Investigating Vertical Cloud Motion in the Amazon
ARM data provide important insight into vertical motions in deep convective clouds in the Amazon rainforest.
In order to produce accurate projections of the Earth’s water cycle under current and future climate conditions, climate models need to accurately simulate precipitation from tall, rain-producing clouds, known as “deep convection”. A key element for accurately modeling deep convection is the vertical velocity, or upward motion within the cloud. While vertical velocity has typically been determined from infrequent aircraft measurements, recent studies have illustrated that radar wind profilers (RWPs) have sufficient temporal and vertical resolution to measure vertical velocity at scales needed to study the cores of deep convective clouds. In this paper, researchers use data from radar wind profilers (RWP) deployed by the Atmospheric Radiation Measurement (ARM) Climate Research Facility to the Amazon rainforest to provide critical information about vertical velocity and its relationship with the surrounding atmospheric conditions for model parameterizations of deep convection.
Deep convective vertical velocity and precipitation insights are valuable for unlocking uncertainties in current model simulations of climate change. This study provides the first climatology of vertical motion of Amazon clouds, and investigates the role of environmental forcing on deep convective storm areal coverage and intensity. For Amazonian storms, the researchers confirm that more intense convection is found within the dry season, and there are substantial increases in updraft mass flux (or amount of mass being transported upwards in the cloud) in the wet season. This data provides critical constraints for model simulations of deep convective clouds in the Amazon.
A RWP data set collected during the DOE ARM GoAmazon 2014/15 campaign is used to estimate convective cloud vertical velocity, area coverage, and mass flux profiles. Vertical velocity observations are presented using normalized cumulative frequency histograms (CFADs) and weighted-mean profiles. This is done to provide convective insights in a manner suitable for GCM-model scale comparisons. The sensitivity of storm intensity to changes in environmental conditions and seasonal regime controls is also considered.
Overall, the researchers observe that updrafts and downdrafts increase in magnitude with height to mid-levels (6 to 10 km), with updraft area also increasing with height. Updraft mass flux profiles similarly increase with height, showing a peak in magnitude near 8 km. Stronger vertical velocity profile behaviors are observed under higher convective available potential energy (CAPE) and lower low-level moisture conditions. Sharp contrasts in convective area fraction and mass flux profiles are most pronounced when retrievals are segregated according to Amazon wet and dry season conditions. Wet season regimes favored higher domain mass flux profiles, attributed to more frequent convection that offsets weaker average convective cell vertical velocities.
Environmental & Climate Sciences Department, Brookhaven National Laboratory
Research funding was provided by DOE Office of Biological and Environmental Research (BER) Atmospheric System Research (ASR) and the São Paulo Research Foundation (FAPESP). The work was conducted under scientific licenses 001030/2012-4, 001262/2012-2, and 00254/2013-9 of the Brazilian National Council for Scientific and Technological Development (CNPq). Institutional support was provided by the Central Office of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), the National Institute of Amazonian Research (INPA), the National Institute for Space Research (INPE), Amazonas State University (UEA), and the Brazil Space Agency (AEB). We also acknowledge the Atmospheric Radiation Measurement (ARM) Climate Research Facility.
Giangrande SE, T Toto, MP Jensen, M Bartholomew, Z Feng, A Protat, C Williams, C Schumacher, and L Machado. 2016. “Convective cloud vertical velocity and mass-flux characteristics from radar wind profiler observations during GoAmazon 2014/5.” Journal of Geophysical Research: Atmospheres, 121(21), 10.1002/2016jd025303.