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The Amazon Rainforest sprawls across more than 2 million square miles of South America, taking in carbon dioxide and releasing oxygen as “the lungs of the planet.” When they’re healthy, the world’s tropical forests and vegetation absorb up to 30 percent of the CO2 produced by human activities, but during droughts, that capacity falls off. To understand what that will mean as global warming produces more intense and frequent droughts, we need to understand the water and carbon cycles of the Amazon and how those cycles interact.
That’s easier said than done.
In a paper published today in the early online edition of the Proceedings of the National Academy of Sciences, Usama Anber, a PhD student at Columbia University’s Lamont-Doherty Earth Observatory, and his coauthors explain that general circulation models don’t fully capture the land-atmosphere feedback loop in the Amazon, in particular the role of fog during the wet season. The models also miss some of the seasonality of precipitation and evaporation, and often assume too little rain too early in the day.
To overcome those drawbacks, the team developed a new method that flips the approach of the general circulation models by using high-resolution atmospheric modeling to resolve clouds and convection and parameterize the feedback between convection and atmospheric circulation.
Working with Columbia professors Adam Sobel and Pierre Gentine and associate research scientist Shuguang Wang, Anber was able to use the new approach to simulate the climate of the Amazon in a way that takes into account the timing of precipitation and the impact that the morning fog layer has on evaporation and surface radiation. During the wet season, the fog reflects sunlight in the early mornings, allowing less solar radiation in and keeping more moisture in the forest. During the dry season, when the fog doesn’t form, the forest receives more sunlight, increasing both photosynthesis and evaporation rates. The new modeling approach was able to reproduce the climates experienced in the Amazon with greater accuracy. Producing better estimates of tropical forest evaporation could lead to better water resource management and better climate forecasts.
“Our study demonstrates that using coupled land-atmosphere models with resolved convection and parameterized large-scale dynamics produces very accurate results,” Anber said. “It is critical to our understanding of tropical climates.”