Weather Advances, Listening to Volcanoes, Phragmites. Jan 25, 2019, Part 1
Your smartphone gives you up-to-the-minute weather forecast updates at the tap of a button. Every newscast has a weather segment. And outlets like the Weather Channel talk weather all day, every day. But how much has the process of predicting the weather changed over the past 100 years? Though many of the basic principles are the same, improvements in data collection, satellite imagery, and computer modeling have greatly improved your local forecast—making a five-day look ahead as accurate as a one-day prediction was 40 years ago. Richard Alley, a professor of geoscience at Penn State, describes the evolution of meteorology, and what roadblocks still lie ahead, from data sharing to shifting weather patterns. And Angela Fritz, lead meteorologist for the Capital Weather Gang blog at the Washington Post, describes the day-to-day work of a meteorologist and the challenges involved in accurately predicting your local weekend weather.
When the Chilean volcano Villarrica exploded in 2015, researchers trying to piece together the eruption had a fortuitous piece of extra data to work with: the inaudible infrasound signature of the volcano’s subsurface lava lake rising toward the surface. Volcano forecasters already use seismic data from volcanic vibrations in the ground. But these “infrasound” signals are different. They’re low-frequency sound waves generated by vibrations in the air columns within a volcanic crater, can travel many miles from the original source, and can reveal information about the shape and resonance of the crater… and whether it’s changing. And two days before Villarrica erupted, its once-resonant infrasound signals turned thuddy—as if the lava lake had gotten higher, and left only a loudspeaker-shaped crater to vibrate the air.
Robert Buchsbaum walks into a salt marsh on Boston’s North Shore. Around him towers a stand of bushy-topped Phragmites australis, an invasive plant commonly known as the common reed. Phragmites is an enemy that this regional scientist with the Massachusetts Audubon Society knows all too well. The plant, which typically grows about 13 feet high, looms over native marsh plants, blocking out their sunlight. When Phragmites sheds its lower leaves, or dies, it creates a thick layer of wrack that keeps native plants from germinating. Its stalks clog waterways, thwarting fish travel. The roots secrete a chemical that prevents other plants from growing, and they grow so deep they are nearly impossible to pull out. But this stubborn bully of a plant might have a shot at redemption. A recent study from the Smithsonian Environmental Research Center found that the very traits that make Phragmites a tough invader—larger plants, deeper roots, higher density—enable it to store more carbon in marshy peat. And as climate change races forward, carbon storage becomes a bigger part of the ecosystem equation.
Subscribe to this podcast. Follow our show on Instagram, TikTok, Facebook, and Bluesky @scifri and sign up for our newsletters. Got a science question that’s keeping you up at night? Call us: 877-472-4374
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.