Meteorological Data Acquisition Research Articles

Meteorological data analysis capabilities in the “VEGA constellation” information systems family

Satellite monitoring information systems require joint analysis of heterogeneous data, including meteorological data. To solve these problems, IKI RAS developed a technology for automatic acquisition, storage, presentation and analysis of meteorological data. The archive of meteorological data in IKI RAS is maintained within the Center for Collective Use “IKI-Monitoring“. The data is being continuously updated from a number of sources, primarily with the data obtained by the NCEP model. The data is available for visualization on the map in various ways. Plotting provides time series analysis in comparison to other variables such as vegetation indices. The developed technologies have been applied in development of a number of specialized information systems of satellite monitoring of natural and anthropogenic objects.

Research on GPS Timing Remote Synchronization Algorithm in High Altitude Meteorological Data Acquisition System

The various high altitude meteorological parameter influence each other, and test data of different locations need to be synchronized. In this paper, we propose a GPS timing remote synchronization algorithm for high altitude meteorological data acquisition system, which can make the meteorological data at different locations meet the requirements of synchronization. GPS module uses NEO-M8N chip of UBLOX to achieve GPS timing remote synchronization, which include hardware and software designs for the system. We use the designed system to measure high altitude meteorological data in two different locations, analyze experimental results and show the relationship between meteorological parameters. In the processing for experimental results, we employ Fletcher-Reeves algorithm based on artificial neural network to predict meteorological data, and analyze training errors of the algorithm. The proposed system can realize reception and processing of remote data synchronously, and predict the meteorological data for weather forecast.

The effects of seeding rate on yield, lodging resistance and culm strength in wheat

ABSTRACT We compared the effects of four seeding rates, 60, 100, 140, and 180 seeds m−2, on yield, lodging resistance and culm strength using two Japanese wheat cultivars Ayahikari and Iwainodaichi. With the decreasing seeding rate, maximum tiller number decreased, percentage of productive culms increased and spike number m−2 decreased, and the spikelet number per spike, percentage of fertile spikelets, grain number per spikelet and grain number per spike increased. Consequently, grain yield was not significantly affected. Lodging was not observed, but the lodging index was significantly affected by the seeding rate and was the highest in the plots sown at 180 seeds m−2. The bending moment at the breaking point and flexural rigidity of the basal internode with leaf sheaths were highest in the plots sown at 60 seeds m−2. In conclusion, the culm strength and stem lodging resistance increased with decreasing seeding rate. Section modulus and bending stress, which constitute the bending moment at the breaking point, and the moment of inertia area and Young’s modulus, which represent the flexural rigidity, were highest in plots sown at 60 seeds m−2. Therefore, the seeding rate was considered to influence the culm morphology and functions of the cell wall components. The effects of the seeding rate on culm characteristics and lodging resistance did not differ between the two cultivars, and ‘Ayahikari’ had consistently stronger culms than ‘Iwainodaichi’. We suggest that low seeding rates method would be suitable for heavily fertilized cultivation for both cultivar with high and low culm strength. Abbreviations AMeDAS: the automated meteorological data acquisition system; HSD: honestly significant difference

P1707Non-business hours and cold exposure independently worsen neurological outcome after out-of-hospital cardiac arrest

Abstract Background It has been known that survival rates after out-of-hospital cardiac arrest (OHCA) are lower at night than during the day. It may be explained by diurnal temperature changes. Purpose The purpose of the present study was to test our hypothesis that diurnal variation of the prognosis after OHCA would be independent from the ambient temperature changes. Methods We used the All-Japan Utstein Registry (2005–2010) combined with atmospheric temperature from the Automated Meteorological Data Acquisition System, and enrolled adult OHCA patients who had suffered from a witnessed cardiac arrest and who had been resuscitated. The primary outcome was a favorable neurological outcome one month after OHCA and the secondary outcome was the presence of return of spontaneous circulation (ROSC) before hospital admission. Effects of business vs. non-business hours and ambient temperature on the primary and secondary outcomes were assessed with adjustment for factors that are known to potentially affect OHCA outcomes. Sub-group analysis based on the initial cardiac rhythm (VT/Vf, PEA and Asystole) was also performed. Results Among the 263,750 witnessed OHCA patients, neurological survival and ROSC rates were significantly increased with an adjusted odds ratio (OR) of 1.13 (95% CI 1.08–1.18) and hazard ratio (HR) of 1.06 (95% CI 1.04–1.09) for non-business hours, and OR of 1.11 (95% CI 1.05–1.17) and HR of 1.05 (95% CI 1.02–1.08) for each 20°C increase in temperature. The effects were different between business vs. non-business hours and ambient temperature dependent on the initial cardiac rhythm. Conclusions These findings suggest that both the outdoor temperature and business hours are independent factors for predicting neurological outcomes after OHCA with different characteristics based on the initial cardiac rhythms. Diurnal variability of prognosis after OHCA is likely to be attributable to diurnal variation of medical resources.

