Sensitivity of the Amazonian Convective Diurnal Cycle to Its Environment in Observations and Reanalysis

Abstract

Atmospheric model parameterizations of tropical deep convection struggle to reproduce the observed diurnal variability of convection in the Amazon leading to climatological biases in the energy budget and water cycle. To identify the physical process contributions to these biases, we analyze the relationships between the convective diurnal cycle and atmosphere state variables relevant to convection in the Amazon using satellite observations and reanalysis data sets for wet and dry seasons between 2002 and 2016 and two Green Ocean Amazon periods. The analysis first stratifies the diurnal cycle into convective and nonconvective days using a daily maximum rain rate threshold of 0.5 mm/hr. Second, the population of days is constrained by requiring reanalysis and observations to agree on the occurrence of convective rain rates, controlling for frequency‐dependent biases in convection. The model‐generated precipitation phase in Modern‐Era Retrospective Analysis for Research and Applications‐2 is closer to observations than ERA during 2002–2016, which exhibits a systematic noontime bias and exaggerated diurnal amplitude. Despite the systematic noontime precipitation bias, ERA produces better agreement with Green Ocean Amazon observations due to the frequent midmorning arrival of the coastal front acting to shift the observed diurnal cycle closer to noon. Model disagreement between middle‐tropospheric vertical velocity is largest overnight during the dissipation stage of convection, acting to sustain biases through radiative effects. Specifically, the slower dissipation of convection in Modern‐Era Retrospective Analysis for Research and Applications‐2 acts to reduce morning surface fluxes and increase convective inhibition, whereas enhanced nocturnal midtropospheric subsidence and higher boundary layer humidity in ERA reduce morning convective inhibition leading to an earlier initiation of afternoon deep convection.

Development of time-varying global gridded <i>T</i><sub>s</sub>–<i>T</i><sub>m</sub> model for precise GPS–PWV retrieval

“…Therefore, we interpolated the coefficients in the T s -T m equations from the neighboring grids to the radiosonde sites. The interpolation formula is expressed as follows (Jade and Vijayan, 2008):…”

“…This can be explained by the fact that our fitting analyses are based on the T m values derived from ERA-Interim profiles. The quality of ERA- Interim data can be very poor in the regions with sparse observation data (Itterly et al, 2018).…”

Thermodynamic analysis of convective events that occurred in Belém-PA city

“…Among the difficulties encountered in numerical prediction, one of the main difficulties is to associate the moisture of the atmosphere with precipitation, which can vary in a linear or non-linear way, depending on the degree of organization of the convection and the time interval analyzed (Bengtsson et al, 2011;Masunaga, 2012;Back, Hansen and Handlos, 2017), but it has already been shown that strong and organized convection, with large areas of stratiform clouds, has a greater contribution to the increase in rainfall in humid tropical atmospheres (Tan, Jakob and Lane, 2013;Deng et al 2014). Other research suggests that convection models are producing excess moisture in the boundary layer, perhaps because the parameterization schemes for this layer are too mixed (Sherwood et al, 2010;Itterly, Taylor and Dodson, 2018;Kuo et al, 2020), which probably collaborates for an anticipated precipitation. And the simulation of insufficient moisture transport can lead to less active convection, which can make it difficult to trigger deep convection (Vilà-Guerau de Arellano et al, 2020).…”

“…In other words, the thermodynamic conditions of the atmosphere are extremely important for the release of convection, formation of clouds and occurrence of precipitation in the tropical region (Gille and . So, the daytime convection cycle, its sensitivity to atmospheric conditions and its representation in numerical models is of fundamental importance to understand its role in the climate system (Adams et al, 2015;Itterly, Taylor and Dodson, 2018). And in addition to thermodynamic instability, small, meso and large-scale dynamics, another factor that could play a fundamental role in activation and suppression of convective elements is the wind shear (Adams, Souza and Costa, 2009;Rudolph and Friedrich, 2014).…”

Suppressed Daytime Convection Over the Amazon River

“…Furthermore, the importance of boundary layer moisture may depend on seasons, as the differences in precondition between shallow and deep convection show a more significant signal in boundary layer moisture during the dry‐to‐wet transition (Zhuang et al., 2017). Climate model studies have shown that boundary layer humidity also lowers the convective inhibition (CIN), which modifies the spatial and temporal patterns of precipitation (Itterly et al., 2018).…”