1 / 16

Analyzing Ice Cloud Properties with Radar Reflectivity Factor and Temperature Relationship

This overview explores the use of mass-size relationships in calculating radar reflectivity from aircraft size spectra in ice clouds. It covers the derivation of ice water content (IWC) using Rayleigh and non-Rayleigh scattering, as well as evaluating model IWC in precipitation cases. Comparisons from the Clouds, Water Vapour and Climate (CWVC) and Cloud Lidar and Radar Experiment (CLARE’98) are discussed, highlighting the impact of temperature variations on IWC estimations. The text delves into radar calibration techniques, scanning capabilities, and the sensitivity of radar measurements in rainfall events. Results show reliable accuracies within certain temperature ranges, emphasizing the importance of considering radar sensitivity. Various models and comparisons regarding ice water observations are also examined, along with the effects of non-Rayleigh scattering. The discussion includes methodologies for analyzing ice water content and temperature relationships using radar and aircraft data, providing insights into the challenges and implications of different scattering mechanisms on measuring ice cloud properties.

quinlan-brooks
Download Presentation

Analyzing Ice Cloud Properties with Radar Reflectivity Factor and Temperature Relationship

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Ice water content from radar reflectivity factorand temperature Robin Hogan Anthony Illingworth Marion Mittermaier

  2. Overview • Use of mass-size relationships in calculating Z from aircraft size spectra in ice clouds • Radar-aircraft comparisons of Z • Derivation of IWC(Z,T): Rayleigh scattering • Evaluation of model IWC in precipitating cases using 3 GHz radar data • The problem of non-Rayleigh scattering • Derivation of IWC(Z,T): non-Rayleigh scattering

  3. Interpretation of aircraft size spectra • To use aircraft size distributions to derive IWC(Z,T), need to be confident of mass-size relationship • Brown and Francis used m=0.0185D1.9 (SI units) • It produced the best agreement between IWC from size spectra and from independent bulk measurement • But can we use it for calculating radar reflectivity factor? • Use scanning 3 GHz data from Chilbolton during the Clouds, Water Vapour and Climate (CWVC) and Cloud Lidar and Radar Experiment (CLARE’98) • Rayleigh-scattering Z prop. to mass squared • Error in mass-size relationship of factor of 2 would lead to a 6 dB disagreement in radar-measured and aircraft-calculated values!

  4. Comparisons from CLARE’98 T=-32ºC, Z=-0.7dB, m=-8% T=-15ºC, Z=-1.0dB, m=-11%

  5. Comparisons from CWVC T=-21ºC, Z=+0.3dB, m=+3% T=-10ºC, Z=+0.3dB, m=+4%

  6. Another CLARE case But this case was mixed-phase: liquid water leads to riming and depositional growth rather than aggregation: higher density T=-7ºC, Z=+3.7dB, m=+54% Implies particle mass/density is up to factor 2 too small

  7. 3 GHz Mean slope: IWC~Z0.6

  8. Relationship for Rayleigh scattering Observations by Field et al. (2004) demonstrate the T dependence of N0 • Relationship derived for Rayleigh-scattering radars: • log10(IWC) = 0.06Z – 0.0197T – 1.70 i.e. IWC  Z0.6f(T ) • What is the origin of the temperature relationship? • For an exponential distribution with density  D-1: • IWC  N0D03 and Z  N0D05 • If T is a proxy for D0 then eliminate N0: • IWC  ZD0-2  Zf(T ) • Not observed! • If T is a proxy for N0 then eliminate D0: • IWC  Z 0.6N00.4  Z0.6f(T ) • Correct!

  9. IWC evaluation using 3 GHz radar • Now evaluate Met Office mesoscale model in raining events using Chilbolton 3 GHz radar • Advantages over cloud radar: • Rayleigh scattering: Z easier to interpret • Very low attenuation: retrievals possible above rain/melting ice • Radar calibration to 0.5 dB using Goddard et al. (1994) technique • Scanning capability allows representative sample of gridbox • 39 hours of data from 8 frontal events in 2000 • Apply IWC(Z,T) relationship and average data in horizontal scans to model grid • Threshold observations & model at 0.2 mm/h • Need to be aware of radar sensitivity; only use data closer than 36 km where minimum detectable reflectivity is –11 dBZ

  10. Comparison of mean IWC • Results: • Accurate to 10% between –10ºC and -30ºC • Factor of 2 too low between -30ºC and -45ºC • Results at colder temperatures unreliable due to sensitivity sensitivity at 10 km sensitivity at 36 km

  11. Comparison of IWC distribution • Distribution generally too narrow in model, problem worse at warmer temperatures

  12. Non-Rayleigh scattering Mie-scattering using equivalent area diameter Mie-scattering using mean of max dimensions • Representation of Mie scattering has large effect… Equivalent-area diameter Mean of max dimensions Typical aircraft crystal image

  13. 35 GHz log10(IWC) = 0.000242 ZT + 0.0699 Z – 0.0186T – 1.63 Non-Rayleigh scattering

  14. 94 GHz log10(IWC) = 0.000580 ZT + 0.0923 Z – 0.00706T – 0.992 Non-Rayleigh scattering

  15. Ice water Observations Met Office Mesoscale Model ECMWF Global Model Meteo-France ARPEGE Model KNMI RACMO Model Swedish RCA Model

  16. Comparison of the IWC products (lidar/radar vs. Z,T) retrieved from Chilbolton data (2003) IWCZT =IWC Linear regression The linear regression fit in log-space of all data is close to the 1 to 1 line. The distribution is wide and not symmetric

More Related