Share to raise climate awareness

This article was written by Laura Faye Tenenbaum who is a science communicator at NASA’s Jet Propulsion Laboratory in California. Laura features Gavin Schmidt, climatologist and director of The Goddard Institute for Space Studies (GISS) who asks the computer to calculate the weather in 20-minute time steps. (Rolly Montpellier~Managing Editor of BoomerWarrior). 

Heating Up

Abbreviated version of the visualization ‘Heating Up,’ which depicts climate model projection of 21st century global temperatures. Credit: NASA Scientific Visualization Studio.

Standard YouTube Licence
Uploaded on Jun 11, 2015

I was eager to speak with Dr. Schmidt because of his passion for communicating climate science to public audiences on top of his work as a climatologist. Schmidt is a co-founder and active blogger at Real Climate and was also awarded the inaugural Climate Communications Prize, by the American Geophysical Union (AGU) in 2011. “My goal in communicating,” he explained,“ is a totally futile effort to raise the level of the conversation so that we actually discuss the things that matter.”

Since the mere mention of a computer model can cause an otherwise normal person’s face to glaze over, I thought Schmidt, a leader in climate simulations and Earth system modeling, would be the ideal candidate to explain one of the most important, yet probably one of the most misunderstood, instruments scientists have for studying Earth’s climate. See, people commonly confuse climate and weather, and this confusion is perhaps most pronounced when it comes to understanding the difference between a weather forecast and a climate simulation.

700,000 Lines of Computer Code – a Numerical Laboratory

Schmidt’s work routine is much like that of any other scientist. He spends a few months preparing experiments, then a few more months conducting the experiments, then a few more months refining and improving the experiments, then a few more months going back and looking at fine details, then a few more months … you get the idea.

A Typical Climate Simulation is 700,000 Lines of Computer Code, boomer warrior
The models project North America to experience significant warming by the end of the century – NASA

Climate scientists use complex computer simulations as numerical laboratories to conduct experiments because we don’t have a bunch of spare Earths just lying around. These simulations model Earth’s conditions as precisely as possible. “A single run can take three months on up on super computers,” Schmidt said. “For really long runs, it can take a year.” NASA scientists can reserve time for High-End Computing Capability at the NASA Advanced Supercomputing facility and/or the NASA Center for Climate Simulation to run simulations. Like an astronomer who reserves time on a large telescope to run her experiments, Schmidt books time on these computers to run his.

Schmidt asks the computer to calculate the weather in 20-minute time steps and see how it changes. Every 20 minutes it updates its calculation over hundred-year or even thousand-year periods in the past or the future. “The models that we run process about three to four years of simulation, going through every 20 minute time step, every real day.”

A typical climate simulation code is large, as in 700,000 lines of computer code large. For comparison, the Curiosity Rover required about 500,000 lines of code to autonomously descend safely on Mars, a planet 140 million miles away with a signal time delay of about 14 minutes. The size of a typical app, such as our Earth Now mobile app, is just over 6,000 lines of code. Climate simulations require such a large quantity of code because Earth’s climate is so extraordinarily complex. And, according to Schmidt, “Complexity is quite complex.”

Like a scientist who runs an experiment in a science lab, climate modelers want code that’s consistent from one experiment to another. So they spend most of their time developing that code, looking at code, improving code and fixing bugs.

The model output is compared to data and observations from the real world to build in credibility. “We rate the predictions on whether or not they’re skillful; on whether we can demonstrate they are robust.” When models are tested against the real world, we get a measure of how skillful the model is at reproducing things that have already happened. Then we can be more confident about the accuracy in predicting what’s going to happen. Schmidt wants to find out where the models have skill and where they provide useful information. For example, they’re not very useful for tornado statistics, but they’re extremely useful on global mean temperature. According to Schmidt, the credible and consistently reliable predictions include ones that involve adding carbon dioxide to the atmosphere. “You consistently get increases in temperature and those increases are almost always greater over land than they are in the ocean. They’re always larger in the Arctic than in the mid-latitudes and always more in the northern hemisphere than the southern, particularly Antarctica. Those are very, very robust results.”

Lately, his team has been working on improving the code for sea ice dynamics to include the effects of brine pockets (very salty fluid within the ice matrix) as well as the wind moving the ice around. For example, to understand the timeline for Arctic sea ice loss, his team has to work on the different bits of code for the wind, the temperature, the ocean and the water vapor and include the way all these pieces intersect in the real world. After you improve the code, you can see the impact of those improvements.

I asked Schmidt what people’s behavior would look like “if they understood that burning fossil fuels produces carbon dioxide, which causes global warming.” He replied, “People would start focusing on policies and processes that would reduce the amount of fossil fuels without ruining the economy or wrecking society.” Then he added, “I think, I hope! that people will get it before it’s too late.”

I hope so, too.

Share to raise climate awareness


  1. Great article Laura. So many people have no idea how much work goes onto climate modelling and this is a real education.

    Trying to understand climate is like trying to capture quick silver… Only the right tools will work. Hats off to our scientists who have worked so hard to give us accurate data and haven’t been discouraged by our slowness to understand what that data means!

  2. Haha I must have written more more code than that in my career in IT.

    Whoop de do. I might be impressed if these Weather reports, which the meteorologists around here, cant even predict from Monday to Friday. If one does a least squares regression on RSS current data, which is empirical, you will find that the climate temperature has been static for nearly 20 years and only increased with the current El Nino. We must wait and see what happens when the El Nino finally putters out.

    Any way the point is that the climate models are not even close to the empirical data. Karl Popper would say that such a mismatch in data disproves the CO2 causes Global Warming hypothesis.

    Frankly I can do better weather predictions than the Met office anyway. It involves looking out my window in the morning and observing the wind directlion and clouds etc.

    Who in their right mind would rely on predictions for years and decades into the future?




Please enter your comment!
Please enter your name here