Correlating cloud organization with precipitation efficiency in the Amazon

• Grant number: 24/17448-9
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: February 01, 2025
• End date: January 31, 2027
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Meteorology
• Principal Investigator: Micael Amore Cecchini
• Grantee: André Cezar Pugliesi da Silva
• Host Institution: Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 22/13257-9 - Connecting the level of cloud organization to the hydrologic and aerosol cycles in the Amazon (CLOUDORG), AP.PFPMCG.JP

Abstract

Our main hypothesis deals with precipitation efficiency, defined as the ratio of the atmospheric water vapor to the surface accumulated precipitation. Precipitation is the result of multiple chaining and non-linear processes that depend on factors such as the large-scale meteorological context, the vertical profiles of moisture, temperature, and winds, alongside aerosol concentrations and cloud field dynamics. For a given vertically integrated water vapor amount, we want to evaluate whether fewer but larger clouds (highly aggregated cloud fields) are more efficient than more numerous but smaller clouds (low aggregation) to convert water vapor into precipitation over the Amazon. While the specialized literature teaches us that cloud depth is proportional to accumulated precipitation, thus potentially having higher efficiency, there are still many open questions that need to be addressed for better representations of the local hydrological cycle.We will address this issue for locally driven convection over the Amazon, pertaining to the transition of shallow cumulus clouds to deep convection (the so-called shallow-to-deep transition). We will apply a quantification to the level of aggregation of cloud fields and correlate it to atmospheric characteristics such as the vertical profiles of temperature, moisture and winds, as well as aerosol concentrations. This will be achieved by a combination of observational datasets including vertically pointing radars, satellites and GPS to unveil the relative roles of individual atmospheric properties, as well as a combination between them, on cloud aggregation. Later, we will correlate cloud aggregation to precipitation efficiency to assess the validity of our main hypothesis. This effort will benefit the representation of the Amazonian hydrological cycle, including the daily precipitation cycle that has been a longstanding problem for the tropics.We will address this issue for locally driven convection over the Amazon, pertaining to the transition of shallow cumulus clouds to deep convection (the so-called shallow-to-deep transition). We will apply a quantification to the level of aggregation of cloud fields and correlate it to atmospheric characteristics such as the vertical profiles of temperature, moisture and winds, as well as aerosol concentrations. This will be achieved by a combination of observational datasets including vertically pointing radars, satellites and GPS to unveil the relative roles of individual atmospheric properties, as well as a combination between them, on cloud aggregation. Later, we will correlate cloud aggregation to precipitation efficiency to assess the validity of our main hypothesis. This effort will benefit the representation of the Amazonian hydrological cycle, including the daily precipitation cycle that has been a longstanding problem for the tropics.We will address this issue for locally driven convection over the Amazon, pertaining to the transition of shallow cumulus clouds to deep convection (the so-called shallow-to-deep transition). We will apply a quantification to the level of aggregation of cloud fields and correlate it to atmospheric characteristics such as the vertical profiles of temperature, moisture and winds, as well as aerosol concentrations. This will be achieved by a combination of high-resolution modeling experiments to unveil the relative roles of individual atmospheric properties, as well as a combination between them, on cloud aggregation. Later, we will correlate cloud aggregation to precipitation efficiency to assess the validity of our main hypothesis. This effort will benefit the representation of the Amazonian hydrological cycle, including the daily precipitation cycle that has been a longstanding problem for the tropics.