Prototyping low-cost automatic weather stations for natural disaster monitoring

Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.

Analysis and Treatment of Faults in the Operation of Rainfall Sensors in Automatic Weather Stations

Based on the structure and working principle of rain sensors in new automatic weather stations,according to the abnormal precipitation records found in the observation business,the possible faults of rain sensors were analyzed,and treatment methods were discussed. Daily maintenance and management measures were put forward to ensure the normal operation of rain sensors and improve the quality of surface meteorological observation business.

Adaptive Coding Design of Automatic Weather Station Message for"Cloud+End"Networking

A large number of automatic weather stations with different observation elements and gradient configurations are connected for operation,in order to meet the meteorological service needs of different scenes.The station density and observation frequency are encrypted to obtain observation data with higher spatial and temporal resolution.The original message with fixed element data location is the data combination of all observation elements and the maximum observation gradient of each element,which not only has higher invalid data redundancy,but also restricts the efficiency of data collection and processing,and also increases communication costs.An adaptive coding design method for the original message of automatic weather station is proposed.The embedded software coding algorithm of the weather station collector is optimized according to"plug and output"to realize intelligent networking,intelligent identification of observation elements and gradients,and dynamic flexible output of messages with variable length.The intelligent networking and business application of nearly 4000 automatic weather stations across the province show that the networking data acquisition and processing are efficient and stable.

Towards Increasing Data Availability for Meteorological Services: Inter-Comparison of Meteorological Data from a Synoptic Weather Station and Two Automatic Weather Stations in Kenya

Meteorological data is useful for varied applications and sectors ranging from weather and climate forecasting, landscape planning to disaster management among others. However, the availability of these data requires a good network of manual meteorological stations and other support systems for its collection, recording, processing, archiving, communication and dissemination. In sub-Saharan Africa, such networks are limited due to low investment and capacity. To bridge this gap, the National Meteorological Services in Kenya and few others from African countries have moved to install a number of Automatic Weather Stations (AWSs) in the past decade including a few additions from private institutions and individuals. Although these AWSs have the potential to improve the existing observation network and the early warning systems in the region, the quality and capacity of the data collected from the stations are not well exploited. This is mainly due to low confidence, by data users, in electronically observed data. In this study, we set out to confirm that electronically observed data is of comparable quality to a human observer recorded data, and can thus be used to bridge data gaps at temporal and spatial scales. To assess this potential, we applied the simple Pearson correlation method and other statistical tests and approaches by conducting inter-comparison analysis of weather observations from the manual synoptic station and data from two Automatic Weather Stations (TAHMO and 3D-PAWS) co-located at KMD Headquarters to establish existing consistencies and variances in several weather parameters. Results show there is comparable consistency in most of the weather parameters between the three stations. Strong associations were noted between the TAHMO and manual station data for minimum (r = 0.65) and maximum temperatures (r = 0.86) and the maximum temperature between TAHMO and 3DPAWS (r = 0.56). Similar associations were indicated for surface pressure (r = 0.99) and RH (r > 0.6) with the weakest correlations occurring in wind direction and speed. The Shapiro test for normality assumption indicated that the distribution of several parameters compared between the 3 stations were normally distributed (p > 0.05). We conclude that these findings can be used as a basis for wider use of data sets from Automatic Weather Stations in Kenya and elsewhere. This can inform various applications in weather and climate related decisions.

Fault Analysis and Maintenance of DZZ Series of Automatic Weather Stations

The instruments of regional automatic weather station are placed outside to measure daily changes of meteorological factors. Due to common influence of sun,wind,rain and other factors,it is very easy to cause various faults and damages of the instrument. The construction of regional automatic weather station network plays an important role in improving forecast accuracy,servicing local government and ecological civilization construction,providing scientific disaster prevention and relief decision-making basis for government department. In this paper,based on daily operation situation of regional automatic weather station in Shaoyang region,combining communication,hardware and software,fault situation of collector,temperature and humidity sensor,wind sensor and rainfall sensor in automatic weather station is analyzed in detail. Moreover,some common fault cases are listed and analyzed,some troubleshooting methods are summarized,and daily maintenance measures are proposed.

