ALBERT

Description: [1]  CMIP5 multimodel ensemble projection of midlatitude storm track changes has been examined. Storm track activity is quantified by temporal variance of meridional wind and sea level pressure (psl), as well as cyclone track statistics. For the Southern Hemisphere (SH), CMIP5 models project clear poleward migration, upward expansion, and intensification of the storm track. For the Northern Hemisphere (NH), the models also project some poleward shift and upward expansion of the storm track in the upper troposphere/lower stratosphere, but mainly weakening of the storm track toward its equatorward flank in the troposphere. Consistent with these, CMIP5 models project significant increase in the frequency of extreme cyclones during the SH cool season, but significant decrease in such events in the NH. Comparisons with CMIP3 projections indicate high degrees of consistency for SH projections, but significant differences are found in the NH. Overall, CMIP5 models project larger decrease in storm track activity in the NH troposphere, especially over North America in winter, where psl variance as well as cyclone frequency and amplitude are all projected to decrease significantly. In terms of climatology, similar to CMIP3, most CMIP5 models simulate storm tracks that are too weak and display equatorward biases in their latitude. These biases have also been related to future projections. In the NH, the strength of a model's climatological storm track is negatively correlated with its projected amplitude change under global warming, while in the SH, models with large equatorward biases in storm track latitude tend to project larger poleward shifts.

Description: [1]  Cyclones are responsible for much of the high impact weather in the extratropics, thus how they will change under global warming is of great concern. Several studies have used the multi-model climate simulations conducted under Phase 5 of the Coupled Model Intercomparison Project (CMIP5) to examine such changes. One study suggested that the frequency of strong cyclones is projected to decrease over the North Pacific, while another concluded that this frequency will increase. [2]  A single tracking algorithm has been used to derive cyclone statistics from 23 CMIP5 simulations using two different definitions of cyclones: cyclones as minima in total sea level pressure (SLP), or cyclones as minima in SLP perturbations about a large scale, low frequency background. When cyclones are defined by total SLP, the frequency of deep cyclones over the Pacific is projected to increase, while if cyclones are defined as perturbations, this frequency is projected to decrease. These differences are shown to be due to a projected deepening of the climatological mean Aleutian low. [3]  In view of these results, it is important to critically assess how cyclones should be defined. Preliminary results suggest that among CMIP5 simulations, over the Pacific, both the projected changes in the frequency of high wind events and mean available potential energy are better correlated with the projected changes in the frequency of cyclones defined as perturbations. It is concluded that more research should be done to quantify and understand the impacts of the different definitions of cyclones.

Description: [1]  Many studies have attempted to estimate the equilibrium climate sensitivity (CS) to the doubling of CO 2 concentrations. One common methodology is to compare versions of Earth Models of Intermediate Complexity (EMICs) to spatially and/or temporally averaged historical observations. Despite the persistent efforts, CS remains uncertain. It is, thus far, unclear what is driving this uncertainty. Moreover, the effects of the internal climate variability on the CS estimates obtained using this method have not received thorough attention in the literature. [2]  Using a statistical approximator (“emulator”) of an EMIC, we show in an observation system simulation study, that unresolved internal climate variability appears to be a key driver of CS uncertainty (as measured by the 68% credible interval). We first simulate many realizations of pseudo-observations from an emulator at a “true” prescribed CS, and then re-estimate the CS using the pseudo-observations and an inverse parameter estimation method. [3]  We demonstrate that a single realization of the internal variability can result in a sizable discrepancy between the best CS estimate and the truth. Specifically, the average discrepancy is 0.84 °C, with the feasible range up to several °C. The results open the possibility that recent climate sensitivity estimates from global observations and EMICs are systematically considerably lower or higher than the truth, since they are typically based on the same realization of climate variability. This possibility should be investigated in future work. We also find that estimation uncertainties increase at higher climate sensitivities, suggesting that a high CS might be difficult to detect.