scholarly journals The effect of environmental factors on the growth of alfalfa in the field.

1962 ◽  
Vol 10 (4) ◽  
pp. 247-253
Author(s):  
G. Stanhill
Keyword(s):  
Environmental Factors ◽  
Solar Radiation ◽  
Root Growth ◽  
Air Temperature ◽  
Meteorological Data ◽  
Crop Canopy

DM production from a heavily fertilized lucerne crop grown at Gilat and irrigated daily was compared with potential photosynthesis calculated from meteorological data [see F.C.A. 12: 1940]. After corrections were applied for losses due to respiration, root growth and light wasted beneath the crop canopy, calculated amounts agreed well with those measured. The percentage of light utilized was 33% with cutting at 31-day intervals and 46% with cutting at 48-day intervals. DM production was correlated positively with solar radiation and negatively with air temperature.-R.B. (Abstract retrieved from CAB Abstracts by CABI’s permission)

scholarly journals Estimating Solar Radiation Intensity from Other Meteorological Data

1969 ◽  
Vol 54 ◽  
pp. 377-389
Author(s):  
Modesto Capiel
Keyword(s):  
Regression Analysis ◽  
Solar Radiation ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Air Temperature ◽  
Meteorological Data ◽  
Solar Radiation Intensity ◽  
Period Data ◽  
The Mean ◽  
Analysis Equation

Estimates of solar radiation (Ri) by 15-day periods were calculated from other available meteorological data by multiple regression analysis of Eo = f(Ri, u, Ta) ed), and then solving for Ri from the most significant equation of the model given above. Only solar radiation wind speed (u) and air temperature (Ta) were found to correlate significantly with Eo. The solution in terms of Ri (equation /4/) then was used to obtain estimates of solar radiation for 1- to 5-day periods. The mean ratio of estimated Ri to measured Ri approached unity (0.95), while the coefficient of variation was 8.9 percent, as compared to 5.1 percent for the original 15-day period data. It was found when these were compared to measured values that neglect of air temperature reduced precision of the estimates. Equation /4/ (the indirect solution) next was evaluated on the basis of foreign data, representing extreme meteorological conditions as those in Bet Dagan, Israel and Cristobal, Panamá. This equation also was compared at the same time to a direct solution of Ri by multiple regression analysis (equation /6/), a solution which directly minimizes the deviations about Ri. Statistical data are presented which compare the precision of the estimates by either equation (/4/ and /6/).

scholarly journals Árbol De Decisión, Aplicación Con Datos Meteorológicos/Decision Tree, Application With Meteorological Data

2020 ◽  
Author(s):  
Silvia Mariana Haro Rivera
Keyword(s):  
Data Mining ◽  
Solar Radiation ◽  
Decision Tree ◽  
Air Temperature ◽  
Meteorological Data ◽  
Barometric Pressure ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Diffuse Solar Radiation ◽  
Abstract Data

La minería de datos es una técnica que hoy en día se aplica en muchas áreas de las ciencias, es por ello que con el objetivo de identificar variables meteorológicas predominantes a ocho intervalos de tiempo se aplicó la técnica supervisada árbol de clasificación en data mining. La información se obtuvo de la estación Alao, misma que se encuentra ubicada a 3064 m.s.m en la provincia de Chimborazo, Ecuador. El estudio se realizó mediante código desarrollado en el software estadístico R; los datos corresponden a información por hora del año 2016, las variables analizadas fueron; temperatura del aire, humedad relativa, presión barométrica, radiación solar difusa, radiación solar global, temperatura del suelo a −20cm y velocidad de viento. El árbol mostró que la principal variable en esta zona es la radiación solar global, a horas comprendidas de 06h00 a 08h00, si ésta es mayor o igual a 120w/m2, entonces se puede determinar la presión barométrica de 09h00 a 11h00 de la mañana; y si ésta es mayor o igual que 709w/m2, entonces se predice la temperatura del aire. El árbol de decisión es una técnica que permitió identificar variables meteorológicas relevantes, en determinadas horas donde se encuentra ubicada la estación Alao. Abstract: Data mining is a technique that today is applied in many areas of science, which is why in order to identify predominant meteorological variables at eight time intervals the supervised tree classification technique was applied in data mining. The information was obtained from the Alao station, which is located at 3064 m.s.m in the province of Chimborazo, Ecuador. The study was carried out using a code developed in statistical software R, the data correspond to information by hour of the year 2016, the variables analyzes were air temperature, relative humidity, barometric pressure, diffuse solar radiation, global solar radiation, soil temperature at −20cm and wind speed. The showed that the main variable in this area is the global solar radiation, at hours between 06h00 and 08h00, if it is greater than or equal to 120w/m2, then the barometric pressure can be determined from 09h00 to 11h00 of the morning, if, and it is great than or equal to 709w/m2, then the air temperature is predicted. The decision tree is a technique that allowed us to identify relevant meteorological variables in certain hours where the Alao station is located. Palabras clave: árboles de decisión, datos meteorológicos. Keywords: decision tree, meteorological data.

