自动气象站采集器显示板维修经验

根据ZQZ—CⅡ型自动气象站采集器的显示板的工作原理及维修实际经验，介绍了维修显示板的基本方法及主要芯片的性能，并对典型故障进行举例分析。     

PC机电源维修之我见

ＰＣ机电源维修之我见＠刘武斌＠唐来林￥省气候中心ＰＣ机电源维修之我见刘武斌（省气象装备中心０３０００２）唐来林（省气候中心０３０００６）ＰＣ机的维修已经进入“板级维修”时代，对它维修不再像过去维修其它设备那样，要求维修人员对所维修的设备的原理及线路结构有足...     

呼和浩特701C雷达测距分机距离显示故障原因分析

701C雷达的距离显示在原701雷达基础上做了很大改进,使原来的电子管电路彻底晶体管化、集成化,距离测定、显示实现了自动化。数字电路的大量引进使我们在实际故障维修中不能目测元器件的好坏,必须借助于新的维修方法和技术。701C雷达技术说明书只简单地介绍了距离显示的基本原理．各级电路的测量方法和实测参数并未给出。本文将结合在实际工作中的维修经验,以实例给出701C雷达距离显示故障分析方法。     

浅谈理论机务维修故障定位

对于机务维修人员来说,每一台设备或一套系统维修的前提是不仅要清楚该设备硬件的机械、电器、电子线路原理,而且熟练掌握软件的使用。通过实践,总结经验,达到快速准确地定位故障点,从而解决设备出现的问题,确保设备的正常运转。现在的气象设备不是单一的,大都是成一系统或网络,这给定位故障带来许多麻烦。这就要求对系统的整体构造、各单元、各板、甚至于各元件的功能及线路原理都要清楚。由于各地的情况不一,要求也不一样,但对我们来说,现在的大规模集成电路能达到板级维修就可以了。但有时手头上有零部件,为了节约开支,争取时间也需要达…     

PC—1500计算机特殊故障维修

PC-1500计算机在气象部门拥有量较大,该机使用一段时间后,显示器及打印机容易出故障。本文向大家介绍几点非元器件永久性损坏的维修经验。 1.开机后显示字迹较暗或看不清显示:这主要是显示用电压的调整电路故障所致。调整     

探空数据接收机疑难故障分析与排除

文章通过对探空数据接收机方位显示始终为0°故障原理阐述及对产生故障现象的原因进行全面分析,按照分析步骤进行排查,现场绘制电路板和天线座内元件及连接电缆电路图、准确判断断开的两根芯线接线位置,最终排除故障,从而深刻体会到在维修实践中要不断总结经验,还要在实践经验指导下进行维修工作。     

DYYZ系列自动站气象站地温要素故障及排除

DYYZ系列自动站气象地温要素的故障非常频繁，约占维修故障总量的50％以上。本从地温传感器、地温转接盒板和7芯通讯电缆3个引起地温要素故障因素分析引发的故障现象及相应的故障排除方法。     

七七式激光测云仪维修经验两例

目前大部分台站维修设备多数仅限于万用表,少数台站拥有信号发生器、示波器。本机的大部分电路是单脉冲工作的,难以用示波器观察其波形。所以维修前应弄清其原理,再根据故障现象,找出故障原因。作者根据多年的维修经验和对设备的研究,摸索出一些快捷的维修技巧。在此把测云仪较常见故障,且较难直接判断出故障点的十进制计数板的特殊维修处理方法,以及触发板的故障检查步骤介绍给大家,供参考。１　十进制计数板的特殊检修处理方法　　由于十进制计数电路采用分立元件,给维修工作带来一定的困难。在正常工作情况下,计数操作在１５０…     

防雷二极管引发的雨量故障维修分析

自动气象站雨量传感器出现故障的概率较高,多数疑难故障都是由电子器件性能变差但未完全损坏引发。若能围绕故障现象及相关因素确定好维修思路,就能快速准确地排除故障。以维修DYYZ-Ⅱ型自动站雨量回路的一次故障（降水时显示基本正常,但降水结束后较长时间内仍出现乱跳现象,约几小时后又趋于正常。为例说明。     

PC─1500计算机常见故障及维修

PC—1500计算机已使用多年了,它给测报发报、审核地面报表以及其它工作带来很多方便,现在其显示器及打印机的故障较多,这里介绍几点维修经验,供大家参考。1开机后显示为“0”,且字迹较暗uw电压值不够,应调整un电压。2开机后显示窗上全部显示“0”这是vnG整流二极管正极线路板铜箔断裂或是3.3p电容器负极线路的铜格断开。维修时焊上断裂处即可。3开机后显示全部是“8”是自动清零电路中二极管处线路板断开所致。4显示屏上内容模糊不贷,出现重叠检查右边的圆点标志。如果园点很淡或消失,则表明干电池已消耗尽。更换四节五号干电池即…     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;