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Journal articles on the topic 'Average monthly'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2025

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1

Veeran, P. K., and S. Kumar. "Analysis of monthly average daily global radiation and monthly average sunshine duration at two tropical locations." Renewable Energy 3, no. 8 (1993): 935–39. http://dx.doi.org/10.1016/0960-1481(93)90054-k.

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2

Festa, R., C. F. Ratto, and D. DeGol. "A procedure to obtain average daily values of meteorological parameters from monthly averages." Solar Energy 40, no. 4 (1988): 309–13. http://dx.doi.org/10.1016/0038-092x(88)90003-5.

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3

Aptukov, Valery N., and Victor Yu Mitin. "STATISTICAL MODELS FOR FORECASTING AVERAGE MONTHLY TEMPERATURE AND MONTHLY PRECIPITATION AMOUNT IN PERM." Географический вестник = Geographical bulletin, no. 2(57) (2021): 84–95. http://dx.doi.org/10.17072/2079-7877-2021-2-84-95.

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The article proposes an approach to forecasting mean temperature and total precipitation for the upcoming month, based on the study of the regularities of the influence of statistical characteristics of temperature and precipitation of previous periods on them. Among the predictors, along with the basic statistical characteristics, we use the fractality index which is an indicator of the randomness/ determinism of the climate series. Within the framework of this approach, we have developed models of different levels to predict the temperature and total precipitation amount in the upcoming mont

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4

Andrade-Bejarano, Mercedes. "Monthly Average Temperature Modeling in an Intertropical Region." Weather and Forecasting 28, no. 5 (2013): 1099–115. http://dx.doi.org/10.1175/waf-d-12-00077.1.

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Abstract Data for this research come from time series of monthly average temperatures from 28 sites over the Valle del Cauca of Colombia in South America, collected over the period 1971–2002. Because of the geographical location of the study area, monthly average temperature is affected by altitude and El Niño–La Niña (El Niño–Southern Oscillation, or ENSO phenomenon). Time series for some of the sites show a tendency to increase. Also, because of the two dry and wet periods in the study area, a seasonal pattern of behavior in monthly average temperature is seen. Linear mixed models are formul

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5

Akhtar, Iram, Sheeraz Kirmani, Mohmmad Ahmad, and Sultan Ahmad. "Average Monthly Wind Power Forecasting Using Fuzzy Approach." IEEE Access 9 (2021): 30426–40. http://dx.doi.org/10.1109/access.2021.3056562.

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6

Sobolev, Oleg Serafimovich. "AVERAGE MONTHLY CO2 EMISSIONS ESTIMATES MODEL IN AGRICULTURE." Экономика сельского хозяйства России, no. 8 (August 1, 2022): 71–76. http://dx.doi.org/10.32651/228-71.

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7

Vicente-Serrano, S. M., A. El Kenawy, C. Azorin-Molina, et al. "Average monthly and annual climate maps for Bolivia." Journal of Maps 12, no. 2 (2015): 295–310. http://dx.doi.org/10.1080/17445647.2015.1014940.

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8

Bannani, F. K., T. A. Sharif, and A. O. R. Ben-Khalifa. "Estimation of monthly average solar radiation in Libya." Theoretical and Applied Climatology 83, no. 1-4 (2005): 211–15. http://dx.doi.org/10.1007/s00704-005-0157-9.

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9

Ding, Feng, Andrey Savtchenko, Thomas Hearty, et al. "Assessing the Impacts of Two Averaging Methods on AIRS Level 3 Monthly Products and Multiyear Monthly Means." Journal of Atmospheric and Oceanic Technology 37, no. 6 (2020): 1027–50. http://dx.doi.org/10.1175/jtech-d-19-0129.1.

