Department for Aeronautical Meteorology Experimentations Vigna di Valle - ITALY

1. Department for Aeronautical Meteorology ExperimentationsVigna di Valle - ITALY The Italian Air-Force observation networks for the environmental and meteorological monitoring: from the Control to the Quality Assurance Maj. Fabio MALASPINA Cap.Francesco FOTI Mountains, witnesses of the global changes Rome November 16th 2005

2. Department for Aeronautical Meteorology ExperimentationsVigna di Valle - ITALY In the mouth of a volcano

3. SUBJECTS: Mountains, witnesses of the global changes Rome November 16th 2005 • Brief presentation about the Re.S.M.A.; • The Italian Air Force environmental and meteorological observation networks; • Which’s the purpose of the measures? • Which kind of information would we like to find in a measure? • Which kind of problems arise in measuring? • Important goal: from the data control to the process quality assurance; • Conclusions

4. Department for Aeronautical Meteorology ExperimentationsVigna di Valle - ITALY Mobile Meteo Unit Head Quarter Meteorological Station Experimental Area One century of meteorology on the Lake of Bracciano

5. It has been designated as Site for the World Rain Gauges Intercomparison promoted by the World Meteorology Organization and planned to develop in Vigna di Valle for two years from 2007. Mountains, witnesses of the global changes Rome November 16th 2005

6. SUBJECTS: Mountains, witnesses of the global changes Rome November 16th 2005 • Brief presentation about the Re.S.M.A.; • The Italian Air Force environmental and meteorological observation networks; • Which’s the purpose of the measures? • Which kind of information would we like to find in a measure? • Which kind of problems arise in measuring? • Important goal: from the data control to the process quality assurance; • Conclusions

7. OBSERVATION NETWORKS OF ITALIAN AIR-FORCE METEOROLOGICAL SERVICE • Men-Controlled Weather Stations: • Radiosounding n.6+1 • 24 h a day n.44 • Time reduction n.40 • Airport Stations n.28 • Isolated Stations n.56 • TOT. n.84 • Automatic Weather Stations (Data Collection Platform): • Installed n.73 • Ready to install n.30 • In maintenance n. 7 • TOT. n.110 Mountains, witnesses of the global changes Rome November 16th 2005

8. Antartic:CollabrationI.M.S. with Scientific Proget Responsible Andrea Pellegrini PNRA SCrl Operative Unit Responsible for meteorological data acquisition Paolo Grigioni ENEA CLIM-OSSExperimental Analysis and Observations Section • Paganella m.2129 • Cimone Mountain m.2165 • Plateu Rosà m.3480 Some Mountains Meteorological Stations of Italian Air Force

9. PRECIPITATION COLLECTION Special Stations OZONE SOLAR RADIATION SINCE 1975 SINCE 1957 SINCE 1958 Mountains, witnesses of the global changes Rome November 16th 2005

10. CARBON DIOXIDE TOTAL OZONE Start measurements: 1957 Start measurements: 1979 Instrument: Dobson Brewer Calibration: Every two years Instrument: No dissipation Infrared (NDIR) Calibration: Every three years, the last some days ago • Operative Stations: • Vigna di Valle • Messina • Sestola Operative Station: Monte Cimone m2165

11. SUBJECTS: Mountains, witnesses of the global changes Rome November 16th 2005 • Brief presentation about the Re.S.M.A.; • The Italian Air Force environmental and meteorological observation networks; • Which’s the purpose of the measures? • Which kind of information would we like to find in a measure? • Which kind of problems arise in measuring? • Important goal: from the data control to the process quality assurance; • Conclusions

12. Observation networks purpose is to produce qualitydata about some atmospheric parameters and to make available such data to the scientific community and not only. • The long historical series acquire more and more value with time passing and they constitute a national and humanity patrimony; • Every new measure modifies or creates new knowledge. Mountains, witnesses of the global changes Rome November 16th 2005

13. Two different monitoring networks for two different purposes: Mountains, witnesses of the global changes Rome November 16th 2005 • Global Pollution: not influenced “directly” from sources connected to the human activity and with a mainly climatological impact. Both special and meteorological measures must be carried out in stations situated far from polluting sources, measure of least quantity for long periods and in apparently uncontaminated areas like highMountains; http://www.empa.ch/gaw/gawsis/default.asp • Local Pollution:collected near to the polluting sources, in speaking of metropolises it is known as “Urban”. Its concentrations are higher, there is a short period impact (overcoming of threshold values) and its measure is mainly carried out for the guardianship of the human health; • GAW Urban Research Meteorology and Environment (GURME) programme

