Orographic lifting of air masses and other topographically modified flows induce cloud and precipitation formation at larger scales and preferential deposition of precipitation at smaller scales. In this study, we examine orographic effects on small-scale snowfall patterns in Alpine terrain. A polarimetric X-band radar was deployed in the area of Davos (Switzerland) to determine the spatial variability of precipitation. In order to relate measured precipitation fields to flow dynamics, we model flow fields with the atmospheric prediction model "Advanced Regional Prediction System. " Additionally, we compare radar reflectivity fields with snow accumulation at the surface as modeled by Alpine3D. We investigate the small-scale precipitation dynamics for one heavy snowfall event in March 2011 at a high resolution of 75 m. The analysis of the vertical and horizontal distribution of radar reflectivity at horizontal polarization and differential reflectivity shows polarimetric signatures of orographic snowfall enhancement near the summit region. Increasing radar reflectivity at horizontal polarization over the windward slopes toward the crest and downwind decreasing reflectivity over the leeward slopes is observed. The temporal variation of the location of maximum concentration of snow particles is partly attributed to the effect of preferential deposition of snowfall: For situations with strong horizontal winds, the concentration maximum is shifted from the ridge crest toward the leeward slopes. Qualitatively, we discuss the relative role of cloud microphysics such as the seeder-feeder mechanism versus atmospheric particle transport in generating the observed snow deposition at the ground.

Stratiform rain situations are generally associated with the presence of a melting layer characterized by a strong signature in polarimetric radar variables. This layer is an important feature as it indicates the transition from solid to liquid precipitation. The melting layer remains poorly characterized, particularly from a polarimetric radar point of view. In this work a new algorithm to automatically detect the melting layer on polarimetric RHI radar scans using gradients of reflectivity and copolar correlation is first proposed. The algorithm was applied to high-resolution X-band polarimetric radar data and validated by comparing the height of the detected layer with freezing-level heights obtained from radiosoundings and was shown to give both small errors and bias. The algorithm was then used on a large selection of precipitation events (more than 4000 RHI scans) from different seasons and climatic regions (South of France, Swiss Alps and plateau, and Iowa, USA) to characterize the geometric and polarimetric signatures of the melting layer. The melting layer is shown to have a very similar geometry on average, independent of the topography and climatic conditions. Variations in the thickness of the melting layer during and between precipitation events was shown to be strongly related to the presence of rimed particles, to the vertical velocity of hydrometeors and to the intensity of the bright band.

[1] In mountainous regions, snow accumulation on the ground is crucial for mountain hydrology and water resources. The present study investigates the link between the spatial variability in snowfall and in snow accumulation in the Swiss Alps. A mobile polarimetric X-band radar deployed in the area of Davos (Switzerland) . The spatial distribution of snow accumulation exhibits a strong interannual consistency that can be generalized over the winters in the area. This unique configuration makes the comparison of the variability in total snowfall amount estimated from radar and in snow accumulation possible over the diverse winter periods. As expected, the spatial variability, quantified by means of the variogram, is shown to be larger in snow accumulation than in snowfall. However, the variability of snowfall is also significant, especially over the mountain tops, leads to preferential deposition during snowfall and needs further investigation. The higher variability at the ground is mainly caused by snow transport.

Abstract. Daytime equatorial electrojet plasma irregularities were investigated using five distinct radar diagnostics at Jicamarca including range-time-intensity (RTI) mapping, Faraday rotation, radar imaging, oblique scattering, and multiplefrequency scattering using the new AMISR prototype UHF radar. Data suggest the existence of plasma density striations separated by 3-5 km and propagating slowly downward. The striations may be caused by neutral atmospheric turbulence, and a possible scenario for their formation is discussed. The Doppler shifts of type 1 echoes observed at VHF and UHF frequencies are compared and interpreted in light of a model of Farley Buneman waves based on kinetic ions and fluid electrons with thermal effects included. Finally, the up-down and east-west asymmetries evident in the radar observations are described and quantified.

An ambitious radar deployment to collect high-quality observations of heavy precipitation systems developing over and in the vicinity of a coastal mountain chain is discussed.

The daytime atmospheric convective boundary layer (CBL) is characterized by strong turbulence that is primarily caused by buoyancy forced from the heated underlying surface. The present study considers a combination of a virtual radar and large eddy simulation (LES) techniques to characterize the CBL. Data representative of a daytime CBL with wind shear were generated by LES and used in the virtual boundary layer radar (BLR) with both vertical and multiple off-vertical beams and frequencies. To evaluate the virtual radar, a multiple radar experiment (MRE) was conducted using five virtual radars with common resolution volumes at two different altitudes. Three-dimensional wind fields were retrieved from the virtual radar data and compared with the LES output. It is shown that data produced from the virtual BLR are representative of what one expects to retrieve using a real BLR and the measured wind fields match those of the LES. Additionally, results from a frequency domain interferometry (FDI) comparison are presented, with the ultimate goal of enhancing the resolution of conventional radar measurements. The virtual BLR produces measurements consistent with the LES data fields and provides a suitable platform for validating radar signal processing algorithms.

Agriculture is one of the main economic activities in the Peruvian Andes, rain water alone irrigates more than 80% of the fields used for agriculture purposes. However, the cloud and rain generation mechanisms in the Andes still remain mostly unknown. In early 2014, the Instituto Geofísico del Perú (IGP) decided to intensify studies in the central Andes to better understand cloud microphysics; the Atmospheric Microphysics And Radiation Laboratory officially started operations in 2015 at IGP’ Huancayo Observatory. In this work, a Ka-band cloud profiler (MIRA-35c), a UHF wind profiler (CLAIRE), and a VHF wind profiler (BLTR), are used to estimate rainfall rate at different conditions. The height dependence of the drop size diameter versus the terminal velocity, obtained by the radars, in the central Andes (3350 m asl) was evaluated. The estimates of rainfall rate are validated to ground measurements through a disdrometer (PARSIVEL2) and two rain gauges. The biases in the cumulative rainfall totals for the PARSIVEL2, MIRA-35c, and CLAIRE were 18%, 23%, and -32%, respectively, and their respective absolute biases were 19%, 36%, and 63%. These results suggest that a real-time calibration of the radars, MIRA-35c and CLAIRE, is necessary for better estimation of precipitation at the ground. They also show that the correction of the raindrop terminal fall velocity, obtained by separating the vertical wind velocity (BLTR), used in the estimation the raindrop diameter is not sufficient, especially in convective conditions.

No abstract