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AbstractThe Atmospheric Infrared Sounder (AIRS) on board NASA’s Aqua satellite provides more than 16 years of data. Its monthly gridded (Level 3) product has been widely used for climate research and applications. Since counts of successful soundings in a grid cell are used to derive monthly averages, this averaged by observations (ABO) approach effectively gives equal importance to all participating soundings within a month. It is conceivable then that days with more observations due to day-to-day orbit shift and regimes with better retrieval skills will contribute disproportionately to the m

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10

Minarecioğlu, Necmiye, and Hatice Çıtakoğlu. "Trend Analysis of Monthly Average Flows of Kizilirmak Basin." Journal of Anatolian Environmental and Animal Sciences 4, no. 3 (2019): 454–59. http://dx.doi.org/10.35229/jaes.595095.

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11

., Debazit Datta. "MODELING MONTHLY AVERAGE DAILY DIFFUSE RADIATION FOR DHAKA, BANGLADESH." International Journal of Research in Engineering and Technology 02, no. 12 (2013): 540–44. http://dx.doi.org/10.15623/ijret.2013.0212090.

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12

Nasir, Najah, Ruhaidah Samsudin, and Ani Shabri. "Monthly streamflow forecasting with auto-regressive integrated moving average." Journal of Physics: Conference Series 890 (September 2017): 012141. http://dx.doi.org/10.1088/1742-6596/890/1/012141.

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13

Ilboudo, Jacques, Dominique Bonkoungou, Sosthene Tassembedo, and Zacharie Koalaga. "General Models for Monthly Average Daily Global Solar Irradiation." Science Journal of Energy Engineering 12, no. 4 (2024): 81–90. https://doi.org/10.11648/j.sjee.20241204.12.

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With the world’s growing demand for electricity and the crucial need to reduce greenhouse gas emissions, it’s more important than ever to develop renewable energies, particularly solar power. The study carried out in this document is in line with the same principle, i.e. to improve the exploitation of solar energy. Its aim is to develop a mathematical model for mean monthly daily global solar irradiation that is independent of measurement data and suitable for all sites worldwide. For this study, we used daily global solar irradiation data for a horizontal surface. These data are from 60 sites

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14

Beato, Rafael. "Re: “Monthly average optical efficiency of flat plate collectors”." Solar Energy 35, no. 2 (1985): 207. http://dx.doi.org/10.1016/0038-092x(85)90012-x.

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15

Beyer, H. G., H. M. Henning, J. Luther, and K. R. Schreitmüller. "The monthly average daily time pattern of beam radiation." Solar Energy 47, no. 5 (1991): 347–53. http://dx.doi.org/10.1016/0038-092x(91)90028-u.

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16

SHEN, SAMUEL S. P., DAVID NEW, THOMAS M. SMITH, and PHILLIP A. ARKIN. "HHT ANALYSIS OF THE GLOBAL AVERAGE MONTHLY PRECIPITATION DATA." Advances in Adaptive Data Analysis 04, no. 03 (2012): 1250018. http://dx.doi.org/10.1142/s1793536912500185.

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This paper uses the Hilbert–Huang transform (HHT) method to make time–frequency diagnostic analyses of four monthly time series of the global precipitation: MERG (1900–2008), REOF (1900–2008), GPCP (1979–2009), and CMAP (1979–2009). All these data are the global land and ocean average of precipitation anomalies with respect to the mean of the entire data period. The MERG and REOF are spectral reconstructions based on historical data. The GPCP and CMAP are based on station gauge data and satellite remote sensing data. We have made the following analysis of the four datasets: (a) extract intrins

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17

Bin Gadhi, S. M., R. S. Megdad, and S. A. A. Albakri. "Monthly average daily global solar radiation in P.D.R. Yemen." Renewable Energy 1, no. 1 (1991): 109–13. http://dx.doi.org/10.1016/0960-1481(91)90110-b.

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18

Li, Long, and Yong Zha. "Estimating monthly average temperature by remote sensing in China." Advances in Space Research 63, no. 8 (2019): 2345–57. http://dx.doi.org/10.1016/j.asr.2018.12.039.

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19

Abughres, S. M. "Monthly average daily insolation for horizontal and inclined surfaces." Solar & Wind Technology 2, no. 2 (1985): 119–30. http://dx.doi.org/10.1016/0741-983x(85)90005-0.