Geophysical features of shallow landslides induced by the 2015 Kanto-Tohoku heavy rain in Kanuma city, Tochigi Prefecture, Japan

Heavy precipitation accompanied by a typhoon and a seasonal rain front fell over the main island of Japan on 9–11 September 2015, causing severe damage due to landslides and river flooding. In the Kanto and Tohoku regions, some automated meteorological data acquisition system observatories recorded high precipitation rates; rainfall on the first 2 days of the disaster (9–10 September) was more than twice the average monthly rainfall in September 1981–2010. The rainfall, known as the Kanto-Tohoku heavy rain, triggered shallow landslides on a relatively gentle hillslope behind some residences in Kanuma city, Tochigi Prefecture. The source areas of the landslides appeared neither along a clear longitudinal hollow nor around a transverse concave. To reveal the geophysical features affecting the induction of shallow landslides, seismic and electrical resistivity surveys were conducted. Portable cone penetration tests and soil sampling were also carried out to determine the physical properties of the soil. For surface geophysical surveys, a longitudinal survey line was situated on the left bank of a shallow landslide to measure the surface geophysical properties of the landslide area, based on the assumption that the slope next to the landslide has the same properties as the landslide area. Also, two transverse survey lines were situated just upslope of two shallow landslides to capture lateral variations in surface geophysical properties between the landslide and the area around the landslide. Topsoil in the source areas exhibited lower S-wave velocity, higher electrical resistivity, greater soil depth, and lower dry bulk density than soil along other parts of the survey line. These features indicate that the topsoil in the source area was composed of loose relatively deep sand and could be considered to be potentially susceptible to rainfall-induced landslides. Thus, combining surface geophysical surveys with other methods, such as airborne surveys and satellite observations, to detect landslide-prone zones in vast areas may effectively locate areas that do not initially appear different from their surroundings but are high risk of landslides.

A Simple Predictive Performance Model of Solar Cell under Very Hot and Humide Climate

In the scope of solar energy-based electrical needs in rural tropical regions, the present article develops and confronts experimental power models from the using of manufacturer data and a new model made with the meteorological and electrical data acquired. These data are registered through an acquisition station around a monocrystalline photovoltaic panel, designed and realized in the scope of this work. After the acquisition of meteorological data, a choice of the most relevant meteorological variable as input vectors to express the output powers obtained was carried out. Around the Single-Diode model, seven models are performed with analytics equations, iterative methods and an optimization method with a multi-objective function to get internal parameters. The proposed experimental model is made by a combination of the solution got at STC of an iterative method, with the value of nameplate and the use of an open circuit voltage equation with experimental coefficient to predict power output in operating conditions, and it’s demonstrated more efficient. The optimization of a multi-objective function using Nonlinear Squares (NLS) through the Leveng-Marqued method to solve the parameter estimation of a PV panel has been well done and the results are useful, like classic iterative method and less time-consuming.

Development of dynamic thermal input models for simulation of photovoltaic generators

ABSTRACT Development of dynamic thermal input models for simulation of photovoltaic generators (PVG) is the main concern of this work. The dynamic thermal input models consist of insolation and temperature models. The model development involves acquisition of meteorological input data for Kampala at latitude (0.3476oN) and longitude (32.5825oE), measurement of physical conditions in which PVG is operating, carrying out thermal balance around PVG and application of solar analytic equations. The emerging models are simple simulated dynamic insolation and temperature models. These models were superimposed with quadruple sinusoidal waves to obtain superimposed simulated dynamic models. Furthermore, the superimposed insolation models were validated with the superimposed sky model and meteorological data while the corresponding temperature model was validated with the experimental data. The developed models become universal by substituting localised input parameters. Moreover, these models are useful for operation, installation, design and dynamic performance analysis of PVG.

