1. New developments and operational experience with surface observation technology and national networks Jitze P. van der Meulen, Royal Netherlands Meteorological Institute TECO 2006

2. 2006-12-04TECO-20062 Historic Background 1643: Evangelista Torricelli discovers vacuum invents mercury barometer and suggested   p  1645:René Descartes suggests p = p ( h )  1650: Blaise Pascal and Robert Boyle, by experiment:   p & p = p ( h ), using a mercury barometer All using calculus: hydrostatics & mathematics

3. 2006-12-04TECO-20063 Historic Background 1802: Alexander von Humboldt, explorer to discover environmental phenomena: t = t ( h ), later on with Joseph-Louis Gay-Lussac < 1850: phenomenological studies with a deterministic approach, e.g. networks to measuring the intensity of Earth's magnetic field > 1850: use of mathematics comes up and experiments produce quantitative data to prove any theory by calculus Discovery of phenomena (qualitative), later on mathematics (quantitative)

4. 2006-12-04TECO-20064 Historic Background > 1835: networks to measure the geological behavior of the earth electromagnetic field in combination with barometers and themometers, to discover any correlation Measurements of the variable behaviour of atmospheric pressure : a relation with wind (speed and direction) was discovered Tendency of pressure useful to forecast weather ( still popular today at home ) Geospatial relationship of pressure gradients and the behaviour of wind Discovery of phenomena

5. 2006-12-04TECO-20065 Historic Background > 1845: introduction of Telegraphy, providing in "near real time“ and synoptic surface observations to be plotted in synoptic charts (a ‘nearly instantaneous picture of the state of the atmosphere’)  1900: postulation that hydrostatic formulas could be used to describe the current state of the atmosphere and for forecasts (‘calculating the weather’) > 1945 introduction of operational upper air measurements and NWP Use of geophysical data in weather charts, calculus requires “infinite amount” of arithmetics

6. 2006-12-04TECO-20066 Historic Background

7. 2006-12-04TECO-20067 Historic Background Today: Both science and operational services (meteorology, climatology, etc. ) are oriented on both – discovery of weather phenomena (the classic deterministic approach), and on – thermodynamics with plenty of mathematics (used in NWP & NCP models). This statement not only holds for in situ measurements but also for remote sensing and especially for observations from satellites (Earth Observation).

8. 2006-12-04TECO-20068 Systems development and functional requirements functional specifications of networks and weather stations have a complex background A network should provide – present weather information expressed in pre- defined parameters, like type-of-cloud, special phenomena, type-of-precipitation, icing – numerical data, i.e. quantitative physical variables Complex? Simple compared to the present needs of the multiform disciplines in meteorology and the available technologies of observation, both in situ and remotely sensed

9. 2006-12-04TECO-20069 Systems development and functional requirements Development of observing systems, in particular those systems based on satellite born remote sensing ('discovery' entity, but also producing quantities) Geospatial differences in network densities Differences in representativety (area averaged vs. point measurements) Differences in observation times and frequency in situsatellite

10. 2006-12-04TECO-200610 Systems development and functional requirements Development of observing systems, in particular those systems based on satellite born remote sensing ('discovery' entity, but also producing quantities) Geospatial differences in network densities Representativety (area averaged vs. point measurements) wind derived from the ERS-2 scatterometer, south- east of Greenland, 2006-10-15 21:30 UTC

11. 2006-12-04TECO-200611 Systems development and functional requirements The various disciplines in meteorology, climatology, hydrology, etc. expressed an increasing demand on observational data and with discipline specific conditions. Alternative or new observations, performance, representativety and frequency of observations. Complete automation (of subjective observations, present weather, phenomena), modern AWS Strong increasing diversity in both the users' requirements and in observation technology

12. 2006-12-04TECO-200612 Systems development and functional requirements Cl ¿ ¿ ¿ INFO USER INFO ¿ ¿ ¿ Ag Hy Ae Ma AS Sy ¿ SOURCE #1 SOURCE #2 SOURCE #3 SOURCE #N SOURCE #N-1 OBSERVATIONS [Sy] Synoptical Meteorology, [Cl] Climatology, [Hy] Hydrology, [Ag] Agro-meteorology, [Ae] Aeronautical meteorology, [Ma] Marine meteorology, [AS] Sciences of the atmosphere.

