Curious Kids: what was the biggest dinosaur that ever lived?

Nic Rawlence, University of Otago

What actually was the biggest dinosaur?

– Zavier, 14, Tauranga, New Zealand.

Great question Zavier, and one that palaeontologists (scientists who study fossil animals and plants) are interested in all around the world.

And let’s face it, kids of all ages (and I include adults here) are fascinated by dinosaurs that break records for the biggest, the longest, the scariest or the fastest. It’s why, to this day, one of most famous dinosaurs is still Tyranosaurus rex, the tyrant king.

These record-breaking dinosaurs are part of the reason why the Jurassic Park movie franchise has been so successful. Just think of the scene where Dr Alan Grant (played by New Zealand actor Sam Neill) is stunned by the giant sauropod dinosaur rearing up to reach the highest leaves in the tree with its long neck.

But how do scientists work out how big and heavy a dinosaur was? And what were the biggest dinosaurs that ever lived?

Calculating dinosaur size

In an ideal world, calculating how big a dinosaur was would be easy – with a nearly complete skeleton. Standing next to the remarkable Triceratops skeleton on permanent display at Melbourne Museum makes you realise how gigantic and formidable these creatures were.

By measuring bone proportions (such as length, width or circumference) and plugging them into mathematical formulas and computer models, scientists can compare the measurements to those of living animals. They can then work out the likely size and weight of dinosaurs.

Calculating the size of dinosaurs is easy when you have near complete skeletons like this Triceratops at Melbourne Museum. Ginkgoales via Wikimedia Commons, CC BY-NC-SA

Every palaeontologist has their own favourite formula or computer model. Some are more accurate than others, which can lead to heated arguments!

In palaeontology, however, we are not always blessed with nearly complete skeletons. In a process called “taphonomy” – basically, what happens to the bones after an animal dies – dinosaur skeletons can be broken up and bones lost.

The more fragmented the remains of a dinosaur are, the more error is introduced into size and weight estimates.

Enter the titanosaurs

If we could travel back in time to South America during the Cretaceous period (about 143 million to 66 million years ago), we’d find a land ruled by a group of four-legged, long-necked and long-tailed, plant-eating sauropods. They would have towered over us, and the ground would shake with every step they took.

These were the titanosaurs. They reached their largest sizes during this period, before an asteroid crashed into what is now modern day Mexico 66 million years ago, making them extinct.

There are several contenders among the titanosaurs for the biggest dinosaur ever. Even the list below is controversial, with my palaeontology students pointing out several other possible contenders.

But based on six partial skeletons, the best estimate is for Patagotitan, which is thought to have been 31 meters long and to have weighed 50–57 tonnes.

A couple of others might have been as big or even bigger. Argentinosaurus has been calculated to be longer and heavier at 30–35 metres and 65–80 tonnes. And Puertasaurus was thought to be around 30 metres long and 50 tonnes.

But while the available bones of Argentinosaurus and Puertasaursus suggest reptiles of colossal size (the complete thigh bone of Argentinosaurus is 2.5 metres long!), there is currently not enough fossil material to be confident of those estimates.

Spinosaurus rules North Africa

An ocean away from South America’s titanosaurs, Spinosaurus lived in what is now North Africa during the Cretaceous period.

By a very small margin, Spinosaurus is currently thought to have been the largest carnivorous (meat-eating) dinosaur, weighing in at 7.4 tonnes and 14 meters long. Other Cretaceous giants are right up there, too, including Tyranosaurus rex from North America, Gigantosaurus from South America, and Carcharodontosaurus from North Africa.

Spinosaurus is unique among predatory dinosaurs in that it was semi-aquatic and had adapted to eating fish. You can see in the picture above how similar its skull shape was to a modern crocodile.

Palaeontology is now more popular than ever – maybe because of the ongoing Jurassic Park series – with a fossil “gold rush” occurring in the Southern Hemisphere.

The latest Jurassic Park movie – in cinemas from July 2025 – is about finding the biggest prehistoric species from land, sea, and air.

Members of the public (known as “fossil forecasters”) are making new discoveries all the time.

So, who knows? The next discovery might turn out to be a new record holder as the biggest or longest dinosaur to have ever lived. There can be only one!

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Hello curious kids! Do you have a question you’d like an expert to answer? Ask an adult to send your question to curiouskids@theconversation.edu.au

Nic Rawlence, Associate Professor in Ancient DNA, University of Otago

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read More........→March 19, 2025

What’s the difference between climate and weather models? It all comes down to chaos

Nadia Piet/AIxDESIGN & Archival Images of AI / Better Images of AI , CC BY-SA Andy Hogg, Australian National University; Aidan Heerdegen, Australian National University, and Kelsey Druken, Australian National University

Weather forecasts help you decide whether to go for a picnic, hang out your washing or ride your bike to work. They also provide warnings for extreme events, and predictions to optimise our power grid.

