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Agriculture is one of the main economic activities in the Peruvian Andes; rainwater 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’s Huancayo Observatory. In this work, a Ka-band cloud profiler [cloud and precipitation profiler (MIRA-35c)], a UHF wind profiler [Clear-Air and Rainfall Estimation (CLAIRE)], and a VHF wind profiler [Boundary Layer and Tropospheric Radar (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 MSL) was evaluated. The estimates of rainfall rate are validated to ground measurements through a disdrometer [second-generation Particle, Size, and Velocity (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.

A set of instruments to measure several physical, microphysical, and radiative properties of the atmosphere and clouds are essential to identify, understand and, subsequently, forecast and prevent the effects of extreme meteorological events, such as severe rainfall, hailstorms, frost events and high pollution events, that can occur with some regularity in the central Andes of Peru. However, like many other Latin American countries, Peru lacks an adequate network of meteorological stations to identify and analyze extreme meteorological events. To partially remedy this deficiency, the Geophysical Institute of Peru has installed a set of specialized sensors (LAMAR) on the Huancayo observatory (12.04° S, 75.32° W, 3350 m ASL), located in the Mantaro river basin, which is a part of the central Andes of Peru, especially in agricultural areas. LAMAR consists of a set of sensors that are used to measure the main atmosphere and soil variables located in a 30-meter-high tower. It also has a set of high-quality radiation sensors (BSRN station) that helps measure the components of short-wave (SW) (global, diffuse, direct and reflected) and long-wave (LW) (emitted and incident) irradiance mounted in a 6-meter-high tower. Moreover, to analyze the microphysics properties of clouds and rainfall, LAMAR includes a set of profiler radars: A Ka-band cloud profiler (MIRA-35c), a UHF wind profiler (CLAIRE), and a VHF wind profiler (BLTR), along with two disdrometers (PARSIVEL2) and two rain gauges pluviometers. The present study performs a detailed dynamic and energetic analysis of two extreme rainfall events, two intense frost events, and three high-pollution events occurring on the Huancayo observatory between 2018 and 2019. The results show that the rainfall events are similar to the 1965–2019 climatological 90th percentile of the daily accumulated rainfall. The results also highlighted the patterns of reflectivity in function of height for both events, which is measured by highlighting the presence of convective and stratiform rainfall types for both events. The first intense rainfall event was associated with strong easterly circulations at high levels of the atmosphere, and the second one was associated with the presence of strong westerly circulations and the absence of BH-NL system around the central Andes. The first frost event was mainly associated with continuous clear sky conditions in the few previous days, corresponding to a radiative frost event. The second one was mainly associated with the intrusion of cold surges from extra-tropical South America. For both events, the energy budget components were strong-lower in comparison to the mean monthly values during early morning hours. Finally, for the high pollution events, the study identified that the main source of aerosols were the forest fires that took place in Peru with certain contributions from the fires in the northern area of Bolivia.

The first weather radar campaign over Lima, the capital of Peru, a desertic area on the western side of the Peruvian Andes, was carried out to study the occurrence of rain events in summer 2018. The weather radar was installed strategically and was able to overlook three river basins: Rimac, Chillon, and Lurin. An X-band radar (PX-1000) was used, which operates at 9.55 GHz. PX-1000 was built by the Advanced Radar Research Center (ARRC) at the University of Oklahoma (U.S.A.). The radar operated from January 26th to April 1st, 2018, at Cerro Suche located 2910 m ASL and 55 km from the city of Lima. The PX-1000 performed plan-position-indicators (PPI) for elevations starting at 0° up to 20°. The data presented here were obtained using a three-dimensional constant-altitude plan-position-indicator (3D CAPPI), which was generated by high resolution (250 m) nearest point algorithm.

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.

The development of Unmanned Aerial Vehicles (UAVs) has gained importance over the last few years due to the innovations brought to farming, architecture, and/or medicine. A novel field where they have been used is volcanology for its long-distance control and the possibility to add multiple sensors for sensing volcano parameters. Two UAVs will be constructed: a multi-rotor (quadcopter) and a fix wing airplane for studying the most active volcano in Peru, the Ubinas. The objective is to get important and useful volcano data without risking the lives of researchers. The quadcopter will be used for image capturing and video recording of the plume, while the airplane will fly close or through to the volcanic plume measuring temperature, humidity, carbon dioxide, sulfuric dioxide, and hydrogen sulfide.

