scholarly journals Generación de mapas climatológicos mediante el desarrollo de una estación meteorológica automática móvil

2020 ◽  
pp. 1-10
Author(s):  
Gabriel Romero-Rodríguez ◽  
Erick Eduardo Huesca-Lazcano ◽  
Óscar Flores-Ramírez ◽  
Karla Cecilia Apan-Araujo
Keyword(s):  
Climate Models ◽  
Meteorological Data ◽  
Electrical Power ◽  
Global Solar Radiation ◽  
Remote Transmission ◽  
Movement Dynamics ◽  
Global Positioning ◽  
Interesting Possibility ◽  
Power Stage ◽  
Geographical Point

Agricultural studies present a common constraint in making decisions based on meteorological data, since climate models lack precise values of their parameters depending on the geographical point where information is acquired, so that weather acquisition in positions specific geographical results is an interesting possibility. The objective of the present study was to develop a mobile automatic weather station (AWS) with sensors that measure the air temperature (° C), the relative humidity of the air (%), the global solar radiation (Wm2), the wind speed (m/s) ) and the concentration of carbon dioxide (ppm); the sensors were connected to a controller medium to which they were incorporated: a real-time clock to adapt the acquisition intervals, a display to show the information to the user, a storage module for the acquired data, a module for remote transmission of the data and a global positioning system. In addition, the mobile unit contains a chassis, four wheels with their respective electric motors, power stage, two servomotors, two ultrasonic sensors and the general electrical power that give autonomy in their movement dynamics. The climate map of a polygon of 120m2 was obtained.

scholarly journals Instrumentación electrónica de una estación meteorológica automática

2020 ◽  
pp. 19-30
Author(s):  
Gabriel Romero-Rodríguez ◽  
Erick Eduardo Huesca-Lazcano ◽  
Óscar Flores-Ramírez ◽  
Jorge Rafael Martínez-Ángeles
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Climate Models ◽  
Meteorological Data ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Interesting Possibility ◽  
Electronic Instrumentation ◽  
Geographical Point

Climatological studies present a common restriction in decisionmaking based on meteorological data, since climate models often lack precise values of their parameters depending on the geographical point where the information is acquired, therefore, climate acquisition in specific geographical positions is an interesting possibility. The objective of the present study was to develop the electronic instrumentation of an automatic weather station (AWS) using a controlling medium with sensors that measure air and soil temperature (°C), relative humidity (%), solar radiation (Wm2 ) and wind speed (m/s). The acquired data were compared with commercial stations Vantage Pro (VP) and GroWeather (GW) of the Davis Instruments family where an R2 of 0.93 was obtained in Temperature and Relative Humidity of the air and an R2 of 0.94 for solar radiation. Thus, the developed AWS presents benefits in the quality of the acquired data that can be used for studies of mathematical modeling and generation of decision-making.

scholarly journals A Deep Learning Algorithm for Solar Radiation Time Series Forecasting: A Case Study of El Kelaa Des Sraghna City

2020 ◽  
Vol 34 (5) ◽  
pp. 563-569
Author(s):  
Mohammed Ali Jallal ◽  
Abdessalam El Yassini ◽  
Samira Chabaa ◽  
Abdelouhab Zeroual ◽  
Saida Ibnyaich
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Solar Radiation ◽  
Missing Values ◽  
Learning Algorithm ◽  
Meteorological Data ◽  
Electrical Power ◽  
Autoregressive Process ◽  
Global Solar Radiation ◽  
Elman Neural Network

Nowadays, the studies that address solar radiation (SR) forecasting tend to focus on the implementation of conventional techniques. This provides good results, but researchers should focus on the creation of new methodologies that help us in going further and boost the prediction accuracy of SR data. The prime aim of this research study is to propose an efficient deep learning (DL) algorithm that can handle nonlinearities and dynamic behaviors of the meteorological data, and generate accurate real-time forecasting of hourly global solar radiation (GSR) data of the city of El Kelaa des Sraghna (32°2’53”N 7°24’30”W), Morocco. The proposed DL algorithm integrates the dynamic model named Elman neural network with a new input configuration-based autoregressive process in order to learn from the seasonal patterns of the historical SR measurements, and the actual measurements of air temperature. The attained performance proves the reliability and the accuracy of the proposed model to forecast the hourly GSR time series in case of missing values detection or pyranometer damage. Hence, electrical power engineers can adopt this forecasting tool to improve the integration of solar power resources into the power grid system.

