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This study elaborates on how aircraft-based horizontal geometries of trade wind cumulus clouds differ whether a one-dimensional (1D) profiler or a two-dimensional (2D) imager is used. While nadir profiling devices are limited to a 1D realization of the cloud transect size, with limited representativeness of horizontal cloud extension, 2D imagers enhance our perspectives by mapping the horizontal cloud field. Both require high resolutions to detect the lower end of the cloud size spectrum. In this regard, the payload aboard the HALO (High Altitude and LOng Range Research Aircraft) achieves a comparison and also a synergy of both measurement systems. Using the NARVAL II (Next-Generation Aircraft Remote-Sensing for Validation Studies) campaign, we combine HALO observations from a 35.2 GHz cloud and precipitation radar (1D) and from the hyperspectral 2D imager specMACS (Munich Aerosol Cloud Scanner), with a 30 times higher along-track resolution, and compare their cloud masks. We examine cloud size distributions in terms of sensitivity to sample size, resolution and the considered field of view (2D or 1D). This specifies impacts on horizontal cloud sizes derived from the across-track perspective of the high-resolution imager in comparison to the radar curtain. We assess whether and how the trade wind field amplifies uncertainties in cloud geometry observations along 1D transects through directional cloud elongation. Our findings reveal that each additional dimension, no matter of the device, causes a significant increase in observed clouds. The across-track field yields the highest increase in the cloud sample. The radar encounters difficulties in characterizing the trade wind cumuli size distribution. More than 60 % of clouds are subgrid scale for the radar. The radar has issues in the representation of clouds shorter than 200 m, as they are either unresolved or are incorrectly displayed as single grid points. Very shallow clouds can also remain unresolved due to too low radar sensitivity. Both facts deteriorate the cloud size distribution significantly at this scale. Double power law characteristics in the imager-based cloud size distribution do not occur in radar observations. Along-track measurements do not necessarily cover the predominant cloud extent and inferred geometries' lack of representativeness. Trade wind cumuli show horizontal patterns similar to ellipses, with a mean aspect ratio of 3:2 and having tendencies of stronger elongation with increasing cloud size. Instead of circular cloud shape estimations based on the 1D transect, elliptic fits maintain the cloud area size distribution. Increasing wind speed tends to stretch clouds more and tilts them into the wind field, which makes transect measurements more representative along this axis. [ABSTRACT FROM AUTHOR]

This study elaborates how aircraft-based horizontal geometries of trade-wind cumulus clouds differ whether a one-dimensional (1D) profiler or a two-dimensional (2D) imager is used. While nadir profiling devices are limited to 1D realisation of the cloud transect size with limited representativeness of horizontal cloud extension, 2D imagers enhance our perspectives by mapping the horizontal cloud field. Both require high-resolution to detect the lower end of the cloud size spectrum. In this regard, the payload aboard the High Altitude and Long Range Research Aircraft (HALO) achieves a comparison and also a synergy of both measurement systems. Using the NARVAL-II campaign, we combine HALO observations from a 35.2 GHz cloud and precipitation radar (1D) and from the hyperspectral 2D imager specMACS, having a 30 times higher along-track resolution and compare their cloud masks. We examine cloud size distributions in terms of sensitivity to sample size, resolution and the considered field of view (2D or 1D). This specifies impacts on horizontal cloud sizes derived from the across-track perspective of the high-resolution imager in comparison to the radar curtain. We assess whether and how the trade-wind field amplifies uncertainties in cloud geometry observations along 1D transects through directional cloud elongation. Our findings reveal that each additional dimension, no matter of the device, causes a significant increase of observed clouds. The across-track field yields the highest increase in the cloud sample. The radar encounters difficulties to characterize the trade-wind cumuli size distribution. More than 60 % of clouds are subgrid scale for the radar. While the radar cannot resolve clouds shorter than 200 m and has a lower sensitivity, the amount of small invisible clouds leads to deviations in the size distribution. Double power law characteristics in the imager based cloud size distribution do not occur in radar observations. Along-track measurements do not necessarily cover the predominant cloud extent and inferred geometries lack of representativeness. Trade-wind cumuli show horizontal patterns similar to ellipses with a mean aspect ratio of 3: 2. Instead of circular estimations based on the 1D transect, elliptic fits maintain the cloud area size distribution. Increasing wind speed tends to stretch clouds more and tilts them into the wind field, which makes transect measurements more representative along this axis. [ABSTRACT FROM AUTHOR]