Dual-frequency Dual-polarization Doppler Radar Research Articles

Dual-Frequency Radar Retrievals of Snowfall Using Random Forest

The microphysical parameters of snowfall directly impact hydrological and atmospheric models. During the International Collaborative Experiment hosted at the Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018), dual-frequency radar retrievals of particle size distribution (PSD) parameters were produced and assessed over complex terrain. The NASA Dual-frequency Dual-polarized Doppler Radar (D3R) and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometer observations were used to develop retrievals. The conventional look-up table method (LUT) and random forest method (RF) were applied to the disdrometer data to develop retrievals for the volume-weighted mean diameter (Dm), the shape factor (mu), the normalized intercept parameter (Nw), the ice water content (IWC), and the snowfall rate (S). Evaluations were performed between the D3R radar and disdrometer observations using these two methods. The mean errors of the retrievals based on the RF method were small compared with those of the LUT method. The results indicate that the RF method is a promising way of retrieving microphysical parameters, because this method does not require any assumptions about the PSD of snowfall.

Robust Linear Depolarization Ratio Estimation for Dual-Polarization Weather Radar

Linear depolarization ratio (LDR) is often difficult to measure in low and moderate signal-to-noise ratio conditions because the cross-polar echo power is typically two to three orders of magnitude weaker than the copolar echo power. For radars operating at attenuating frequencies such as X-, Ku-, and Ka-bands, differential attenuation must be accounted for to accurately estimate the LDR. A method for robust estimation of the LDR is introduced and evaluated that addresses both of these issues. In practice, the “enhanced” LDR offers robust LDR estimation over current estimation methods. The enhanced LDR is insensitive to noise, radar calibration error, and path-integrated attenuation. The proposed estimator is experimentally validated using Ku-band observations from the National Aeronautics and Space Administration dual-frequency dual-polarization Doppler radar (D3R).

Real-Time Noise Estimation and Correction in Dual-Polarization Radar Systems

Accurate noise-power estimation in dual-polarization weather radar is necessary for the correction of all power-based moments in low signal-to-noise ratio environments. A method of real-time noise-power estimation for dual-polarization radar systems using copolar correlation and receiver power is introduced. This real-time noise-power estimation algorithm is implemented in the NASA dual-frequency dual-polarization Doppler radar, and the performance results are presented.

Estimation of Light Rainfall Using Ku-Band Dual-Polarization Radar

The light rain (less than or equal to a few mm hr-1) is critical to the Earth's ecosystem due to the high occurrence rate, particularly in middle and high latitude (over 80%). However, it is challenging to use rainfall gauge to measure light rain due to the sampling time and bucket volume resolution. Dual-polarization radar has become an important tool for quantitative precipitation estimation because of its relatively large covering area and ability to fill the sampling void. This paper presents the application of Ku-band dual-polarization radar for light rainfall estimation. The Ku-band radar rainfall algorithms and their error structure are described. The Ku-band observations from the National Aeronautics and Space Administration (NASA) Dual-frequency Dual-polarization Doppler Radar (D3R) during the NASA Iowa Flood Studies (IFoodS) field campaign are used to derive the rainfall products. The comparisons are performed between radar rainfall estimates and ground rainfall measurements from rain gauge and Autonomous Parsivel Unit (APU). It is shown here that the radar rainfall measurements at different timescales (i.e., 5, 10, and 15 min) agree with the APU observations very well. The normalized difference error is about 26.1%, 24.8%, and 23.7%, for 5-min, 10-min, and 15-min rainfall accumulations, respectively. The excellent performance of Ku-band rainfall algorithm for light rain estimation indicates the great potential of using D3R as a ground validation tool for the Global Precipitation Measurement (GPM) satellite precipitation product evaluations.

Polarimetric Variables Retrieval with Clutter Suppression for Staggered PRT Sequences

AbstractThis paper presents a procedure to filter ground clutter from dual-polarized staggered pulse repetition time (PRT) radar data in simultaneous and alternating transmission modes for polarimetric variables retrieval. The filter is designed in the time domain so that polarimetric variables such as the differential phase () and the copolar correlation coefficient () can be estimated directly from clutter-filtered time series data using a conventional method. In the case of the simultaneous mode, a single filter is used for both channels to maintain the signal correlation after filtering. For the alternating mode, because the polarizations are transmitted in different waveforms, two separate filters are required. However, the filters are designed so that the responses of the filters to the signals are identical within the extended Doppler range. Based on radar simulation, it is shown that the method can provide accurate retrieval of polarimetric variables even in the case of strong clutter contamination. Also, the performance of the method is illustrated on dual-polarized staggered PRT ⅔ data from the NASA dual-frequency dual-polarized Doppler radar (D3R).

Sensitivity Enhancement System for Pulse Compression Weather Radar

AbstractThe use of low-power solid-state transmitters in weather radar to keep costs down requires a pulse compression technique that maintains an adequate minimum detectable signal. However, wideband pulse compression filters will partly reduce the system’s sensitivity performance. In this paper, a sensitivity enhancement system (SES) for pulse compression weather radar is developed to mitigate this issue. SES uses a dual-waveform transmission scheme and an adaptive pulse compression filter. The waveforms’ diversity can be done in the frequency domain or the time domain. The adaptive filter is designed based on the self-consistency between signal returns from the two waveforms. Analysis based on radar-simulated data and observations from NASA’s dual-frequency dual-polarized Doppler radar (D3R) shows that by using SES, the system sensitivity can be improved by 7–10 dB when compared to that of the conventional matched filter.