Ozone Concentration Prediction using Artificial Neural Networks

2017 ◽  
Vol 68 (10) ◽  
pp. 2224-2227 ◽  
Author(s):  
Camelia Gavrila
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Ozone Concentration ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Time Data ◽  
Marquardt Algorithm ◽  
Sensitivity Tests ◽  
Artificial Neural ◽  
The Relationship

The aim of this paper is to determine a mathematical model which establishes the relationship between ozone levels together with other meteorological data and air quality. The model is valid for any season and for any area and is based on real-time data measured in Bucharest and its surroundings. This study is based on research using artificial neural networks to model nonlinear relationships between the concentration of immission of ozone and the meteorological factors: relative humidity (RH), global solar radiation (SR), air temperature (TEMP). The ozone concentration depends on following primary pollutants: nitrogen oxides (NO, NO2), carbon monoxide (CO). To achieve this, the Levenberg-Marquardt algorithm was implemented in Scilab, a numerical computation software. Performed sensitivity tests proved the robustness of the model and its applicability in predicting the ozone on short-term.

scholarly journals The seasonal variability of the amount of global solar radiation reaching the ground in urban and rural areas on the example of Warsaw and Belsk

2016 ◽  
Vol 20 (4) ◽  
pp. 29-37
Author(s):  
Kinga Nelken ◽  
Kamil Leziak
Keyword(s):  
Solar Radiation ◽  
Urban Area ◽  
Rural Area ◽  
Rural Areas ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Urban Station ◽  
Reverse Relationship ◽  
Urban And Rural Areas ◽  
The Relationship

AbstractThe aim of this paper is to determine the contemporary differences in the inflow of global solar radiation in Warsaw (urban station) and Belsk (rural station). The meteorological data used comprised daily sums of global solar radiation (in MJ•m−2) and the duration of sunshine (in hours) for the period 2008 2014. On clear days in spring and summer, the rural area receives more solar radiation in comparison to the urban area, whereas in autumn a reverse relationship occurs. On cloudy days in all seasons, the rural area receives more solar radiation than the urban area, and the relationship is the strongest in winter. Differences between urban and rural areas on cloudy days are smaller than those observed on clear days.

scholarly journals Empirical model based on meteorological parameters to estimate the global solar radiation in Nepal

BIBECHANA ◽  
2014 ◽  
Vol 11 ◽  
pp. 25-33
Author(s):  
Krishna R Adhikari ◽  
Shekhar Gurung ◽  
Binod K Bhattarai
Keyword(s):  
Solar Radiation ◽  
Empirical Model ◽  
Meteorological Data ◽  
Cost Effective ◽  
Developed Countries ◽  
Global Solar Radiation ◽  
Develop Model ◽  
Sunshine Hours ◽  
Linear Regression Technique ◽  
Meteorological Characteristic

Solar radiation is the best option and cost effective energy resources of this globe. Only a few stations are there in developing and under developed countries including Nepal to monitor solar radiation and sunshine hours to generate a rational and accurate solar energy database. In this study, daily global solar radiation, and ubiquitous meteorological data (temperature and relative humidity) rather than rarely available sunshine hours have been used for Biratnagar, Kathmandu, Pokhara and Jumla to derive regression constants and hence to develop an empirical model. The model estimated global solar radiation is found to be in close agreement with measured values of respective sites. The estimated values were compared with Angstrom-Prescott model and examined using the statistical tools. Thus, the linear regression technique can be used to develop model at any location in the world. The resultant model may then be used to estimate the missing data of solar radiation for the respective sites and also can be used to estimate global solar radiation for the locations of similar geographic and meteorological characteristic. DOI: http://dx.doi.org/10.3126/bibechana.v11i0.10376   BIBECHANA 11(1) (2014) 25-33

scholarly journals Evaluating quantile-based bias adjustment methods for climate change scenarios

