During his childhood, Ángel Adames, a doctoral student in atmospheric sciences at the UW, experienced a major hurricane while living in Puerto Rico, which left him without power and clean water for weeks. This sparked his curiosity of tropical weather.
Adames studies the Madden-Julian oscillation (MJO), a recurring rainstorm that forms in the tropics. Recently, Adames published a paper called “The MJO as a Dispersive, Convectively Coupled Moisture Wave: Theory and Observations” that summarizes his research on a mathematical model that can be used to track how storms move, and predict where they will occur.
“[The MJO] doesn’t happen all the time, but, when it does, it happens [for] 40 to 50 days,” Adames said.
The timescale of the MJO is much shorter than a weather phenomenon like El Niño. The MJO is a huge burst of monsoon-like thunderstorms followed by a dry period, and vice versa.
“It’s just really, really dry conditions, it’s [thunderstorms] or [no precipitation]. Usually, one is followed by the other, and that’s why we call it an oscillation,” Adames said.
With the high surface temperatures and humidity, thunderstorms form around the Indian Ocean, Indonesia, and the western Pacific. The amount of moisture in the atmosphere directly influences how much precipitation will occur in the tropics.
Once these storms form, they slowly move east. The determinants of the MJO’s strength is derived from its appearance and location. Adames compared the MJO to a vibrating string, but instead of a string, the vibration is coming from moisture.
“That ‘up and down’ moisture is causing storms to develop or seize,” Adames said. “That whole wave of moisture moving eastward.”
This analogy sparked the idea that a system of equations for the MJO can be solved for as a wave and moisture. When the equation is solved for the wave and moisture, the data is compared to the observed MJO. This has been verified through satellite images and models.
“This is probably the most intense work I’ve ever done, and I’ve never thought I’d be doing something like that,” Adames said.
It took several months for Adames to verify his data.
“[The MJO] has been known for more than three decades, and many smart people have tried to explain it without any success,” said Daehyun Kim, co-author and assistant professor of the paper in the UW atmospheric science department.
Adames also collaborated with Scott Powell, UW atmospheric science Ph.D. student, who also does research about the MJO.
“What [Adames’] set of equations really does is [describe] how the MJO maintains itself and moves once it develops,” Powell said.
This mathematical model could help predict weather forecasts. Additionally, the MJO is able to make an impact on weather.
“Eventually [the mathematical model] will help people represent the phenomenon in forecasting models and will enhance accuracy of weather forecast, which will benefit the public,” Kim said.
Being able to predict weather in the long term will benefit people who live in the tropics.
“You really want to predict [the MJO], and know if you’re going to have a really rainy week, especially for agriculture,” Adames said.
The MJO also affects the weather on the West Coast. The amount of precipitation can vary due to the MJO, and it can also interact with El Niño, and either amplify or lessen its impact for a short time span.
There are still various aspects about the MJO that remain a mystery to researchers. The reason why the MJO has a fast horizontal scale, why it propagates eastward, and why it has such a time scale is still unknown Kim said.
However, those aren’t the only major problems researchers face.
“[Researchers] haven’t figured out how [the MJO] gets started,” Powell said.
Unlike the weather models that can accurately predict weather for the Pacific Northwest, predicting the weather in the tropics is difficult. If this mathematical model is correct about how the MJO maintains itself and moves, for the field of atmospheric science, predicting weather patterns in the tropics could be easier.
Reach contributing writer Ayano Swisher at firstname.lastname@example.org. Twitter: @the_ogswisher