13. 2006-12-04TECO-200613 Cl ¿ ¿ ¿ INFO Observations systems USER INFO ¿ ¿ ¿ Ag Hy Ae Ma AS Sy ¿ SOURCE #1 SOURCE #2 SOURCE #3 SOURCE #N SOURCE #N-1 database oriented information generators Systems development and functional requirements

14. 2006-12-04TECO-200614 Systems development and functional requirements Defining functional specifications of physical variables to be measured is relatively straightforward: measurement uncertainty can be expressed quantitatively and references are clearly defined. To specify quality figures for reporting weather events, atmospheric conditions or qualitative descriptions (the assessment of the state and development of the atmosphere, and of significant weather) is complicated and affected by subjectivity: E.g., s hall we use performance indicators like  Skill scores  Success rates  False alarms rate, or  A mixture of these?

15. 2006-12-04TECO-200615 Systems development and functional requirements A contingency matrix is most applicable, but how to interpret? detector yesno realityyesab nocd Probability of Detection: a / (a + b) False Alarm Ratio: c / (a + c) Equitable Skill Score: a / (a + b) – c / (c + d) BIAS = (a + b) / (a + c) [should be 1] Event?

16. 2006-12-04TECO-200616 Performance indicators detector yesno realityyes 15%5% no 5%80% POD = 75% FAR = 25% ESS = 69% BIAS = 1 ‘overall score’ ? range ?: e.g. ‘icing’ most relevant: ‑ 2°C < T < +2°C

17. 2006-12-04TECO-200617 Systems development and functional requirements New challenge: observations in combination with a high resolution model:  using the actual NWP grid-point data as background ( e.g. 11 km grid)  Using a detailed orographic database (relief map)  Climate data for further fine-tuning + knowledge of atmospheric behavior in land- water transitions Now-casting technique with ‘downscaling’ capabilities 50 km Virtual reality ?

18. 2006-12-04TECO-200618 Systems development and functional requirements Methods of observing Present Weather, also virtual reality? Determination based on empirical relations Direct and indirect phenomenological en physical relationships are applied Climate data as filter tool Algorithms, tuned for optimal performance

19. 2006-12-04TECO-200619 Systems development and functional requirements Methods of observing Present Weather, also virtual reality? Examples: Undercooled precipitation using wet & dry bulb temperature Hail detection from doppler weather radars Precipitation determination based on optical characteristics of the hydrometeors in combination with air temperature

20. 2006-12-04TECO-200620 Systems development and functional requirements Methods of observing Present Weather, also virtual reality? Data from the true world is not available, so validation is a hazardous task How to calibrate? What is a reliable reference? Algorithms are not well documented and published A quality standard for such determination is missing (may be in line with ISO 17025)

21. 2006-12-04TECO-200621 Development and new design of instruments Clustering of sensors/instruments, e.g. on one single statue discarding the mutual impacts

22. 2006-12-04TECO-200622 Development and new design of instruments Clustering of sensors/instruments, e.g. on one single statue discarding the mutual impacts Micro-sized systems with 'multi-sensors on a single chip' wind sensor

23. 2006-12-04TECO-200623 Development and new design of instruments Clustering of sensors/instruments, e.g. on one single statue discarding the mutual impacts Micro-sized systems with 'multi-sensors on a single chip' Pressure sensor

24. 2006-12-04TECO-200624 Development and new design of instruments Clustering of sensors/instruments, e.g. on one single statue discarding the mutual impacts Micro-sized systems with 'multi-sensors on a single chip' Introduction of ‘ alternative ’ techniques holograms monostatic radar: drop size distribution ‘Hotplate snowgauge’Acoustic detector

25. 2006-12-04TECO-200625 Trends and criteria for further development, a conclusion Ongoing development of new methods of observation and measurement devices Satellite born remote sensing techniques to observe the surface of the whole earth Ongoing automation of weather stations, automation of observing the weather All kind of observations to be converted into geo- physical quantities Determination of weather parameters based on phenomenological assumptions

26. 2006-12-04TECO-200626 Trends and criteria for further development, a conclusion Priority on efficiency and cost reduction Observation systems and networks will be further optimized; wish to integrate observing systems; surface variables determined from in situ (surface) and remote sensing (satellites) data Automation of subjective observations to be standardized or at least well documented in open literature; requirements on skill scores Focus on specific, dangerous weather events, and on methods of observations to improve the performance of NWP

27. 2006-12-04TECO-200627 Thank you