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A method for estimating cloud‐base heights (CBHs) across wide swaths of passive satellite imagery is introduced. The constrained spectral radiance matching (CSRM) algorithm assigns donor columns observed by CloudSat/CALIPSO to recipient pixels across MODIS imagery. The column meeting the constraint is selected as a donor via spectral radiance matching (SRM). Results are compared using eight cloud characteristics, retrieved from passive imagery, as constraints and distinct values for a matching controlling factor α. Cloud‐top pressure and α = 0.3 are used in the final algorithm. Estimates are made of CBH and layer‐cloud fraction profile made by SRM, CSRM, cloud‐type matching (CTM), and retrieved data matching (RDM) using a data‐exclusion procedure. Results show that the CSRM is superior at estimating lowest CBH and layer‐cloud fraction. It is also shown that, when cloud types are provided by merged CloudSat and CALIPSO data, the CTM provides the best estimates of uppermost CBH, with the CSRM taking second. Both the CSRM method and the straight SRM method construct layer‐cloud fraction profiles very well for clouds between 2 and ∼15 km. A preliminary 3D rendering of tropical storm Soulik is presented.

Abstract. The European Space Agency Aeolus mission aims to measure wind profiles from space. A major challenge is to retrieve high quality winds in heterogeneous atmospheric conditions, i.e. where both the atmospheric dynamics and optical properties vary strongly within the sampling volume. In preparation for launch we aim to quantify the expected error of retrieved winds from atmospheric heterogeneity, particularly in the vertical, and develop algorithms for wind error correction, as part of the level-2B processor (L2Bp).We demonstrate that high-resolution data from radiosondes provide valuable input to establish a database of collocated wind and atmospheric optics at 10 m vertical resolution to simulate atmospheric conditions along Aeolus' lines of sight. The database is used to simulate errors of Aeolus winds retrieved from the Mie and Rayleigh channel signals. The non-uniform distribution of molecules in the measurement bin introduces height assignment errors in Rayleigh channel winds up to 2.5 % of the measurement bin size in the stratosphere which translates to 0.5 m s −1 bias for typical atmospheric conditions, if not corrected. The presence of cloud or aerosol layers in the measurement bin yields biases in Mie channel winds which cannot be easily corrected and mostly exceed the mission requirement of 0.4 m s −1 . The collocated Rayleigh channel wind solution is generally preferred because of smaller biases, in particular for transparent cloud and aerosol layers with one-way transmission above 0.8.The results show that Aeolus L2Bp, under development, can be improved by the estimation of atmosphere optical properties to correct for height assignment errors and to identify wind solutions potentially detrimental when used in Numerical Weather Prediction.

Abstract.A new method to determine the shape and fall velocity of hydrometeors by using a single CCD camera is proposed in this paper, and a prototype of a video precipitation sensor (VPS) is developed. The instrument consists of an optical unit (collimated light source with multi-mode fibre cluster), an imaging unit (planar array CCD sensor), an acquisition and control unit, and a data processing unit. The cylindrical space between the optical unit and imaging unit is sampling volume (300 mm × 40 mm × 30 mm). As the precipitation particles fall through the sampling volume, the CCD camera exposes twice in a single frame, which allows the double exposure of particles images to be obtained. The size and shape can be obtained by the images of particles; the fall velocity can be calculated by particle displacement in the double-exposure image and interval time; the drop size distribution and velocity distribution, precipitation intensity, and accumulated precipitation amount can be calculated by time integration. The innovation of VPS is that the shape, size, and velocity of precipitation particles can be measured by only one planar array CCD sensor, which can address the disadvantages of a linear scan CCD disdrometer and an impact disdrometer. Field measurements of rainfall demonstrate the VPS's capability to measure micro-physical properties of single particles and integral parameters of precipitation.

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