Air‐sea exchanges across oceanic fronts are critical in powering cloud formation, precipitation, and atmospheric storms. Oceanic submesoscale fronts of scales 1–10 km are characterized by strong sea surface temperature (SST) gradients. However, it remains elusive how submesoscale fronts affect the overlying atmosphere due to a lack of high‐resolution observations or models. Based on rare high‐resolution in situ observations in the Kuroshio Extension region, we quantify the air‐sea exchanges across an oceanic submesoscale front. The cross‐front SST and turbulent heat flux gradients reaches 2.4°C/km and 47 W/m²/km, respectively, far stronger than that typically found in mesoscale‐resolving products. The stronger SST gradient drives substantially stronger air‐sea fluxes and vertical mixing than mesoscale fronts, enhancing cloud formations. The intense air‐sea exchanges across submesoscale fronts are confirmed in idealized model simulations, but not resolved in mesoscale‐resolving climate models. Our finding provides essential knowledge for improving simulations of cloud formation, precipitation, and storms in climate models.

Because it uses a set of model integrations to simulate the temporally varying background probability distribution function and implement Bayes' theorem, the ensemble Kalman filter (EnKF), which produces an optimal data assimilation solution that coherently combines model dynamics and observational information, has been widely used in weather and climate studies. However, in practice, the EnKF has two limitations: (1) the insufficient representation of error statistics of low‐frequency background flows due to its finite ensemble size and model integration over time and (2) the high demand of computational power for ensemble model integrations in high‐resolution coupled Earth system models. Given that background error statistics consist of stationary, slow‐varying, and fast‐varying parts, a multi‐timescale, high‐efficiency approximate EnKF (MSHea‐EnKF) is designed to increase the representation of low‐frequency background error statistics and enhance its computational efficiency. The MSHea‐EnKF is a combination of multi‐timescale filters implemented by regressions based on data sampled from the time series of a single‐model solution. Validation shows that with the improved representation of stationary and slow‐varying background statistics, the MSHea‐EnKF only requires a small fraction of computer resources and shows a comparable performance relative to a finite size EnKF. Our experiments also show that the result can be further improved by using a small set of MSHea‐EnKFs through second‐stage EnKF filtering if sufficient computer resources are available. This new algorithm makes it practical to assimilate multisource observations into any high‐resolution coupled Earth system model that is intractable with current computing power for weather‐climate analysis and predictions.

With a pair of high‐resolution (HR, 10 km ocean and 25 km atm) and low‐resolution (LR, 100 km ocean and 100 km atm) Community Earth System Model (CESM) simulations, we investigate and compare the long‐term mean Northern Hemisphere (NH) wintertime storm tracks against reanalysis data. Based on several Eulerian measures, the CESM‐HR shows a poleward shift of the NH storm tracks and a reduced equatorward bias in the North Pacific relative to the CESM‐LR. Those may be associated with the refined topography of the Tibetan Plateau as well as the improved subtropical jet, stationary planetary waves, atmospheric baroclinity, and baroclinic energy conversion over the North Pacific. We also find that sharper oceanic fronts along the Kuroshio Extension accompanied by enhanced local atmospheric baroclinity and strengthened eddy heat flux over the northern North Pacific could be related to those improvements. Nevertheless, the North Atlantic storm track in HR is placed too north, leading to a larger negative bias over the subtropical zone than in LR. The simulated insufficient subtropical sensible and latent heat fluxes and northward zonal winds in HR seemingly coincide with the deficits in the North Atlantic storm track. The stronger NH branch of the Hadley cell and its poleward expansion in HR may be linked to the changes in the tropical precipitation and the poleward shift of the NH storm tracks. Further studies of attributing these biases to a specific aspect of the climate model by sensitivity experiments are warranted for further clarification of the mechanisms.