Jacques Testud

The retrieval of ice-cloud properties from cloud radar and lidar synergy

Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

Estimate of Precipitation from the Dual-Beam Airborne Radars in TOGA COARE. Part II: Precipitation Efficiency in the 9 February 1993 MCS

Abstract Dual-beam airborne Doppler radars are commonly used in convection experiments for their ability to describe the dynamical structure of weather systems. However, instrumental limitations impose the use of wavelengths such as X-band, which are largely attenuated through heavy rain. This paper is the second of a series of two, which aim at developing schemes for attenuation correction. The authors’ final objective is to improve the estimation of precipitation sampled from airborne radars. The first paper was dealing with the application of “differential algorithms” (“stereoradar” and “quad beam”) to the independent retrieval of the specific attenuation and nonattenuated reflectivity, which shed some light on the physics of the precipitation. This second paper develops a more extensive procedure based upon the hybridization of a “differential” and an “integral” algorithm. It is much more flexible than the methods proposed in part one and allows full rainfall-rate retrievals in single aircraft experim...

Estimate of Precipitation from the Dual-Beam Airborne Radars in TOGA COARE. Part 1: The K–Z Relationships Derived from Stereo and Quad-Beam Analysis

Abstract The recent development of dual-beam airborne Doppler weather radar offers the possibility to perform high-resolution observations of the three-dimensional air motion and precipitation fields associated with severe weather systems. However, the limited size of the onboard antennas imposes the use of high radar frequencies (e.g., X band) in order to achieve satisfactory beam resolutions. Therefore, the sampled radar reflectivity is attenuated when intercepting intense rain cells. This paper aims at developing algorithms for correcting the observed radar reflectivity for attenuation that fully exploit the dual-beam sampling strategy and the multiple aircraft operations conducted in Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). Its specific contribution is twofold. Algorithm development. On the one hand, the former stereoradar analysis helps to retrieve independently the“true” (nonattenuated) radar reflectivity Z and specific attenuation K when using ...

Cloud parameter retrieval from combined remote sensing observations

Abstract To appreciate the radiative impact of clouds in the dynamics of the global atmosphere, it is important to deploy from space, from aircraft, or from ground, instruments able to describe the cloud layering and to document the cloud characteristics (namely liquid and/or ice water content, and the effective particle radius). Combining passive and active remote sensing techniques, microwave or VIS/IR, is a possible way to achieve this goal. A statistical knowledge of particle spectra drawn from microphysical data base is nevertheless indispensable to build the inverse model and algorithms needed to retrieve the cloud parameters from remote sensing observations. The present paper covers three subjects: • - Techniques to analyse particle spectra from cloud databases: What are the key parameters to characterise a particle spectrum? What are their statistics? How do they vary with temperature? • - Building of the inverse model: How do the parameters which define the response of remote sensing instruments (radar reflectivity Z, radar specific attenuation K, lidar backscattering coefficient β, lidar extinction coefficient α) relate to the cloud parameters interesting to evaluate cloud radiative properties (liquid water content LWC, ice water content IWC, effective radius of particles ree. • - Algorithm retrieval: What are the uncertainties in the retrievals of radar or lidar alone? What do combined observations of radar and lidar bring? What kind of combined algorithm can we consider to improve the retrieval? Results of the combining algorithm applied tot data sets are then presented.

Synergetic radar and lidar algorithm for the retrieval of radiative and microphysical properties in ice clouds

To appreciate the radiative impact of clouds in the dynamics of the global atmosphere, it is important to deploy from space, from aircraft, or from ground, instruments able to describe the cloud layering and to document the cloud characteristics (namely liquid and/or ice water content, and the effective particle radius). In the framework of EarthCARE (ESA), that plans to associate a cloud radar and a lidar on the same spatial platform, RALI (RAdar-LIdar) airborne system is an interesting demonstrator. RALI combines the 95 GHz radar of the CETP and the 0.5 μm wavelength backscattering lidar of the SA. In order to derive the radiative and microphysical properties of clouds, a synergetic algorithm has been developed. It combines the apparent backscatter coefficient, βa, from the lidar and the apparent reflectivity, Za, from the radar to infer properties of the particle size distribution. The principle of this algorithm is to apply in parallel the Hitschfeld-Bordan algorithm to the radar and the Klett algorithm to the lidar. Taken separately, these two algorithms are unstable, but by considering a mutual constraint, it is shown that a stable solution can be established. This solution formulates the retrieval of the true reflectivity and backscattering coefficient, to access microphysical and radiative parameters of clouds. This algorithm allows also to retrieve the variable N0* parameter, which is a normalization parameter of the particle size distribution. This synergetic algorithm has been tested with simulated cases, and results of the algorithm applied on real data are validated by microphysical in-situ measurements.

Spaceborne cloud-profiling radar: instrument parameter optimization for resolving highly layered cloud structures

EarthCARE, a candidate Earth Explorer Core mission of ESA, aims to improve our knowledge of the impact of clouds and aerosols on the Earths radiative budget. The satellite will carry two nadir sounding active instruments: a Cloud Profiling Radar (CPR) and a backscatter lidar. In addition, a multispectral cloud-imager, a Fourier transform spectrometer and a broadband radiometer complement the payload. The objective of the present study was to optimize the parameters of the CPR for retrieving accurate radiative profiles for highly layered cloud structures. Realistic cloud scenarios taken from ground-based experiments have been used for simulating the radar response to cloud layers. A radar simulator was developed initially for one-dimensional simulation of the radar echos. The cloud microphysical properties were retrieved using a model as a function of the reflectivity factor and temperature, based on information from in-situ measurements. An extensive parametric analysis was performed for various vertical resolutions and sensitivities which have direct impacts on the radar design and necessary resources on-board the satellite. The analysis demonstrated that the proposed radar characteristics will meet the top-of-the-atmosphere radiative flux density estimation accuracy of 10 W/m2 as recommended by WCRP.