Low-level radio frequency(LLRF)systems stabilize the electromagnetic field in the RF cavities used for beam acceleration in particle accelerators.Reliable,accurate,and precise detection of RF amplitude and phase is pa...Low-level radio frequency(LLRF)systems stabilize the electromagnetic field in the RF cavities used for beam acceleration in particle accelerators.Reliable,accurate,and precise detection of RF amplitude and phase is particularly important to achieve high field stability for pulsed accelerators of free-electron lasers(FEL).The digital LLRF systems employ analog-to-digital converters to sample the frequency down-converted RF signal and use digital demodulation algorithms to calculate the RF amplitude and phase.Different sampling strategies and demodulation algorithms have been developed for these purposes and are introduced in this paper.This article focuses on advanced topics concerning RF detection,including accurate RF transient measurement,wideband RF detection,and RF detection with an asynchronous trigger,local oscillator,or clock.The analysis is based on the SwissFEL measurements,but the algorithms introduced are general for RF signal detection in particle accelerators.展开更多
Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss pos...Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.展开更多
文摘Low-level radio frequency(LLRF)systems stabilize the electromagnetic field in the RF cavities used for beam acceleration in particle accelerators.Reliable,accurate,and precise detection of RF amplitude and phase is particularly important to achieve high field stability for pulsed accelerators of free-electron lasers(FEL).The digital LLRF systems employ analog-to-digital converters to sample the frequency down-converted RF signal and use digital demodulation algorithms to calculate the RF amplitude and phase.Different sampling strategies and demodulation algorithms have been developed for these purposes and are introduced in this paper.This article focuses on advanced topics concerning RF detection,including accurate RF transient measurement,wideband RF detection,and RF detection with an asynchronous trigger,local oscillator,or clock.The analysis is based on the SwissFEL measurements,but the algorithms introduced are general for RF signal detection in particle accelerators.
文摘Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.