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The European Space Agency (ESA) wind mission, Aeolus, hosts the first space-based Doppler Wind Lidar (DWL) world-wide. The primary mission objective is to demonstrate the DWL technique for measuring wind profiles from space, intended for assimilation in Numerical Weather Prediction (NWP) models. The wind observations will also be used to advance atmospheric dynamics research and for evaluation of climate models. Mission spin-off products are profiles of cloud and aerosol optical properties. Aeolus was launched on 22 August 2018, and the Atmospheric LAser Doppler INstrument (Aladin) instrument switch-on was completed with first high energy output in wind mode on 4 September 2018 [1], [2]. The on-ground data processing facility worked excellent, allowing L2 product output in near-real-time from the start of the mission. First results from the wind profile product (L2B) assessment show that the winds are of very high quality, with random errors in the free Troposphere within (cloud/aerosol backscatter winds: 2.1 m/s) and larger (molecular backscatter winds: 4.3 m/s) than the requirements (2.5 m/s), but still allowing significant positive impact in first preliminary NWP impact experiments. The higher than expected random errors at the time of writing are amongst others due to a lower instrument out-and input photon budget than designed. The instrument calibration is working well, and some of the data processing steps are currently being refined to allow to fully correct instrument alignment related drifts and elevated detector dark currents causing biases in the first data product version. The optical properties spin-off product (L2A) is being compared e.g. to NWP model clouds, air quality model forecasts, and collocated ground-based observations. Features including optically thick and thin particle and hydrometeor layers are clearly identified and are being validated.

We examine the linearity of the Ensemble of Data Assimilations ( EDA) technique with respect to the amplitude of the applied observation perturbations. We provide explicit examples to assess the linear relationship between such modifications of the observing system and the resulting changes in the EDA ensemble spread. The results demonstrate that, for a state-of-the-art numerical weather prediction ( NWP) system, such linearity between the applied observation perturbations and the EDA ensemble spread holds well for temporal and spatial regimes relevant to global medium-range weather prediction: specifically, for forecast lead-times of up to approximately 5 days, in the vertical throughout the troposphere up to the lower and middle stratosphere and for broad horizontal scales. [ABSTRACT FROM AUTHOR]

The ESA Aeolus mission aims to measure wind profiles from space. In preparation for launch we aim to assess the expected bias in retrieved winds from the Mie and Rayleigh channel signals induced by atmospheric heterogeneity. Observation biases are known to be detrimental when gone undetected in Numerical Weather Prediction (NWP). Aeolus processing equipment should therefore be prepared to detect heterogeneous atmospheric scenes and take measures, e.g., reject or reduce the weight of observations when used in NWP. Radiosondes provide the wind vector at about 10m resolution. We present a method to simulate co-located cloud and aerosol optical properties from radiosonde observations. We show that cloud layers can be detected along the radiosonde path from radiosonde measured relative humidity and temperature. A parameterization for aerosol backscatter and extinction along the radiosonde path is presented based on a climatological aerosol backscatter profile and radiosonde relative humidity. The resulting high-resolution database of atmospheric wind and optical properties serves as input for Aeolus wind simulations. It is shown that Aeolus wind error variance grows quadratically with bin size and the wind-shear over the bin. Strong scattering aerosol or cloud layers may cause biases exceeding 1 ms-1 for typical tropospheric conditions and 1 km Mie channel bin size, i.e., substantially larger than the mission bias requirement of 0.4 ms-1. Advanced level-2 processing of Aeolus winds including estimation of atmosphere optical properties is needed to detect regions with large heterogeneity, potentially yielding biased winds. Besides applicable for Aeolus the radiosonde database of co-located high-resolution wind and cloud information can be used for the validation of atmospheric motion wind vectors (AMV) or to correct their height assignment errors. [ABSTRACT FROM AUTHOR]

The article focuses on the concept of atmospheric database as an important component of simulation studies in preparation of future earth observing remote sensing satellites. It mentions the ADM-Aeolus mission which was scheduled for launch in medium 2012 to measure wind profiles from the surface up to about 32 kilometers with a global coverage. Further, it notes that the vertical profile resolution is limited but may be changed during in-orbit operation.

A new 3D Fourier imaging method based on sparse radial scanning (SRS-FT) of k space is proposed. It allows acquisition of FIDs and is therefore well suited to imaging objects with very short T2. Use of a Bayesian procedure allows (1) an important reduction of scan time to below that of the projection-reconstruction (PR) method by reducing the number of "Cartesian radial" encoding directions, and (2) a good image quality by estimating missing and corrupted Cartesian samples. SRS-FT images reconstructed from FIDs are compared to conventional FT and PR images.