采用独立化设计方法,将仿生手分为控制模块、手指模块、散热模块并进行单独设计,制作了集成化的仿生手,可以快捷地实现模块化手指的分离与组装。采用形状记忆合金丝作为驱动器,设计了可以实现驱动位移放大的凸轮结构,使S M A在驱动过程...采用独立化设计方法,将仿生手分为控制模块、手指模块、散热模块并进行单独设计,制作了集成化的仿生手,可以快捷地实现模块化手指的分离与组装。采用形状记忆合金丝作为驱动器,设计了可以实现驱动位移放大的凸轮结构,使S M A在驱动过程中的有效输出位移得到有效放大。在Matlab中对仿生手进行了运动空间仿真,并通过3 D打印制作了总质量为410 g的仿生手样机。采用温度反馈方式,提高了仿生手在不同温度环境中的响应能力以及对SMA的温度保护,对日常生活物品进行了抓取实验验证。结果表明,新型仿生手具有较大的抓取尺寸和抓取重量,具有拆装方便、控制简单、抓取稳定的优点,实现了控制与驱动的高度集成。展开更多
This study evaluated the simulated cloud radiative feedbacks(CRF)during the El Ni?o–Southern Oscillation(ENSO)cycle in the latest version of the Chinese Academy of Meteorological Sciences climate system model(CAMS-CS...This study evaluated the simulated cloud radiative feedbacks(CRF)during the El Ni?o–Southern Oscillation(ENSO)cycle in the latest version of the Chinese Academy of Meteorological Sciences climate system model(CAMS-CSM).We conducted two experimental model simulations:the Atmospheric Model Intercomparison Project(AMIP),forced by the observed sea surface temperature(SST);and the preindustrial control(PIcontrol),a coupled run without flux correction.We found that both the experiments generally reproduced the observed features of the shortwave and longwave cloud radiative forcing(SWCRF and LWCRF)feedbacks.The AMIP run exhibited better simulation performance in the magnitude and spatial distribution than the PIcontrol run.Furthermore,the simulation biases in SWCRF and LWCRF feedbacks were linked to the biases in the representation of the corresponding total cloud cover and precipitation feedbacks.It is interesting to further find that the simulation bias originating in the atmospheric component was amplified in the PIcontrol run,indicating that the coupling aggravated the simulation bias.Since the PIcontrol run exhibited an apparent mean SST cold bias over the cold tongue,the precipitation response to the SST anomaly(SSTA)changes during the ENSO cycle occurred towards the relatively warmer western equatorial Pacific.Thus,the corresponding cloud cover and CRF shifted westward and showed a weaker magnitude in the PIcontrol run versus observational data.In contrast,the AMIP run was forced by the observational SST,hence representing a more realistic CRF.Our results demonstrate the challenges of simulating CRF in coupled models.This study also underscores the necessity of realistically representing the climatological mean state when simulating CRF during the ENSO cycle.展开更多
Climate sensitivity and feedbacks are basic and important metrics to a climate system. They determine how large surface air temperature will increase under CO_2 forcing ultimately, which is essential for carbon reduct...Climate sensitivity and feedbacks are basic and important metrics to a climate system. They determine how large surface air temperature will increase under CO_2 forcing ultimately, which is essential for carbon reduction policies to achieve a specific warming target. In this study, these metrics are analyzed in a climate system model newly developed by the Chinese Academy of Meteorological Sciences(CAMS-CSM) and compared with multi-model results from the Coupled Model Comparison Project phase 5(CMIP5). Based on two idealized CO_2 forcing scenarios, i.e.,abruptly quadrupled CO_2 and CO_2 increasing 1% per year, the equilibrium climate sensitivity(ECS) and transient climate response(TCR) in CAMS-CSM are estimated to be about 2.27 and 1.88 K, respectively. The ECS is near the lower bound of CMIP5 models whereas the TCR is closer to the multi-model ensemble mean(MME) of CMIP5 due to compensation of a relatively low ocean heat uptake(OHU) efficiency. The low ECS is caused by an unusually negative climate feedback in CAMS-CSM, which is attributed to cloud shortwave feedback(λSWCL) over the tropical Indo-Pacific Ocean.The CMIP5 ensemble shows that more negative λSWCL is related to larger increase in low-level(925–700 hPa)cloud over the tropical Indo-Pacific under warming, which can explain about 90% of λSWCL in CAMS-CSM. Static stability of planetary boundary layer in the pre-industrial simulation is a critical factor controlling the low-cloud response and λSWCL across the CMIP5 models and CAMS-CSM. Evidently, weak stability in CAMS-CSM favors lowcloud formation under warming due to increased low-level convergence and relative humidity, with the help of enhanced evaporation from the warming tropical Pacific. Consequently, cloud liquid water increases, amplifying cloud albedo, and eventually contributing to the unusually negative λSWCL and low ECS in CAMS-CSM. Moreover, the OHU may influence climate feedbacks and then the ECS by modulating regional sea surface temperature responses.展开更多
