无线输液报警系统设计

提出了一种基于MSP430单片机的能够自动实时监控输液状态的无线报警系统.系统采用OPA2335放大来自称重传感器的模拟信号,经ADS7818转换为数字信号;由MSP430单片机监控输液状态,产生报警信息并通过无线发射系统发出;地址匹配的接收端接收到报警信号后显示报警的地址和床位信息等.系统具有体积小、功耗低、传输距离较远的特点,实用性强、性能稳定,有一定的推广价值.     

河南省东亚飞蝗发生的时间序列分析

利用1953—2000年河南省东亚飞蝗的发生时间序列资料，做了飞蝗大发生年的游程检验，结果表明，1953—2000年间河南省东亚飞蝗的大发生年是随机出现的。     

Analysis of the Microphysical Properties of a Stratiform Rain Event Using an L-Band Profiler Radar

This paper investigates spatial and temporal distributions of the microphysical properties of precipitating stratiform clouds based on Doppler spectra of rain particles observed by an L-band profiler radar.The retrieval of raindrop size distributions（RSDs） is accomplished through eliminating vertical air motion and isolating the terminal fall velocity of raindrops in the observed Doppler velocity spectrum.The microphysical properties of raindrops in a broad stratiform region with weak convective cells are studied using data collected from a 1320-MHz wind profiler radar in Huayin,Shaanxi Province on 14 May 2009.RSDs and gamma function parameters are retrieved at altitudes between 700 and 3000 m above the surface,below a melting layer.It is found that the altitude of the maximum number of raindrops was closely related to the surface rain rate.The maximum number of large drops was observed at lower altitudes earlier in the precipitation event but at higher altitudes in later periods,suggesting decreases in the numbers of large and medium size raindrops.These decreases may have been caused by the breakup of larger drops and evaporation of smaller drops as they fell.The number of medium size drops decreased with increasing altitude.The relationship between reflectivity and liquid water content during this precipitation event was Z = 1.69×10~4M~（1.5）,and the relationship between reflectivity and rain intensity was Z = 256I~（1.4）.     

虚拟地形环境中的空间认知问题初探

虚拟地形环境是一个由计算机生成的以视觉感受为主,包括听觉、触觉可感知的综合模拟系统.本文简要介绍了虚拟地形环境空间认知的相关理论,并在多感觉通道空间认知、交互性、空间认知功效影响因素等方面进行了探讨.     

CMIP6陆面、雪和土壤湿度模式比较计划（LS3MIP）评述

<正>土壤湿度、积雪等陆面要素通过改变陆面热力状况,进而对大气环流、区域乃至全球气候产生重要影响。研究表明,土壤湿度是影响陆-气耦合的重要地表变量,它可以影响地表蒸发、调控地表热通量,从而对气候产生局地及非局地影响^[1-3]。积雪通过积雪-反照率效应和积雪-水文效应调节陆面热力状况,是大气环流和气候的重要影响因素^[4-6]。在海-陆-气耦合的全球气候模式中,     

虚拟数字视频积分器的研制及应用

从理论和实际两个方面具体的论述了虚拟数字视频积分器的原理和研制过程，简化了数字天气雷达系统的强度场数字处理终端。把所有的数字处理和计算交给电脑完成、从而用虚拟的终端代替了原来的数字视频积分器(DVIP)。     

两个气象应用项目软件的研制与应用

介绍了《三峡自动站报表软件》和《气象自记风报表信息化与格检、质检软件》的设计技术和基本功能。其中《三峡自动站报表软件》通过数据库视图技术从三峡水文气象数据库获取基本数据,通过SQL查询技术统计合计,最后通过开发动态链接库,调用Excel模版完成可视化报表;《气象自记风报表信息化与格检、质检软件》通过可视化界面,实现人工录入数据的采集、格检、保存,在此基础上进行对比质检和A模式存储。     

Predictable patterns and predictive skills of monsoon precipitation in Northern Hemisphere summer in NCEP CFSv2 reforecasts

