Climate vs Weather — How Do We Know the Planet Is Warming?
Season 1 Episode 13 · Whimsical Wavelengths
Episode overview
Climate change is often discussed in terms of global averages, but experienced locally through weather, hazards, and impacts that feel personal. In this episode, research meteorologist Jared Rennie from NOAA’s National Centers for Environmental Information joins Whimsical Wavelengths to unpack how scientists actually measure Earth’s temperature—and why “just a degree or two” matters far more than it sounds.
The conversation moves step by step through how global temperature records are constructed, from individual weather stations and ocean buoys to internationally agreed-upon standards set by the World Meteorological Organization. Along the way, the episode explores quality control, bias correction, and why independent organizations using different methods all reach the same conclusion: the planet is warming.
This episode also focuses heavily on science communication—how climate data connects to people’s lived experiences, why local impacts matter more than global averages, and how scientists can better communicate risk without oversimplifying the data.
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What we discuss in this episode
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The difference between weather and climate
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How global average temperature is actually calculated
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Why measuring Earth’s temperature is harder than it sounds
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Land-based weather stations vs ocean temperature measurements
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NOAA’s Global Historical Climatology Network (GHCN)
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Sea surface temperature data and the ERSST dataset
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Quality control vs bias correction in climate data
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Why stations move—and how that affects long-term records
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Why independent groups (NOAA, NASA, Copernicus, Berkeley Earth) agree
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Why global averages hide extreme regional changes
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How climate change shows up through floods, droughts, heat, and snow loss
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The challenge of communicating climate data to different audiences
What is actually being measured?
Global temperature is not taken from a single thermometer. Instead, it is reconstructed using tens of thousands of land-based weather stations and ocean measurements collected from ships, buoys, and satellites. These data are aggregated over time—hourly to daily, daily to monthly—and combined using internationally recognized standards.
Jared Rennie explains how NOAA merges land and ocean datasets into a single global temperature record, applies rigorous quality control, corrects for non-climatic biases, and compares modern temperatures to historical baselines that extend back to the mid-19th century.
Key questions explored
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How do scientists “take the temperature” of an entire planet?
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What does a 30-year climate average actually represent?
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Why do weather stations need bias corrections over time?
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How do we know climate data hasn’t been manipulated?
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Why do different organizations use different methods—but get the same result?
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Why does a global increase of 1–2 °C matter so much?
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How does climate change affect people differently depending on where they live?
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What data resonates most when communicating climate risk to the public?
Episode format
This episode is a long-form expert interview focused on:
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Climate data fundamentals
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Scientific methodology and uncertainty
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Real-world interpretation of abstract numbers
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Science communication and public understanding
The discussion is technical where necessary, but intentionally explanatory, emphasizing transparency, process, and why climate conclusions are robust across institutions.
Episode details
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Season: 1
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Episode: 13
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Topic: Climate science, meteorology, science communication
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Guest: Jared Rennie
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Affiliation: NOAA National Centers for Environmental Information (NCEI)
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Key themes: Climate data, global temperature records, local impacts
Enjoyed this episode?
If you’re interested in how scientists turn massive datasets into meaningful climate insights—or how climate change connects to everyday weather and hazards—this episode is a foundational listen. Explore other Whimsical Wavelengths episodes that examine climate, natural hazards, and how scientific evidence is communicated beyond the lab.
