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Alain Dabas

Abstract

The author proposes a heuristic semiempirical model for predicting the reliability of a matched-filter frequency estimator applied to Doppler lidar signals. The model is tuned by a single coefficient β empirically related to the ratio of the number of signal samples per estimate over the number of speckles. It can deal with any signal characteristics (spectrum width, number of samples, etc.) as well as any factor of accumulation.

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Alain Dabas, Julie Périn, and Pierre H. Flamant

Abstract

An airborne pulsed Doppler lidar implementing a downlooking conical scan rotating around the vertical axis is under development. The information contained in the measured radial velocities is studied to assess the capacity to retrieve the 3D wind field at mesoscale. First, in the frame of a variational analysis, it is shown that the observations cannot resolve horizontal scales shorter than approximately 5 km. Then, constraints of mass conservation and regularity as well as various boundary conditions are added to improve the resolution. The various constraints are tested on synthetic data. Further, a full analysis scheme is proposed that combines a preanalysis at low resolution followed by a finer resolution analysis. The achievable performances are discussed as well as the main limitations.

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Alain M. Dabas, Philippe Drobinski, and Pierre H. Flamant

Abstract

Frequency estimates by heterodyne Doppler lidar (HDL) may result in velocity bias due to the atmospheric speckle effect and an asymmetrical power spectrum of the probing pulse, as discussed in a previous paper by Dabas et al. In this paper, it has been shown that the velocity bias can be accounted for and corrected on a single measurement basis for a mean frequency estimator (e.g., pulse pair). In the present paper, a new procedure is proposed and validated for adaptive filters (e.g., Levin, notch, etc.), which accounts for nonstationary conditions such as wind turbulence, wind shear, and backscattered power gradient. The present study is conducted using both numerical simulations and actual data taken by a 10-μm HDL.

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Alain M. Dabas, Philippe Drobinski, and Pierre H. Flamant

Abstract

Unreliable frequency estimates at low signal-to-noise ratios, provided by a heterodyne Doppler lidar (HDL), undermines any data analysis scheme requiring high-accuracy wind fields retrievals. To meet demanding specifications, that is, high accuracy associated with high reliability on radial velocity components, a quality control (QC) procedure has to be implemented at signal processing level. The authors propose use of a recursive implementation of an adaptive filter for frequency estimate coupled with a QC that combines a statistical test on the signal energy filtered out as proposed by Rye and Hardesty and a persistency criterion (PC). The PC leads to improved performance with respect to the percentage of data finally accepted and frequency accuracy. The performance is validated using simulated signals and HDL actual data.

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Alain M. Dabas, Philippe Drobinski, and Pierre H. Flamant

Abstract

Radial wind velocity measurements by a pulsed CO2 Doppler lidar may be biased even in stationary atmospheric conditions. The authors show it is due to random speckle fluctuations of the backscattered signal and is related to the dissymmetry of the transmitted laser pulse periodogram. A procedure is proposed to correct for the bias on a shot-to-shot basis when a pulse-pair mean-frequency estimator is used for processing. The procedure is validated on simulated and actual lidar signals.

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Joël Van Baelen, Jean-Pierre Aubagnac, and Alain Dabas

Abstract

In this study, the authors compare the integrated water vapor (IWV) retrieved with a global positioning system (GPS) receiver, radiosondes (RS), and a microwave radiometer (MWR) using data collected simultaneously during a 3-month campaign in the fall of 2002 in Toulouse, France. In particular for this study, the GPS analysis was performed in near–real time to provide estimates of the IWV in order to evaluate the potential of GPS observations for operational meteorological purposes. Although the three instrument estimates agree quite well together, the IWV estimates retrieved by GPS are generally larger than those of RS, while evidence is shown of a marked diurnal cycle: the differences are larger during the day (up to 2 mm) than at night (less than 0.5 mm). This can be explained by a daytime dry bias of the RS. Regarding the MWR, similar findings but to a lesser extent (differences between 0 and 1 mm) are reported. Furthermore, it has been established that the GPS estimates exhibit a strong dependency upon the IWV values resulting in a 15% faster variation when compared to the other means of IWV estimation in this study.

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Philippe Drobinski, Alain M. Dabas, and Pierre H. Flamant

Abstract

Heterodyne Doppler lidars (HDLs) are used to monitor atmospheric wind field and wind turbulence at remote distance. This last application calls for the derivation of wind spectra, which can be characterized by the dissipation rate and the κ-spectral peak (or outer scale of turbulence). However, the HDL technique may suffer two problems. First, HDL measurements result in spatial averaging of the true wind velocity along the line of sight, because of the laser pulse duration and windowing effect on processed signals. Second, even at high signal-to-noise ratio, the retrieved turbulent velocity field may be contaminated by errors due to speckle fluctuations. It is shown that both spatial averaging and error contribution to the wind spectra can be modeled starting from the transmitted laser pulse characteristics and signal processing parameters, so that their effect can be predicted. The rms difference between the estimated and predicted turbulent spectra is minimized in order to infer the turbulence parameters. This procedure is tested on simulated signals and validated on actual data taken by a 10-μm HDL during a field campaign in 1995.

