ARM data shows that rainfall during the Amazonian dry season is mainly controlled by non-local factors
The health and extent of the Amazon rainforest critically depends on the precipitation received during the dry season. Our analysis suggests that the daytime precipitation during the dry season occurs during days with higher moisture content at low and mid-levels, while the total rainfall received during the dry season is primarily determined by the propagating storm systems.
The control of daytime precipitation during the dry season on the presence of moisture in the lower atmosphere, and the total rainfall on propagating squall lines, suggest that coarse-resolution models should be able to accurately simulate the dry season precipitation over the Amazon basin.
The Amazon rainforest plays an important role in the global energy and hydrologic cycle, with the extent of the rainforest critically dependent on the precipitation received during the dry season. With various degree of variability, most of the global climate models (GCM) forecast the dry season to get longer and drier in the future. In this study, we have used the data collected during the Green Ocean Amazon 2014/15 (GOAmazon2014/15) field campaign to determine the factors controlling the precipitation during the Amazonian dry season. Precipitation during the daytime results from the local land-atmosphere interactions, while that at night is associated with propagating storm systems. Detailed comparisons between days with and without daytime precipitation suggested the increased moisture at low- and mid-levels to be responsible for lowering the lifting condensation level, reducing convective inhibition and entrainment, and thus triggering the transition from shallow to deep convection. Although the monthly accumulated rainfall decreased during progression of the dry season, the contribution of daytime precipitation to it increased, suggesting the decrease to be mainly due to reduction in propagating squall lines. Broadly, our analysis suggests the control of daytime precipitation to be on large-scale moisture, while the control of total precipitation to be on propagating storms.
Contacts (BER PM)
ASR Program Manager
ARM Program Manager
Argonne National Laboratory
This work was primarily supported by the U.S. Department of Energy’s (DOE) Atmospheric System Research (ASR), an Office of Science, Office of Biological and Environmental Research (BER) program, under Contract DE-AC02-06CH11357 awarded to Argonne National Laboratory and Contract DE-SC00112704 awarded to Brookhaven National Laboratory. This research was also supported by the National Science Foundation (NSF) Grant AGS-1445831 awarded to the University of Chicago. All the data used in this study were obtained from the Atmospheric Radiation Measurement (ARM) program sponsored by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division (CESD). We gratefully acknowledge the computing resources provided on Blues, a high-performance computing cluster operated by the Laboratory Computing Resource Center (LCRC) at the Argonne National Laboratory.
VP Ghate and P Kollias, "On the Controls of Daytime Precipitation in the Amazonian Dry Season." Journal of Hydrometeorology, 17, (2016). [10.1175/jhm-d-16-0101.1]. (Reference link)
ASR Highlight: Controls of Precipitation in the Amazonian Dry Season
SC-23.1 Climate and Environmental Sciences Division, BER
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]
May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]
May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]
May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]
Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]
List all highlights (possible long download time)