文摘采用独立化设计方法,将仿生手分为控制模块、手指模块、散热模块并进行单独设计,制作了集成化的仿生手,可以快捷地实现模块化手指的分离与组装。采用形状记忆合金丝作为驱动器,设计了可以实现驱动位移放大的凸轮结构,使S M A在驱动过程中的有效输出位移得到有效放大。在Matlab中对仿生手进行了运动空间仿真,并通过3 D打印制作了总质量为410 g的仿生手样机。采用温度反馈方式,提高了仿生手在不同温度环境中的响应能力以及对SMA的温度保护,对日常生活物品进行了抓取实验验证。结果表明,新型仿生手具有较大的抓取尺寸和抓取重量,具有拆装方便、控制简单、抓取稳定的优点,实现了控制与驱动的高度集成。
基金Supported by the National Key Research and Development Program(2018YFC1506002)National Natural Science Foundation of China(41606011,41705059,41630423,and 41420104002)+6 种基金Basic Scientific Research and Operation Foundation of Chinese Academy of Meteorological Sciences(2017Y007)National Science Foundation AGS-1565653National(Key)Basic Research and Development(973)Program of China(2015CB453200)Startup Foundation for Introducing Talent of NUIST,LASG Open Projectopen fund of State Key Laboratory of Loess and Quartary Geology(SKLLQG1802)NUIST Excellent Bachelor Dissertation Funding(1241591901003)the Earth System Modeling Center(ESMC)contribution(No.247)
文摘This study evaluated the simulated cloud radiative feedbacks(CRF)during the El Ni?o–Southern Oscillation(ENSO)cycle in the latest version of the Chinese Academy of Meteorological Sciences climate system model(CAMS-CSM).We conducted two experimental model simulations:the Atmospheric Model Intercomparison Project(AMIP),forced by the observed sea surface temperature(SST);and the preindustrial control(PIcontrol),a coupled run without flux correction.We found that both the experiments generally reproduced the observed features of the shortwave and longwave cloud radiative forcing(SWCRF and LWCRF)feedbacks.The AMIP run exhibited better simulation performance in the magnitude and spatial distribution than the PIcontrol run.Furthermore,the simulation biases in SWCRF and LWCRF feedbacks were linked to the biases in the representation of the corresponding total cloud cover and precipitation feedbacks.It is interesting to further find that the simulation bias originating in the atmospheric component was amplified in the PIcontrol run,indicating that the coupling aggravated the simulation bias.Since the PIcontrol run exhibited an apparent mean SST cold bias over the cold tongue,the precipitation response to the SST anomaly(SSTA)changes during the ENSO cycle occurred towards the relatively warmer western equatorial Pacific.Thus,the corresponding cloud cover and CRF shifted westward and showed a weaker magnitude in the PIcontrol run versus observational data.In contrast,the AMIP run was forced by the observational SST,hence representing a more realistic CRF.Our results demonstrate the challenges of simulating CRF in coupled models.This study also underscores the necessity of realistically representing the climatological mean state when simulating CRF during the ENSO cycle.
基金Supported by the National Key Research and Development Program(2017YFA0603503)National Natural Science Foundation of China(41605057 and 41661144009)
文摘Climate sensitivity and feedbacks are basic and important metrics to a climate system. They determine how large surface air temperature will increase under CO_2 forcing ultimately, which is essential for carbon reduction policies to achieve a specific warming target. In this study, these metrics are analyzed in a climate system model newly developed by the Chinese Academy of Meteorological Sciences(CAMS-CSM) and compared with multi-model results from the Coupled Model Comparison Project phase 5(CMIP5). Based on two idealized CO_2 forcing scenarios, i.e.,abruptly quadrupled CO_2 and CO_2 increasing 1% per year, the equilibrium climate sensitivity(ECS) and transient climate response(TCR) in CAMS-CSM are estimated to be about 2.27 and 1.88 K, respectively. The ECS is near the lower bound of CMIP5 models whereas the TCR is closer to the multi-model ensemble mean(MME) of CMIP5 due to compensation of a relatively low ocean heat uptake(OHU) efficiency. The low ECS is caused by an unusually negative climate feedback in CAMS-CSM, which is attributed to cloud shortwave feedback(λSWCL) over the tropical Indo-Pacific Ocean.The CMIP5 ensemble shows that more negative λSWCL is related to larger increase in low-level(925–700 hPa)cloud over the tropical Indo-Pacific under warming, which can explain about 90% of λSWCL in CAMS-CSM. Static stability of planetary boundary layer in the pre-industrial simulation is a critical factor controlling the low-cloud response and λSWCL across the CMIP5 models and CAMS-CSM. Evidently, weak stability in CAMS-CSM favors lowcloud formation under warming due to increased low-level convergence and relative humidity, with the help of enhanced evaporation from the warming tropical Pacific. Consequently, cloud liquid water increases, amplifying cloud albedo, and eventually contributing to the unusually negative λSWCL and low ECS in CAMS-CSM. Moreover, the OHU may influence climate feedbacks and then the ECS by modulating regional sea surface temperature responses.