A document by Nicholas Lutsko. Click on the document to view its contents.

Climate sensitivity peaks around 310K in a wide variety of climate models, ranging from idealized single column models to fully comprehensive climate models. Although an explanation for this peak has been developed using single column models with fixed relative humidity and line-by-line radiation, the relevance of this theory for explaining the peak in comprehensive climate models is unclear. In this paper we increase CO2 using a clear-sky 3-dimensional climate model with a radiation scheme that maintains accuracy for high CO2 and temperature levels. The Equilibrium Climate Sensitivity (ECS) of our model shows a plateau around 310K with the moistening of the subtropical regions caused by a slowdown in atmospheric circulation increasing the ECS at very high CO2 values. Though the changes in CO2 and temperature presented here are extreme, this study shows the potential importance of changes in atmospheric circulation and relative humidity in quantitative assessments of climate sensitivity.

Climate energy balance models (EBMs) – simple energy-balance-based models of climate change – are widely used. The simplest “linear” EBM is deficient in capturing the behavior of complex climate models, so a “two-layer” model with an additional degree of complexity, i.e. two vertical layers, is typically used. Other additional degrees of complexity are equally plausible as well, however, and different approaches to add a degree complexity have not been compared quantitatively. Here we compare four types of EBMs - two-layer, order-two (temperature-dependent feedback), two-region (in space), and two-timescale (fast and slow climate responses) - specifically, their ability to capture historical temperature change and simulated temperature changes in abrupt (4x) and gradual (1%-ramp) forcing scenarios. The two-region model outperforms the others. The two-region model’s best-fit parameters to historical temperatures are also more physically plausible than the next-best-fitting model, the two-layer model. We therefore conclude that the two-region model is the preferred climate EBM.

The Equatorial Pacific and ENSO have climatologically important seasonal cycles, with maximum Western Pacific SSTs occurring during boreal autumn and ENSO events peaking during boreal winter. In this work, we use the concept of a monsoonal mode to show that the presence of a large landmass in the northern hemisphere leads to this seasonal cycle. Specifically, warm air moving east from the Asian summer monsoon suppresses surface fluxes in the West Pacific, leading to increased heat content there during the following months. This, in turn, enhances ENSO growth rates during boreal autumn and causes ENSO events to peak in boreal winter.

Estimates of Earth’s clear-sky longwave feedback from climate models and observations robustly give a value of approximately -2 W/m^2/K, suggesting that this feedback can be estimated from first principles. Here we derive an analytical model for Earth’s clear-sky longwave feedback based on a novel spectral decomposition that splits the feedback into components from surface emission, CO2, H2O, and the H2O continuum. Analytic expressions are given for each of these terms based on their underlying physics, and the model can also be framed in terms of Simpson’s Law and deviations therefrom. We validate the model by reproducing line-by-line radiative transfer calculations across a wide range of climates, as well as the spatial dependence of the clear-sky feedback from radiative kernels. The latter result motivates us to estimate the spatial pattern of Earth’s clear-sky longwave feedback from reanalysis data, which shows good agreement with climate model data. Together, these results show that Earth’s clear-sky longwave feedback, its spatial variations, and its state-dependence across past and future climates can be successfully understood from only a handful of physical principles.

Improving understanding of the two-way interactions between clouds and large-scale atmospheric circulations requires modeling set-ups that can resolve cloud-scale processes, while also including representations of the circulations themselves. In this study, we investigate the potential for mock-Walker simulations to help untangle these interactions by assessing their ability to reproduce the observed climate over the equatorial Pacific. Mock-Walker simulations with realistic zonal sea-surface temperature (SST) gradients show qualitative similarities with reanalysis and satellite data, though notable differences include (1) the presence of double-celled overturning circulations, (2) extreme upper tropospheric dryness over the cold pools, and (3) substantially weaker longwave cloud radiative effects. The double-cell circulations are part of a transition from single to double cells as mean SST is increased, with the transition occurring near present day temperatures. The circulation changes dominate the response of mock-Walker simulations to warming, though their effects are smaller for relatively weak zonal SST gradients. Mock-Walker simulations also exhibit a wide range of climate sensitivities, due to cloud feedbacks that are strongly negative for larger SST gradients and strongly positive for weaker SST gradients. Finally, we show that radiative-subsidence balance can be used to explain the development of the double cells, but are unable to further explain the dynamics of the transition given the complex vertical profiles of stability and atmospheric radiative cooling in these simulations. Since Earth’s present-day climate is close to our simulated transition to a double-celled circulation, these dynamics merit further investigation.

The northeast United States is a densely-populated region with a number of major cities along the climatological storm track. Despite its economic and social importance, as well as the area’s vulnerability to flooding, there is significant uncertainty regarding future trends in extreme precipitation over the region. Here, we undertake a regional study of the projected changes in extreme precipitation over the NEUS through the end of the 21st century using an ensemble of high-resolution, dynamically-downscaled simulations from the NA-CORDEX project. We find that extreme precipitation increases throughout the region, with the largest changes in coastal regions and smaller changes inland. These increases are seen throughout the year, though the smallest changes in extreme precipitation are seen in the summer, in contrast to earlier studies. The frequency of heavy precipitation also increases, such that there are relatively fewer days with moderate precipitation and relatively more days with either no or strong precipitation. Averaged over the region, extreme precipitation increases by +3-5\%/$^{\circ}$C of local warming, with the largest fractional increases in southern and inland regions, and occurring during the winter and spring seasons. This is lower than the +7\%/$^{\circ}$C rate expected from thermodynamic considerations alone, and suggests that dynamical changes damp the increases in extreme precipitation. These changes are qualitatively robust across ensemble members, though there is notable intermodel spread associated with models’ climate sensitivity and with changes in mean precipitation. Together, the NA-CORDEX simulations suggest that this densely populated region may require significant adaptation strategies to cope with the increase in extreme precipitation expected at the end of the next century.