An Image-based Canopy Reconstruction Framework for Field Maize

Plant canopy reconstruction is the fundamental and central problem of functional-structural plant modeling. In order to reconstruct geometric models of plant canopy by real-time image driving, this paper proposes a framework of imagebased maize canopy modeling. The framework builds field image and meteorological data acquisition system to acquire real-time information of plant canopy, then extracts plant growth position and plant azimuthal plane of each plant in the canopy. Morphological parameters of plants are generated using crop model. Finally, geometric model of target canopies are reconstructed by parametric modeling and self-regulating from the image extracted coverage parameter. Experimental results shows that the average coverage error of five treatment maize canopies is 2.57% and LAI errors are smaller than ±1%. Light distribution verification average error of five canopies is 8.02%. This framework will provide technical support for maize field growth analysis and decision making based on Internet of things.

A novel meteorological sensor data acquisition approach based on unmanned aerial vehicle

Meteorological sensor data acquisition is critical for various applications and researches. Currently, meteorological sensor data monitoring and acquisition mainly relies on the automatic weather station (AWS), wireless sensor network, satellites, and airborne remote sensing, etc. However, these conventional methods have some insuperable deficiencies. Recent advances in the unmanned aerial vehicle (UAV) for scientific use make drones easily overcome some of the paucity generated by these means. UAV as a sensor bearing platform can be used to collect sensor data in a more responsive, timely, three dimensional, and cost-effective manners. By implementing sensor network alike methods, drones can simulate the mobile ad-hoc networks in a mission and reduce the communication energy cost between each sensor node. This paper first demonstrates the feasibility of this approach, then proposes a sensor bearing framework aiming to bridge UAV remote sensing technique and customised meteorological sensor. A system prototype is developed and some real-world field tests indicate the application of the proposed framework is practical.

Circularly Polarized Antenna Array with Sequential Rotation for Nanosatellites

This paper presents the design and characterization of an aperture-coupled microstrip antenna array to be installed onto a nanosatellite. The proposed antenna array has been optimized to operate at 2.26 GHz (S-Band), which is the operating frequency of the downlink channel of the Brazilian System for Meteorological Data Acquisition. The electromagnetic analyses are done by using the HFSS electromagnetic simulator. For the design validation, prototypes of single elements and antenna array were manufactured. The comparison between simulations and measurements indicates good performance of the designed antennas.

「ひまわり」や「アメダス」のCD-ROMデータを利用した地域大気環境に関する教材開発

「ひまわり」や「アメダス」のCD-ROMデータを利用した地域大気環境に関する教材開発

Parametric Modelling of Potential Evapotranspiration: A Global Survey

We present and validate a global parametric model of potential evapotranspiration (PET) with two parameters that are estimated through calibration, using as explanatory variables temperature and extraterrestrial radiation. The model is tested over the globe, taking advantage of the Food and Agriculture Organization (FAO CLIMWAT) database that provides monthly averaged values of meteorological inputs at 4300 locations worldwide. A preliminary analysis of these data allows for explaining the major drivers of PET over the globe and across seasons. The model calibration against the given Penman-Monteith values was carried out through an automatic optimization procedure. For the evaluation of the model, we present global maps of optimized model parameters and associated performance metrics, and also contrast its performance against the well-known Hargreaves-Samani method. Also, we use interpolated values of the optimized parameters to validate the predictive capacity of our model against monthly meteorological time series, at several stations worldwide. The results are very encouraging, since even with the use of abstract climatic information for model calibration and the use of interpolated parameters as local predictors, the model generally ensures reliable PET estimations. Exceptions are mainly attributed to irregular interactions between temperature and extraterrestrial radiation, as well as because the associated processes are influenced by additional drivers, e.g., relative humidity and wind speed. However, the analysis of the residuals shows that the model is consistent in terms of parameters estimation and model validation. The parameter maps allow for the direct use of the model wherever in the world, providing PET estimates in case of missing data, that can be further improved even with a short term acquisition of meteorological data.

Frequency analysis of annual maximum hourly precipitation and determination of best fit probability distribution for regions in Japan

In the design of irrigation and other hydraulic structures, evaluating the extreme rainfall for a specific probability of occurrence is important. The capacity of such structures is usually designed to cater to the probability of occurrence of extreme rainfall during its lifetime. In this study, a frequency analysis of annual maximum hourly rainfall for 15 locations in Japan was carried out using the Expanded Automated Meteorological Data Acquisition System (EA) weather data of 20years from 1981 to 2000. Eight formulas were used to expect the return period in years of annual maximum hourly rainfall. Five different probability distribution functions (PDFs) were adopted to predict the probability distribution of occurrence of annual maximum hourly rainfall. The goodness of fit was evaluated using Chi-square test. It indicated that the Log-Pearson type 3 (LP3) distribution is the overall best fit PDF for annual maximum hourly rainfall at most locations of Japan.

