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Jan Handwerker and Winfried Straub

Abstract

Measured raindrop size distributions are often approximated by analytical functions. The parameters determining such functions are usually derived from measured data. This procedure can suffer from various uncertainties. The most important of which are (i) the limited detection range of measuring devices such as, for example, disdrometers, and (ii) poor statistics resulting from the rare appearance of relatively large drops.

One way to derive the parameters is the moments method that has a degree of freedom in the choice of the moments. The aim of this study is to find an optimal choice of moments. To this end, numerical experiments are performed by calculating random samples from drop populations with gamma-shaped size distributions. These samples are evaluated as they were recorded by an ideal disdrometer whose single limitation is the cutoff with respect to very small and very large raindrops. From that data the parameters mentioned above are determined by the moments method. The truncation of the measurement is explicitly taken into account during the retrieval. Further, all possible combinations of three different moments used to derive the gamma parameters are impartially compared.

It turns out that parameters derived on the basis of low-order moments are less affected by biases and noise than parameters derived by larger-order moments, that is, the sampling problem is more severe than the truncation problem, especially because the latter can be overcome much more efficiently within the retrieval algorithm. It is shown that by using very low-order moments and estimating the unmeasured fraction of the moments, optimal results from real measurements can be obtained.

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Katja Träumner, Jan Handwerker, Andreas Wieser, and Jens Grenzhäuser

Abstract

Remote sensing systems like radars and lidars are frequently used in atmospheric measurement campaigns. Because of their different wavelengths, they operate in different scattering regimes. Combined use may result in new measurement options. Here, an approach to estimate raindrop size distribution using vertical velocities measured by a lidar–radar combination is introduced and tested using a 2-μm Doppler lidar and a 35.5-GHz cloud radar. The lidar spectra are evaluated to deduce air motion from the aerosol peak and the fall velocity of the raindrops from the rain peak. The latter is weighted by the area (D 2) of the scatters. The fall velocity derived from radar measurements is weighted by D 6 (Rayleigh approximation). Assuming a size-dependent fall velocity and an analytical description of the drop size distribution, its parameters are calculated from these data. Comparison of the raindrop size distribution from the lidar–radar combination with in situ measurements on the ground yields satisfying results.

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Pieter Groenemeijer, Christian Barthlott, Ulrich Corsmeier, Jan Handwerker, Martin Kohler, Christoph Kottmeier, Holger Mahlke, Andreas Wieser, Andreas Behrendt, Sandip Pal, Marcus Radlach, Volker Wulfmeyer, and Jörg Trentmann

Abstract

Measurements of a convective storm cluster in the northern Black Forest in southwest Germany have revealed the development of a warm and dry downdraft under its anvil cloud that had an inhibiting effect on the subsequent development of convection. These measurements were made on 12 July 2006 as part of the field campaign Prediction, Identification and Tracking of Convective Cells (PRINCE) during which a number of new measurement strategies were deployed. These included the collocation of a rotational Raman lidar and a Doppler lidar on the summit of the highest mountain in the region (1164 m MSL) as well as the deployment of teams carrying radiosondes to be released in the vicinity of convective storms. In addition, an aircraft equipped with sensors for meteorological variables and dropsondes was in operation and determined that the downdraft air was approximately 1.5 K warmer, 4 g kg−1 drier, and therefore 3 g m−3 less dense than the air at the same altitude in the storm’s surroundings. The Raman lidar detected undulating aerosol-rich layers in the preconvective environment and a gradual warming trend of the lower troposphere as the nearby storm system evolved. The Doppler lidar both detected a pattern of convergent radial winds under a developing convective updraft and an outflow emerging under the storm’s anvil cloud. The dryness of the downdraft air indicates that it had subsided from higher altitudes. Its low density reveals that its development was not caused by negative thermal buoyancy, but was rather due to the vertical mass flux balance accompanying the storm’s updrafts.

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