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20

Jain, P. C. "Estimation of monthly average hourly global and diffuse irradiation." Solar & Wind Technology 5, no. 1 (1988): 7–14. http://dx.doi.org/10.1016/0741-983x(88)90085-9.

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21

Rollo, Antonino, Vittorio Ferraro, and Piero Bevilacqua. "Photovoltaic cooling techniques’ effect on the average monthly performance." Acta IMEKO 13, no. 1 (2024): 1–9. http://dx.doi.org/10.21014/actaimeko.v13i1.1660.

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Nowadays, mitigating climate-altering emissions resulting from air conditioning and mechanical ventilation of indoor spaces is of utmost importance. Encourage the adoption of renewable energy sources for power generation is a critical approach in this regard. Among the available technologies, photovoltaic technology stands as the most mature option. However, it does have limitations, such as reduced efficiency and performance degradation at elevated temperatures. To enhance the efficiency of photovoltaic systems, various solutions have been proposed over time, with significant research focusin

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22

Tavarov, Saidjon, Aleksandr Sidorov, and Natalia Glotova. "Forecasting Average Daily and Peak Electrical Load Based on Average Monthly Electricity Consumption Data." Electricity 6, no. 2 (2025): 26. https://doi.org/10.3390/electricity6020026.

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This article is devoted to the determination of the average daily electric load and the average electric load during the hours of maximum load, taking into account the generalized coefficient Ai, using data on electricity consumption for apartment buildings and individual residential buildings in Chelyabinsk and the cities of Dushanbe and Khorog in the Republic of Tajikistan. The results of modeling the average daily electric load, taking into account the developed generalized coefficient Ai, showed that the specific power values for apartments in apartment buildings and in individual resident

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23

Narazaki, Yukinori, Akihiro Sakoda, Naofumi Akata, Hisanori Itoh, and Noriyuki Momoshima. "Analysis of Factors Contributing to the Increase in 7Be Activity Concentrations in the Atmosphere." International Journal of Environmental Research and Public Health 19, no. 16 (2022): 10128. http://dx.doi.org/10.3390/ijerph191610128.

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In March 2013, increased 7Be activity concentrations in the atmosphere were observed for successive days in Dazaifu, western Japan. The daily 7Be activity concentration ranged from 0.93 to 14 mBq/m3, with a monthly average of 8.3 mBq/m3. This average was the highest among the monthly averages observed between 1999 and 2015, and higher than the monthly average over this period (4.7 mBq/m3) plus twice the standard deviation. Also, this exceeded the monthly average (6.0 mBq/m3) only for March 1999–2015 (excluding 2013, when the cosmic-ray intensity, a component producing 7Be, decreased). Based on

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24

Helevera, Olha, Mykola Mostipan, and Sergii Topolnyi. "Winter and spring long-term dynamic of air temperature in Central Ukraine." 59, no. 59 (December 1, 2023): 83–94. http://dx.doi.org/10.26565/2410-7360-2023-59-07.

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This study aimed to analyze data from meteorological stations in central Ukraine that have the longest observation period and to search for patterns in the dynamics of temperature indicators over the past 140-200 years. Data and methods. To characterize the climate of central Ukraine, we analyzed the average monthly and average annual temperatures of Uman, Kropyvnytskyi, and Poltava, which have the longest continuous or almost continuous periods of observation. Based on these data, we have constructed graphs of changes in the average annual and average monthly temperatures for the winter and s

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25

Rhyner, Charles R. "Monthly Variations in Solid Generation." Waste Management & Research: The Journal for a Sustainable Circular Economy 10, no. 1 (1992): 67–71. http://dx.doi.org/10.1177/0734242x9201000107.

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The monthly quantities of residential, commercial, industrial and other wastes generated between 1985-1989 in Brown County, Wisconsin, U.S.A. are analysed. For each month and each waste type, the quantity of waste generated is compared with the monthly average and the difference is computed as a percentage. The means and standard deviations of these percentage differences are computed for each month using the five values computed for each of the five years. The generation patterns for residential, commercial, construction and demolition wastes, and discarded tires show lower than average gener

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26

Christy, John R. "Monthly Temperature Observations for Uganda." Journal of Applied Meteorology and Climatology 52, no. 10 (2013): 2363–72. http://dx.doi.org/10.1175/jamc-d-13-012.1.