Impact of sea breeze penetration over urban areas on midsummer temperature distributions in the Tokyo Metropolitan area

We investigate the relationship between sea breeze penetration and anomalously high summer daytime temperatures in the inland suburbs of Tokyo, with consideration of the relative position of sea breeze fronts. We use data from the high‐density temperature observation network (Extended‐METROS) established by our research group to clarify in detail the mechanisms creating these high‐temperature areas.We conducted case and composite analyses of the temperature and wind distributions when typical sea breeze fronts developed. The observations showed that the highest temperatures were near Kawagoe City in the early afternoon, which is 40 km leeward of central Tokyo, on all days analysed, and that the high‐temperature inland areas were located leeward of Tokyo. The high temperatures near Kawagoe City were not observed by the Automated Meteorological Data Acquisition System (AMeDAS). From the case and composite analyses, there was a 2‐h time lag between the sea breeze front penetrating the area leeward of Tokyo and extreme high temperatures being observed around Kawagoe City. Significant divergence was also observed during this time, and a decrease in the dew point temperature was also observed around Kawagoe City on the case study day; these conditions persisted for approximately 2 h. These results suggest the existence of a subsidence flow near Kawagoe City, and the resulting adiabatic compression heating contributed to the observed extreme high temperatures. In the late evening, a high‐temperature band was observed leeward of the northern suburbs of Tokyo, even though southerly sea breezes were recorded over the entire Kanto Plain, and cold advection dominated at that time. However, the cold advection in this high‐temperature band was less notable than in the periphery. Thus, temperature declines were small in this area, and overall temperatures remained relatively high.

Physical Flood Vulnerability Mapping Applying Geospatial Techniques in Okazaki City, Aichi Prefecture, Japan

Flooding has been increasing since 2004 in Japan due to localized heavy rainfall and geographical conditions. Determining areas vulnerable to flooding as one element of flood hazard maps related to disaster management for urban development is necessary. This research integrated Remote Sensing data, the Geography Information System (GIS) method and Analytical Hierarchy Process (AHP) calculation to determine the physical flood-vulnerable area in Okazaki City. We developed this research by applying data from the Geospatial Information Authority of Japan (GSI) to generate the slope map and drainage density; AMEDAS (Automated Meteorological Data Acquisition System) from the Japan Meteorological Agency (JMA) to generate the rainfall data; Soil map from the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) data; and Sentinel-2 imagery to generate the land cover map. We applied the AHP calculation for weighting pairwise the parameters by comparing five iterations of the normalized matrix. We utilized the spatial analysis tool in ArcGIS to run the pairwise comparison to adjudicate the distribution of flooding according to the AHP procedure. The percentage of relative weight was slope (43%), drainage density (20%), rainfall intensity (17%), then both infiltration rate and land cover (10%). The consistency value was reasonable: consistency index (CI—0.007) and consistency ratio (CR—0.6%). We generated high accuracy for flood vulnerability prediction; 0.88 for Probability of Detection (POD), 0.28 for Probability of False Detection (POFD), 0.44 for Critical Success Index (CSI), 1.9 for Bias, and 95 of Area under Curve (AUC). The flood vulnerability was matched to the flood inundation survey of Okazaki City in August 2008 and indicated an excellent Relative Operating Characteristic (ROC).

The Design and Implementation of a Remote Fault Reasoning Diagnosis System for Meteorological Satellites Data Acquisition

Under the background of the trouble shooting requirements of FENGYUN-3 (FY-3) meteorological satellites data acquisition in domestic and oversea ground stations, a remote fault reasoning diagnosis system is developed by Java 1.6 in eclipse 3.6 platform. The general framework is analyzed, the workflow is introduced. Based on the system, it can realize the remote and centralized monitoring of equipment running status in ground stations，triggering automatic fault diagnosis and rule based fault reasoning by parsing the equipment quality logs, generating trouble tickets and importing expert experience database, providing text and graphics query methods. Through the practical verification, the system can assist knowledge engineers in remote precise and rapid fault location with friendly graphical user interface, boost the fault diagnosis efficiency, enhance the remote monitoring ability of integrity operating control system. The system has a certain practical significance to improve reliability of FY-3 meteorological satellites data acquisition.

