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Clouds of different optical depth t should be treated differently

RadOn : Retrieval of microphysical and radiative properties of ice clouds from Doppler cloud radar observations J. Delanoë and A. Protat IPSL / CETP. Clouds of different optical depth t should be treated differently Lidar-Radiometer for very thin clouds (not detected by radar)

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Clouds of different optical depth t should be treated differently

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  1. RadOn : Retrieval of microphysical and radiative properties of ice clouds from Doppler cloud radar observationsJ. Delanoë and A. Protat IPSL / CETP Clouds of different optical depth t should be treated differently Lidar-Radiometer for very thin clouds (not detected by radar) Radar-Lidar / Radar-Radiometer for t < 3 Radar / Radar-Radiometer / Dual-Wavelength Radar for t > 3

  2. Illustration for the need of different methods Radar Z Radar Lidar  Radar+Lidar Lidar Existing radar methods : Matrosov Z+V (2002) and Hogan IWC-Z-T (2005)

  3. The two measurements of a Doppler cloud radar For a vertically-pointing cloud radar : Reflectivity factor Doppler velocity These measurements are related to N(D)

  4. The ice cloud properties are also related to N(D) The ice cloud properties re= f (IWC /  )

  5. The normalized particle size distribution High variability in ice clouds Scaling the PSD so that it does not depend on IWC, Dm N(D) = No* F (Deq/Dm) Delanoë et al. (JGR, 2005) : shape F can be approximated by a single analytical form for all ice clouds (<10% error) The unknowns to get cloud properties : No* and Dm Then Re = ( (7) / 2 (6) ) DmIWC = No*wDm4 / 44  = (3/2) IWC / Re= • The idea in RadOn and Matrosov (2002) is to get it • from the two radar measurements Z and VD

  6. The normalized particle size distribution Mean spectra for all experiments Analytical formulation • CLARE 98, CARL 99,EUCREX, ARM IOP, FASTEX, CEPEX, CRYSTALFACE 5% 10% 1 dB 0.5 dB Z error=f(T) IWC error=f(T)

  7. Principle of the radar retrieval method Z Doppler velocity VD=VT+w VT –Z statistical relationships or mean VD : VT retrieval  Most representative density-diameter and area-diameter relationships Dm (VT, r(D), A(D)) IWC, a, re , t N0* =f(Dm,Z)

  8. Principle of the radar retrieval method First step : Retrieval of VT from (VD , Z) Hypothesis : for a long enough time span <w> << <VT> Error = synoptic ascent / descent (typically 5 cms-1) A VT - Z relationship is derived for each cloud scatter = w contribution

  9. Principle of the radar retrieval method First step : Retrieval of VT from (VD , Z) Alternative approach : 20-minutes means (Matrosov 2002) Improvement : Running means over 20 minutes (resolution) IWCRW IWCVTZ aRW aVTZ

  10. Principle of the radar retrieval method Z Doppler velocity VD=VT+w VT –Z statistical relationships or mean VD : VT retrieval Most representative density-diameter and area-diameter relationships Dm (VT, r(D), A(D)) IWC, a, re , t N0* =f(Dm,Z)

  11. Principle of the radar retrieval method Second step : Retrieval of most representative r(D),A(D) relationships Using the microF in-situ database and theoretical v(D) = f(r(D),A(D)) for different ice particle shapes and habits we have computed synthetic VT-Z relationships For each cloud, we compare the synthetic and radar-derived VT-Z relationships  the set of r(D),A(D) relationships that minimises the difference is retained 14

  12. Principle of the radar retrieval method Z Doppler velocity VD=VT+w VT –Z statistical relationships or mean VD : VT retrieval  Most representative density-diameter and area-diameter relationships Dm (VT, r(D), A(D)) IWC, a, re , t N0* =f(Dm,Z)

  13. Principle of the radar retrieval method Third step : Dm retrieval from VT , r(D), A(D) Knowing r(D) and A(D) and using an analytical form for the normalised PSD shape F, there is a direct relation between VT and Dm Vt=f(Dm) Dm=f(Vt) -Vt radar

  14. Principle of the radar retrieval method Z Doppler velocity VD=VT+w VT –Z statistical relationships or mean VD : VT retrieval  Most representative density-diameter and area-diameter relationships Dm (VT, r(D), A(D)) IWC, a, re , t N0* =f(Dm,Z)

  15. Principle of the radar retrieval method Fourth step : N0* retrieval from Dm and Z In Mie regime there is a direct expression that relates N0*, Dm and Z

  16. Evaluation of RadOn using the mF in-situ database Compute Vt,Z, IWC, a and re from the in-situ data, with A(D) and r(D) constant Vt + Zmicrof RadOn Hogan IWC-Z-T Matrosov Z+V Database: CLARE 98, CARL 99, EUCREX, ARM IOP, FASTEX, CEPEX, CRYSTAL-FACE We use r(D)=0.00556(D in cm)-1.1, A(D)=p/4D², radar at 95GHz. Global error analysis IWC,a, re microf IWC,a, re retrieved Similar study for other A(D) / r(D) Error estimates are comparable

  17. Evaluation of RadOn using the IPSL Ra-Li method 27 Chilbolton clouds selected for intercomparisons 5 cases : bias + Mie effect 9 cases : good 6 cases : bias 7 cases : Mie effect IWC IWC IWC These differences in performance are due Mie scattering not in Ra-Li method. The 9 good cases : RadOn density retrieval close to Ra-Li (Brown-Francis 1995). a IWC We restrict to the 9 good cases

  18. Evaluation of RadOn using optical depth from lidar Optical depth from lidar can be obtained from difference in molecular return Comparisons with RadOn optical depths and those lidar cases Limitations : Can only be done when radar and lidar thicknesses comparable + lidar traverses entirely + no occurrence of SLW  case study approach only OK Thin SLW layer OK Overall : when good conditions errors < 0.1, fractional error +15% / -25%

  19. Conclusions and perspectives This method works for these radar frequencies : 3, 10, 35, 95 GHz Yields very encouraging results : -17%<errIWC<+17%, -22.5%<erra<+15%, -5.5%<errre<+15.5% During CloudNet this method allowed (see talk this afternoon): • Statistics of r(D) / A(D) from CloudNet radars • Climatology of European ice cloud properties • Evaluation of the representation of clouds in the CloudNet NWP models Available to all ground-based remote sensing sites (Matlab code)

  20. Z 3 march 2003: prefrontal cloud Vd Vt=96.3Z0.177857 A(D)=0.2D1.6 r(D)=0.0156D-1 Aggregates

  21. 14 april 2003: Thick ice cloud Vt=66.44Z0.189598 A(D)=0.5D1.8 r(D)=0.0132D-0.9 Aggregates

  22. 15 april 2003: thin cirrus Vt=57.954Z0.184944 A(D)=p/4D1.8 r(D)=0.0318D-0.8 Dl=170µm, up to this diameter solid ice

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