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AbstractThe International Surface Temperature Initiative is a worldwide effort to locate weather observations, digitize them for public access, and attach provenance to them. As part of that effort, this study sought documents of temperature observations for the nation of Uganda. Although scattered reports were found for the 1890s, consistent record keeping appears to have begun in 1900. Data were keyed in from images of several types of old forms as well as accessed electronically from several sources to extend the time series of 32 stations with at least 4 yr of data back as far as data were

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27

Yamada, Yuji. "Valuation and hedging of weather derivatives on monthly average temperature." Journal of Risk 10, no. 1 (2007): 101–25. http://dx.doi.org/10.21314/jor.2007.157.

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28

Sediakgotla, Keorapetse, Wilford Molefe, and Dahud Kehinde Shangodoyin. "Time Series Modelling of Monthly average Temperature in Gaborone-Botswana." African Journal of Applied Statistics 6, no. 2 (2019): 689–710. http://dx.doi.org/10.16929/ajas/2019.689.237.

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29

Gelegenis, J. J. "Estimation of hourly temperature data from their monthly average values:." Renewable Energy 18, no. 1 (1999): 49–60. http://dx.doi.org/10.1016/s0960-1481(98)00779-4.

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30

Taşdemiroğlu, E., and R. Sever. "Estimation of monthly average, daily, horizontal diffuse radiation in Turkey." Energy 16, no. 4 (1991): 787–90. http://dx.doi.org/10.1016/0360-5442(91)90030-p.

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31

Fennessey, Neil M. "ESTIMATING AVERAGE MONTHLY LAKE EVAPORATION IN THE NORTHEAST UNITED STATES." Journal of the American Water Resources Association 36, no. 4 (2000): 759–69. http://dx.doi.org/10.1111/j.1752-1688.2000.tb04304.x.

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32

Beluco, Alexandre, Alfonso Risso, and Fausto A. Canales. "Simplified evaluation of energetic complementarity based on monthly average data." MethodsX 6 (2019): 1194–98. http://dx.doi.org/10.1016/j.mex.2019.05.019.

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33

Soler, A. "Global and diffuse illuminances: Estimation of monthly average hourly values." Lighting Research & Technology 22, no. 4 (1990): 193–96. http://dx.doi.org/10.1177/096032719002200405.

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34

Sopian, Kamaruzzaman, and Mohd Yusof Hj Othman. "Estimates of monthly average daily global solar radiation in Malaysia." Renewable Energy 2, no. 3 (1992): 319–25. http://dx.doi.org/10.1016/0960-1481(92)90044-4.

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35

Malik, A. Q., and Sufian Hj Tamam. "Estimation of monthly average daily diffuse radiation for Brunei Darussalam." Renewable Energy 6, no. 4 (1995): 425–27. http://dx.doi.org/10.1016/0960-1481(95)00005-5.

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36

Gil-Alana, Luis A., and Marlon J. Castillo. "Long Memory in Average Monthly Temperatures and Precipitations in Guatemala." Journal of Applied Meteorology and Climatology 63, no. 1 (2024): 85–103. http://dx.doi.org/10.1175/jamc-d-23-0007.1.

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Abstract In this paper, we perform a fractional integration analysis of the average monthly temperature and precipitation data in 17 departments of Guatemala. Two analyses are performed, the first with the original data and the second with the anomalies based on the period January 1994–December 1999. The results indicate that there is a significant positive time trend in temperatures in the departments of Guatemala (0.0045°C month−1), Quetzaltenango (0.0040°C month−1), Escuintla (0.0034°C month−1), and Huehuetenango (0.0047°C month−1), whereas in the case of precipitation no time trend was obs

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37

Sennikova, A. E., I. M. Koryagin, and M. Yu Miroshnichenko. "ANALYSIS OF THE AVERAGE MONTHLY NOMINAL SALARY: A REGIONAL ASPECT." Вестник Алтайской академии экономики и права 2, no. 12 2023 (2023): 328–33. http://dx.doi.org/10.17513/vaael.3176.