2021 ◽  
Author(s):  
Fabian Lehner ◽  
Imran Nadeem ◽  
Herbert Formayer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Climate Change Signal ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Statistical Bias ◽  
Bias Adjustment ◽  
Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

scholarly journals Risk assessment of freezing injury during overwintering of wheat in the northern boundary of the Winter Wheat Region in China

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12154
Author(s):  
Jiahui Guo ◽  
Xionghui Bai ◽  
Weiping Shi ◽  
Ruijie Li ◽  
Xingyu Hao ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Winter Wheat ◽  
Injury Risk ◽  
Climate Models ◽  
Meteorological Data ◽  
Wheat Variety ◽  
Freezing Injury ◽  
Short Term ◽  
Northern Boundary ◽  
Significant Downward Trend

Freezing injury is one of the main restriction factors for winter wheat production, especially in the northern part of the Winter Wheat Region in China. It is very important to assess the risk of winter wheat-freezing injury. However, most of the existing climate models are complex and cannot be widely used. In this study, Zunhua which is located in the northern boundary of Winter Wheat Region in China is selected as research region, based on the winter meteorological data of Zunhua from 1956 to 2016, seven freezing disaster-causing factors related to freezing injury were extracted to formulated the freezing injury index (FII) of wheat. Referring to the historical wheat-freezing injury in Zunhua and combining with the cold resistance identification data of the National Winter Wheat Variety Regional Test (NWWVRT), consistency between the FII and the actual freezing injury situation was tested. Furthermore, the occurrence law of freezing injury in Zunhua during the past 60 years was analyzed by Morlet wavelet analyze, and the risk of freezing injury in the short term was evaluated. Results showed that the FII can reflect the occurrence of winter wheat-freezing injury in Zunhua to a certain extent and had a significant linear correlation with the dead tiller rate of wheat (P = 0.014). The interannual variation of the FII in Zunhua also showed a significant downward trend (R2 = 0.7412). There are two cycles of freezing injury in 60 years, and it showed that there’s still exist a high risk in the short term. This study provides reference information for the rational use of meteorological data for winter wheat-freezing injury risk assessment.

scholarly journals Comparison of meteorological data, related to reference evapotranspiration, from conventional and automatic stations in the Sertão and Agreste regions of Pernambuco, Brazil

DYNA ◽  
2021 ◽  
Vol 88 (216) ◽  
pp. 176-183
Author(s):  
Iug Lopes ◽  
Miguel Julio Machado Guimarães ◽  
Juliana Maria Medrado de Melo ◽  
Ceres Duarte Guedes Cabral de Almeida ◽  
Breno Lopes ◽  
...  
Keyword(s):  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Concordance Index ◽  
Good Relationship ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Daily Scale ◽  
Weather Stations ◽  
Meteorological Elements

The objective was to perform a comparative study of the meteorological elements data that most cause changes in the reference Evapotranspiration (ETo, mm) and its own value, of automatic weather stations AWS and conventional weather stations CWS of the Sertão and Agreste regions of Pernambuco State. The ETo was calculated on a daily scale using the standard method proposed by the Food and Agriculture Organization (FAO), Penman-Monteith (FAO-56). The ETo information obtained from AWS data can be used to update the weather database of stations, since there is a good relationship between the ETo data obtained from CWS and AWS, statistically determined by the Willmott's concordance index (d > 0.7). The observed variations in the weather elements: air temperature, relative humidity, wind speed, and global solar radiation have not caused significant changes in the ETo calculation.

scholarly journals AVALIAÇÃO DE DUAS ESTAÇÕES METEOROLÓGICAS AUTOMATIZADAS, PARA ESTIMATIVA DIÁRIA DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA OBTIDA PELO MÉTODO DE PENMAN-MONTEITH

