| 1. |
- Flynn, Clare Marie, et al.
(författare)
-
Hadley Cell Size and Strength Responses Depend on Turbulent Drag
- 2023
-
Ingår i: Journal of the Atmospheric Sciences. - 0022-4928 .- 1520-0469. ; 80:4, s. 1047-1064
-
Tidskriftsartikel (refereegranskat)abstract
- The position and strength of the Hadley cell circulation determine the habitable zones in the tropics, yet our understanding of and ability to predict changes in the circulation is limited. One potentially important source of uncertainty is the dependence of the Hadley cell on turbulent drag. Here, the sensitivity of the Hadley cell and associated features such as the intertropical convergence zone to variations in the magnitude of the turbulent drag is explored with an atmospheric general circulation model in aquaplanet configuration. The tropical circulation and precipitation, and extratropical features such as the polar jet stream, displayed a strong sensitivity to the strength of the parameterized turbulent drag, with distinct low- or high-drag regimes. However, the response of the meridional heat transport produced a surprising departure from previous expectations: with greater drag, simulations exhibited less heat transport than low-drag simulations, which is in the opposite sense to that from Held and Hou. This may be due to the energetic constraints in the present model framework. When exposed to a uniform global warming, the response of the ITCZ precipitation depends strongly on the choice of drag, whereas most simulations exhibit a poleward expansion of the subtropics.
|
|
| 2. |
- Flynn, Clare Marie, et al.
(författare)
-
On the climate sensitivity and historical warming evolution in recent coupled model ensembles
- 2020
-
Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 20:13, s. 7829-7842
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 3. |
- Flynn, Clare Marie, et al.
(författare)
-
Strong aerosol cooling alone does not explain cold-biased mid-century temperatures in CMIP6 models
- 2023
-
Ingår i: Atmospheric Chemistry And Physics. - : Copernicus Publications. - 1680-7316 .- 1680-7324. ; 23:23, s. 15121-15133
-
Tidskriftsartikel (refereegranskat)abstract
- The current generation of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibits a surprisingly cold-biased ensemble-mean mid-20th century global-mean surface temperature anomaly, compared to the previous generation Phase 5 (CMIP5) and to the observed mid-century (1940-1970) temperature anomaly. Most CMIP6 models, 31 of 36 models in contrast to 17 of 27 CMIP5 models, are colder than the uncertainty range of the observed anomaly, indicating that the CMIP6 suppressed warming is not caused by a few cold models. However, no clear cause that sufficiently explains the tendency towards suppressed mid-20th century warming emerges. Whereas models that best match observations exclusively exhibit weaker aerosol forcing than that exhibited by colder models, there is not a clear relationship between mid-century temperatures and aerosol forcing. Likewise, no systematic differences emerge among other model aerosol representations, such as inclusion of aerosol-cloud interactions for ice clouds in the model or the type of aerosol model input data set used, nor variations in greenhouse gas forcing or climate sensitivity, that could explain the suppressed warming. This indicates the presence of another cause, or more likely a set of causes, of the suppressed warming in many CMIP6 models. Thus, the prospect of a strong constraint on present-day aerosol forcing based on the mid-century warming is weakened, even if it is encouraging that those models that do match the observed warming best all have relatively weak aerosol forcing.
|
|
| 4. |
- Renoult, Martin, et al.
(författare)
-
A Bayesian framework for emergent constraints : case studies of climate sensitivity with PMIP
- 2020
-
Ingår i: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 16:5, s. 1715-1735
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper we introduce a Bayesian framework, which is explicit about prior assumptions, for using model ensembles and observations together to constrain future climate change. The emergent constraint approach has seen broad application in recent years, including studies constraining the equilibrium climate sensitivity (ECS) using the Last Glacial Maximum (LGM) and the mid-Pliocene Warm Period (mPWP). Most of these studies were based on ordinary least squares (OLS) fits between a variable of the climate state, such as tropical temperature, and climate sensitivity. Using our Bayesian method, and considering the LGM and mPWP separately, we obtain values of ECS of 2.7K (0.6-5.2, 5th-95th percentiles) using the PMIP2, PMIP3, and PMIP4 datasets for the LGM and 2.3K (0.5-4.4) with the PlioMIP1 and PlioMIP2 datasets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7K (0.7-5.2) using the LGM and 2.3K (0.4-4.5) using the mPWP. An advantage of the Bayesian framework is that it is possible to combine the two periods assuming they are independent, whereby we obtain a tighter constraint of 2.5K (0.8-4.0) using the restricted ensemble. We have explored the sensitivity to our assumptions in the method, including considering structural uncertainty, and in the choice of models, and this leads to 95% probability of climate sensitivity mostly below 5K and only exceeding 6K in a single and most uncertain case assuming a large structural uncertainty. The approach is compared with other approaches based on OLS, a Kalman filter method, and an alternative Bayesian method. An interesting implication of this work is that OLS-based emergent constraints on ECS generate tighter uncertainty estimates, in particular at the lower end, an artefact due to a flatter regression line in the case of lack of correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation for their potential use in future probabilistic estimations of climate sensitivity.
|
|