A Novel Meteorological Sensor Data Acquisition Approach Based on Unmanned Aerial Vehicle

Meteorological sensor data acquisition is critical for various applications and researches. Currently, meteorological sensor data monitoring and acquisition mainly relies on the automatic weather station (AWS), wireless sensor network, satellites, and airborne remote sensing, etc. However, these conventional methods have some insuperable deficiencies. Recent advances in the unmanned aerial vehicle (UAV) for scientific use make drones easily overcome some of the paucity generated by these means. UAV as a sensor bearing platform can be used to collect sensor data in a more responsive, timely, three dimensional, and cost-effective manners. By implementing sensor network alike methods, drones can simulate the mobile ad-hoc networks in a mission and reduce the communication energy cost between each sensor node. This paper first demonstrates the feasibility of this approach, then proposes a sensor bearing framework aiming to bridge UAV remote sensing technique and customised meteorological sensor. A system prototype is developed and some real-world field tests indicate the application of the proposed framework is practical.

2015-2016冬期の新潟県アメダスへの積雪変質モデルSMAPの適用

積雪変質モデルSMAPを2015-2016冬期の新潟県内アメダス13地点に適用し，積雪深を再現した結果を示す．SMAPの入力データには，アメダス観測結果から捕捉率補正を施した降水量，気温，風速を与えた．捕捉率補正に際しては予め雨雪分離を行っておく必要があるが，本研究では分離の指標として気温を採用し，その閾値Tdiscを現実的な範囲で0，0.5，及び1℃に変化させる3パターンの入力データを作成した．モデルの駆動に必要なそれ以外のデータ（下向き短波・長波放射量，雲量，湿度，及び気圧）は気象庁非静力学モデルの計算結果から与えた．計算された積雪深は，長岡ではTdisc=0.5℃の時に最も良い再現精度が得られていたものの，津南を除く全地点においてはTdisc=0℃の時のスコアが最も良くなっていた．また，SMAPの計算結果がTdiscに非常に敏感であり，Tdiscが1℃と0℃の場合の積雪深計算結果平均偏差が最大で0.41m（小出）にまで達していたことも分かった．一方で，この平均偏差が0.10mと相対的に小さい場所（関山）も見られたことから，雨雪判別方法に敏感な場所とそうでない場所が存在することが示唆された．冬期降水曲線を用いた解析の結果によると，この場所による特性の違いは，降水量自体と降水が最も頻繁に起きる気温帯の違いによって説明出来ることが明らかとなった．

Performance of Onboard Wake–Vortex Prediction Systems Employing Various Meteorological Data Sources

In this work the accuracy of wake–vortex predictions of DLR’s wake encounter avoidance and advisory system (WEAA) is analyzed by means of data gathered from a flight test campaign in April 2014. The system is based on airborne data exchange between aircraft and allows pilots to avoid potentially dangerous wake–vortex encounters. As the vortex evolution is strongly controlled by atmospheric parameters, the acquisition of meteorological data is crucial for WEAA. The accuracy of the wake–vortex predictions is investigated, employing first the current automatic dependent surveillance (ADS-B) standard, which is then extended by additional meteorological data transmitted via telemetry, or data from numerical weather predictions.

ANALYSIS OF DEBRIS FLOW DISASTER DUE TO HEAVY RAIN BY X-BAND MP RADAR DATA

On August 20 of 2014, Hiroshima City (Japan) was struck by local heavy rain from an autumnal rain front. The resultant debris flow disaster claimed 75 victims and destroyed many buildings. From 1:30 am to 4:30 am on August 20, the accumulated rainfall in Hiroshima City exceeded 200 mm. Serious damage occurred in the Asakita and Asaminami wards of Hiroshima City. As a disaster prevention measure, local heavy rain (localized torrential rains) is usually observed by the Automated Meteorological Data Acquisition System (AMeDAS) operated by the Japan Meteorological Agency (JMA) and by the C-band radar operated by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan, with spatial resolutions of 2.5 km and 1 km, respectively. The new X-band MP radar system enables more detailed rainfall observations than the C-band radar. In fact, this radar can observe local rainfall throughout Japan in near-real time over a minimum mesh size of 250 m. A fine-scale accumulated rainfall monitoring system is crucial for disaster prevention, and potential disasters can be alerted by the hazard levels of the accumulated rainfall.