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38

Liczbińska, Grażyna, Jörg Peter Vögele, and Marek Brabec. "Climate and disease in historical urban space: evidence from 19th century Poznań, Poland." Climate of the Past 20, no. 1 (2024): 137–50. http://dx.doi.org/10.5194/cp-20-137-2024.

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Abstract. This study examines the relationship between temperature levels and precipitation amounts as explanatory variables for the probability of death due to waterborne and airborne diseases in historical urban space. To date, the literature has not focused on the climatological epidemiology of 19th century Polish urban areas. We used individual mortality data from Poznań parish death registers between 1850 and 1900. Each deceased individual was assigned average monthly temperature values and precipitation amounts in the month of death, LAG1 (1-month-lagged) temperature and LAG1 rainfall, a

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39

Kang, Seongmin, Jeahyung Cha, Changsang Cho, Ki-Hyun Kim, and Eui-Chan Jeon. "Estimation of appropriate CO2 concentration sampling cycle for MSW incinerators." Energy & Environment 31, no. 3 (2019): 535–44. http://dx.doi.org/10.1177/0958305x19877698.

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For this study, the CO2 concentrations of three municipal solid waste incinerators were measured for a year by using the continuous measurement method, and then the collected monthly, quarterly, and half-yearly samples were compared against the average yearly samples, in order to find out the appropriate CO2 concentration sampling cycle. The results of the Kruskal–Wallis test showed that the averages of the monthly, quarterly, half-yearly, and yearly samples of the three municipal solid waste incinerators were different. Then, the monthly, quarterly, and half-yearly samples were compared to th

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40

Ayvazoğluyüksel, Özge, and Ümmühan Başaran Filik. "Estimation of Monthly Average Hourly Global Solar Radiation from the Daily Value in Çanakkale, Turkey." Journal of Clean Energy Technologies 5, no. 5 (2017): 389–93. http://dx.doi.org/10.18178/jocet.2017.5.5.403.

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41

Meng, Ming, Wei Shang, and Dongxiao Niu. "Monthly Electric Energy Consumption Forecasting Using Multiwindow Moving Average and Hybrid Growth Models." Journal of Applied Mathematics 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/243171.

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Monthly electric energy consumption forecasting is important for electricity production planning and electric power engineering decision making. Multiwindow moving average algorithm is proposed to decompose the monthly electric energy consumption time series into several periodic waves and a long-term approximately exponential increasing trend. Radial basis function (RBF) artificial neural network (ANN) models are used to forecast the extracted periodic waves. A novel hybrid growth model, which includes a constant term, a linear term, and an exponential term, is proposed to forecast the extrac

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42

Elhadidy, M. A. "Global Energy in the Different Spectral Bands at Dhahran, Saudi Arabia." Journal of Solar Energy Engineering 113, no. 4 (1991): 290–94. http://dx.doi.org/10.1115/1.2929975.

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Global, spectral isolation data measured every minute over a four-year period at Dhahran (26° 32′ N, 50° 13′ E) Saudi Arabia, using five Schott filters with cutoff at “285, 500, 530, 630, and 695” nm, and ultraviolet radiation sensor, 295–385nm, are analyzed. Monthly averages of the diurnal variations of these bands are presented. The rainfall, dust/sand storm, cloud and air mass effects on the band radiation are also investigated. Comparisons of the yearly average of band radiation measured at Dhahran and those reported in Goldberg and Klein (1977) for Jerusalem (32° N) and Rockville (39° N)

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43

Ikpang, Ikpang Nkereuwem, and Ekom-obong Jackson Okon. "Modeling Average Rainfall in Nigeria With Artificial Neural Network (ANN) Models and Seasonal Autoregressive Integrated Moving Average (SARIMA) Models." International Journal of Statistics and Probability 11, no. 4 (2022): 53. http://dx.doi.org/10.5539/ijsp.v11n4p53.