Irriga ◽  
2008 ◽  
Vol 13 (3) ◽  
pp. 339-354 ◽  
Author(s):  
José Eduardo Pitelli Turco ◽  
José Carlos Barbosa
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Meteorological Data ◽  
Linear Regression Analysis ◽  
Reference Method ◽  
Global Solar Radiation ◽  
Engineering Department ◽  
Weather Stations ◽  
Set Up ◽  
Reference Crop

AVALIAÇÃO DE DUAS ESTAÇÕES METEOROLÓGICAS AUTOMATIZADAS, PARA ESTIMATIVA DIÁRIA DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA OBTIDA PELO MÉTODO DE PENMAN-MONTEITH  José Eduardo Pitelli Turco1; José Carlos Barbosa21Departamento de Engenharia Rural, Faculdade de Ciências Agrária e Veterinária, Universidade Estadual Paulista, Câmpus de Jaboticabal, Jaboticabal, SP, [email protected] de Ciências Exatas, Faculdade de Ciências Agrária e Veterinária, Universidade Estadual Paulista, Câmpus de Jaboticabal, Jaboticabal, SP  1        RESUMO              A finalidade deste trabalho foi a avaliação de estações meteorológicas automatizadas da marca Davis Instruments e Campbell Scientific, procurando detectar possíveis diferenças nas suas medições e estimativas. Foi, também, avaliada, nas duas estações, a integridade dos dados meteorológicos para estimativa da ETo. Os dados meteorológicos avaliados foram os seguintes: radiação solar global, saldo de radiação, temperatura do ar, umidade do ar, velocidade do vento e precipitação pluviométrica. O método de estimativa diária da evapotranspiração de referência avaliado foi o de Penman-Monteith, recomendado pela FAO como método padrão para estimar a ETo. As estações meteorológicas automatizadas da marca Davis Instruments e Campbell Scientific foram instaladas em uma área experimental do Departamento de Engenharia Rural da FCAV/UNESP, Campus de Jaboticabal, SP. Os dados foram coletados diariamente e analisados estatisticamente, por meio de análise de regressão. Foi aplicada uma técnica que verifica a integridade dos dados meteorológicos para estimativa da evapotranspiração de referência. O resultado da avaliação das duas estações, utilizando-se análise de regressão linear, mostra que as estimativas diárias da evapotranspiração de referência (ETo) apresentam diferenças aceitáveis. Aplicando a técnica que verifica a integridade dos dados meteorológicos, verificou-se que os dados de umidade relativa das duas estações e de precipitação da Campbell não foram de boa qualidade. UNITERMOS: evapotranspiração, estações automatizadas, intercomparação.  TURCO, J. E. P.; BARBOSA, J. C. TWO AUTOMATIC WEATHER  STATIONS  METEOROLOGICAL DATA EVALUATION BY  PENMAN-MONTEITH REFERENCE EVAPOTRANSPIRATION METHOD  2        ABSTRACT The objective of this study was to evaluate and compare measurements and estimates from Davis and Campbell Scientific Instruments in two automatic weather stations. Integrity of meteorological data for estimates of evapotranspiration of reference crop (ETo) from both stations was also evaluated. The following meteorological data were evaluated: air temperature, air humidity, wind speed, precipitation, net radiation and global solar radiation. The Penman-Monteith reference method to estimate ETo was evaluated daily. The weather stations were set up in an experimental area of the Rural Engineering Department- FACV/UNESP, in Jaboticabal, State of Sao Paulo. Data were collected daily and statistical analysis was performed using linear regression analysis. The integrity of meteorological data to estimate ETo was evaluated. The results of the study in the stations using linear regression analysis showed that daily estimates for ETo had acceptable differences. The technique which evaluates the integrity of meteorological data revealed that data of relative humidity from both stations and of precipitation using Campbell Instruments were not good.           KEY WORDS: evapotranspiration, automatic weather station, intercomparison

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