EarthCARE
Our research focuses on the development of “tools” that represent our state-of-the-art understanding in radar hardware and software and in the interaction of the electromagnetic wave with the hydrometeors and the surface. These tools will allow us to study using realistic scenarios, either through the use of existing data set (e.g., ARM and CloudSat observations) or high-resolution model scenes (e.g. Cloud Resolving Models), the performance of different spaceborne radar configurations. We are also actively involved in the development of retrieval algorithms.
Application of Matched Statistical Filters for EarthCARE Cloud Doppler Products
Until the launch of EarthCARE (EC), numerical simulations are the only means to investigate the performance of EC-Cloud Profiling Radar (CPR). These simulations can be done starting from either numerical products of cloud-resolving models or from actual W-band Doppler measurements acquired from a ground-based or airborne platform. Following this principle, various methods have been proposed to detect and correct for multiple-scattering problems [7], NUBF errors [4], [5], aliasing [8], pointing inac- curacies [6], or random-fluctuation problems [9]. Focusing on the latter, the common solution consists in performing a longer onboard integration of the radar echoes, i.e. increasing the number of radar pulses that are used in the PP estimation of the Doppler reflectivity and velocity [3]. Due to the correlation that exists between radar returns, the reduction in the variance of the velocity estimate is generally smaller than the theoretical variance reduction achievable by integrating mutually statistically independent radar pulses [10]. However, the longer integration comes at the cost of a coarser spatial sampling of the final radar product, which raises the issue of the representativeness and practical usefulness of the integrated data [9].
The aim of this paper is to address the issue of the random fluctuations of the measured mean Doppler velocity, whereas the NUBF and aliasing were addressed in [8]. Instead of the traditional constant integration, we propose to apply an adaptive low-pass filter to the Fourier spectrum of the pulse-to-pulse correlation function, from which the filtered mean velocity is deduced by PP processing. Working with the spectrum of the correlation function circumvents possible aliasing problems that occur when using the mean velocity. The characteristics of the optimal filter are obtained by applying various optimization schemes to the statistical parameters of the filtered velocity field. […] ”
Impact of Receiver Saturation on Surface Doppler Velocity Measurements
” […] Several factors affect the quality of the Doppler measurements from space, and mitigation strategies have been the subject of extensive research in the recent past […] In addition to the Earth’s surface Doppler velocity, the Earth’s surface echo intensity is also of great interest. In the absence of significant multiple scattering [11] and strong precipitation attenuation, the Earth’s surface produces the highest Cloud Profiling Radar (CPR) returns [12], and its intensity has been used to retrieve the path-integrated attenuation (PIA), a strong constraint in rainfall rate retrievals from space [13]. Two major requirements for the utilization of the Earth’s surface echo for PIA estimates are the absence of multiple scattering [11] and the avoidance of the CPR receiver saturation by the surface return. […]Here, we are concerned with the expected saturation of the EC CPR linear amplifier receiver channel that is used to estimate the Doppler velocity using the I/Q digitized time series. Linear amplifier receivers typically do not compress the amplitude of the return signal, thus saturate much earlier than logarithmic amplifier receivers. In the case of the EC CPR preliminary measurements have demonstrated that the receiver saturation is driven by a clipping-type saturation of the I/Q detector. The linear amplifier receiver is expected to saturate at least 25 dB earlier than the logarithmic receiver (NICT personal communication). Thus, it is expected that the Earth’s surface return will almost always saturate the CPR linear receiver. According to Fig. 1 water and snow/ice-covered surfaces— which accounts for 65% and 11% of the surfaces observed by CloudSat will be saturated for more than 99% of the times while land surfaces (free from snow and ice) will saturate for roughly 75% of the times.
[…] The clipping assumption on the type of receiver saturation therefore represents the fundamental hypothesis underpinning this work. Some of the key science questions that we would like to address are:
- what is the effect of receiver saturation on the estimates of Earth’s surface Doppler velocity for different levels of the signal above the saturation point?
- How CPR receiver saturation will affect the use of Earth’s surface Doppler referencing techniques for correcting the antenna mispointing?
- What is the impact for future systems that will employ either larger antennas or higher Pulse Repetition Frequencies (PRF) to mitigate some of the Doppler challenges from space? […] “
Doppler Velocity Measurements in Particle Sedimentation Regimes
” The availability of Doppler measurements from space will offer a unique opportunity for the collection of a global dataset of vertical motions in clouds and precipitation. Such a global dataset is expected to improve our understanding of convective motions in clouds and to help evaluate current parameterizations of convective mass flux in cloud-resolving models (e.g., Manabe and Strickler 1964; Tiedtke 1989; Bechtold et al. 2001). Furthermore, global climate models (GCMs) required an accurate representation of ice particle sedimentation rates (e.g., Mitchell et al. 2008; Sanderson et al. 2008), which the Cloud Profiling Radar (CPR) Doppler measurements can potentially provide. The Doppler measurements from space will also help to constraint the retrieval of particles’ characteristic size in drizzling and large-scale precipitation conditions. […]Early detailed studies of Doppler measurements with spaceborne radars articulate the challenges in developing Doppler capability for atmospheric research from space due to the platform motion and second-trip echoes (Lhermitte 1989; Amayenc et al. 1993; Meneghini and Kozu 1990). […] The main challenge in space-borne Doppler measurements from low-Earth-orbiting (LEO) satellites arises from their high relative speed (Vsat ; 7.6 km s21) that introduces significant broadening of the Doppler spectrum, even if the radar is pointing perfectly perpendicular to its motion. Doppler velocity aliasing, cloud inhomogeneity (Tanelli et al. 2002a,b; Schutgens 2008), multiple scattering (Battaglia et al. 2010, 2011), and pointing uncertainty (Tanelli et al. 2005) are additional sources of error and uncertainty in Doppler moment estimation from space.
Here, the expected uncertainty in EC-CPR Doppler velocity measurements in nonconvective conditions is investigated using an EC-CPR Doppler velocity simulator that uses as input ground-based radar data. […] ”
