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Developments in Radar Refractivity Retrieval

Developments in Radar Refractivity Retrieval. John Nicol 1 , Anthony Illingworth 1 , Kim Bartholomew 1 , Tim Darlington 2 Malcolm Kitchen 2 , Jon Eastment 3 and Owain Davies 3 1 University of Reading 2 UK Met Office 3 Chilbolton Observatory, RAL.

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Developments in Radar Refractivity Retrieval

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  1. Developments in Radar Refractivity Retrieval John Nicol1, Anthony Illingworth1, Kim Bartholomew1, Tim Darlington2 Malcolm Kitchen2, Jon Eastment3 and Owain Davies3 1 University of Reading 2 UK Met Office 3 Chilbolton Observatory, RAL Joint 8th COPS Workshop and CSIP Meeting 2009 26th-28th October 2009, Madingley Hall, Cambridge, UK.

  2. Radar Refractivity RetrievalBackground • A technique to derive maps of refractive index changes from radar data was first demonstrated using an S-band (10 cm) weather radar in Fabry et. al. (1997) • For stationary targets (ground clutter), phase changes are typically dominated by changes in the refractive index (n) of the air near the surface • Refractivity N=(n-1)106 • Refractivity changes (N) are proportional to the phase change gradient with respect to range Motivation • Refractivity changes are very closely linked to changes in humidity • Changes in the spatial distribution of near-surface water vapour are not currently well-observed by other means • Near-surface fields of refractivity (humidity) changes may benefit QPE and Nowcasting through data assimilation in Numerical Weather Prediction models

  3. First application of radar refractivity in the UKACROBAT – Chilbolton CSIP L-band wavelength (23cm) Designed for detecting weak meteorological echoes (Bragg scatter) Coded pulse  greater sensitivity for low-power radars  range artefacts from intense returns Radar refractivity estimates were good at times, though often inaccurate when changes were large… CSIP IOP 8, 13/07/2005 Sea-breeze passes Chilbolton after 15:00 RH increases 10% across sea-breeze front

  4. The Operational Weather Radar Network in the UK Magnetron transmitters • prone to frequency drift (due to ambient temperature changes in the receiver cabin) measure transmitted frequency in real-time  C-band wavelength (5 cm) • phase changes are more sensitive to target motion at shorter wavelengths Digital terrain model x x • Testing and development of radar refractivity retrieval at Cobbacombe, Devon • Quantitative evaluation using synoptic station measurements, N(T,P,e)

  5. Application (deriving hourly refractivity changes) 1. Identify stationary targets Target motion affects the phase during the measurement process Phase Quality Indicator (PQI) is recorded for every ray (≈ 44 pulses/deg.) at each range gate • Identify correlated range-gates Independent range-gates → refractivity changes  Highly-correlated range-gates → transmitted frequency changes  Magnetron transmitters (Nfreq = -fT/fT .10-6) Klystron transmitters (Nfreq = 0) Incoherent signal power Total signal power PQI = Optimum threshold ≈ -5 dB  dBZ

  6. Application cont. (deriving hourly refractivity changes) 3. Correct local oscillator frequency changes (e.g. STALO frequency changes) Local oscillator frequency changes cause a range dependent phase change ( = 4fLOd/c) 4. Smooth phase change field Smoothing function Inverse-distance squared with base length = 1.5km (range) x 4 km (azimuth) 5. Calculate the phase change gradient w.r.t. range for all target pairs local mean → refractivity change local std. dev. → error estimate N N

  7. Comparison of hourly refractivity changes with synoptic station obs. March 2008 June 2008 correlation 0.60 slope 0.63 correlation 0.51 slope 0.48 Synoptic stations show greater variability (‘point’ measurements vs. area average [4km]) Nrad Nrad Nsyn Nsyn Refractivity error evaluation March 2008 June 2008 Calculate rms difference as a function of the error estimate rms (Nrad-Nsyn) rms (Nrad-Nsyn) rms difference ≈ error estimate / 2 N N Importance of eliminating correlated range-gates Correlation between Nfreq and NradStation 1 2 (1 & 2) with elimination of correlated range-gates 0.00 0.03 0.01 without elimination of correlated range-gates 0.16 0.22 0.19

  8. Met Office Unified Model comparisons Case study: Isolated convection 07/06/2008 Synoptic station refractivity Model refractivity Correlation with synoptic observations of refractivity. Radar rainfall Station 1 2 Radar 0.52 0.51 UM 4km 0.04 0.33 UM 12km 0.36 0.36 Temperature and pressure often well-captured in the model … but not humidity

  9. Summary and Future Work (1) Initial comparisons between radar refractivity retrieval and the Met Office Unified Model output suggest that radar refractivity retrieval may improve the representation of humidity in the model (not well-captured at present) Radar refractivity error estimates should provide useful constraints for data assimilation Future work will aim to evaluate the benefit of assimilating radar refractivity measurements in the Unified Model regarding the initiation/suppression of convection

  10. Summary and Future Work (2) Radar refractivity retrieval is possible with magnetron radars and has highlighted the importance of eliminating correlated range-gates, which bias refractivity change estimates. Klystron radars will be biased towards N=0 ! Inconsistent results from CSIP may well be due to this effect, in conjunction with the pulse-coding artefacts. Data soon to be re-analysed! Newly-developed theory suggests exact target location could be retrieved using frequency hopping from pulse-to-pulse. Use exact spacing rather than range-gate spacing to calculate phase change gradients. To be tested on ACROBAT (no pulse coding).

  11. Thanks for your attention!

  12. Relation between refractivity and meteorological variables Total Density (dry) term Wet term 250-460 250-280 80-180 could be caused by any of the following  Refractivity changes are dominated by humidity changes in warm conditions

  13. Stockland Hill TV Mast (235m at 30km) dBZ azimuth range phase Single targets may contaminate many range gates

  14. Frequency changes from dominant ‘point’ clutter targets When a single target dominates the returned signal across adjacent range gates, the phase change gradient with respect to range will be proportional to the change in transmitted frequency This requires that the reference frequency is either corrected for or remains unchanged By averaging the estimates from such targets, changes in the transmitted frequency can be accurately determined (black) In addition, the transmitted frequency is independently measured in real-time by sampling the transmitted pulse (red) B k j Comparisons between these two estimates have confirmed that the measured transmitted frequency and the recorded reference frequency are accurate to better than 1kHz

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