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En este estudio, se evalúan los resultados de la aplicación del modelo metereológico Weather Research and Forecasting (WRF) en 103 días donde ocurrieron eventos de precipitación extrema (percentil 90) dentro de la cuenca del río Mantaro. Se utilizó el modelo atmosférico WRF para cuatro áreas mediante anidamiento múltiple, y se lograron obtener resoluciones espaciales de 18, 6, 3 y 0.75 km, respectivamente. Se realizaron pronósticos de precipitación extrema y se evaluó la eficacia de las salidas numéricas, utilizando datos observados {\emph in-situ}, mediante la red de estaciones meteorológicas del SENAMHI e información satelital. Los valores de estimadores estadísticos, muestran que el modelo tiende a subestimar los datos de lluvia en muchos casos y en otros los sobre-estima, teniendo limitaciones en representar la variabilidad espacial de los datos observados. Los datos satelitales de precipitación acumulada, siempre sobre estiman los valores de precipitación, pero tiene la capacidad de determinar las zonas específicas donde probablemente esta ocurriendo lluvias extremas.

The life cycle of clouds consists of mainly into three phases, namely developing, mature, and dissipating phases. The information about the vertical structure of the precipitation during different phases of development will improve their representation in the cloud models. Whether specific regimes over Peru favor the formation or decay of the cloud systems and how their intensity varies during different phases of development will provide the insight into the precipitation structure over Peru. We used two satellite-based data, namely from Global Precipitation Measurement dual Precipitation Radar (GPM-DPR) and GOES (Geostationary Operational Environmental Satellite) to expose the vertical structure of precipitation during different phases of the precipitating cloud systems (PCSs). A PCS is defined using the GPM based near surface rainfall data and then GOES-based brightness temperature (BT) is used to identify a specific phase of PCS. In particular 9 hours of BT (e.g., time series of BT) data for a GPM DPR overpass is used to a specific phase of PCS. Once, all the PCSs are identified into a specific phase, their statistical properties are studied. The highest convective fraction area (~26%) and near surface rain rate (RR; 4.97 mm hr−1) are observed in developing phase of PCSs. Also, the convective fraction area and near surface RR decreases as cloud matures, and, least convective fraction area and RR (~4.11 mm hr−1) are observed in dissipating phase PCSs. The vertical structure of precipitation consists of more complex relation among different phases of PCSs. The vertical distributors of hydrometeors (e.g., radar reflectivity, RR, and DSD parameters) during various phases have different characteristics above and below the freezing height (~5 km). For example, convective precipitation has small concentration of higher sized hydrometeors below the freezing height, whereas mature has PCSs show different behavior. The total amount of water analysis shows that liquid and ice water amount varies during different phases and affect the rainfall characteristics. It is observed that precipitation characteristics during different phases are influenced by the Andes Mountain and developing phase PCSs have higher sized of hydrometeors with higher near surface RR at the north-eastern continent of Peru.

The present study explores the cloud microphysics (MPs) impact on the simulation of two convective rainfall events (CREs) over the complex topography of Andes mountains, using the Weather Research and Forecasting- Advanced Research (WRF-ARW) model. The events occurred on December 29 2015 (CRE1) and January 7 2016 (CRE2). Six microphysical parameterizations (MPPs) (Thompson, WSM6, Morrison, Goddard, Milbrandt and Lin) were tested, which had been previously applied in complex orography areas. The one-way nesting technique was applied to four domains, with horizontal resolutions of 18, 6, and 3 km for the outer ones, in which cumulus and MP parameterizations were applied, while for the innermost domain, with a resolution of 0.75 km, only MP parameterization was used. It was integrated for 36 h with National Centers for Environmental Prediction (NCEP Final Operational Global Analysis (NFL) initial conditions at 00:00 UTC (Coordinated Universal Time). The simulations were verified using Geostationary Operational Environmental Satellites (GOES) brightness temperature, Ka band cloud radar, and surface meteorology variables observed at the Huancayo Observatory. All the MPPs detected the surface temperature signature of the CREs, but for CRE2, it was underestimated during its lifetime in its vicinity, matching well after the simulated event. For CRE1, all the schemes gave good estimations of 24 h precipitation, but for CRE2, Goddard and Milbrandt underestimated the 24 h precipitation in the inner domain. The Morrison and Lin configurations reproduced the general dynamics of the development of cloud systems for the two case studies. The vertical profiles of the hydrometeors simulated by different schemes showed significant differences. The best performance of the Morrison scheme for both case studies may be related to its ability to simulate the role of graupel in precipitation formation. The analysis of the maximum reflectivity field, cloud top distribution, and vertical structure of the simulated cloud field also shows that the Morrison parameterization reproduced the convective systems consistently with observations.