8 research outputs found

    Processing reflectivity and Doppler velocity from EarthCARE's cloud-profiling radar: the C-FMR, C-CD and C-APC products

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    The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission is a joint effort by the European Space Agency (ESA) and the Japanese Aerospace Exploration Agency (JAXA). The EarthCARE mission features the first spaceborne 94 GHz cloud-profiling radar (CPR) with Doppler capability. The raw CPR observations and auxiliary information are used as input to three Level-2 (L2) algorithms: (1) C-APC: Antenna Pointing Characterization; (2) C-FMR: CPR feature mask and reflectivity; (3) C-CD: Corrected CPR Doppler Measurements. These algorithms apply quality control and corrections to the CPR primary measurements and derive important geophysical variables, such as hydrometeor locations, and best estimates of particle sedimentation fall velocities. The C-APC algorithm uses natural targets to introduce any corrections needed to the CPR raw Doppler velocities due to the CPR antenna pointing. The C-FMR product provides the feature mask based on only-reflectivity CPR measurements and quality-controlled radar-reflectivity profiles corrected for gaseous attenuation at 94 GHz. In addition, C-FMR provides best estimates of the path-integrated attenuation (PIA) and flags identifying the presence of multiple scattering in the CPR observations. Finally, the C-CD product provides the quality-controlled, bias-corrected mean Doppler velocity estimates (Doppler measurements corrected for antenna mispointing, non-uniform beam filling and velocity folding). In addition, the best estimate of the particle sedimentation velocity is estimated using a novel technique.</p

    Evaluation of EarthCARE cloud profiling radar doppler velocity measurements in particle sedimentation regimes

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    The joint European Space Agency-Japan Aerospace Exploration Agency (ESA-JAXA) Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is scheduled for launch in 2016 and features the first atmospheric Cloud Profiling Radar (CPR) with Doppler capability in space. Here, the uncertainty of the CPR Doppler velocity measurements in cirrus clouds and large-scale precipitation areas is discussed. These regimes are characterized by weak vertical motion and relatively horizontally homogeneous conditions and thus represent optimum conditions for acquiring high-quality CPR Doppler measurements. A large dataset of radar reflectivity observations from ground-based radars is used to examine the homogeneity of the cloud fields at the horizontal scales of interest. In addition, a CPR instrument model that uses as input ground-based radar observations and outputs simulations of CPR Doppler measurements is described. The simulator accurately accounts for the beam geometry, nonuniform beam-filling, and signal integration effects, and it is applied to representative cases of cirrus cloud and stratiform precipitation. The simulated CPR Doppler velocities are compared against those derived from the ground-based radars. The unfolding of the CPR Doppler velocity is achieved using simple conditional rules and a smoothness requirement for the CPR Doppler measurements. The application of nonuniform beam-filling Doppler velocity bias-correction algorithms is found necessary even under these optimum conditions to reduce the CPR Doppler biases. Finally, the analysis indicates that a minimum along-track integration of 5000mis needed to reduce the uncertainty in the CPR Doppler measurements to below 0.5ms-1 and thus enable the detection of the melting layer and the characterization of the rain- and ice-layer Doppler velocities. © 2014 American Meteorological Society

    Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product

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    The Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission is a joint endeavour developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) and features a 94GHz Doppler Cloud Profiling Radar. This paper presents the theoretical basis of the cloud and precipitation microphysics (C-CLD) EarthCARE Level 2 (L2) algorithm. The C-CLD algorithm provides the best estimates of the vertical profiles of water mass content and hydrometeor characteristic size, obtained from radar reflectivity, path-integrated signal attenuation and hydrometeor sedimentation Doppler velocity estimates using optimal estimation (OE) theory. To obtain the forward model relations and the associated uncertainty, an ensemble-based method is used. This ensemble consists of a collection of in situ measured drop size distributions that cover natural microphysical variability. The ensemble mean and standard deviation represent the forward model relations and their microphysics-based uncertainty. The output variables are provided on the joint standard grid horizontal and EarthCARE Level 1b (L1b) vertical grid (1km along track and 100m vertically). The OE framework is not applied to liquid-only clouds in drizzle-free and lightly drizzling conditions, where a more statistical approach is preferred

    EarthCARE Cloud Profiling Radar (CPR) Doppler measurements in deep convection: challenges, post-processing and science applications

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    The Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite is a joint European Space Agency and Japanese Aerospace Exploration Agency mission scheduled to launch in 2021. EarthCARE (EC) will host the first Doppler cloud profiling radar (CPR) in space which, in addition to constraining microphysical retrievals in particle sedimentation regimes, is expected to provide the first ever global observations of convective vertical air motion and associated mass fluxes. Here, the potential of the EC-CPR velocity measurements in convection is evaluated using forward-simulations performed using a state-of-the-art EC-CPR Doppler simulator and output from high-resolution, bulk microphysics numerical models. Results indicate that the EC-CPR has the potential to measure Doppler velocities in the top 40 % of convective cores, the rest being not observed/contaminated by attenuation and multiple scattering. In these observable regions, non-uniform beam filling (NUBF) and velocity aliasing could affect the quality of the velocity measurements. We show how observed reflectivity gradient can be used to correct for NUBF effects on Doppler velocity to achieve an accuracy higher than 0.3-0.5 ms-1 . Velocity aliasing remains an important challenge. Our results suggest that the current Nyquist velocity of the EC-CPR will enable it to document, with minimal need for de-aliasing correction, convective events with vertical velocity below 7-8 ms-1 while the information collected about more vigorous events is expected to be more challenging to recover. Overall, despite it being affected by several limiting factors, the EC-CPR has the potential to collect valuable velocity observations in deep convection thus complementing the current sparse ground-based record
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