Next month, after a yearlong delay because of the pandemic, the U.N. Intergovernmental Panel on Climate Change (IPCC) will begin to release its first major assessment of human-caused global warming since 2013. The report, the first part of which will appear on 9 August, will drop on a world that has starkly changed in 8 years, warming by more than 0.3°C to nearly 1.3°C above preindustrial levels. Weather has grown more severe, seas are measurably higher, and mountain glaciers and polar ice have shrunk sharply. And after years of limited action, many countries, pushed by a concerned public and corporations, seem willing to curb their carbon emissions.https://www.sciencemag.org/news/2021/07/un-climate-panel-confronts-implausibly-hot-forecasts-future-warming
But as climate scientists face this alarming reality, the climate models that help them project the future have grown a little too alarmist. Many of the world’s leading models are now projecting warming rates that most scientists, including the modelmakers themselves, believe are implausibly fast. In advance of the U.N. report, scientists have scrambled to understand what went wrong and how to turn the models, which in other respects are more powerful and trustworthy than their predecessors, into useful guidance for policymakers. “It’s become clear over the last year or so that we can’t avoid this,” says Gavin Schmidt, director of NASA’s Goddard Institute for Space Studies.
Ahead of each major IPCC report, the world’s climate modeling centers run a set of scenarios for the future, calculating how different global emissions paths will alter the climate. These raw results, compiled in the Coupled Model Intercomparison Project (CMIP), then feed directly into the IPCC report. The results live on as other scientists use them to assess the impacts of climate change, insurance companies and financial institutions forecast effects on economies and infrastructure, and economists calculate the true cost of carbon emissions, says Jean-François Lamarque, a lead climate modeler at the National Center for Atmospheric Research (NCAR) and CMIP’s new director. “This is not an ivory tower type of exercise.”
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A cadre of researchers dedicated to the task of translating the models into useful projections could also help, says Angeline Pendergrass, a climate scientist at Cornell University who helped develop one technique for weighting the model results by their accuracy and independence. “It’s an actual job to go between the basic science and the tools I’m messing around with,” she says.
For now, policymakers and other researchers need to avoid putting too much stock in the unconstrained extreme warming the latest models predict, says Claudia Tebaldi, a climate scientist at Pacific Northwest National Laboratory and one of the leaders of CMIP’s climate projections. Getting that message out will be a challenge. “These issues don’t translate very well in practice,” she says. “It’s going to be hard for people looking to make some projection of a water basin in the West to make sense of it.”
Already scientific papers are appearing using CMIP’s unconstrained worst-case scenarios for 2100, adding fire to what are already well-justified fears. But that practice needs to change, Schmidt says. “You end up with numbers for even the near-term that are insanely scary—and wrong.”
Next month, after a yearlong delay because of the pandemic, the U.N. Intergovernmental Panel on Climate Change (IPCC) will begin to release its first major assessment of human-caused global warming since 2013. The report, the first part of which will appear on 9 August, will drop on a world that has starkly changed in 8 years, warming by more than 0.3°C to nearly 1.3°C above preindustrial levels. Weather has grown more severe, seas are measurably higher, and mountain glaciers and polar ice have shrunk sharply. And after years of limited action, many countries, pushed by a concerned public and corporations, seem willing to curb their carbon emissions.https://www.sciencemag.org/news/2021/07/un-climate-panel-confronts-implausibly-hot-forecasts-future-warming
But as climate scientists face this alarming reality, the climate models that help them project the future have grown a little too alarmist. Many of the world’s leading models are now projecting warming rates that most scientists, including the modelmakers themselves, believe are implausibly fast. In advance of the U.N. report, scientists have scrambled to understand what went wrong and how to turn the models, which in other respects are more powerful and trustworthy than their predecessors, into useful guidance for policymakers. “It’s become clear over the last year or so that we can’t avoid this,” says Gavin Schmidt, director of NASA’s Goddard Institute for Space Studies.
Ahead of each major IPCC report, the world’s climate modeling centers run a set of scenarios for the future, calculating how different global emissions paths will alter the climate. These raw results, compiled in the Coupled Model Intercomparison Project (CMIP), then feed directly into the IPCC report. The results live on as other scientists use them to assess the impacts of climate change, insurance companies and financial institutions forecast effects on economies and infrastructure, and economists calculate the true cost of carbon emissions, says Jean-François Lamarque, a lead climate modeler at the National Center for Atmospheric Research (NCAR) and CMIP’s new director. “This is not an ivory tower type of exercise.”
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A cadre of researchers dedicated to the task of translating the models into useful projections could also help, says Angeline Pendergrass, a climate scientist at Cornell University who helped develop one technique for weighting the model results by their accuracy and independence. “It’s an actual job to go between the basic science and the tools I’m messing around with,” she says.
For now, policymakers and other researchers need to avoid putting too much stock in the unconstrained extreme warming the latest models predict, says Claudia Tebaldi, a climate scientist at Pacific Northwest National Laboratory and one of the leaders of CMIP’s climate projections. Getting that message out will be a challenge. “These issues don’t translate very well in practice,” she says. “It’s going to be hard for people looking to make some projection of a water basin in the West to make sense of it.”
Already scientific papers are appearing using CMIP’s unconstrained worst-case scenarios for 2100, adding fire to what are already well-justified fears. But that practice needs to change, Schmidt says. “You end up with numbers for even the near-term that are insanely scary—and wrong.”