To achieve this, services such as the Australian Bureau of Meteorology use complex mathematical representations of Earth and its atmosphere – weather and climate models.

The same software is also used by scientists to predict our future climate in the coming decades or even centuries. These predictions allow us to plan for, or avoid, the impacts of future climate change.

Weather and climate models are highly complex. The Australian Community Climate and Earth System Simulator, for example, is comprised of millions of lines of computer code.

Without climate and weather models we would be flying blind, both for short-term weather events and for our long-term future. But how do they work – and how are they different?

The same physical principles

Weather is the short-term behaviour of the atmosphere – the temperature on a given day, the wind, whether it’s raining and how much. Climate is about long-term statistics of weather events – the typical temperature in summer, or how often thunderstorms or floods happen each decade.

The reason we can use the same modelling tools for both weather and climate is because they are both based on the same physical principles.

These models compile a range of factors – the Sun’s radiation, air and water flow, land surface, clouds – into mathematical equations. These equations are solved on a bunch of tiny three-dimensional grid boxes and pieced together to predict the future state.

These boxes are sort of like pixels that come together to make the big picture.

These solutions are calculated on a computer – where using more grid boxes (finer resolution) gives better answers, but takes more computing resources. This is why the best predictions need a supercomputer, such as the National Computational Infrastructure’s Gadi, located in Canberra.

Because weather and climate are governed by the same physical processes, we can use the same software to predict the behaviour of both.

But there most of the similarities end.

The starting point

The main differences between weather and climate come down to a single concept: “initialisation”, or the starting point of a model.

In many cases, the simplest prediction for tomorrow’s weather is the “persistence” forecast: tomorrow’s weather will be similar to today. It means that, irrespective of how good your model is, if you start from the wrong conditions for today, you have no hope of predicting tomorrow.

Persistence forecasts are often quite good for temperature, but they’re less effective for other aspects of weather such as rainfall or wind. Since these are often the most important aspects of weather to predict, meteorologists need more sophisticated methods.

So, weather models use complex mathematics to create models that include weather information (from yesterday and today) and then make a good prediction of tomorrow. These predictions are a big improvement on persistence forecasts, but they won’t be perfect.

In addition, the further ahead you try to predict, the more information you forget about the initial state and the worse your forecast performs. So you need to regularly update and rerun (or, to use modelling parlance, “initialise”) the model to get the best prediction.

Weather services today can reliably predict three to seven days ahead, depending on the region, the season and the type of weather systems involved.

Chaos reigns

If we can only accurately predict weather systems about a week ahead before chaos takes over, climate models have no hope of predicting a specific storm next century.

Instead, climate models use a completely different philosophy. They aim to produce the right type and frequency of weather events, but not a specific forecast of the actual weather.

The cumulative effect of these weather events produces the climate state. This includes factors such as the average temperature and the likelihood of extreme weather events.

So, a climate model doesn’t give us an answer based on weather information from yesterday or today – it is run for centuries to produce its own equilibrium for a simulated Earth.

Because it is run for so long, a climate (also known as Earth system) model will need to account for additional, longer-term processes not factored into weather models, such as ocean circulation, the cryosphere (the frozen portions of the planet), the natural carbon cycle and carbon emissions from human activities.

The additional complexity of these extra processes, combined with the need for century-long simulations, means these models use a lot of computing power. Constraints on computing means that we often include fewer grid boxes (that is, lower resolution) in climate models than weather models.

A machine learning revolution?

Is there a faster way?

Enormous strides have been made in the past couple of years to predict the weather with machine learning. In fact, machine learning-based models can now outperform physics-based models.

But these models need to be trained. And right now, we have insufficient weather observations to train them. This means their training still needs to be supplemented by the output of traditional models.

And despite some encouraging recent attempts, it’s not clear that machine learning models will be able to simulate future climate change. The reason again comes down to training – in particular, global warming will shift the climate system to a different state for which we have no observational data whatsoever to train or verify a predictive machine learning model.

Now more than ever, climate and weather models are crucial digital infrastructure. They are powerful tools for decision makers, as well as research scientists. They provide essential support for agriculture, resource management and disaster response, so understanding how they work is vital.

Andy Hogg, Professor and Director of ACCESS-NRI, Australian National University; Aidan Heerdegen, Leader, ACCESS-NRI Model Release Team, Australian National University, and Kelsey Druken, Associate Director (Release Management), ACCESS-NRI, Australian National University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read More........→February 11, 2025