures); • Adaptive (changed requirements or obsolescence of components); Part of a broader performance monitoring: • To ensure rapid response time for periodic transmission of self-checking diagnostic information by the AWS is needed.

  21. ASSOCIATED ACTIVITIES (4)Documentation In addition to standard documentation, such as: • Documentation of initial siting of the system, sensors (maps, photographs); • Ongoing documentation of equipment and siting (metadata) and all changes; • Metadata showing changes in the station’s immediate surroundings or sensors; Documentation of the procedures and algorithms used and all changes to them.

  22. ASSOCIATED ACTIVITIES (5)Training • System performance, system reliability and consequently data quality and availability depend on the skills of the staff. • There is a need for training at all levels of staff not only employed in the observing network divisions.

  23. PART II • Basic requirements for aws • Basic functions of aws

  24. BASIC REQUIREMENTS FOR AWS (1) Should be considered from the point of view: • User data requirements (forecasting & warning system, aviation, climatology, etc.). Present and future: • Observing system design; • Data processing system capability; • Data management system capability; • Telecommunication system capability.

  25. BASIC REQUIREMENTS FOR AWS (2)Siting and Exposure (1) Standard observing site: • On a level piece of ground, covered with short grass or surface representative of the locality. • Meteorological sensors should be sited at a distance which is beyond the influence of obstructions such as buildings and trees (distance depends upon the variable as well as the type of obstruction).

  26. BASIC REQUIREMENTS FOR AWS (3)Siting and Exposure (2) Standard observing site: • Sensors are should be positioned at the same height (and place) to those of classic instruments, • Keep the long-term “stability” of exposure of the site (changing of vegetation, buildings, etc.)

  27. BASIC REQUIREMENTS FOR AWS (4)Siting and Exposure (3) Temperature & Humidity sensor: • Inside a suitable instrument shelter or shield at height of 1.25 to 2.0 m preferred (ventilated or non-ventilated). • Different types and shapes and colors of shields give different results of measurement. • For data comparison and compatibility could be installed in classic Stevenson screen.

  28. BASIC REQUIREMENTS FOR AWS (5)Siting and Exposure (4) Rainfall measurement: • Very open sites which are satisfactory for most instruments are unsuitable for raingauges (need for some degree of shelter or artificial shield). • At 1 m above ground gives different result from measurement made at 3 m or 30 cm height above the ground or inside a pit;

  29. BASIC REQUIREMENTS FOR AWS (6)Siting and Exposure (5) Wind measurement: • Standard exposure is at a height of 10 m above flat ground in the open terrain (distance from obstructions be a minimum of 10 times the height of obstruction); • Wind speed measured at lower height is significantly less than speed measured at 10 m above ground. • Need for another observation point.

  30. BASIC REQUIREMENTS FOR AWS (7)Sensors (1) Care should be taken so that sensors correspond to the user requirements: • Measuring range; • Data representation; • Data compatibility; • Accuracy; • Reliability; • Long term stability.

  31. BASIC REQUIREMENTS FOR AWS (8)Sensors (2) Measuring range: • Depends mainly on climatological conditions where AWS will be installed: • E.g. different requirements concerning temperature measurement and range should be considered in case of Tropic and High latitude or Polar regions. • Depends also on user requirements: • E.g. measurement range of ceilometer CT25K is 0-25.000ft whereas of CT12K is 0-12,500ft only.

  32. BASIC REQUIREMENTS FOR AWS (9)Sensors (3) Data representation: • A meteorological observation is intended to be representative of an area in accordance with its application. • For synoptic purposes, it should be representative of a wide area around the station. • For aviation, it should be representative for the areas of runways, landing and take-off. • For agrometeorological purposes - crop field...

  33. BASIC REQUIREMENTS FOR AWS (10)Sensors (4) Data compatibility: • In order to achieve data compatibility when using different types of sensors, shielding and different exposure of sensor for measuring the same variable, corrections to the actual measurements are necessary. • E.g. in case of measuring precipitation or wind speed in different heights above the ground.

