Scientists Conclude Dire Climate Change Models Were Wrong, Now What?

0
241

by Mish Shedlock, Mish Talk:

Scientists admit they did not model clouds accurately and that they need a supercomputer 1000 times more powerful to accurately do that.

Climate Change Modeling Meets Limits of Science 

The Wall Street Journal reports Climate Scientists Encounter Limits of Computer Models, Bedeviling Policy.

That is a non-paywalled, free-to-read link courtesy of the WSJ.

TRUTH LIVES on at https://sgtreport.tv/

It’s lengthy but an excellent read. I encourage everyone to take a look.

The dire predictions went out the window, seemingly unanimously. But there is plenty in the article for the fearmongers and the sceptics to both say “I told you so”.

Italic emphasis in the snips below is mine.

Introduction

For almost five years, an international consortium of scientists was chasing clouds, determined to solve a problem that bedeviled climate-change forecasts for a generation: How do these wisps of water vapor affect global warming?

They reworked 2.1 million lines of supercomputer code used to explore the future of climate change, adding more-intricate equations for clouds and hundreds of other improvements. They tested the equations, debugged them and tested again.

The scientists would find that even the best tools at hand can’t model climates with the sureness the world needs as rising temperatures impact almost every region.

Dire Forecasts Wrong

When they ran the updated simulation in 2018, the conclusion jolted them: Earth’s atmosphere was much more sensitive to greenhouse gases than decades of previous models had predicted, and future temperatures could be much higher than feared—perhaps even beyond hope of practical remedy.

“We thought this was really strange,” said Gokhan Danabasoglu, chief scientist for the climate-model project at the Mesa Laboratory in Boulder at the National Center for Atmospheric Research, or NCAR. “If that number was correct, that was really bad news.”

The scientists soon concluded their new calculations had been thrown off kilter by the physics of clouds in a warming world, which may amplify or damp climate change. “The old way is just wrong, we know that,” said Andrew Gettelman, a physicist at NCAR who specializes in clouds and helped develop the CESM2 model. “I think our higher sensitivity is wrong too. It’s probably a consequence of other things we did by making clouds better and more realistic. You solve one problem and create another.

UN Plays Down Extreme Forecasts

“We have a situation where the models are behaving strangely,” said Gavin Schmidt, director of the National Aeronautics and Space Administration’s Goddard Institute for Space Sciences, a leading center for climate modeling. “We have a conundrum.”

In November 2021, as leaders met in Glasgow to negotiate limits on greenhouse gases under the auspices of the 2015 Paris Accords, there were more than 100 major global climate-change models produced by 49 different research groups, reflecting an influx of people into the field.

In its guidance to governments last year, the U.N. climate-change panel for the first time played down the most extreme forecasts.

Hind Casting 

Before making new climate predictions for policy makers, an independent group of scientists used a technique called “hind-casting,” testing how well the models reproduced changes that occurred during the 20th century and earlier. Only models that re-created past climate behavior accurately were deemed acceptable.

Computing Clouds 

Because clouds can both reflect solar radiation into space and trap heat from Earth’s surface, they are among the biggest challenges for scientists honing climate models.

At any given time, clouds cover more than two-thirds of the planet. Their impact on climate depends on how reflective they are, how high they rise and whether it is day or night. They can accelerate warming or cool it down. They operate at a scale as broad as the ocean, as small as a hair’s width. Their behavior can be affected, studies show, by factors ranging from cosmic rays to ocean microbes, which emit sulfur particles that become the nuclei of water droplets or ice crystals.

“If you don’t get clouds right, everything is out of whack.” said Tapio Schneider, an atmospheric scientist at the California Institute of Technology and the Climate Modeling Alliance, which is developing an experimental model. “Clouds are crucially important for regulating Earth’s energy balance.”

In an independent assessment of 39 global-climate models last year, scientists found that 13 of the new models produced significantly higher estimates of the global temperatures caused by rising atmospheric levels of carbon dioxide than the older computer models—scientists called them the “wolf pack.” Weighed against historical evidence of temperature changes, those estimates were deemed unrealistic.

Dr. Gettelman, who helped develop CESM2, and his colleagues in their initial upgrade added better ways to model polar ice caps and how carbon and nitrogen cycle through the environment. To make the ocean more realistic, they added wind-driven waves. They fine-tuned the physics in its algorithms and made its vintage Fortran code more efficient.

Even the simplest diagnostic test is challenging. The model divides Earth into a virtual grid of 64,800 cubes, each 100 kilometers on a side, stacked in 72 layers. For each projection, the computer must calculate 4.6 million data points every 30 minutes. To test an upgrade or correction, researchers typically let the model run for 300 years of simulated computer time.

In their initial analysis, scientists discovered a flaw in how CESM2 modeled the way moisture interacts with soot, dust or sea-spray particles that allow water vapor to condense into cloud droplets. It took a team of 10 climate experts almost 5 months to track it down to a flaw in their data and correct it, the scientists said.

Strained Supercomputers 

The NCAR scientists in Boulder would like to delve more deeply into the behavior of clouds, ice sheets and aerosols, but they already are straining their five-year-old Cheyenne supercomputer, according to NCAR officials. A climate model able to capture the subtle effects of individual cloud systems, storms, regional wildfires and ocean currents at a more detailed scale would require a thousand times more computer power, they said.

Climate models need to link rising temperatures on a global scale to changing conditions in a local forest, watershed, grassland or agricultural zone, says NCAR forest ecologist Jacquelyn Shuman and NCAR scientist Gerald Meehl.

“Computer models that contain both large-scale and small-scale models allow you to really do experiments that you can’t do in the real world,” she said. “You can really ramp up the temperature, dial down the precipitation or completely change the amount of fire or lightning strikes that an area is seeing, so you can really diagnose how it all works together. That’s the next step. It would be very computationally expensive.”

“I think the climate models are the best tool we have to understand the future, even though they are far from perfect,” said Dr. Gettelman. “I’m not worried that the new models might be wrong. What scares me is that they might be right.”

Both Sides Now 

Models Will Get Better 

Scientists need to keep doing what they are doing. The models surely will get better.

Despite the models being wrong, they appear to be better than I expected.

Yet, had we listened to the dire forecasts from Al Gore, globetrotting Gretta, President Biden, and media darling AOC, where would we be?

Al Gore wanted to spend $90 trillion to fight climate change.

Read More @ MishTalk.com