14. SUBJECTS: Mountains, witnesses of the global changes Rome November 16th 2005 • Brief presentation about the Re.S.M.A.; • The Italian Air Force environmental and meteorological observation networks; • Which’s the purpose of the measures? • Which kind of information would we like to find in a measure? • Which kind of problems arise in measuring? • Important goal: from the data control to the process quality assurance; • Conclusions

15. What kind of information would we like to find in a measure? Natural Phenomenon: What happens around us. We want to describe in the most complete way and to save it for present and future studies. Mountains, witnesses of the global changes Rome November 16th 2005 “Natural phenomena are written in this big book that it is always opened in front of our eyes …It is written in mathematical language, and the characters are triangles, circles, and other geometric figures… without these it is a vainly wandering for a dark labyrinth.” Galileo Galilei, Il Saggiatore (1623) We sometimes make measures only for mathematical model analysis

16. SUBJECTS: Mountains, witnesses of the global changes Rome November 16th 2005 • Brief presentation about the Re.S.M.A.; • The Italian Air Force environmental and meteorological observation networks; • Which’s the purpose of the measures? • Which kind of information would we like to find in a measure? • Which kind of problems arise in measuring? • Important goal: from the data control to the process quality assurance; • Conclusions

17. Machine cannot completely replace man From: “Guide to the expression of uncertainty in measurement” International Organization for Standardization 1993 Mountains, witnesses of the global changes Rome November 16th 2005 “Although this guide provides a framework for assessing uncertainty, it cannot substitute for critical thinking, intellectual honesty and professional skill.The evaluation of uncertainty is neither a routine task nor a purely mathematical one; it depends on detailed knowledge of the nature of the measurand and of the measurement. The quality and the utility of the uncertainty quoted for the result of the measurement therefore ultimately depend on the understanding, critical analysis, and integrity of those who contribute to the assignement of its value.”

18. Main problems of the observation networks which effect measures of long historical series Mountains, witnesses of the global changes Rome November 16th 2005 • Technological changes; • Measure of least quantity; • Necessity of personnel highly specialized - training; • Remote and uncomfortable site of measure; • High management costs; • Not homogeneous global network (instrumentation, calibrations, methods of measure, exposure). “I affirm that when you can measure and express in numbers what about you are speaking, you know indeed something” Lord Kelvin, 1824-1890

19. Technological changes: A thermometer screen intercomparison Mountains, witnesses of the global changes Rome November 16th 2005 Minimum Temperature Comparison among several thermometer screens. During a 24 h sampling, differences in temperature more than 1.5 °C have been found especially at the dawn and the sunset (A thermometer screen intercomparison – Jitze P. van der Meulen, Royal Netherlands Meteorological Institute)

20. Technological changes:“Radiosounding: possibile change in aerological data due to instrument change” Mountains, witnesses of the global changes Rome November 16th 2005 RS92 is the reference 1997 RS90 Eight launches, time sampling 2 s A systematic error of 0.2 °C has been found (known from Article Luers, problem of the RS90 solved in the RS92). (F.Malaspina, F.Foti, E.Vuerich and G.Casu – “Radiosounding: possible change in aerological data due to instrument change” – Il NUOVO CIMENTO volume 27C n.5, sett-ott 2004) 2003 RS92

21. For CLIMATE studies in particular, temperature measurements are affected by the state of the surrounding, by vegetation, by presence of buildings and other objects, by ground cover, by condition and changes in design of the radiation shield or screen, and by other changes in equipment. Temperature is one of the meteorological quantities whose measurement are particularly sensitive to exposure. (Guide 8 WMO-1996) X { It is important that should be kept not only the meteorological measurement values, but also the circumstances in which the measurements are made. Such information is known as metadata - data about data. H=1.25 ÷2m X snow

22. Measure of least quantity:simple item of the air temperature Mountains, witnesses of the global changes Rome November 16th 2005 Measurement System RESOLUTION=a quantitative expression of the ability of an indicating device to distinguish meaninfully between closely adjacent values of the quantity indicated, for display presentation tenth, hundredth,... Screen or shelter or shield Data Logger Sensor Accuracy ±0.08°C System ACCURACY= the closeness of the agreement between the result of measurement and the true value of the measurand.