Next month, after a yearlong delay because of the pandemic, the U.N. Intergovernmental Panel on Climate Change (IPCC) will begin to release its first major assessment of human-caused global warming since 2013. The report, the first part of which will appear on 9 August, will drop on a world that has starkly changed in 8 years, warming by more than 0.3°C to nearly 1.3°C above preindustrial levels. Weather has grown more severe, seas are measurably higher, and mountain glaciers and polar ice have shrunk sharply. And after years of limited action, many countries, pushed by a concerned public and corporations, seem willing to curb their carbon emissions.
But as climate scientists face this alarming reality, the climate models that help them project the future have grown a little too alarmist. Many of the world’s leading models are now projecting warming rates that most scientists, including the modelmakers themselves, believe are implausibly fast. In advance of the U.N. report, scientists have scrambled to understand what went wrong and how to turn the models, which in other respects are more powerful and trustworthy than their predecessors, into useful guidance for policymakers. “It’s become clear over the last year or so that we can’t avoid this,” says Gavin Schmidt, director of NASA’s Goddard Institute for Space Studies.
Ahead of each major IPCC report, the world’s climate modeling centers run a set of scenarios for the future, calculating how different global emissions paths will alter the climate. These raw results, compiled in the Coupled Model Intercomparison Project (CMIP), then feed directly into the IPCC report. The results live on as other scientists use them to assess the impacts of climate change, insurance companies and financial institutions forecast effects on economies and infrastructure, and economists calculate the true cost of carbon emissions, says Jean-François Lamarque, a lead climate modeler at the National Center for Atmospheric Research (NCAR) and CMIP’s new director. “This is not an ivory tower type of exercise.”
/.../
A cadre of researchers dedicated to the task of translating the models into useful projections could also help, says Angeline Pendergrass, a climate scientist at Cornell University who helped develop one technique for weighting the model results by their accuracy and independence. “It’s an actual job to go between the basic science and the tools I’m messing around with,” she says.
For now, policymakers and other researchers need to avoid putting too much stock in the unconstrained extreme warming the latest models predict, says Claudia Tebaldi, a climate scientist at Pacific Northwest National Laboratory and one of the leaders of CMIP’s climate projections. Getting that message out will be a challenge. “These issues don’t translate very well in practice,” she says. “It’s going to be hard for people looking to make some projection of a water basin in the West to make sense of it.”
Already scientific papers are appearing using CMIP’s unconstrained worst-case scenarios for 2100, adding fire to what are already well-justified fears. But that practice needs to change, Schmidt says. “You end up with numbers for even the near-term that are insanely scary—and wrong.”
AbstractMina rödmarkeringar ovan.
«The Earth's equilibrium climate sensitivity (ECS) to a doubling of atmospheric CO2, along with the transient climate response (TCR) and greenhouse gas emissions pathways, determines the amount of future warming. Coupled climate models have in the past been important tools to estimate and understand ECS. ECS estimated from Coupled Model Intercomparison Project Phase 5 (CMIP5) models lies between 2.0 and 4.7 K (mean of 3.2 K), whereas in the latest CMIP6 the spread has increased to 1.8–5.5 K (mean of 3.7 K), with 5 out of 25 models exceeding 5 K. It is thus pertinent to understand the causes underlying this shift. Here we compare the CMIP5 and CMIP6 model ensembles and find a systematic shift between CMIP eras to be unexplained as a process of random sampling from modeled forcing and feedback distributions. Instead, shortwave feedbacks shift towards more positive values, in particular over the Southern Ocean, driving the shift towards larger ECS values in many of the models. These results suggest that changes in model treatment of mixed-phase cloud processes and changes to Antarctic sea ice representation are likely causes of the shift towards larger ECS. Somewhat surprisingly, CMIP6 models exhibit less historical warming than CMIP5 models, despite an increase in TCR between CMIP eras (mean TCR increased from 1.7 to 1.9 K). The evolution of the warming suggests, however, that several of the CMIP6 models apply too strong aerosol cooling, resulting in too weak mid-20th century warming compared to the instrumental record.»
AbstractMina rödmarkeringar ovan.
«The Earth's equilibrium climate sensitivity (ECS) to a doubling of atmospheric CO2, along with the transient climate response (TCR) and greenhouse gas emissions pathways, determines the amount of future warming. Coupled climate models have in the past been important tools to estimate and understand ECS. ECS estimated from Coupled Model Intercomparison Project Phase 5 (CMIP5) models lies between 2.0 and 4.7 K (mean of 3.2 K), whereas in the latest CMIP6 the spread has increased to 1.8–5.5 K (mean of 3.7 K), with 5 out of 25 models exceeding 5 K. It is thus pertinent to understand the causes underlying this shift. Here we compare the CMIP5 and CMIP6 model ensembles and find a systematic shift between CMIP eras to be unexplained as a process of random sampling from modeled forcing and feedback distributions. Instead, shortwave feedbacks shift towards more positive values, in particular over the Southern Ocean, driving the shift towards larger ECS values in many of the models. These results suggest that changes in model treatment of mixed-phase cloud processes and changes to Antarctic sea ice representation are likely causes of the shift towards larger ECS. Somewhat surprisingly, CMIP6 models exhibit less historical warming than CMIP5 models, despite an increase in TCR between CMIP eras (mean TCR increased from 1.7 to 1.9 K). The evolution of the warming suggests, however, that several of the CMIP6 models apply too strong aerosol cooling, resulting in too weak mid-20th century warming compared to the instrumental record.»
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