Spectral analyses of the dual polarization Doppler weather radar data.

Echoes in clear air from biological scatterers mixed within the resolution volumes over a large region are presented. These echoes were observed with the polarimetric prototype of the forthcoming WSR-88D weather radar. The study case occurred in the evening of September 7, 2004, at the beginning of the bird migrating season. Novel polarimetric spectral analyses are used for distinguishing signatures of birds and insects in multimodal spectra. These biological scatterers were present at the same time in the radar resolution volumes over a large area. Spectral techniques for (1) data censoring, (2) wind retrieval and (3) estimation of intrinsic values/functions of polarimetric variables for different types of scatterers are presented. The technique for data censoring in the frequency domain allows detection of weak signals. Censoring is performed on the level of spectral densities, allowing exposure of contributions to the spectrum from multiple types of scatterers. The spectral techniques for wind retrieval allow simultaneous estimation of wind from the data that are severely contaminated by migrating birds, and assessment of bird migration parameters. The intrinsic polarimetric signatures associated with the variety of scatterers can be evaluated using presented methodology. Algorithms for echo classification can be built on these. The possibilities of spectral processing using parametric estimation techniques are explored for resolving contributions to the Doppler spectrum from the three types of scatterers: passive wind tracers, actively flying insects and birds. A combination of parametric and non-parametric polarimetric spectral analyses is used to estimate the small bias introduced to the wind velocity by actively flying insects

Measures de vent 3D avec le lidar Doppler coherent Live à bord d'un avion

International audienceA three-dimensional (3D) wind profiling Lidar, based on the latest high power 1.5 µm fiber laser development at Onera, has been successfully flown on-board a SAFIRE (Service des Avions Français Instrumentés pour la Recherche en Environnement) ATR42 aircraft. The Lidar called LIVE (LIdar VEnt) is designed to measure wind profiles from the aircraft down to ground level, with a horizontal resolution of 3 km, a vertical resolution of 100 m and a designed accuracy on each three wind vector components better than 0.5 m.s −1. To achieve the required performance, LIVE Lidar emits 410 µJ laser pulses repeating at 14 KHz with a duration of 700 ns and uses a conical scanner of 30 • total opening angle and a full scan time of 17 s.Un lidar vent 3D, basé sur le dernier développement de laser à fibre de 1,5 µm à haute puissance de l’ONERA a été testé avec succès à bord d’un avion SAFIRE ATR42. Le lidar appelé LIVE est conçu pour mesurer les profils de vent de l’avion jusqu'au sol, avec une résolution horizontale de 3 km, une résolution verticale de 100 m et une précision calculée supérieure à 0,5 m / s pour chaque composante du vecteur du vent

Numerical solver for vertical air motion estimation

We present preliminary research on a method to estimate Vertical Air Motion (VAM) at a particular height by comparing the measured rain-rate (RR) by a vertically-pointing S-band Frequency-Modulated Continuous-Wave (FMCW) radar with that of a ground-based disdrometer. The method is based on a constrained parametric solver, assuming high correlation between 5-min averaged rain rates measured by the radar and disdrometer. The method is tested over disdrometer and radar observations during the Verification of the ORigins Tornado EXperiment in South East US (VORTEX-SE) project. Finally, the results are partially validated by means of fitting a gamma distribution to the VAM-corrected DSD profiles and studying its parameters.This research is part of the projects PGC2018-094132-B-I00 and MDM2016-0600 (“CommSensLab” Excellence Unit) funded by Ministerio de Ciencia e Investigación (MCIN)/ Agencia Estatal de Investigación (AEI)/10.13039/501100011033/ FEDER “Una manera de hacer Europa”. The work of A. Salcedo-Bosch was supported under grant 2020 FISDU 00455 funded by Generalitat de Catalunya—AGAUR. The European Commission collaborated under projects H2020 ACTRIS-IMP (GA-871115) and H2020 ATMOACCESS (GA-101008004).Peer ReviewedPostprint (author's final draft

An optimal inverse method using Doppler lidar measurements to estimate the surface sensible heat flux

