Regional and seasonal variations of the double-ITCZ bias in CMIP5 models

Tropical Pacific SST and ITCZ Biases in Climate Models: Double Trouble for Future Rainfall Projections?

“…This result highlights the strong association between spatially coherent precipitation biases and equatorial SST biases, particularly over the western Pacific. Since SST and atmospheric energy budget are strongly correlated near the equator, the link between the cold SST biases and excessive double ITCZ can be explained using the energy flux framework, which predicts stronger double ITCZ in the western Pacific (Adam et al, 2018). Since SST and atmospheric energy budget are strongly correlated near the equator, the link between the cold SST biases and excessive double ITCZ can be explained using the energy flux framework, which predicts stronger double ITCZ in the western Pacific (Adam et al, 2018).…”

“…However, a negative regression coefficient value over a large portion of the SB in Figure 1e may be related to the nonparametric nature of this regression calculation and involves intermodel differences. Since SST and atmospheric energy budget are strongly correlated near the equator, the link between the cold SST biases and excessive double ITCZ can be explained using the energy flux framework, which predicts stronger double ITCZ in the western Pacific (Adam et al, 2018).…”

Feedback of Atmosphere‐Ocean Coupling on Shifts of the Intertropical Convergence Zone

“…For the relation (7) to capture the dependencies of the EFE on the energetic quantities on the right-hand side explicitly, NEI 0 and O 0 should be at most weakly dependent on E to first order. Both can be expected to change as tropical mean temperatures change (e.g., Adam et al, 2017). However, for perturbations that do not change the mean temperature, O 0 and O 0 ∕NEI 0 will primarily vary with oceanic factors such as the width of ocean upwelling (Held, 2001;Levine & Schneider, 2011), which can plausibly be taken to be independent of E to first order.…”

“…Additionally, both NEI 0 and O 0 vary near the equator, so their values vary by several W m −2 depending on whether one evaluates them on the equator or averages within a few degrees of the equator. And both the equatorial net energy input NEI 0 and the ocean energy uptake O 0 differ by up to ±10 W m −2 across current climate models (Adam, Schneider, et al, 2016;Adam et al, 2017). As a result, the damping coefficient = 1 + O 0 ∕NEI 0 is not known precisely from observations and varies from climate model to climate model.…”

Object‐Oriented Identification of Coherent Structures in Large Eddy Simulations: Importance of Downdrafts in Stratocumulus

“…Climate models have difficulties in representing these low clouds, mostly because of uncertainties associated with subgrid parameterized processes (Nam et al, 2012;Mechoso et al, 2014;Dal Gesso et al, 2015). Errors in low clouds then drive a part of surface biases (De Szoeke et al, 2012;Hourdin et al, 2015), uncertainties in climate feedbacks (Ceppi et al, 2017) or circulation biases (Adam et al, 2017) in climate models. Improving physical assumptions on cloud representation remains a difficult yet essential challenge for the climate science.…”