A new paper from Hausfather and colleagues (incl. me) has just been published with the most comprehensive assessment of climate model projections since the 1970s. Bottom line? Once you correct for small errors in the projected forcings, they did remarkably well.
Climate models are a core part of our understanding of our future climate. They also have been frequently attacked by those dismissive of climate change, who argue that since climate models are inevitably approximations they have no predictive power, or indeed, that they aren’t even scientific.
In an upcoming paper in Geophysical Research Letters, Zeke Hausfather, Henri Drake, Tristan Abbott and I took a look at how well climate models have actually been able to accurately project warming in the years after they were published. This is an extension of the comparisons we have been making on RealClimate for many years, but with a broader scope and a deeper analysis. We gathered all the climate models published between 1970 and the mid-2000s that gave projections of both future warming and future concentrations of CO2 and other climate forcings – from Manabe (1970) and Mitchell (1970) through to CMIP3 in IPCC 2007.
We found that climate models – even those published back in the 1970s – did remarkably well, with 14 out of the 17 projections statistically indistinguishable from what actually occurred.
We evaluated these models both on how well modeled warming compared with observed warming after models were published, and how well the relationship between warming and CO2 (and other climate forcings) in models compares to observations (the implied transient climate response) (see Figure). The second approach is important because even if an old model had gotten all the physics right, the future projected warming would be off if they assumed we would have 450 ppm CO2 in 2020 (which some did!). Future emissions depend on human societal behavior, not physical systems, and we can usefully distinguish evaluation of climate models physics from paths of future concentrations.
Figure 2 from Hausfather et al (2019) showing the comparisons between model predictions and observations for a) the temperature trends (above) and b) the implied Transient Climate Response (TCR) which is the trend divided by the forcing and scaled to an equivalent 2xCO2 forcing.
Urban areas may be at greater risk for precipitation-triggered landslides than rural areas, according to a new study that could help improve landslide predictions and hazard and risk assessments.
Landslides cause thousands of deaths and billions of dollars of damage annually. With over half of the world’s population in urban areas, and both urbanization and precipitation extremes expected to increase in the future, understanding how urban landscapes are affected by precipitation-triggered landslides is a pressing need.
The new study used a large database of precipitation-triggered landslides across the Pacific coast of the U.S. and isolated the influence of precipitation changes using a specific type of computer model. When the researchers controlled for other factors, like slope steepness, rock type, and wildfire, they found that urban landslide hazard was up to 10 times more sensitive to variations in precipitation than in rural areas. That means that the same increase in rainfall in rural and urban areas could be 10 times more likely to cause a landslide in a city.
The new research is published in the AGU journal Geophysical Research Letters, which publishes high-impact, short-format reports with immediate implications spanning all Earth and space sciences.
…
La géologie, une science plus que passionnante … et diverse
