Southeast China has comparable stratus cloud to that over the oceans,especially in the cold seasons(winter and spring),and this cloud has a substantial impact on energy and hydrological cycles.However,uncertainties re...Southeast China has comparable stratus cloud to that over the oceans,especially in the cold seasons(winter and spring),and this cloud has a substantial impact on energy and hydrological cycles.However,uncertainties remain across datasets and simulation results about the long-term trend in low-cloud cover in Southeast China,making it difficult to understand climate change and related physical processes.In this study,multiple datasets and numerical simulations were applied to show that low-cloud cover in Southeast China has gone through two stages since 1980—specifically,a decline and then a rise,with the turning point around 2008.The regional moisture transport plays a crucial role in low-cloud cover changes in the cold seasons and is mainly affected by the Hadley Cell in winter and the Walker Circulation in spring,respectively.The moisture transport was not well simulated in CMIP6 climate models,leading to poor simulation of the low-cloud cover trend in these models.This study provides insights into further understanding the regional climate changes in Southeast China.展开更多
为实时传输海量船舶图像,为有效监控船舶实时航行状况提供保障,研究基于云计算的船舶图像网络数据低时延传输方法。结合云计算技术,构建船舶图像网络数据传输平台,通过平台数据接收单元将大量船舶网络数据存入云端服务器内;数据处理单...为实时传输海量船舶图像,为有效监控船舶实时航行状况提供保障,研究基于云计算的船舶图像网络数据低时延传输方法。结合云计算技术,构建船舶图像网络数据传输平台,通过平台数据接收单元将大量船舶网络数据存入云端服务器内;数据处理单元基于云计算的分布式处理特点,结合并行运行框架Map Reduce和并行化K-means聚类算法,并行挖掘云端服务器内的船舶图像网络数据;信道均衡单元结合所构建的船舶通信网络节点能量消耗模型,均衡船舶通信网络信道,运用均衡信道实现所挖掘船舶图像网络数据的传输。结果显示,该方法的数据挖掘速率高,数据传输过程中各信道能量开销均衡,且可低至3.5 k J,传输船舶图像网络数据的时延可低至10.23 ms,实现了数据的低时延传输。展开更多
基金This work was supported by the Ministry of Science and Technology of China[grant number 2017YFA0604002]the National Natural Science Foundation of China[grant numbers 41925023,41575073,41621005,and 91744208]the Collaborative Innovation Center of Climate Change,Jiangsu Province.
文摘Southeast China has comparable stratus cloud to that over the oceans,especially in the cold seasons(winter and spring),and this cloud has a substantial impact on energy and hydrological cycles.However,uncertainties remain across datasets and simulation results about the long-term trend in low-cloud cover in Southeast China,making it difficult to understand climate change and related physical processes.In this study,multiple datasets and numerical simulations were applied to show that low-cloud cover in Southeast China has gone through two stages since 1980—specifically,a decline and then a rise,with the turning point around 2008.The regional moisture transport plays a crucial role in low-cloud cover changes in the cold seasons and is mainly affected by the Hadley Cell in winter and the Walker Circulation in spring,respectively.The moisture transport was not well simulated in CMIP6 climate models,leading to poor simulation of the low-cloud cover trend in these models.This study provides insights into further understanding the regional climate changes in Southeast China.
文摘为实时传输海量船舶图像,为有效监控船舶实时航行状况提供保障,研究基于云计算的船舶图像网络数据低时延传输方法。结合云计算技术,构建船舶图像网络数据传输平台,通过平台数据接收单元将大量船舶网络数据存入云端服务器内;数据处理单元基于云计算的分布式处理特点,结合并行运行框架Map Reduce和并行化K-means聚类算法,并行挖掘云端服务器内的船舶图像网络数据;信道均衡单元结合所构建的船舶通信网络节点能量消耗模型,均衡船舶通信网络信道,运用均衡信道实现所挖掘船舶图像网络数据的传输。结果显示,该方法的数据挖掘速率高,数据传输过程中各信道能量开销均衡,且可低至3.5 k J,传输船舶图像网络数据的时延可低至10.23 ms,实现了数据的低时延传输。
