The ability of the WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to forecast extreme rainfall in the Central Andes of Peru is evaluated in this study, using observations from stations located in the Mantaro basin and GOES (Geostationary Operational Environmental Satellite) images. The evaluation analyzes the synoptic conditions averaged over 40 extreme event cases, and considers model simulations organized in 4 nested domains. We first establish that atypical events in the region are those with more than 27 mm of rainfall per day when averaging over all the stations. More than 50% of the selected cases occurred during January, February, and April, with the most extreme occurring during February. The average synoptic conditions show negative geopotential anomalies and positive humidity anomalies in 700 and 500 hPa. At 200 hPa, the subtropical upper ridge or “Bolivian high” was present, with its northern divergent flank over the Mantaro basin. Simulation results show that the Weather Research and Forecasting (WRF) model underestimates rainfall totals in approximately 50–60% of cases, mainly in the south of the basin and in the extreme west along the mountain range. The analysis of two case studies shows that the underestimation by the model is probably due to three reasons: inability to generate convection in the upstream Amazon during early morning hours, apparently related to processes of larger scales; limitations on describing mesoscale processes that lead to vertical movements capable of producing extreme rainfall; and limitations on the microphysics scheme to generate heavy rainfall.

The aim of the present study is to analyze the triggering mechanisms of three thunderstorms (TSs) associated with severe rainfall, hail and lightening in the tropical central Andes of Peru, specifically above the Huancayo observatory (12.04 ${}^{\circ }$ S, 75.32 ${}^{\circ }$ W, 3313 m a.s.l.) located in the Mantaro valley during the spring-summer season (2015–2016). For this purpose, we used a set of in-situ pluviometric observations, satellite remote sensing data, the Compact Meteorological Ka-Band Cloud Radar (MIRA-35C), the Boundary Layer Tropospheric Radar and downscaling model simulations with the Weather Research and Forecasting (WRF) Model (resolutions: 18 km, 6 km and 2 km), and the Advance Regional Prediction System (ARPS) (resolution: 0.5 km) models in order to analyze the dynamic of the atmosphere in the synoptic, meso and local scales processes that control the occurrence of the three TS events. The results show that at synoptic scale, the TSs are characterized by the southern displacement of the South-east Pacific Subtropical Anticyclone up to latitudes higher than 35 ${}^{\circ }$ S, by the weakening and south-eastern displacement of the Bolivian high–North east low system and by the intrusion of westerly winds along the west side of the central Andes at upper and medium levels of the atmosphere. At meso-scale, apparently, two important moisture fluxes from opposite directions are filtered through the passes along the Andes: one from the north-west and the other from the south-east directions converge and trigger the deep convection into the Mantaro valley. These moisture fluxes are generated by the intrusion of the sea-breeze from the Pacific ocean along the west of the Andes coupling with upper and middle westerly winds and by the thermally induced moisture fluxes coming from the South American low level jet at the east side of the Andes. At the local scale, there is a low-level conditional instability in the previous hours as well as during the occurrence of the TSs above the Huancayo observatory. In addition, the simulation results indicated the possibility of generation of inertial gravity waves in the Amazon basin, associated with geostrophic adjustment which transports energy and moisture into the central Andes plateau and consequently intensifies the thunderstorms above the Mantaro valley.

Global precipitation measurement (GPM) launched in February 2014 as a legacy of Tropical Rainfall Measuring Mission (TRMM). Both satellites carry precipitation radar (PR), which measures the three-dimension structure of precipitation from space. Compared to TRMM PR, GPM has dual-polarized radar (DPR) and provides the raindrop size distribution (DSD) including mass-weighted mean diameter (D_m, in mm) and normalized DSD scaling parameter for concentration (N_w, in mm^–1 m^–3) (DSD parameters), along with radar reflectivity factor (Z_e) from the surface to 21.875 km. Here we investigated the regional differences in intense convective clouds over South East & South Asia (SESA) and explored the differences in the East and West coast of India, by selecting the various areas. We defined two types of clouds, namely Cumulonimbus towers (CbTs) and intense convective clouds (ICCs) based on the Z_e and height thresholds. CbTs must consist of 20 dBZ at 12 km, with echo base height less than 3 km, where ICCs are classified based on Z_e threshold at 8 km (ICC8) and 3 km (ICC3). The average vertical profiles of CbTs indicate a strong west to east gradient, as the west side/coast of India has intense CbTs, with higher hydrometeors size, and decreases at east side/coast of India. The results reveal that the western side of India (Western Himalaya Foothills and Western Ghats) consists of fewer CbTs, but they are more intense. ICC3s are distributed nearly uniformly over the SESA but show the regional differences in Z_e and DSD parameters in the vertical profiles. Despite various height and Z_e thresholds used in the present study, WHF has the strongest vertical profile for all type of cloud cells, and indicate the importance of specific features and orographic modulated flow. The hydrometeors size is highest over Western Himalaya Foothills and least over the Bay of Bengal. Hydrometeors concentration shows the north-south gradient and higher over oceanic areas. Two coastal areas, Western Ghats and Myanmar show the different characteristics. Western Ghats CbTs are more intense, with higher hydrometeors size, whereas Myanmar has weaker convection and consists of small-sized hydrometeors. Hydrometeors size and concentration show the opposite characteristics, as hydrometeors size is higher for intense average Z_e profiles, whereas hydrometeors concentration is less for intense average Z_e profiles.