Inverse methods are widely used in various fields of atmospheric science. However, such methods are not commonly used within the boundary-layer community, where robust observations of surface fluxes are a particular concern. We present a new technique for deriving surface sensible heat fluxes from boundary-layer turbulence observations using an inverse method. Doppler lidar observations of vertical velocity variance are combined with two well-known mixed-layer scaling forward models for a convective boundary layer (CBL). The inverse method is validated using large-eddy simulations of a CBL with increasing wind speed. The majority of the estimated heat fluxes agree within error with the proscribed heat flux, across all wind speeds tested. The method is then applied to Doppler lidar data from the Chilbolton Observatory, UK. Heat fluxes are compared with those from a mast-mounted sonic anemometer. Errors in estimated heat fluxes are on average 18 %, an improvement on previous techniques. However, a significant negative bias is observed (on average −63%) that is more pronounced in the morning. Results are improved for the fully-developed CBL later in the day, which suggests that the bias is largely related to the choice of forward model, which is kept deliberately simple for this study. Overall, the inverse method provided reasonable flux estimates for the simple case of a CBL. Results shown here demonstrate that this method has promise in utilizing ground-based remote sensing to derive surface fluxes. Extension of the method is relatively straight-forward, and could include more complex forward models, or other measurements

Middle Atmosphere Program. Handbook for MAP, volume 28

Extended abstracts from the fourth workshop on the technical and scientific aspects of MST (mesosphere stratosphere troposphere) radar are presented. Individual sessions addressed the following topics: meteorological applications of MST and ST radars, networks, and campaigns; dynamics of the equatorial middle atmosphere; interpretation of radar returns from clear air; techniques for studying gravity waves and turbulence; intercomparison and calibration of wind and wave measurements at various frequencies; progress in existing and planned MST and ST radars; hardware design for MST and ST radars and boundary layer/lower troposphere profilers; signal processing; and data management

Measurements of rainfall rate, drop size distribution, and variability at middle and higher latitudes: application to the combined DPR-GMI algorithm

The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter NW, which normalizes the concentrations, and a scaling diameter Dm, which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between NW and Dm, on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the NW–Dm relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (Dm lt; 1 mm) and large drops (Dm gt; 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates

A satellite-based radar wind sensor

The objective is to investigate the application of Doppler radar systems for global wind measurement. A model of the satellite-based radar wind sounder (RAWS) is discussed, and many critical problems in the designing process, such as the antenna scan pattern, tracking the Doppler shift caused by satellite motion, and backscattering of radar signals from different types of clouds, are discussed along with their computer simulations. In addition, algorithms for measuring mean frequency of radar echoes, such as the Fast Fourier Transform (FFT) estimator, the covariance estimator, and the estimators based on autoregressive models, are discussed. Monte Carlo computer simulations were used to compare the performance of these algorithms. Anti-alias methods are discussed for the FFT and the autoregressive methods. Several algorithms for reducing radar ambiguity were studied, such as random phase coding methods and staggered pulse repitition frequncy (PRF) methods. Computer simulations showed that these methods are not applicable to the RAWS because of the broad spectral widths of the radar echoes from clouds. A waveform modulation method using the concept of spread spectrum and correlation detection was developed to solve the radar ambiguity. Radar ambiguity functions were used to analyze the effective signal-to-noise ratios for the waveform modulation method. The results showed that, with suitable bandwidth product and modulation of the waveform, this method can achieve the desired maximum range and maximum frequency of the radar system

SPATIAL FILTERING OF CLUTTER USING PHASED ARRAY RADARS FOR OBSERVATIONS OF THE WEATHER

Phased array radars are attractive for weather surveillance primarily because of their capacity for extremely rapid scanning through electronic steering. When combined with the recently developed beam multiplexing technique, these radars can provide significantly improved update rates, which are necessary for monitoring rapidly evolving severe weather. A consequence of beam multiplexing, however, is that a small number of contiguous time series samples are typically used, creating a significant challenge for temporal/spectral filters typically used for clutter mitigation. As a result, the accurate extraction of weather products can become the limiting performance barrier for phased array radars that employ beam multiplexing in clutter-contaminated scattered fields. By exploiting the spatial correlation among the signals from the elements of the phased array antenna, the effect of clutter contamination can be reduced through a processed called spatial filtering . In contrast to conventional temporal filtering, spatial filtering is used to adaptively adjust the antenna beam pattern to produce lower gain in the directions of the undesired clutter signals. In this dissertation, the effect of clutter mitigation using spatial filtering was studied using numerical simulations of a tornadic environment and an array antenna configuration similar to the NSSL NWRT Phased Array Radar for changes in signal-to-noise ratio, clutter-to-signal ratio, number of time series samples, and diagonal loading for three types of clutter sources that include nearly stationary ground clutter, moving targets such as aircraft, and wind turbine clutter, which has recently been documented to be increasingly problematic for radars. Since such data are not currently available from a horizontally pointed phased array weather radar, experimental validation was applied to an existing data set from the Turbulent Eddy Profiler (TEP) developed at University of Massachusetts, which is a vertically pointed phased array radar. Results will show that spatial filtering holds promise for the future of phased array radars for the observation of the weather in a clutter environment