The data collected during two periods of two consecutive days (9 and 10 March and 13 and 14 March 1995) are analyzed. On these days, moderate to light winds prevailed. The stability parameter z i/L MO indicated slightly unstable conditions with sometimes probable convection. The HDL measured energy dissipation rates ranging between 0.7 × 10−3 and 8 × 10−3 m2 s−3 in good agreement with sonic anemometer measurements. The κ-spectral peak ranged between 200 and 600 m.

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Jean-Luc Zarader, Gérard Ancellet, Alain Dabas, Nacer K. M'Sirdi, and Pierre H. Flamant

Abstract

An adaptive notch filter (ANF) is proposed for range-resolved frequency estimates of Doppler lidar atmospheric returns. The ANF is based on the spectral filtering of lidar return to remove the atmospheric contribution from noise. An adaptive algorithm is used to retrieve the filter parameters at a time k knowing both the input signal and filter output at times ki, where i = [1, k]. It is shown that ANF performs well at low SNR (−5 dB) compared to the poly-pulse-pair (PPP) estimator currently used for Doppler lidar signal processing. The standard deviation of frequency estimates is 0.01F s − 0.02F s (F s is the sampling frequency) at SNR = −5 dB, depending on the signal spectral width. It corresponds to a wind velocity uncertainty of 2–4 m s−1 for F s = 40 MHz and a laser wavelength λ = 10 µm. The ANF also proved to perform better than PPP in tracking a time-varying frequency, and in the presence of a colored noise.

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Sophie Bastin, Philippe Drobinski, Vincent Guénard, Jean-Luc Caccia, Bernard Campistron, Alain M. Dabas, Patricia Delville, Oliver Reitebuch, and Christian Werner

Abstract

The three-dimensional structure and dynamics of the combination of the sea breeze and the mistral at the Rhône Valley exit, in southeastern France, have been investigated experimentally and numerically on 22 June 2001. The mistral refers to a severe northerly wind that develops along the Rhône Valley. The exit of this valley is located near the Mediterranean Sea where sea-breeze circulation often develops. The sea breeze and the mistral coexist this day because of the weakness of this mistral event.

The event was documented in the framework of the Expérience sur Site pour Contraindre les Modèles de Pollution Atmosphérique et de Transport d'Emissions (ESCOMPTE) field experiment. Several important data sources are used (airborne Doppler lidar, UHF wind profilers, radiosoundings, and surface stations) as well as nonhydrostatic mesoscale simulations.

This paper examines the various mechanisms that drive the time and spatial variability of the mistral and the sea breeze in various regions of the Rhône Valley. In the morning, the sea breeze penetrates inland near the western side of the Rhône Valley then moves back because of the reinforcement of the mistral flow caused by the deepening of the leeward surface low due to convection at noon. At midday, the sea breeze penetrates inland in the middle of the Rhône Valley only. In contrast to pure sea-breeze episodes when the sea breeze can extend inland over a horizontal range of more than 150 km, the presence of the mistral prevents the sea breeze from penetrating more than 40 km onshore. In the late afternoon, the sea breeze reaches the eastern side of the Rhône Valley but over a smaller horizontal range because of higher local topography and because the mistral is more intense in this part of the Rhône Valley.

The situations of sea-breeze–mistral interactions can have a severe impact on regional air quality. Indeed, the southerly sea breeze, which advects toward the countryside the pollutants emitted from the large coastal city of Marseille, France, and its industrialized suburbs, cannot penetrate far inland because of the mistral blowing in the opposite direction. This leads to the stagnation of the pollutants near the area of emission that is also the most densely inhabited area of the region (over one million inhabitants).

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Ad Stoffelen, Angela Benedetti, Régis Borde, Alain Dabas, Pierre Flamant, Mary Forsythe, Mike Hardesty, Lars Isaksen, Erland Källén, Heiner Körnich, Tsengdar Lee, Oliver Reitebuch, Michael Rennie, Lars-Peter Riishøjgaard, Harald Schyberg, Anne Grete Straume, and Michael Vaughan

Abstract

The Aeolus mission objectives are to improve numerical weather prediction (NWP) and enhance the understanding and modeling of atmospheric dynamics on global and regional scale. Given the first successes of Aeolus in NWP, it is time to look forward to future vertical wind profiling capability to fulfill the rolling requirements in operational meteorology. Requirements for wind profiles and information on vertical wind shear are constantly evolving. The need for high-quality wind and profile information to capture and initialize small-amplitude, fast-evolving, and mesoscale dynamical structures increases, as the resolution of global NWP improved well into the 3D turbulence regime on horizontal scales smaller than 500 km. In addition, advanced requirements to describe the transport and dispersion of atmospheric constituents and better depict the circulation on climate scales are well recognized. Direct wind profile observations over the oceans, tropics, and Southern Hemisphere are not provided by the current global observing system. Looking to the future, most other wind observation techniques rely on cloud or regions of water vapor and are necessarily restricted in coverage. Therefore, after its full demonstration, an operational Aeolus-like follow-on mission obtaining globally distributed wind profiles in clear air by exploiting molecular scattering remains unique.

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