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

scholarly journals Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 802
Author(s):  
Kristian Skeie ◽  
Arild Gustavsen
Keyword(s):  
Solar Radiation ◽  
Web Service ◽  
Meteorological Data ◽  
Surface Wind ◽  
Building Energy ◽  
Energy Performance ◽  
Geospatial Data ◽  
Weather Data ◽  
Building Site ◽  
Incident Solar Radiation

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.

scholarly journals The effect of air temperature on hospital admission of adults with community acquired pneumonia in Baotou, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wenfang Guo ◽  
Letai Yi ◽  
Peng Wang ◽  
Baojun Wang ◽  
Minhui Li
Keyword(s):  
Hospital Admission ◽  
Air Temperature ◽  
Meteorological Data ◽  
Community Acquired Pneumonia ◽  
Adult Patients ◽  
Distributed Lag ◽  
Specific Effects ◽  
Lower Temperature Range ◽  
Lower Temperature ◽  
Inner Mongolia Autonomous Region

AbstractThe relationship between air temperature and the hospital admission of adult patients with community-acquired pneumonia (CAP) was analyzed. The hospitalization data pertaining to adult CAP patients (age ≥ 18 years) in two tertiary comprehensive hospitals in Baotou, Inner Mongolia Autonomous Region, China from 2014 to 2018 and meteorological data there in the corresponding period were collected. The exposure–response relationship between the daily average temperature and the hospital admission of adult CAP patients was quantified by using a distributed lag non-linear model. A total of 4466 cases of adult patients with CAP were admitted. After eliminating some confounding factors such as relative humidity, wind speed, air pressure, long-term trend, and seasonal trend, a lower temperature was found to be associated with a higher risk of adult CAP. Compared to 21 °C, lower temperature range of 4 to –12 °C was associated with a greater number of CAP hospitalizations among those aged ≥ 65 years, and the highest relative risk (RR) was 2.80 (95% CI 1.15–6.80) at a temperature of − 10 °C. For those < 65 years, lower temperature was not related to CAP hospitalizations. Cumulative lag RRs of low temperature with CAP hospitalizations indicate that the risk associated with colder temperatures appeared at a lag of 0–7 days. For those ≥ 65 years, the cumulative RR of CAP hospitalizations over lagging days 0–5 was 1.89 (95% CI 1.01–3. 56). In brief, the lower temperature had age-specific effects on CAP hospitalizations in Baotou, China, especially among those aged ≥ 65 years.

scholarly journals Solar Radiation, Air Temperature, Relative Humidity, and Dew Point Study: Damak, Jhapa, Nepal

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Arun Kumar Shrestha ◽  
Arati Thapa ◽  
Hima Gautam
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Air Temperature ◽  
Gaussian Function ◽  
Great Influence ◽  
Dew Point ◽  
Upward Trend ◽  
Summer Maximum ◽  
Online Calculator ◽  
Climatic Phenomenon

Monitoring and prediction of the climatic phenomenon are of keen interest in recent years because it has great influence in the lives of people and their environments. This paper is aimed at reporting the variation of daily and monthly solar radiation, air temperature, relative humidity (RH), and dew point over the year of 2013 based on the data obtained from the weather station situated in Damak, Nepal. The result shows that on a clear day, the variation of solar radiation and RH follows the Gaussian function in which the first one has an upward trend and the second one has a downward trend. However, the change in air temperature satisfies the sine function. The dew point temperature shows somewhat complex behavior. Monthly variation of solar radiation, air temperature, and dew point shows a similar pattern, lower at winter and higher in summer. Maximum solar radiation (331 Wm-2) was observed in May and minimum (170 Wm-2) in December. Air temperature and dew point had the highest value from June to September nearly at 29°C and 25°C, respectively. The lowest value of the relative humidity (55.4%) in April indicates the driest month of the year. Dew point was also calculated from the actual readings of air temperature and relative humidity using the online calculator, and the calculated value showed the exact linear relationship with the observed value. The diurnal and nocturnal temperature of each month showed that temperature difference was relatively lower (less than 10°C) at summer rather than in winter.

scholarly journals Transmission of solar radiation through clouds on melting glaciers: a comparison of parameterizations and their impact on melt modelling

2011 ◽  
Vol 57 (202) ◽  
pp. 367-381 ◽  
Author(s):  
Francesca Pellicciotti ◽  
Thomas Raschle ◽  
Thomas Huerlimann ◽  
Marco Carenzo ◽  
Paolo Burlando
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Radiative Forcing ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Swiss Alps ◽  
Cloud Radiative Forcing ◽  
Correct Definition ◽  
Diurnal Range ◽  
The Impact

AbstractWe explore the robustness and transferability of parameterizations of cloud radiative forcing used in glacier melt models at two sites in the Swiss Alps. We also look at the rationale behind some of the most commonly used approaches, and explore the relationship between cloud transmittance and several standard meteorological variables. The 2 m air-temperature diurnal range is the best predictor of variations in cloud transmittance. However, linear and exponential parameterizations can only explain 30–50% of the observed variance in computed cloud transmittance factors. We examine the impact of modelled cloud transmittance factors on both solar radiation and ablation rates computed with an enhanced temperature-index model. The melt model performance decreases when modelled radiation is used, the reduction being due to an underestimation of incoming solar radiation on clear-sky days. The model works well under overcast conditions. We also seek alternatives to the use of in situ ground data. However, outputs from an atmospheric model (2.2 km horizontal resolution) do not seem to provide an alternative to the parameterizations of cloud radiative forcing based on observations of air temperature at glacier automatic weather stations. Conversely, the correct definition of overcast conditions is important.

Estimation of the total solar radiation from meteorological data

Solar Energy ◽  
1977 ◽  
Vol 19 (3) ◽  
pp. 307-311 ◽  
Author(s):  
J.A. Sabbagh ◽  
A.A.M. Sayigh ◽  
E.M.A. El-Salam
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Total Solar Radiation
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