Benchmarking the Robustness of Cellular Up-Links in Automatic Weather Station Networks

We present a problem for benchmarking the robustness of cellular up-links, in an automatic weather station (AWS) testbed. Based on the problem, we conduct a small-scale measurement study of robustness, where the AWS is equipped with four (4) cellular modems for weather data delivery. The effectiveness of up-links is challenging because of overlapping spatial-temporal factors such as the presence of good reflectors that lead to multi-path effects, interference, network load or other reasons. We argue that, there is a strong need for independent assessments of their robustness, to perform end-to-end network measurement. However, it is yet difficult to go from a particular measurement to an assessment of the entire network. We extensively measure the variability of Radio Signal Strength (RSSI) as link metric on the cellular modems. The RSSI is one of the important link metrics that can determine the robustness of received RF signals, and explore how they differed from one another at a particular location and instant time. We also apply the statistical analysis that quantifies the level of stability by considering the robustness, referring short-term variation, and determines good up-link in comparison to weak one. The results show that the robustness of cellular up-links exists for an unpredictable period of time and lower than one could hope. More than 50% of up-links are intermittent. Therefore, we plan to extend our work by exploring RSSI thresholds, to develop a classification scheme supporting a decision whether a link is either intermittent or not. This will help in normalizing the level of stability, to design the RSSI estimation metric for the robust routing protocol in weather data networks.

QA/QC Procedures for <i>in-Situ</i>Calibration of a High Altitude Automatic Weather Station: The Case Study of the AWS Pyramid, 5050 m asl, Khumbu Valley, Nepal

In-situ calibrations of weather stations are usually performed by positioning standard instruments close to the station under calibration and comparing the obtained results. This procedure could be useful to evaluate the proper functioning of the monitoring equipments, but do not allowed the determination of a calibration curve that allow the corrections of the acquired parameters. Thus, the development of a dedicated facility for in-situ calibration of weather stations, enabling simultaneous generation of a wide range of temperatures and pressures could offer important improvements in this framework, particularly if this facility is applied to high mountains monitoring stations where the weather stations calibrations could be very difficult. This paper will present the calibration chamber developed in the framework of the EMRP-METEOMET (Metrology for Meteorology) Project, which aims is to bring metrological traceability to high altitude meteorological instruments and through this experience will provide a general overview on the importance of the application of this methodology at different levels.

Quality Control System of Meteorological Real-time Data from Automatic Weather Stations in Shandong

The quality control system for meteorological real-time data from automatic weather stations in Shandong realized integration of communi- cation system and provincial quality control system, and an interaction platform which was mainly created by Web was set up. The system not only was fully guaranteed for the funning of basic business, also improved the reliability of the data.

Application of RIA Technology in WEB Platform in the Regional Automatic Meteorological Station

Started from the business reality of automatic weather station,the basic idea that the information platform(system) of regional automatic weather station was designed and realized by using RIA technology was put forward.Based on that RIA technology and the client-side development technology FLEX were expounded,'Regional Automatic Weather Station Information Platform' which had the non-refresh operation,the good user experience and data processing capability was designed and realized by introducing ArcGIS API for Flex,and the technology advantage of RIA was fully embodied.

2013-2020年海河流域农田水热碳通量及气象要素观测数据集

本研究以海河流域官厅水库旁农田生态系统为研究对象,采用蒸渗仪、涡动相关仪、大孔径闪烁仪和自动气象站/气象要素梯度等观测系统,开展农田生态系统多尺度通量和气象要素的长期定位观测。本数据集由多尺度通量(米,百米,公里级)和气象要素数据组成,观测项目包括生态系统净碳交换量、潜热通量/蒸散发、感热通量、空气温度、空气相对湿度、风速、风向、向下/上短波辐射、向下/上长波辐射、净辐射、大气压、降水、红外辐射温度、光合有效辐射、土壤温度、土壤水分、土壤热通量、平均土壤温度等。本数据集经过了严格的处理和质量控制,可用于研究水库消涨对周边生态系统碳水等物质和能量的循环带来的影响,也可为相关遥感模型或过程模型等研究提供有力的数据基础。

地面自动气象站数据流式处理设计与实现

针对观测密度和频次日益增加的海量地面自动气象站数据,在气象大数据云平台(天擎)中设计了基于Storm的实时流式处理,利用大规模并行处理的优势提高地面自动气象站数据的处理时效。在流式处理中,设计处理拓扑直接解码标准格式的数据消息;消息确认采用手工确认的方式,将数据解码组件锚定数据接入组件,实现每条数据的可靠处理;数据解码时进行字节校验和时间检查等,过滤异常数据;应用批量加定时的发送策略,解决海量监控信息发送气象综合业务实时监控系统(天镜)的问题;集群部署时保留部分剩余资源,有效应对单节点异常。应用效果表明:国家气象站小时数据的服务时效由全国综合气象信息共享系统(CIMISS)的175 s提高至天擎的78 s,约6×10^(4)个区域气象站小时数据的服务时效由CIMISS的5 min提高至天警的2 min,实况分析系统将数据源切换至天擎后,相同时间检索可获取的站点数量较CIMISS增加1倍。2021年12月基于Storm的流式处理与天擎一同在国省业务化运行,实现了长期稳定运行,为MICAPS4、SWAN2.0、实况分析系统等用户提供高效稳定的地面自动气象站数据。

