Spatial Variability of the Background Diurnal Cycle of Deep Convection around the GoAmazon2014/5 Field Campaign Sites

Abstract

The isolation of the Amazon rain forest makes it challenging to observe precipitation forming there, but it also creates a natural laboratory to study anthropogenic impacts on clouds and precipitation in an otherwise pristine environment. Observations were collected upwind and downwind of Manaus, Brazil, during the “Observations and Modeling of the Green Ocean Amazon 2014–2015” experiment (GoAmazon2014/5). Besides aircraft, most of the observations were point measurements made in a spatially heterogeneous environment, making it hard to distinguish anthropogenic signals from naturally occurring spatial variability. In this study, 15 years of satellite data are used to examine the spatial and temporal variability of deep convection around the GoAmazon2014/5 sites using cold cloud tops (infrared brightness temperatures colder than 240 K) as a proxy for deep convection. During the rainy season, convection associated with the inland propagation of the previous day’s sea-breeze front is in phase with the diurnal cycle of deep convection near Manaus but is out of phase a few hundred kilometers to the east and west. Convergence between the river breezes and the easterly trade winds generates afternoon convection up to 10% more frequently (on average ~4 mm day−1 more intense rainfall) at the GoAmazon2014/5 sites east of the Negro River (T0e, T0t/k, and T1) relative to the T3 site, which was located west of the river. In general, the annual and diurnal cycles of precipitation during 2014 were similar to climatological values that are based on satellite data from 2000 to 2013.

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

“…Giangrande et al (2016) have presented the statistical behaviour of vertical cloud motions as a function of season, instability, and convective inhibition. Burleyson et al (2016) have discussed the diurnal cycle and spatial variability of deep convection among the different GoAmazon sites. Giangrande et al (2017) have also presented an overview of cloud, thermodynamics, and radiation interactions.…”

“…Burleyson et al (2016) used 15 years of satellite data to show a heterogeneous spatial distribution of convection that results from numerous local effects of rivers and vegetation cover. Using radar data, Saraiva et al (2016) also found the Amazonas diurnal cycle to vary regionally.…”

The Green Ocean: Precipitation Insights from the GoAmazon2014/5 Experiment

“…Recently, the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment was motivated by demands to gain a better understanding of aerosol, cloud and precipitation interactions on climate and the global circulation (Martin et al, 2016(Martin et al, , 2017. The inability of GCMs to adequately represent cumulus clouds and precipitation over the Amazon highlights one example of the observational needs for future improvement to GCM cloud parameterizations and the larger-scale 10 circulation connections therein (e.g., Richter and Xie, 2008;Nobre et al, 2009;Yin et al, 2013).…”

Overview: Precipitation Characteristics and Sensitivities to the Environmental Conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

“…Giangrande et al (2016) presented the statistical behaviour of cloud vertical motions as function of season, instability and convective inhibition. Burleyson et al (2016) discussed the diurnal cycle and 20 spatial variability of deep convection among the different GoAmazon sites. Giangrande et al (2017) presented an overview of cloud, thermodynamics, and radiation interactions.…”

“…Burleyson et al (2016) used 15 years of satellite data to show a heterogeneous spatial distribution of convection that results from numerous local effects of the rivers and vegetation cover. Saraiva et al (2016), using radar data, also found the Amazonas diurnal cycle to be regionally varying.…”