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Rainfall prediction is one of the most essential and challenging operational obligations undertaken by meteorological services globally. In this article we conduct a comparative study between the ANN models and the traditional SARIMA models to show the most suitable model for predicting rainfall in Nigeria. Average monthly rainfall data in Nigerian for the period Jan. 1991 to Dec.2020 were considered. The ACF and PACF plots clearly identifies the SARIMA (1,0,2)x(1,1,2)12 as an appropriate model for predicting average monthly rainfall. The performance of the trained Neural Network (NN) analysis

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44

Gurrib, Ikhlaas. "Performance of the Average Directional Index as a market timing tool for the most actively traded USD based currency pairs." Banks and Bank Systems 13, no. 3 (2018): 58–70. http://dx.doi.org/10.21511/bbs.13(3).2018.06.

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The aim of this study is to test a trading system based on the average directional index, which is complemented with the parabolic stop and reverse indicator. The trend-based system is tested onto the most actively traded USD based foreign currency pairs, using both monthly and weekly data set over 2000–2018. Sharpe and Sortino measures are used to track the performance of the currency pairs, based on total risk and downside risk assumptions. Results are robust tested by decomposing the data into pre and post 2008 financial crisis. Using an investment horizon over 18 years, the reliance upon t

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45

Danzer, J., H. Gleisner, and S. B. Healy. "CHAMP climate data based on inversion of monthly average bending angles." Atmospheric Measurement Techniques Discussions 7, no. 7 (2014): 7811–35. http://dx.doi.org/10.5194/amtd-7-7811-2014.

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Abstract. GNSS Radio Occultation (RO) refractivity climatologies for the stratosphere can be obtained from the Abel inversion of monthly average bending-angle profiles. The averaging of large numbers of profiles suppresses random noise and this, in combination with simple exponential extrapolation above an altitude of 80 km, circumvents the need for a "statistical optimization" step in the processing. Using data from the US-Taiwanese COSMIC mission, which provides ~ 1500–2000 occultations per day, it has been shown that this Average-Profile Inversion (API) technique provides a robust method fo

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46

Kabashova, Elena, and Alfiya Kuznetsova. "Forecasting the average monthly accrued wages of employees by econometric modeling." Russian Electronic Scientific Journal 27, no. 1 (2018): 26–46. http://dx.doi.org/10.31563/2308-9644-2018-27-1-26-46.

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47

Mohammad Natheer, Ammar, Basil Ibraheem Ahmad, and Abdul Kadir Shakir Abdula Shakir Abdula. "A Study on Monthly and Annual Average Temperature Variations in Mosul." JOURNAL OF EDUCATION AND SCIENCE 26, no. 4 (2013): 88–96. http://dx.doi.org/10.33899/edusj.2013.89969.

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48

Ismail, Emal, and Aissa Boudjella. "Modelling Afghanistanâ€™s Average Monthly Temperature from 1901 to 2015." Asia Proceedings of Social Sciences 1, no. 3 (2019): 61–66. http://dx.doi.org/10.31580/apss.v1i3.434.

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The purpose of this investigation is to examine the variation of temperature in Afghanistan over the past 114 years. The historical dataset of the monthly average temperature from 1901 to 2015 were analyzed. The relationship between temperature and time during the four time intervals, i.e. (1901 -1930), (1931-1960), (1961-1990) and (1991-2015) is presented using a new analytical model based on the last â€“square method of estimation. We accurately fit a polynomial regression trend of degree 4 to the time series to describe the temperature variation. The results show the average difference of t

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49

Cooper, C. David, and Marten Arbrandt. "Mobile Source Emission Inventories—Monthly or Annual Average Inputs to MOBILE6?" Journal of the Air & Waste Management Association 54, no. 8 (2004): 1006–10. http://dx.doi.org/10.1080/10473289.2004.10470968.

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50

Mahmud, Ishtiak, Sheikh Hefzul Bari, and M. Tauhid Ur Rahman. "Monthly rainfall forecast of Bangladesh using autoregressive integrated moving average method." Environmental Engineering Research 22, no. 2 (2016): 162–68. http://dx.doi.org/10.4491/eer.2016.075.

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