中国地面自动气象站小时降水质量控制方法

高时空分辨率自动气象站降水观测作为重要数据来源,已被广泛应用于强对流天气监测、模式评估、预报复盘等研究工作。仪器故障、特殊天气条件下观测设备的局限性等因素是自动气象站降水数据不确定性的主要来源,这些问题在无人值守气象站尤为突出。该研究基于2021—2023年中国自动气象站实时观测降水量数据、高时空分辨率雷达数据和高灵敏性降水类天气现象数据,发展适应于中国自动气象站小时降水数据的多源数据协同质量控制方法(multi-source data collaborative quality control,MDC)。通过综合定量指标与典型个例分析,对MDC的应用效果进行全面评估。结果显示:MDC判识正确率为99.92%,错误数据命中率较现行业务提升39.3%。基于多源降水观测数据时空一致性,MDC显著提升了晴空降水、融雪性降水和虚假零值降水等异常数据的甄别能力,有效弥补了传统方法的不足。

石家庄市夏季短时强降水特征及其影响因子

利用2013—2020年6—8月石家庄市215个地面加密自动气象站逐小时降水资料,采用数理统计学方法对其夏季短时强降水事件(flash heavy rainfall events,FHR events)和暴雨的精细化分布特征及影响因子进行研究。结果发现,石家庄夏季FHR events具有西部山区发生频次少,高频区分散且局地性强的特点。[200,600)m自动气象站分布在FHR events高频区的比例最大,600 m以上山地发生频次减少。山地高频区与山体走向和地形坡度有关。山地FHR events较平原持续时长长,但小时降水强度小。63.6%的暴雨日伴随FHR events发生,随着地形高度增加和暴雨日发生频次减少,有FHR events发生的暴雨日比例下降。短时强降水逐时发生站次随降水强度增大而骤减,60 mm·h^(-1)以上短时强降水日变化不明显。短时强降水平均小时降水强度日变化呈多峰型。石家庄FHR events高频区局地性强,发生于弱天气尺度强迫型下的FHR events为预报的难点,其地理环境及本地特征的影响有待深入分析。

地面风传感器加热装置设计及试验研究

在冬季雨雪、冻雨、雨凇和雾凇等天气现象发生时,自动气象站风传感器转动部件容易发生冻结,造成风向风速观测数据缺测。为解决风传感器冻结的问题,设计一种基于分级加热技术的风传感器加热装置,采用多级加热元件组合控制的方式,实现自适应启动不同级别的加热模式。通过试验对风传感器加热装置性能进行测试,以及对风向风速观测数据进行处理分析,评估风传感器加热装置在气象观测业务中应用的可行性。结果表明,带有加热装置的风传感器起到了很好的防冻结作用,运行更加稳定;带有加热装置的风向风速数据完整性优于未带有加热装置的风传感器,两者风速具有较强的相关性,相关系数均在95%以上;两者风向一致性显著,均在80%以上,10 min风向一致性优于2 min风向一致性。可见,风传感器加热装置可有效减少风传感器冻结发生的次数,及时消除结冰层,降低观测人员设备维护工作量,提高风传感器运行的稳定性和数据的连续性,为风传感器加热装置应用于气象观测业务提供决策支撑。

中国第1-10次北极科学考察走航自动气象站观测数据集(1999-2019年)

气象数据是地球系统科学重要的基础性数据之一。在1999–2019年间中国北极科学考察的10个航次中,利用船载自动气象站(Lica-701、Vaisala MILOS500、天诺CR3000和XZC6-1)采集了走航气象数据。本研究对中国第1–10次北极考察走航气象数据进行了标准化整理、质量控制和评估,形成本数据集,主要包括气温、相对湿度、气压、风向和风速5个气象要素,共有20个气象数据文件,数据时间分辨率为1小时。本数据集能够为深入了解北极区域气候变化、研究北极区域天气变化过程及评估气候变化对生态环境影响等研究提供数据支撑。