Although Earth’s troposphere does not superrotate in the annual-mean, for most of the year – from October to May – the winds of the tropical upper troposphere are westerly. We investigate this seasonal superrotation using reanalysis data and a single-layer model for the winds of the tropical upper troposphere. The temporal and spatial structures of the tropospheric superrotation are characterized, and the relationships between the superrotation and the leading modes of tropical interannual variability are quantified. It is also shown that the strength of the superrotation has remained roughly constant over the past few decades, despite the winds of the tropical upper troposphere decelerating (becoming more easterly) in other months. The underlying dynamics of the seasonal superrotation are studied using a combination of momentum budget analysis and numerical simulations with an axisymmetric, single-layer model of the tropical upper troposphere. Momentum flux convergence by stationary eddies accelerates the superrotation, while cross-equatorial easterly momentum transport associated with the Hadley circulation decelerates the superrotation. The seasonal modulations of these two competing factors shape the superrotation. The single-layer model is able to qualitatively reproduce the seasonal progression of the winds in the tropical upper troposphere, and highlights the northward displacement of the Intertropical Convergence Zone in the annual-mean as a key factor responsible for the annual cycle of the tropical winds.

We spectrally resolve the conventional clear-sky temperature and water vapor feedbacks in an idealized single-column framework, and show that the well-known partial compensation of these feedbacks is actually due to an almost perfect cancellation of the spectral feedbacks at wavenumbers where H2O is optically thick. This cancellation is a natural consequence of ‘Simpson’s Law’, which says that H2O emission temperatures do not change with surface warming if RH is fixed. We provide an explicit formulation and validation of Simpson’s Law, and furthermore show that this spectral cancellation of feedbacks is naturally incorporated in the alternative RH-based framework proposed by Held and Shell (2012) and Ingram (2012, 2013), thus bolstering the case for switching from conventional to RH-based feedbacks. We also find a negligible RH-based clear-sky lapse rate feedback, suggesting that the impact of changing lapse rates depends crucially on whether relative or specific humidity is held fixed

Previous results indicate that the global hydrological cycle is more sensitive to Solar Radiation Modification (SRM) than is the surface temperature. Thus, it is expected that restoring temperature with SRM would decrease evaporation and precipitation. However, here we show that a more complete radiative antidote to CO2 can be obtained by spectrally tuning the SRM intervention, reducing insolation at some wavelengths more than others. By concentrating solar dimming at near-infrared wavelengths, where H2O has strong absorption bands, the direct effect of CO2 on the tropospheric energy budget can be offset, which minimizes perturbations to the hydrological cycle. Idealized cloud-resolving simulations of radiative-convective equilibrium confirm that spectrally-tuned SRM can simultaneously maintain surface temperature and precipitation at their unperturbed values even as large quantities of CO2 are added to the atmosphere. These results illuminate the connection between the spectral properties of SRM interventions and their potential impacts on precipitation.

Low-cloud based emergent constraints have the potential to substantially reduce uncertainty in Earth’s Equilibrium Climate Sensitivity, but recent work has shown that previously-developed constraints fail in the latest generation of climate models, suggesting that new approaches are needed. Here, we investigate the potential for emergent constraints to reduce uncertainty in regional cloud feedbacks, rather than the global-mean cloud feedback. Strong relationships are found between the monthly/interannual variability of tropical clouds and the tropical net cloud feedback. These relationships are combined with observations to substantially narrow the uncertainty in the tropical cloud feedback and demonstrate that the tropical cloud feedback is likely $> 0$. Promising relationships are also found in the 90$^\circ$-60$^\circ$S and 30$^\circ$-60$^\circ$N regions, though these relationships are not robust across model generations and we have not identified the associated physical mechanisms.

While the higher mean Equilibrium Climate Sensitivity (ECS) in CMIP6 has been attributed to more positive cloud feedbacks, it is unclear what causes the greater range of ECS values across CMIP6 models compared to CMIP5. Here we investigate the relationship between radiative forcing and cloud feedbacks across the two model generations to explain the very high ECS values in some CMIP6 models. The relationship is sensitive to the definition of the forcing, particularly in CMIP6, but fixed-SST simulations suggest the shortwave cloud feedback ($\lambda_{SW, cl}$) is anti-correlated with the forcing in CMIP5 and weakly positively correlated with the forcing in CMIP6. These relationships reflect the cloud adjustment to the forcing, which is anti-correlated with $\lambda_{SW, cl}$ in CMIP5 and positively correlated in CMIP6. Although we are unable to identify a systematic change across the model generations, we do show that modifications to the land components of climate models are not responsible for the change in the relationship between cloud adjustments and cloud feedbacks, and that cloud adjustments are generally driven by low and, especially mid-level clouds. Moreover, models derived from the MOHC and NCAR modeling centers seem to be responsible for much of the trend between CMIP5 and CMIP6. Our analysis is severely limited by the available simulations, highlighting the need for targeted simulations to probe the sources of intermodel differences in cloud adjustments.