The predictable patterns and predictive skills of monsoon precipitation in the Northern Hemisphere summer (June–July–August) are examined using reforecasts (1983–2010) from the National Center for Environmental Prediction Climate Forecast System version 2 (CFSv2). The possible connections of these predictable patterns with global sea surface temperature (SST) are investigated. The empirical orthogonal function analysis with maximized signal-to-noise ratio is used to isolate the predictable patterns of the precipitation for three regional monsoons: the Asian and Indo-Pacific monsoon (AIPM), the Africa monsoon (AFM), and the North America monsoon (NAM). Overall, the CFSv2 well predicts the monsoon precipitation patterns associated with El Niño-South Oscillation (ENSO) due to its good prediction skill for ENSO. For AIPM, two identified predictable patterns are an equatorial dipole pattern characterized by opposite variations between the equatorial western Pacific and eastern Indian Ocean, and a tropical western Pacific pattern characterized by opposite variations over the tropical northwestern Pacific and the Philippines and over the regions to its west, north, and southeast. For NAM, the predictable patterns are a tropical eastern Pacific pattern with opposite variations in the tropical eastern Pacific and in Mexico, the Guyana Plateau and the equatorial Atlantic, and a Central American pattern with opposite variations in the eastern Pacific and the North Atlantic and in the Amazon Plains. The CFSv2 can predict these patterns at least 5 months in advance. However, compared with the good skill in predicting AIPM and NAM precipitation patterns, the CFSv2 exhibits little predictive skill for AFM precipitation, probably because the variability of the tropical Atlantic SST plays a more important than ENSO in the AFM precipitation variation and the prediction skill is lower for the tropical Atlantic SST than the tropical Pacific SST.     

CLDASSD: Reconstructing Fine Textures of the Temperature Field Using Super-Resolution Technology

Before 2008,the number of surface observation stations in China was small.Thus,the surface observation data were too sparse to effectively support the High-resolution China Meteorological Administration’s Land Assimilation System(HRCLDAS)which ultimately inhibited the output of high-resolution and high-quality gridded products.This paper proposes a statistical downscaling model based on a deep learning algorithm in super-resolution to research the above problem.Specifically,we take temperature as an example.The model is used to downscale the 0.0625°×0.0625°,2-m temperature data from the China Meteorological Administration’s Land Data Assimilation System(CLDAS)to 0.01°×0.01°,named CLDASSD.We performed quality control on the paired data from CLDAS and HRCLDAS,using data from 2018 and 2019.CLDASSD was trained on the data from 31 March 2018 to 28 February 2019,and then tested with the remaining data.Finally,extensive experiments were conducted in the Beijing-Tianjin-Hebei region which features complex and diverse geomorphology.Taking the HRCLDAS product and surface observation data as the"true values"and comparing them with the results of bilinear interpolation,especially in complex terrain such as mountains,the root mean square error(RMSE)of the CLDASSD output can be reduced by approximately 0.1℃,and its structural similarity(SSIM)was approximately 0.2 higher.CLDASSD can estimate detailed textures,in terms of spatial distribution,with greater accuracy than bilinear interpolation and other sub-models and can perform the expected downscaling tasks.     

基于能见度及AOD数据的北京市PM2.5浓度的反演

选择北京市为研究地区,对2014～2017年AERONET（Aerosol Robotic Network）提供的CE-318太阳光度计440 nm波段反演的气溶胶光学厚度（AOD）进行风速订正,对订正后 AOD 日均数据与同期地面监测站PM2.5日均浓度数据做季节相关性分析并建立回归模型。又引入能见度因子并利用广义差分法构建2015～2017年北京市AOD与PM2.5浓度、能见度的三元回归模型,最后将2014年数据分为污染日和非污染日分别进行模型检验。结果表明:AOD与PM2.5浓度存在显著的线性正相关性,且存在季节性差异,夏季相关性最强、秋季次之、春季和冬季最低。引入能见度因子并消除自相关后,四季的模型相对误差均显著减小,模型拟合优度显著提高。检验结果为四季整体的平均相对误差在21%～31%范围内,与前人的结果相比拟合曲线的准确性得到了明显地提高。且模型对低PM2.5浓度日的模拟效果较好,对于高PM2.5浓度日的模拟效果较差。本研究对构建北京地区PM2.5浓度长期的历史数据具有重要的科学意义。