  34. BASIC REQUIREMENTS FOR AWS (11)Sensors (5) Accuracy: • The closeness of the agreement between the result of a measurement and a true value of the measurand. • There are different operational accuracy requirements depending on applications as well as different achievable accuracy for individual variables. • E.g. Height of cloud: required accuracy is 10 % for height > 100 m, achievable accuracy (using CT25K) is 50 ft for the whole range of measurement.

  35. BASIC REQUIREMENTS FOR AWS (12)Sensors (6) Reliability: • It refers to the reproducibility of a measurement. One can quantify reliability simply by taking several measurements on the same subject. • Poor reliability degrades the precision of a single measurement and reduces your ability to track changes in measurements. • Frequent replacement of unreliable instruments increases significantly the total cost of measurement corresponding variable and decreases quality of measurement.

  36. BASIC REQUIREMENTS FOR AWS (13)Sensors (7) Long term stability: • The ability to keep its known accuracy of measurement over a long period and can be expressed by drift (the stability of the sensor's calibration with time). • Good stability means lower calibration costs, saves time and trouble.

  37. BASIC REQUIREMENTS FOR AWS (14) Sensor characteristics (1) Fundamental characteristics of sensors (to ensure accuracy and precision of measurement) are: • Resolution; • Repeatability; • Linearity; • Response time; • Drift; • Hysteresis.

  38. BASIC REQUIREMENTS FOR AWS (15) Sensor characteristics (2) Resolution: • It is the smallest change the device can detect. • It is a quantitative expression of the ability of an indicating device to distinguish meaningfully between closely adjacent values of the quantity indicated.

  39. BASIC REQUIREMENTS FOR AWS (16) Sensor characteristics (3) Repeatability: • It is the ability of the sensor to measure a variable more than once and produce the same result in identical circumstances. Linearity: • Defines the deviation of the sensor from ideal straight line behavior.

  40. BASIC REQUIREMENTS FOR AWS (17) Sensor characteristics (4) Response time: • Normally defined as the time the sensor takes to measure 63% of the change. • The time interval between the instant when a stimulus is subjected to a specified abrupt change and the instant when the response reaches and remains within specified limits around its final steady value.

  41. BASIC REQUIREMENTS FOR AWS (18) Sensor characteristics (5) Drift: • It is the stability of the sensor’s calibration with time. Hysteresis: • It is the ability of the sensor to produce the same measurement whether the phenomenon is increasing or decreasing.

  42. BASIC REQUIREMENTS FOR AWS (19) Sensor characteristics (6) • Some of above mentioned characteristics are more important in particular situations than others. • For example: • for monitoring climatic temperature changes a sensor is required which has very little drift, • for measuring wind gusts the repeatability of the device and the response time become more important.

  43. BASIC FUNCTIONS OF AWS (1) • Data acquisition and (pre)processing; • Data check and quality control; • Data formats and messages; • Data transmission; • Data storage.

  44. BASIC FUNCTIONS OF AWS (2)Data acquisition and processing (1) Among others: • Sampling of sensor output; • Conversion of sensor output; • Linearization; • Smoothing and Averaging; • Corrections; • Derived data computation.

  45. BASIC FUNCTIONS OF AWS (3)Data acquisition and processing (2) Sampling (scanning) of sensor output: • A sample – a single measurement, typically one of a series of spot readings of a sensor system (an observation is derived from a number of samples). • Different sampling frequency is used: • for temperature (5-6 times a minute), • for wind gust (every 3 seconds), etc..

  46. BASIC FUNCTIONS OF AWS (4)Data acquisition and processing (3) Conversion of sensor output: • It is the transformation of the electrical output values of sensors into meteorological units.

  47. BASIC FUNCTIONS OF AWS (5)Data acquisition and processing (4) Linearization: • If the transducer output is not exactly proportional to the quantity being measured, then the signal must be linearized, making use of the instrument’s calibration.

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