• Energy Research

Abstract Increases in cloud optical depth and liquid water path (LWP) are robust features of global warming model simulations in high latitudes, yielding a negative shortwave cloud feedback, but the mechanisms are still uncertain. Here the importance of microphysical processes for the negative optical depth feedback is assessed by perturbing temperature in the microphysics schemes of two aquaplanet models, both of which have separate prognostic equations for liquid water and ice. It is found that most of the LWP increase with warming is caused by a suppression of ice microphysical processes in mixed-phase clouds, resulting in reduced conversion efficiencies of liquid water to ice and precipitation. Perturbing the temperature-dependent phase partitioning of convective condensate also yields a small LWP increase. Together, the perturbations in large-scale microphysics and convective condensate partitioning explain more than two-thirds of the LWP response relative to a reference case with increased SSTs, and capture all of the vertical structure of the liquid water response. In support of these findings, a very robust positive relationship between monthly mean LWP and temperature in CMIP5 models and observations is shown to exist in mixed-phase cloud regions only. In models, the historical LWP sensitivity to temperature is a good predictor of the forced global warming response poleward of about 45°, although models appear to overestimate the LWP response to warming compared to observations. The results indicate that in climate models, the suppression of ice-phase microphysical processes that deplete cloud liquid water is a key driver of the LWP increase with warming and of the associated negative shortwave cloud feedback.

Abstract Increases in cloud optical depth and liquid water path (LWP) are robust features of global warming model simulations in high latitudes, yielding a negative shortwave cloud feedback, but the mechanisms are still uncertain. Here the importance of microphysical processes for the negative optical depth feedback is assessed by perturbing temperature in the microphysics schemes of two aquaplanet models, both of which have separate prognostic equations for liquid water and ice. It is found that most of the LWP increase with warming is caused by a suppression of ice microphysical processes in mixed-phase clouds, resulting in reduced conversion efficiencies of liquid water to ice and precipitation. Perturbing the temperature-dependent phase partitioning of convective condensate also yields a small LWP increase. Together, the perturbations in large-scale microphysics and convective condensate partitioning explain more than two-thirds of the LWP response relative to a reference case with increased SSTs, and capture all of the vertical structure of the liquid water response. In support of these findings, a very robust positive relationship between monthly mean LWP and temperature in CMIP5 models and observations is shown to exist in mixed-phase cloud regions only. In models, the historical LWP sensitivity to temperature is a good predictor of the forced global warming response poleward of about 45°, although models appear to overestimate the LWP response to warming compared to observations. The results indicate that in climate models, the suppression of ice-phase microphysical processes that deplete cloud liquid water is a key driver of the LWP increase with warming and of the associated negative shortwave cloud feedback.

AbstractFuture shifts of the austral midlatitude jet are subject to large uncertainties in climate model projections. Here we show that, in addition to other previously identified sources of intermodel uncertainty, changes in the timing of the stratospheric polar vortex breakdown modulate the austral jet response to greenhouse gas forcing during summertime (December–February). The relationship is such that a larger delay in vortex breakdown favors a more poleward jet shift, with an estimated 0.7–0.8° increase in jet shift per 10‐day delay in vortex breakdown. The causality of the link between the timing of the vortex breakdown and the tropospheric jet response is demonstrated through climate modeling experiments with imposed changes in the seasonality of the stratospheric polar vortex. The vortex response is estimated to account for about 30% of the intermodel variance in the shift of the summertime austral jet and about 45% of the mean jet shift.

AbstractFuture shifts of the austral midlatitude jet are subject to large uncertainties in climate model projections. Here we show that, in addition to other previously identified sources of intermodel uncertainty, changes in the timing of the stratospheric polar vortex breakdown modulate the austral jet response to greenhouse gas forcing during summertime (December–February). The relationship is such that a larger delay in vortex breakdown favors a more poleward jet shift, with an estimated 0.7–0.8° increase in jet shift per 10‐day delay in vortex breakdown. The causality of the link between the timing of the vortex breakdown and the tropospheric jet response is demonstrated through climate modeling experiments with imposed changes in the seasonality of the stratospheric polar vortex. The vortex response is estimated to account for about 30% of the intermodel variance in the shift of the summertime austral jet and about 45% of the mean jet shift.

AbstractHow low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

AbstractHow low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

Significance In current climate models, the anticipated amount of warming under greenhouse gas forcing, quantified by the “effective climate sensitivity,” increases as time passes. Consequently, effective climate sensitivity values inferred from the historical record may underestimate the future warming. However, the mechanisms of this increase in effective climate sensitivity are not understood, limiting our confidence in climate model projections of future climate change. Here, we present observational and modeling evidence that the magnitude of effective climate sensitivity partly depends on the evolution of the vertical profile of atmospheric warming. In climate models, as the Earth warms overall, the warming becomes increasingly muted aloft, and this alters the strength of feedbacks controlling the radiative response to greenhouse gas forcing.