John Nash Upper Air Technology Centre Met Office , UK

1. Expert team on Upper Air Systems Comparison, Agenda item 3.1 Introduction to performance of modern radiosondes based on WMO Radiosonde Comparison results, Temperature John Nash Upper Air Technology Centre Met Office , UK

2. Progress in radiosondes • Since the mid 1990’s, there have been a major changes in the technology applied to radiosonde design and production by European manufacturers. Next generation European radiosondes will be built using types of electronics and production techniques implemented in mobile phones. • This progress with modern radiosondes has led to a bigger gap in performance compared to the national radiosonde that have not really been modernised yet, i.e. those in China and India, and to some extent Russia. • The changes have been partly driven by the development of GPSradiosondes which require much more processing power on the radiosonde than was ever feasible before. The radiosondes will have more working Memory than the Met Office ground system in 1989.

3. Modern GPS radiosonde with narrow bandwidth , stable frequency, frequency tuneable before flight

4. One type of radiosonde(China) used widely in a national network for many years, but now being replaced , sample from 1989

5. Test procedures • The results shown in the following slides are derived from WMO Comparison tests or tests of an equivalent standard • Test1(UK) 1984,2(USA) 1985, 3(KAZAKH) 1989, PREF(UK)1992, 4 (JAPAN01993, RH95(USA) 1995, BRAZ GPS (BRAZIL) 2001 • In these tests from 3 to 6 radiosondes were flown together suspended from one balloon. An individual data set will include a minimum of 15 successful test flights and some will have more than twenty flights at a given time of day. • Vaisala(Finland) and Sippican (VIZ, USA) radiosonde participated in all tests and are used to link the results together.

6. Test procedures • Comparisons between radiosondes are based on simultaneous samples of temperature and pressure/height. Thus, differences in the temperature sensors are examined independent of the differences between the radiosondes introduced by pressure/height differences. • Temperatures at night are referenced to the measurements from 3 thermistor radiosondes (available in PREF, and Phase 4) and the equivalent references derived from the link radiosondes ( e.g. the UK MK3 links Phase I to PREF, RS80 + Sippican links Phase 4 to RH95 and BRAZ) • Linking daytime to night time measurements cannot be achieved so accurately, so daytime performance was directly measured against 3 thermistor in PREF and Phase 4, and the other tests are linked by examining day-night differences to indicate the most plausible daytime estimate.

7. Results on accuracy of best radiosonde temperature measurements • Accuracy depends on temperature sensor error and also the error in the height(pressure) assigned to the temperature • Temperature sensor errors are smaller at night, as long as sensor coating has low emissivity in the infrared (e.g. Vaisala RS80 , RS90, RS92) • Solar heating introduces significant systematic errors, difficult to correct, at pressures lower than 100 hPa • Random errors in temperature are less than 0.2 K at night and less than 0.3 K in daytime in the troposphere and lower stratosphere

8. Results from WMO Radiosonde Comparison demonstrating the range of systematic errors in RS80 temperature sensor from 1984 to 2003 NIGHT Increase in error with height result of wrong software correction at low pressures used extensively 1985-??? Around 1989-91, one of the two calibration facilities was faulty in the factory giving an additional positive offset at low temperatures for some batches of radiosondes Software correction at low pressures much smaller in recent software, 1995- 2003 [ Met Office systems , 1990 -2003]

9. NIGHT Effect of typical height error of RS80 on reported temperature over UK This shows the typical ranges of measurement errors to be found with recent Vaisala radiosonde systems at night

10. Effect of cloud on a daytime temperature measurement • The next slide shows a detailed comparison from a PREFRS flight through thick medium and upper cloud, using the average of two three thermistor radiosonde measurements as the reference ( These should be accurate to better than  0.2 °C at these heights ) • The Vaisala RS80 ground system has a software correction to compensate solar heating, based on normal conditions. In this flight the backscattering above the cloud is much higher than usual and the software correction was too small by about 0.6 °C

11. RS80 temperature correction at 200 hPa is -0.6 deg C but is too low given the high solar albedo of this thick cloud Infrared cooling of VIZ and AIR white rod thermistors increases to a larger extent than solar heating increases on emerging from the cloud, Reference is average of measurements from VIZ and AIR 3 thermistor radiosondes , PREFRS 1992

12. Results from WMO Radiosonde Comparison in the day .The most reliable estimates are for Phase 4 and PREFRS, with the large difference between the two the result of the correction algorithm not representing two very different conditions. DAY Phase 4 Low albedo over open sea PREFRS, High albedo over thick cirrus

13. White rod thermistors • White rod thermistors manufactured by VIZ Manufacturing Co in the USA ( later taken over to become Sippican, Inc) were used widely throughout the world on many radiosonde types • In each of the WMO Comparisons there were usually two systems using these sensors, so the results obtained should have been comparable in accuracy with the Vaisala RS80 results. • Errors from these sensors are large at night because although the sensors were white in the visible the sensors were effectively black in the infrared. • In the UK stratospheric temperatures change considerably with season, so this gave the chance to demonstrate that the infrared errors errors were not stable, but depended on how far ambient temperature was from radiative equilibrium at the given height.

14. Temperature indicated by white rod thermistor at this level is about 0.4°C lower than with no cloud NIGHT T= -65 °C Cloud layer T= -30 °C

15. Results from WMO Radiosonde Comparison show the errors in US white rod thermistors at night are influenced by infrared radiation and are less consistent than for Vaisala radiosondes NIGHT

16. IR errors at 10 hPa depend on atmospheric temperature and vary with cloud cover, surface temperature,etc . At very low temperatures the infrared exchange produces a positive bias in temperature. Data are for flights with low cloud amount. 10 hPa, NIGHT Radiative equilibrium at -66 °C

17. The range of errors at 32 hPa is not as large at 10 hPa, with the stratosphere over the UK rarely warm enough to give large negative temperature errors. Errors have been estimated from days with low cloud amount. 32 hPa, NIGHT Radiative equilibrium at -62 °C

18. The range of errors at 200 hPa is relatively low, on days with low cloud amount. 200 hPa, NIGHT Radiative equilibrium at -56 °C, on average

19. The errors in US rod thermistors introduced during the day [not usually corrected].PREFRS and Phase 4 results were the most reliable. DAY PREFRS, High albedo over thick cirrus Phase 4 Low albedo over open sea

20. Results from other radiosondes at night [1]. All these radiosondes show signs of infrared cooling at night , either from a white sensor or the black coating on the inside of protective ducts apart from the RS2-91 (Japan) . NIGHT

21. Results from other radiosondes at night [2]. Indian and Russian radiosondes have some infrared cooling, but the support wires to the sensor are unpainted and relatively thick. So, the infrared error on the sensor is compensated by thermal conduction from the uncoated wires . UKRS3, new Sippican and RS90 have very small infrared errors NIGHT

22. Conclusions • Results from WMO Comparisons can be expected to represent operational results at night for radiosondes where temperature sensors are insensitive to infrared radiation errors. • Linking daytime measurements is more difficult. Hence the reason to reduce susceptibility to daytime heating in next generation radiosonde designs. • The other limitation on relating temperature comparisons to operational data is is where pressure errors are significant . Changes in performance of pressure sensors are poorly documented in many countries.