Precipitation types | EPFL Graph Search

In meteorology, the different types of precipitation often include the character, formation, or phase of the precipitation which is falling to ground level. There are three distinct ways that precipitation can occur. Convective precipitation is generally more intense, and of shorter duration, than stratiform precipitation. Orographic precipitation occurs when moist air is forced upwards over rising terrain and condenses on the slope, such as a mountain. Precipitation can fall in either liquid or solid phases, is mixed with both, or transition between them at the freezing level. Liquid forms of precipitation include rain and drizzle and dew. Rain or drizzle which freezes on contact with a surface within a subfreezing air mass gains the preceding adjective "freezing", becoming the known freezing rain or freezing drizzle. Slush is a mixture of both liquid and solid precipitation. Frozen forms of precipitation include snow, ice crystals, ice pellets (sleet), hail, and graupel. Their re

Maximisation numérique et mesures acoustiques des précipitations

Knowledge of extreme precipitation phenomena is of crucial importance to the safety of civil engineering works and for electricity production management in a country of lakes and mountains like Switzerland. In order to study the distribution in space and the evolution of strong rain episodes, the work presented here relies on the complementary approaches of field observation and numerical simulation. The experimental portion of this project relies on a novel, acousticbased, rain metrology instrument. Based on the results, a methodology for the determination of raindrop size distribution (disdrometer facility) and rainfall rate (rain gauge facility) has been developed and is described in the present dissertation. In addition, numerical modelling and simulation methods were developed with the aim of calculating — for a given watershed topography — the Probable Maximum Precipitation (PMP). The method relies on the separation of the different phenomenological contributions and on the climatic characterization of atmospheric situations leading to extreme rain events. Boundary and initial conditions are represented by theoretical profiles of the wind speed, wind direction, temperature, and water contents, turbulent energy and dissipation rate variables. The numerical model calculates the consequent wind and rain fields within the simulation domain for the desired atmospheric situation. The hydrodynamic code (CFX4) is based on the finite volume approach and is particularly adapted to complex geometries, allowing an excellent representation of the topography. The code is partially open and several specific atmospheric models were implemented. Microphysics schemes considered are Kessler's warm classic scheme (1969) and the Caniaux detailed scheme (1993). The latter includes solid ice particles, aggregates and graupel and allows the simulation of convective as well as orographic cloud system precipitation cycles. Sensitivity studies of the results with respect to the dominant parameters of each situation, lead to a maximisation procedure successfully applied to convective as well as frontal precipitation. The work shows that the maximisation method consisting of maximising severe events into critical events can be more effective than using statistical approaches. Use of this method compensates for the relative lack of measurement facilities in many regions.

EPFL2004

A polarimetric radar operator to evaluate precipitation from the COSMO atmospheric model

Daniel Wolfensberger

Weather radars provide real-time measurements of precipitation at a high temporal and spatial resolution and over a large domain. A drawback, however, it that these measurements are indirect and require careful interpretation to yield relevant information about the mechanisms of precipitation. Radar observations are an invaluable asset for the numerical forecast of precipitation, both for data assimilation, parametrization of subscale phenomena and model verification. This thesis aims at investigating new uses for polarimetric radar data in numerical weather prediction. The first part of this work is devoted to the design of an algorithm able to automatically detect the location and extent of the melting layer of precipitation , an important feature of stratiform precipitation, from vertical radar scans. This algorithm is then used to provide a detailed characterization of the melting layer, in several climatological regions, providing thus relevant information for the parameterization of melting processes and the evaluation of simulated freezing level heights. The second part of this work uses a multi-scale approach based on the multifractal framework to evaluate precipitation fields simulated by the COSMO weather model with radar observations. A climatological analysis is first conducted to relate multifractal parameters to physical descriptors of precipitation. A short-term analysis, that focuses on three precipitation events over Switzerland, is then performed. The results indicate that the COSMO simulations exhibit spatial scaling breaks that are not present in the radar data. It is also shown that a more advanced microphysics parameterization generates larger extreme values, and more discontinuous precipitation fields, which agree better with radar observations. The last part of this thesis describes a new forward polarimetric radar operator, able to simulate realistic radar variables from outputs of the COSMO model, taking into account most physical aspects of beam propagation and scattering. An efficient numerical scheme is proposed to estimate the full Doppler spectrum, a type of measurement often performed by research radars, which provides rich information about the particle velocities and turbulence. The operator is evaluated with large datasets from various ground and spaceborne radars. This evaluation shows that the operator is able to simulate accurate Doppler variables and realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the polarimetric variables tend to be underestimated. A detailed sensitivity analysis of the radar operator reveals that, in the liquid phase, the simulated radar variables depend very much on the hypothesis about drop geometry and drop size distributions. In the solid phase, the potential of more advanced scattering techniques is investigated, revealing that these methods could help to resolve the strong underestimation of polarimetric variables in snow and graupel.

EPFL2018

Multifractal evaluation of simulated precipitation intensities from the COSMO NWP model

Alexis Berne, Daniel Wolfensberger

The framework of universal multifractals (UM) characterizes the spatio-temporal variability in geophysical data over a wide range of scales with only a limited number of scale-invariant parameters. This work aims to clarify the link between multifractals (MFs) and more conventional weather descriptors and to show how they can be used to perform a multi-scale evaluation of model data. The first part of this work focuses on a MF analysis of the climatology of precipitation intensities simulated by the COSMO numerical weather prediction model. Analysis of the spatial structure of the MF parameters, and their correlations with external meteorological and topographical descriptors, reveals that simulated precipitation tends to be smoother at higher altitudes, and that the mean intermittency is mostly influenced by the latitude. A hierarchical clustering was performed on the external descriptors, yielding three different clusters, which correspond roughly to Alpine/continental, Mediterranean and temperate regions. Distributions of MF parameters within these three clusters are shown to be statistically significantly different, indicating that the MF signature of rain is indeed geographically dependent. The second part of this work is event-based and focuses on the smaller scales. The MF parameters of precipitation intensities at the ground are compared with those obtained from the Swiss radar composite during three events corresponding to typical synoptic conditions over Switzerland. The results of this analysis show that the COSMO simulations exhibit spatial scaling breaks that are not present in the radar data, indicating that the model is not able to simulate the observed variability at all scales. A comparison of the operational one-moment microphysical parameterization scheme of COSMO with a more advanced two-moment scheme reveals that, while no scheme systematically outperforms the other, the two-moment scheme tends to produce larger extreme values and more discontinuous precipitation fields, which agree better with the radar composite.

Copernicus GmbH2017