[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) collected valuable and continuous information on small-scale precipitation for the winter seasons of 2009/2010 and 2010/2011. Local measurements of snow accumulation were collected with airborne laser-scanning for the winters of 2007/2008 and 2008/2009. 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.

Due to diverse and extreme weather conditions, the Peruvian population is vulnerable to high-impact natural disasters. A continuous monitoring of all weather conditions is necessary for accurate weather models, forecast, and nowcast along the territory. To cope with this problem, the Jicamarca Radio Observatory (JRO) is developing a low-cost, portable CLear AIr and Rainfall Estimations (CLAIRE) Radar that will provide tropospheric winds, turbulence, and rainfall estimations that will help analyze and quantify meteorological phenomena. CLAIRE consists of four Yagi-Uda antenna phased arrays, one for transmission and three for reception, arranged in a quasimonostatic system. The 445-MHz CLAIRE system is sensitive to both clear-air and precipitation echoes. The aim is to separate the two types of echoes through spectral analysis and process them independently. For the wind and turbulence measurements, Spaced Antenna technique will be applied, while precipitation measurements will be obtained by analyzing the corresponding radar reflectivity factor (Ze).

The daytime convective boundary layer (CBL) is characterized by strong turbulence that is primarily forced by buoyancy transport from the heated underlying surface. The present study focuses on an example of flow structure of the CBL as observed in the U.S. Great Plains on June 8, 2007. The considered CBL flow has been reproduced using a numerical large eddy simulation (LES), sampled with an LES-based virtual boundary layer radar (BLR), and probed with an actual operational radar profiler. The LES-generated CBL flow data are then ingested by the virtual BLR and treated as a proxy for prevailing atmospheric conditions. The mean flow and turbulence parameters retrieved via each technique (actual radar profiler, virtual BLR, and LES) have been cross-analyzed and reasonable agreement was found between the CBL wind parameters obtained from the LES and those measured by the actual radar. Averaged vertical velocity variance estimates from the virtual and actual BLRs were compared with estimates calculated from the LES for different periods of time. There is good agreement in the estimates from all three sources. Also, values of the vertical velocity skewness retrieved by all three techniques have been inter-compared as a function of height for different stages of the CBL evolution, showing fair agreement with each other. All three retrievals contain positively skewed vertical velocity structure throughout the main portion of the CBL. Radar estimates of the turbulence kinetic energy (eddy) dissipation rate (ε) have been obtained based on the Doppler spectral width of the returned signal for the vertical radar beam. The radar estimates were averaged over time in the same fashion as the LES output data. The agreement between estimates was generally good, especially within the mixing layer. Discrepancies observed above the inversion layer may be explained by a weak turbulence signal in particular flow configurations. The virtual BLR produces voltage measurements consistent with the LES data fields. First-, second-, and third-order statistics (mean wind, variance, and skewness) of vertical velocity obtained from BLR output demonstrate its suitability for validating radar-profiler signal processing algorithms.

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.

The radar network deployed in southern France during the first special observing period (SOP 1) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX) was designed to precisely document the 3D structure of moist upstream flow impinging on complex terrain as a function of time, height, and along-barrier distance, and surface rainfall patterns associated with orographic precipitation events. This deployment represents one of the most ambitious field experiments yet, endeavoring to collect high-quality observations of thunderstorms and precipitation systems developing over and in the vicinity of a major mountain chain. Radar observations collected during HyMeX represent a valuable, and potentially unique, dataset that will be used to improve our knowledge of physical processes at play within coastal orographic heavy precipitating systems and to develop, and evaluate, novel radar-based products for research and operational activities. This article provides a concise description of this radar network and discusses innovative research ideas based upon preliminary analyses of radar observations collected during this field project with emphasis on the synergetic use of dual-polarimetric radar measurements collected at multiple frequencies.

Estimates of the wind retrieved from boundary layer radars are inherently averaged in space and time. Using large eddy simulation (LES) results, we are able to examine to what extent these measurements are representative of the underlying parameters of the convective boundary layer (CBL) and how they are impacted by various averaging methodologies. Comparisons between an LES with real forcing and Boundary Layer Radar (BLR) wind retrievals have been analyzed. Good agreement between the LES winds and those estimated using the BLR is observed. After removing an instrumental bias, an estimate of the probability density function (PDF) and skewness of the radar and LES vertical velocity estimates was calculated as a function of height. The PDFs of vertical velocity and the height profiles of the skewness of vertical velocity exhibit good agreement for both the LES and BLR calculations and have the expected canonical structure.