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Key Points A preexisting stratocumulus deck is more persistent when experiencing warm‐air advection than cold‐air advection This persistence is due to reduced entrainment drying as a result of decoupling, which outweighs decreased cloud‐base moisture transport The mechanism is more notable when free‐tropospheric humidity is higher 

Understanding interactions between low clouds and land surface fluxes is critical to comprehending Earth's energy balance, yet their relationships remain elusive, with discrepancies between observations and modeling. Leveraging long‐term field observations over the Southern Great Plains, this investigation revealed that cloud‐land interactions are closely connected to cloud‐land coupling regimes. Observational evidence supports a dual‐mode interaction: coupled stratiform clouds predominate in low sensible heat scenarios, while coupled cumulus clouds dominate in high sensible heat scenarios. Reanalysis data sets, MERRA‐2 and ERA‐5, obscure this dichotomy owing to a shortfall in representing boundary layer clouds, especially in capturing the initiation of coupled cumulus in high sensible heat scenarios. ERA‐5 demonstrates a relatively closer alignment with observational data, particularly in capturing relationships between cloud frequency and latent heat, markedly outperforming MERRA‐2. Our study underscores the necessity of distinguishing different cloud coupling regimes, essential to the understanding of their interactions for advancing land‐atmosphere interactions.

 

The security of the Autonomous Driving (AD) system has been gaining researchers’ and public’s attention recently. Given that AD companies have invested a huge amount of resources in developing their AD models, e.g., localization models, these models, especially their parameters, are important intellectual property and deserve strong protection. In thiswork,we examine whether the confidentiality of productiongrade Multi-Sensor Fusion (MSF) models, in particular, Error-State Kalman Filter (ESKF), can be stolen from an outside adversary. We propose a new model extraction attack called TaskMaster that can infer the secret ESKF parameters under black-box assumption. In essence, TaskMaster trains a substitutional ESKF model to recover the parameters, by observing the input and output to the targeted AD system. To precisely recover the parameters, we combine a set of techniques, like gradient-based optimization, search-space reduction and multi-stage optimization. The evaluation result on real-world vehicle sensor dataset shows that TaskMaster is practical. For example, with 25 seconds AD sensor data for training, the substitutional ESKF model reaches centimeter-level accuracy, comparing with the ground-truth model. 

Abstract Coherent structures are critical for controlling turbulent boundary layers due to their roles in momentum and heat transfer in the flow. Turbulent coherent structures can be detected by measuring wall shear stresses that are footprints of coherent structures. In this study, wall shear stress fluctuations were measured simultaneously in a zero pressure gradient turbulent boundary layer using two house-made wall shear stress probes aligned in the spanwise direction. The wall shear stress probe consisted of two hot-wires on the wall aligned in a V-shaped configuration for measuring streamwise and spanwise shear stresses, and their performance was validated in comparison with a direct numerical simulation result. Relationships between measured wall shear stress fluctuations and streamwise velocity fluctuations were analyzed using conditional sampling techniques. The peak detection method and the variable-interval time-averaging (VITA) method showed that quasi-streamwise vortices were inclined toward the streamwise direction. When events were simultaneously detected by the two probes, stronger fluctuations in streamwise velocity were detected, which suggests that stronger coherent structures were detected. In contrast to the former two methods, the hibernating event detection method detects events with lower wall shear stress fluctuations. The ensemble-averaged mean velocity profile of hibernating events was shifted upward compared to the law of the wall, which suggests low drag status of the coherent structures related with hibernating events. These methods suggest significant correlations between wall shear stress fluctuations and coherent structures, which could motivate flow control strategies to fully exploit these correlations. 

Lightweight and elastically deformable soft materials that are thermally conductive are critical for emerging applications in wearable computing, soft robotics, and thermoregulatory garments. To overcome the fundamental heat transport limitations in soft materials, room temperature liquid metal (LM) has been dispersed in elastomer that results in soft and deformable materials with unprecedented thermal conductivity. However, the high density of LMs (>6 g cm⁻³) and the typically high loading (⩾85 wt%) required to achieve the desired properties contribute to the high density of these elastomer composites, which can be problematic for large‐area, weight‐sensitive applications. Here, the relationship between the properties of the LM filler and elastomer composite is systematically studied. Experiments reveal that a multiphase LM inclusion with a low‐density phase can achieve independent control of the density and thermal conductivity of the elastomer composite. Quantitative design maps of composite density and thermal conductivity are constructed to rationally guide the selection of filler properties and material composition. This new multiphase material architecture provides a method to fine‐tune material composition to independently control material and functional properties of soft materials for large‐area and weight‐sensitive applications.