Contrast Analysis of Two Low Vortices Weather Processes

Two cold vortex weather processes in Liaoning Province in June of 2006 were analyzed.In the process of low vortex of June 3,strong convection weather,such lightning storm and hailstone,came forth in most areas of Liaoning Province.White and bright cloud was shown in satellite nephogram.Bow echo and cyclonic circumfluence were shown in weather radar production.In the process of low vortex of June 14,strong precipitation weather came forth in most area of Liaoning Province.Based on the velocity field production of weather radar,the relative place of front and radar station can be judged.The weather situation and forecast were the main basis of short-term prediction.And satellite nephogram,weather radar,automatic weather station play important roles in the monitoring and short-term prediction of disaster weathers.

Extreme Antarctic Cold of Late Winter 2023

Extreme cold temperatures were observed in July and August 2023,coinciding with the WINFLY(winter fly-in)period of mid to late August into September 2023,meaning aircraft operations into McMurdo Station and Phoenix Airfield were adversely impacted.Specifically,with temperatures below−50℃,safe flight operation was not possible because of the risk of failing hydraulics and fuel turning to gel onboard the aircraft.The cold temperatures were measured across a broad area of the Antarctic,from East Antarctica toward the Ross Ice Shelf,and stretching across West Antarctica to the Antarctic Peninsula.A review of automatic weather station measurements and staffed station observations revealed a series of sites recording new record low temperatures.Four separate cold phases were identified,each a few days in duration and occurring from mid-July to the end of August 2023.A brief analysis of 500-hPa geopotential height anomalies shows how the mid-tropospheric atmospheric environment evolves in relation to these extreme cold temperatures.The monthly 500-hPa geopotential height anomalies show strong negative anomalies in August.Examination of composite geopotential height anomalies during each of the four cold phases suggests various factors leading to cold temperatures,including both southerly off-content flow and calm atmospheric conditions.Understanding the atmospheric environment that leads to such extreme cold temperatures can improve prediction of such events and benefit Antarctic operations and the study of Antarctic meteorology and climatology.

基于LoRa的自动气象站故障诊断装置的设计与实现

为了改善人工定位设备故障难度高、耗时长的问题,设计了一款基于LoRa无线通信技术的自动气象站故障诊断装置;该装置包含4个监测单元和1个主控单元,通过STM32系统实现对相关信号的采集和处理;其中,4个监测单元分别布设在自动气象站的各关键组成部分,可采集相关供电信号、传感器输出信号和工作状态信息等,并通过LoRa通信将信息无线传输至主控单元;主控单元则对信息进行汇总和分析,结合其内置的故障综合诊断方法来定位出故障发生的准确位置,并经HMI屏幕输出定位结果,以协助业务人员及时排除故障;经测试表明,该装置能够实现自动气象站故障位置的自动判定,可大幅缩短故障排除耗时,提高装备保障效率。

2016—2021年5—10月辽宁省降水量时空分布精细化特征分析

选用2016—2021年5—10月辽宁省小时加密观测降水资料,分析辽宁省降水过程、短时强降水过程、极端短时强降水过程降水量时空分布特征,应用K均值聚类法对汛期短时强降水过程降水累积小时数的空间分布进行分类。结果表明:辽宁省短时强降水过程(小时降水量大于或等于20 mm)和极端短时强降水过程(小时降水量大于或等于该站点历史降水量升序后的第99.9百分位)受地形影响较大。短时强降水高发区主要分布在辽宁东南部的沿海地区、辽宁西部的沿海平原和地势较高地区及辽宁东南部的迎风坡地区。辽宁省汛期降水受季风环流影响,有明显的季节变化,平均降水量和降水频次最大值发生在7月和8月,降水时段主要集中在午后至夜间。辽宁省短时强降水过程降水频次的区域间差异较大,极端短时强降水过程区域间差异较小。

甘肃省区域自动气象站数据质量评估应用程序研究

文章利用python编程语言开发了一款对甘肃省区域自动气象站质控疑误数据自动统计分析应用程序,能够自动链接甘肃省气象资料业务系统(MDOS)区域自动站后台数据库,对全年各月质控出的全省区域自动站疑误数据进行分站点、分要素、分疑误类型的筛选、分析,快速自动生成EXCEL统计图形和表格,自动生成WORD格式的甘肃省区域站逐月数据质量分析报告模板;程序的业务应用对提高区域站设备运行的可靠性和数据可用性具有重要意义。