23. “If a man will depart from certainties he will find himself at the end with doubts; if instead he will be satisfied with departing from doubts, it will reach certainties.” Francis Bacon (1561-1626) Mountains, witnesses of the global changes Rome November 16th 2005 }   instrumental error + Randon process generally non stationary with high accurancy Prob{T(to)= (to)±1.96 (to) }0.95 = 1.96 (to)  instrumental error

24. The statistic error has to be consistent with the precision with which the measures have been performed as also the average and standard deviation ACCURACY Measure of least quantity:simple item of the air temperature …. Data-elaboration must respect: Resolution  accuracy Example: the choice of the average meaningful digits must be consistent with the accuracy of the measuring system “The true problem for the climatologist to settle during the present century is not whether the climate has lately changed, but what our present climate is, what its well-defined features are, and how they can most clearly be expressed in numbers” Cleveland Abbe, 1889 – Chief scientist in the weather service of the Army Signal Office

25. An open sky laboratory The accumulations under the Stevenson Screen change the albedo

26. Remote and often uncomfortable site of measure Mountains, witnesses of the global changes Rome November 16th 2005 By Claudio Rafanelli Cnr- Isac, Rome

27. Remote and often uncomfortable site of measure Mountains, witnesses of the global changes Rome November 16th 2005 By Claudio Rafanelli Cnr- Isac, Rome

28. Remote and often uncomfortable site of measure Mountains, witnesses of the global changes Rome November 16th 2005 By Claudio Rafanelli Cnr- Isac, Rome

29. No homogeneity among instruments: UV-A radiation Mountains, witnesses of the global changes Rome November 16th 2005 Different spectral response for similar instruments produce very different results. (Rafanelli-CNR ISAC-Rome)

30. SUBJECTS: Mountains, witnesses of the global changes Rome November 16th 2005 • Brief presentation about the Re.S.M.A.; • The Italian Air Force environmental and meteorological observation networks; • Which’s the purpose of the measures? • Which kind of information would we like to find in a measure? • Which kind of problems arise in monitoring background pollution? • Important goal: from the data control to the process quality assurance; • Conclusions

31. “good quality data” not necessary excellent: Mountains, witnesses of the global changes Rome November 16th 2005 I want to be sure of the quality of your data Data are of good quality when they satisfies the requisite dictated by the purpose for which they have been produced. Data are not necessarily excellent, but it is essential that their quality is known and demostrable. Without a quality system, data must be regarded as being of uncertain or unknown quality, and their usefullness is diminished (Guide n.8 WMO 1996) Only the “well defined” information turns the uncertainty into Measurable Risk and can engrave in the decisional process.

32. What means “Quality Control”? It consists of examination of final data Quality Control is the best known component of quality management system, and it is the irreducible minimum of any system. It consists of examination of data in stations and in data centers to detect errors so that the data may be either corrected or deleted. (Guide n. 8 WMO- 1996) Measure method Variable of influence Operator ONE MEASURE: number, uncertainty, Measure unit Measure process Input Ouput Signals Measure equipment Measuring • MAIN PROBLEMS: • -Lost data irrecoverable and of no use cost, and control can be made after long time; • Generally the Statistical description of the past is not the probability evaluation of future(David Hume) we can exclude the most meaningful data; • -Data absence during a period makes not representative the historical series.

33. What means “Quality Assurance”? It consists of examination in the whole process The provision of good quality meteorological data is not a simple matter, and it is impossible without a quality management system. The best quality systems operate continuously at all point in the whole observation system, from network planning and training, through installation and station operations to data trasmission and archiving, and they include feed-back and follow-up provisions on time scales from near-real time to annual reviews. Variable of influence Measure method Operator Without a quality system, the data must be regarded as being of uncertain or unknown quality, and their usefullness is diminished (Guide n.8 WMO 1996) ONE MEASURE: number, uncertainty, Measure unit Measure process Input Ouput Signals Measure equipment Measuring

34. CONCLUSIONS:“Not all numbers are data” Mountains, witnesses of the globalchanges Rome November 16th 2005 • In climate studies it is important to know the circumstances in which the measurements are made (exposure, calibration, etc); • The main purpose of monitoring networks must be to describe natural phenomena in the most complete way; • Machine cannot completely replace man, the choice of the meaningful digits must be consistent with the uncertainity in measurement; • “Good quality data” need examination in the whole measurement process: quality is not a cost, but an investment; • Every new measure modifies or creates new knowledge, long historical series constitute an humanity patrimony.

35. THANK YOU “But, in order that the meteorological studies give a real advantage for the human consortium, it is not enough that many observatories are established on a vast extension of the country, and that in everyone of these the observations are made with intelligence and accuracy; it is required besides that everywhere it is observed and investigated with the same understanding and with the same equipments, which means with unity of method and with well compared instruments among them”. Father Francesco Denza, 1872- Italian Meteorological Society For further informations: Email: foti@meteoam.it , f.malaspina@meteoam.it