Presentation describes Parametric Time Domain Method (PTDM) to separate cloud and drizzle moments for the W-band ARM cloud radar located at Graciosa Island, Portugal.

1. Separation of Cloud and Drizzle using
spectral analysis for ARM Cloud Radar
V.Chandrasekar*, Shashank Joshil, Pratik Ramdasi
Colorado State University, 1373 Campus Delivery, Fort Collins, Colorado
*chandra@engr.colostate.edu
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2. Overview
• Introduction
• ARM cloud radar
• PTDM methodology
• Flowchart to separate cloud and drizzle
• Implementation and Results
• Summary
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3. Introduction
• The potential of retrieving cloud and precipitation properties from Doppler spectra has
been recognized since the early days of the radar meteorology.
• The separation of radar signatures depicting cloud and drizzle within a pulse radar
volume is a fundamental problem whose solution is required to decouple the
microphysical and dynamical processes introduced by turbulence. Such a solution
would lead to the development of new meteorological products.
• A Parametric Time Domain Method (PTDM) to detect, estimate and separate cloud
and drizzle echoes from vertically pointing Doppler spectra ARM cloud radar is
developed.
• PTDM model is developed using the collected ARM radar Doppler spectra data to
retrieve the signal spectral moments.
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4. • In the case when only clouds are present, the Doppler spectrum
is symmetrical and is well approximated by a Gaussian. To
extract cloud echoes, a parametric maximum likelihood estimator
in the time domain is employed using the recorded radar Doppler
spectra data.
• Goodness of fit parameters specifying the features of cloud
Doppler spectra are defined. If the detection parameters exceed
predetermined thresholds, the signal contains a mixture of cloud
and drizzle.
• A drizzle map is processed to accommodate the location of cloud
base.
• At the locations where cloud and drizzle co-exist, the model is
modified to include cloud and drizzle spectral parameters.
• To identify which echoes are associated with cloud or drizzle
similarity-based classifier is implemented.
• Retrieved signal from the cloud top and observed signal from the
cloud base are used as constraints to optimize the detection and
estimation algorithm performance. 4

5. ARM Cloud Radar
• W-band Atmospheric Radiation Measurement
(ARM) Program Cloud Radar (WACR) are the
zenith pointing Doppler radars operating at
95.04 GHz.
• Gives estimates for first three spectra moments
namely reflectivity(0th moment), radial
velocity(1st moment), spectral width(2nd
moment) for each range gate up to 15km.
• Operates only in co-polarization and cross-
polarization mode. We have considered the co-
polarization mode for the analysis.
• The data used for analysis if from Graciosa
Island, Azores, Portugal.
http://www.arm.gov/news/facility/post/34876
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6. Methodology
Parametric Time Domain Method (PTDM)
• The Radar power spectrum corresponding to N echoes in the received signal can be
given as:
𝑆 𝑣 =
𝑖=1
𝑁
𝑆𝑖 𝑣 + 𝑃𝑛
𝑆𝑖 𝑣 =
𝑆𝑖 𝑝
𝜎𝑖 2𝜋
𝑒
−
𝑣− 𝑣 𝑖
2
2𝜎𝑖
2
• Spectral moments can be obtained by minimizing the negative log likelihood
𝐿 𝜃 = ln det 𝑹 𝜃 + 𝑡𝑟𝑎𝑐𝑒 𝑹𝑹−1 𝜃
𝜃 = [𝑣1, 𝜎1, 𝑃1, … , 𝑣 𝑁, 𝜎 𝑁, 𝑃 𝑁, 𝑃𝑛]
where 𝑅 and 𝑅 𝜃 are the covariance matrix from recorded power spectrum and the
model covariance matrix, respectively. 6

7. Goodness of fit parameters
• 𝑇𝑟𝑣𝑎𝑟 is a goodness of fit parameter and is defined as:
𝑇𝑟𝑣𝑎𝑟 = 𝑠𝑡𝑑{𝑑𝑖𝑎𝑔 𝑹𝑹−1
𝜃 }
If it’s value is close to zero it indicates a good fit.
• 𝑅 𝑠𝑞 is another goodness of fit parameter. It is a fraction of the total signal
variance explained by the model and the closer it is to unity, the better fit.
.
.
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8. Noise only:
Gaussian spectrum:
Bimodal spectrum:
Bimodal spectrum:
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Representation of radar Doppler spectra and goodness of fit parameters

9. Flowchart
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10. Results Azores data analysis: case 12th May 2010 at 1.00 - 2.00 (UTC)
Measured Reflectivity and Velocity Cloud Reflectivity and Velocity Drizzle Reflectivity and Velocity
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11. Algorithm verification
Comparison of retrieved drizzle reflectivity one gate above cloud base (CB+1)
and observed drizzle reflectivity one gate below cloud base (CB-1)
Comparison of retrieved drizzle velocity one gate above cloud base (CB+1)
and observed drizzle velocity one gate below cloud base (CB-1)
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12. Measured Reflectivity and Velocity Cloud Reflectivity and Velocity Drizzle Reflectivity and Velocity
Azores data analysis: case 27th July 2010 at 10.00 – 11.00 (UTC)
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13. Algorithm verification
Comparison of retrieved drizzle reflectivity one gate above cloud base (CB+1)
And observed drizzle reflectivity one gate below cloud base (CB-1)
Comparison of retrieved drizzle velocity one gate above cloud base (CB+1)
And observed drizzle velocity one gate below cloud base (CB-1)
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14. Summary
• The PTDM method works with ARM cloud radar power spectra
profile and performs well.
• Drizzle reflectivity can be obtained accurately when cloud and
drizzle echoes overlap heavily.
• The distributions of the retrieved cloud and drizzle reflectivities
above the cloud base and observed reflectivities below the cloud
base agree very well. This says that the proposed approach
performs well for the separation of cloud and drizzle.
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15. References
[1] Atlas, D., R. S. Srivastava, and R. S. Sekhon, 1973: Doppler radar characteristics of precipitation at vertical incidence.
Rev. Geophys. Space Phys., 11, 1–35.
[2] Bringi, V. N., and V. Chandrasekar, 2001: Polarimetric Doppler Weather Radar: Principles and Applications. Cambridge
University Press, 636 pp.
[3] Cuong M. Nguyen, Dmitri N. Moisseev, and V. Chandrasekar, 2008: A Parametric Time Domain Method for Spectral
Moment Estimation and Clutter Mitigation for Weather Radars. J. Atmos. Oceanic Technol., 25, 83–92.
[4] Edward P. Luke and Pavlos Kollias, 2012: Separating Cloud and drizzle radar moments during precipitation onset using
Doppler spectra. J. Atmos. Oceanic Technol., 30, 1656–1671
[5] Zong Rong, Liu liping and Yin Yan, 2015: Relationship between cloud characteristics and radar reflectivity based on
aircraft and cloud radar co-observations. Advances in Atmos. Sciences, vol 30, No 5, 1275-1286.
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Acknowledgement
This research has been supported by U.S. Department of Energy, ARM climate research facility.

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Thank you and Questions?