Biweekly sea surface temperature (SST) variability significantly contributes to over 50% of the intraseasonal variability in the eastern equatorial Pacific (EEP) and Atlantic (EEA). Our study investigates this biweekly variability, employing a blend of in-situ and reanalysis datasets. The research identifies biweekly signals in SST, meridional wind, and ocean currents, notably in September-November in EEP and June-August in EEA. Biweekly southerly (northerly) drives simultaneous northward (southward) ocean currents in EEP, but with a 1-2-day phase delay in EEA. Consequently, these currents lead to SST anomalies with a 3-4-day lag in both EEP and EEA due to the presence of the cold tongue. The study reveals the origin of biweekly wind fluctuations in the western Pacific for EEP and the subpolar Pacific for EEA, connected by Rossby waves validated through a linearized non-divergent barotropic model. This research affirms the influence of subtropical and subpolar atmospheric forcing on equatorial SST.

Ocean warming is a key factor impacting future changes in climate. Here we investigate vertical structure changes in globally averaged ocean heat content (OHC) in high- (HR) and low-resolution (LR) future climate simulations with the Community Earth System Model (CESM). Compared with observation-based estimates, the simulated OHC anomalies in the upper 700 m and 2000 m during 1960-2020 are more realistic in CESM-HR than -LR. Under RCP8.5 scenario, the net surface heat into the ocean is very similar in CESM-HR and -LR However, CESM-HR has a larger increase in OHC in the upper 250 m compared to CESM-LR, but a smaller increase below 250 m. This difference can be traced to differences in eddy-induced vertical heat transport between CESM-HR and -LR in the historical period. Moreover, our results suggest that with the same heat input, upper-ocean warming is likely to be underestimated by most non-eddy-resolving climate models.

We investigate the role of ocean heat transport (OHT) in driving the decadal variability of the Arctic climate by analyzing the pre-industrial control simulation of a high-resolution climate model. While the OHT variability at 65˚N is greater in the Atlantic, we find that the decadal variability of Arctic-wide surface temperature and sea ice area is much better correlated with Bering Strait OHT than Atlantic OHT. In particular, decadal Bering Strait OHT variability causes significant changes in local sea ice cover and air-sea heat fluxes, which are amplified by shortwave feedbacks. These heat flux anomalies are regionally balanced by longwave radiation at the top of the atmosphere, without compensation by atmospheric heat transport (Bjerknes compensation). The sensitivity of the Arctic to changes in OHT may thus rely on an accurate representation of the heat transport through the Bering Strait, which is difficult to resolve in coarse-resolution ocean models.

It has been widely recognized that tropical cyclone (TC) genesis requires favorable large-scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large-scale environmental favorabilities in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relation between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer-learning technique to train ensembles of CNNs first on suites of high-resolution climate simulations with realistic seasonal TC activities and large-scale environmental conditions, and then subsequently on the state-of-the-art reanalysis from 1950 to 2019. Our CNNs can remarkably reproduce the historical TC records, and yields significant seasonal prediction skills when the large-scale environmental inputs are provided by operational climate forecasts. Furthermore, by forcing the ensemble CNNs with 20th century reanalysis products and phase 6 of the Coupled Model Intercomparison Project (CMIP6) experiments, we attempted to investigate TC variabilities and their changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our dynamic projections using TC-permitting high-resolution coupled climate model.

This study further evaluates the modeling approach of Jia et al. (2019) to investigate the potential effects of SST mesoscale variability on the atmospheric dynamics. The approach employs a global atmospheric circulation model coupled to a slab ocean model to produce two ensembles of simulations: one in which the ocean exhibits realistic SST mesoscale variability, and another in which the SST mesoscale variability is suppressed. The latter ensemble is produced by spatially filtering the SST analyses used for the estimation of the oceanic heat flux and the specification of the SST initial condition. The results of the present study, which focuses on the processes of the North Pacific, suggest that while the modeling approach yields the desired SST differences between the two ensembles at the mesoscales, it also introduces SST differences at the large scales that become the primary driver of the large scale differences in the simulated atmospheric flow. Diagnostics based on the eddy kinetic energy indicate that the large scale differences of the atmospheric flow lead to major differences in the dynamics of the jet stream and storm track. Because the large scale SST differences between the two ensembles are primarily driven by the differences between the prescribed estimates of the oceanic heat fluxes, finding a proper pair of those estimates is a necessary condition for the experiment design to detect the atmospheric response to SST mesoscale variability. The paper concludes with proposing a new strategy for the estimation of the oceanic heat fluxes.

This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air-sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy-resolving high-resolution (HR) and eddy-parameterized low-resolution (LR) ocean components. Here, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co-variability over scales between 50-10000 km and 60 days-80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper-ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ~2000-2500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R1, ~600-2000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean-driven variability also shows a surprising temporal persistence, from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that induced by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.

The irregular shapes of atmospheric rivers (ARs) and the scarcity of sounding data have hampered easy AR composite analyses and understandings about AR’s moisture transport mechanism. In this work we develop a method to composite AR-related variables from a reanalysis dataset. By averaging a large number of samples, the three dimensional structure and some evolutionary features of a typical North Pacific AR are revealed. An AR is typically located along and in front of the surface cold front of an extratropical cyclone. A meso-scale secondary circulation is observed in the cross-sections of the AR corridor, where both geostrophic and ageostrophic winds make indispensable contributions to the strong moisture transport. Geostrophic moisture advection across the cold front within the Equatorward half of the AR is created by the baroclinicity of the system, and serves as the primary moisture source of the AR-resided atmosphere. Moisture fluxes from the warm sector of the cyclone are primarily due to ageostrophic winds within the boundary layer, and are more important within the poleward half the AR, particularly during the genesis stage. The faster movement speed of the AR compared with low level winds enables the ARs to collect downwind moisture. While within the Equatorward half moisture transport is mostly attributed to geostrophic advection carried along by the propagating AR-cyclone couple. Driven by the intensifying geostrophic winds, ARs tend to reach peak moisture transport intensity about two days after genesis. Then reduced moisture and influxes from lateral boundaries prevent further moisture flux intensification.

Impacts of model horizontal resolution on sea-surface temperature (SST) biases are studied using high-resolution (HR) and low-resolution (LR) simulations with the Community Earth System Model (CESM) where the nominal resolutions are 0.1° for ocean and sea-ice and 0.25° for atmosphere and land in HR, and 1° for all component models in LR, respectively. Results show that, except within eastern boundary upwelling systems, SST is warmer in HR than LR. Globally averaged surface ocean heat budget analysis indicates that 1°C warmer global-mean SST in HR is mainly attributable to stronger nonlocal vertical mixing and shortwave heat flux, with the former prevailing over the latter in eddy-active regions. In the tropics, nonlocal vertical mixing is slightly more important than shortwave heat flux for the warmer SST in HR. Further analysis shows that the stronger nonlocal mixing in HR can be attributed to differences in both the surface heat flux and shape function strength used in the parameterization. In addition, the shape function shows a nonlinear relationship with surface heat flux in HR and LR, modulated by the eddy-induced vertical heat transport. The stronger shortwave heat flux in HR, on the other hand, is mainly caused by fewer clouds in the tropics. Finally, investigation of ocean advection reveals that the improved western boundary currents in HR also contribute to the reduction of SST biases in eddy-active regions.