Microphysical Characteristics Of Precipitation Research Articles

基于单帧双脉冲成像的降水微物理特征测量仪

基于单帧双脉冲成像的降水微物理特征测量仪

Measuring Hydrometeors with a Precipitation Microphysical Characteristics Sensor: Calibration and Field Measurements

Aiming at the simultaneous measurement of the size, shape, and fall velocity of precipitation particles in the natural environment, we present here a new ground-based precipitation microphysical characteristics sensor (PMCS) based on the particle imaging velocimetry technology. The PMCS can capture autocorrelated images of precipitation particles by double-exposure in one frame, by which the size, axis ratio, and fall velocity of precipitation particles can be calculated. The PMCS is calibrated by a series of glass balls with certain diameters under varying light conditions, and a self-adaptive threshold method is proposed. The shape, axis ratio, and fall velocity of raindrops were calculated and discussed based on the field measurement results of PMCS. The typical shape of large raindrop is an oblate ellipsoid, the axis ratio of raindrops decreases linearly with the diameter, the fall velocity of raindrops approaches its asymptote, and the above observed results are in good agreement with the empirical models; the synchronous observation of a PMCS, an OTT PARSIVEL disdrometer, and a rain gauge shows that the PMCS is able to measure the rain intensity, accumulated rainfall, and drop size distribution with high accuracy. These results have validated the performance of PMCS.

Research on microphysical property of snowfall based on particle imaging velocimetry technology

In order to obtain the microphysical features of snowflakes under the natural conditions by using the self-developed sensor, precipitation microphysical characteristics, capture probability, and space distribution retrieve algorithm based on the velocity of snowflakes are discussed; and the shape, size, velocity, axial ratio, orientation and the space distribution of snowflakes are investigated by the field observation. Results show that the snowlakes may take needles, flakes, and oblate ellipsoids shapes; the falling velocity of snowflakes will increase slightly with inereasing diameter, their axial ratio may increase linearly with the diameter, and their orientations are easily influenced by the wind; the canting angle may be 0.9° and tends to be nearly symmetric with a standard deviation around 13.2°. Empirical equations of velocity and diameter, and of axial ratio and diameter are fitted by nonlinear fitting and linear fitting of observed data respectively. Compared with previous model proposed by authors abroad, this paper further provides the microphysical characteristics of snowflakes with localization features. The above conclusions can be of significance for the research on cloud precipitation physics, ground validation of weather radar, assessment of precipitation-induced microwave attenuation, etc.

Rainfall interception by maize canopy: Development and application of a process-based model

• Simple canopy generator reproduces observed canopy gap fraction. • Model predicts dripping locations, which can trigger localized soil erosion. • Model confirms splashing as considerable source of small throughfall droplets. • Predicted throughfall spatial distribution poses a challenge to correct sampling. The interaction between rain drops and crop canopies changes the microphysical characteristics of precipitation. Understanding the mechanisms driving these changes is a key step towards unveiling the mechanics of soil water recharge, soil erosion under crop canopies, and evaporation of intercepted rainfall. The latter caused by, for example, the reduced aerodynamic resistance to evaporation of splashed droplets. We propose a model that uses drop-size and velocity distributions as well as the three-dimensional geometry of the maize canopy to simulate the movement of raindrops on the surface of the leaves. The model accounts for the interception, redirection, retention, coalescence, and re-interception of drops to predict the location, size, and velocity of throughfall drops beneath the canopy. The throughfall results are presented as two-dimensional matrices, in which each term corresponds to the accumulated volume of drops that dripped in that location, which offers insight into its spatial distribution under the foliage. We examine the modification of the drop-size distribution by the maize canopy by recalculating the drop velocity based on their size and detachment height. They built the three-dimensional digital canopy that is employed in the simulation by creating modified copies of one photogrammetry-generated digital model of a plant located inside their experimental site. The canopy model accounts for the projected overlap of the single plant leaves. We evaluate the results against measurements obtained during 10 storms that occurred between 14 July 2009 and 28 August 2009 in Shueyville, Iowa. The comparison between observations and simulations corroborates the drop detachment threshold of 3.75 mm and indicates that splashing, as opposed to considering solely the rolling or bouncing of droplets that lack the kinetic energy to attach to the foliage, is the likely source of throughfall drops with diameters smaller than 1 mm. The predicted throughfall spatial distribution unveils localized dripping points, which pose a challenge to the correct sampling of throughfall.

Polarimetric radar modeling of mixtures of precipitation particles

With the advances of dual-polarized radar techniques in meteorology it is now possible to deduce precipitation microphysical characteristics in far more detail than possible with reflectivity measurements alone. Radar parameters such as differential reflectivity and differential phase between horizontal and vertical polarizations have been studied in detail as well as linear depolarization ratio, copolar correlation coefficient, and backscatter differential phase. While these parameters can be linked to certain microphysical properties of specific classes of precipitation such as raindrops or hail, very little study has been directed at the practically important cases of mixtures of different types of precipitation particles such as rain, hail, graupel, ice crystals, and snow. Each type can have different size, shape, orientation, and dielectric constant distributions. The present treatment is rigorous and is based on the Mueller matrix formulation. Radar parameters are derived from the averaged Mueller matrix computations. Careful consideration is given to the orientation and size distributions of the different particle types. After calculating single particle scattering characteristics, some simple two-component mixtures such as rain/hail and ice crystals/snow are considered. Finally, a 2D numerical cloud model is used to simulate the rain, hail/graupel, and snow fields of an evolving convective storm from which the radar parameters are derived for the initial, peak, and dissipating stages of the storm. Model computations are performed at C and S-band frequencies.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>