Probabilistic post-processing of gridded atmospheric variables and its application to site adaptation of shortwave solar radiation

Incrementos en la temperatura ambiental y la humedad relativa, unidas al efecto de la radiación solar, ocasionan pérdidas en el bienestar animal, afectando la conducta ingestiva y la productividad animal. Por ello el objetivo de este estudio fue analizar las relaciones entre las variables atmosféricas, como temperatura del aire, humedad relativa, velocidad del viento y radiación solar, con los tiempos de pastoreo y de rumia de bovinos cebú comercial. La investigación se llevó a cabo durante 96 días, entre julio-octubre de 2010, en el C.I. Turipaná de Corpoica (Cereté, Colombia). Bovinos machos enteros (27), con peso promedio 314 ± 29 kg, pastorearon en un área de 18 hectáreas, establecidas en Panicum maximum cv. Mombasa, Cynodonnlem fluensis y Brachiaria híbrido cv. Mulato II, sin disponibilidad de sombra. Se realizaron ocho evaluaciones durante 8 días dentro del periodo experimental de las variables atmosféricas e ingestivas y las anotaciones se hicieron en un lapso de 12 horas continuas (6:00 AM a 6:00 PM). Los resultados resaltan que al aumentar la temperatura del aire, humedad relativa y la radiación solar, disminuyó el tiempo de pastoreo y aumentó el tiempo de rumia, mientras que al aumentar la velocidad del viento se incrementó el tiempo de pastoreo y disminuyó el tiempo de rumia. Los resultados obtenidos indicaron que la temperatura del aire, humedad relativa, radiación solar y velocidad del viento, presentaron una influencia directa sobre el comportamiento ingestivo de los bovinos de carne manejados en sistemas intensivos (sin sombra) en el Valle del Sinú. Effects of environmental conditions on feeding behavior in beef cattle in an intensive system in the Sinú Valley Increases in temperature and relative humidity together with the solar radiation effect are detrimental to animal welfare, affecting their behavior when it comes to feeding and digestive behavior, which affects their productivity. Therefore, the goal of this research was to analyze the link between atmospheric variables, air temperature, relative humidity, wind speed and solar radiation to the time of grazing and rumination of commercial Zebu cattle. The research took place from July to October 2010, at the Turipaná Center, Corpoica (Cereté, Colombia). Male intact bovines (27), with an average weight of 314 ± 29 kg, grazed in an area of 18 hectares, established with Panicum maximum cv. Mombasa, Cynodonnlem fluensis and Brachiaria hybrid cv. Mulato II, without shade availability. Eight evaluations were conducted for 8 days in the experimental period for atmospheric variables and ingestion. Notes were taken in 12 hour time frames (6:00 AM a 6:00 PM). The outcome showed that as the air temperature, relative humidity and solar radiation increased, the grazing time decreased and rumination time lasted longer. However, when wind speed increased, grazing time increased as well and rumination took less time. The results showed that the air temperature, relative humidity, solar radiation and wind speed had a direct influence on the ingestive behavior of beef cattle managed in intensive systems (shadeless) in Valle del Sinú.

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Studying the Changes in Solar Radiation and Their Influence on Temperature Trend in Iraq for a Whole Century

Baghdad Science Journal ◽

10.21123/bsj.2021.18.2(suppl.).1076 ◽

2021 ◽

Vol 18 (2(Suppl.)) ◽

pp. 1076

Author(s):

Basim Abdulsada Al-Knani ◽

Iqbal H. Abdulkareem ◽

Hussain Abodi Nemah ◽

Zahraa Nasir

Keyword(s):

Solar Radiation ◽

Inverse Relationship ◽

Direct Solar Radiation ◽

Sharp Drop ◽

Temperature Levels ◽

Year 2000 ◽

The Relationship ◽

The City ◽

Over Time ◽

Atmospheric Variables

Most studies indicated that the values of atmospheric variables have changed from their general rates due to pollution or global warming etc. Hence, the research indicates the changes of direct solar radiation values over a whole century i.e. from 1900 to 2000 depending on registered data for four cities, namely (Mosul - Baghdad - Rutba - Basra. Moreover, attemptsto correlate the direct solar radiation with the temperature values have been recorded over that period. The results showed that there is a decreasing pattern of radiation quantities over time throughout the study period, where the value of direct radiation over the city of Baghdad 5550 w/m2 was recorded in the year 1900, but this ratio decreased clearly to approximately 5400 w/m2 in the year 2000, which is perhaps due to the increase of general pollution rates in the atmosphere. The results also showed that the city of Rutba recorded the highest annual rate of radiation quantities, and Baghdad with Mosul recorded the lowest radiation ratios compared to the rest of the cities, in addition to that there was a large convergence of radiation ratios between them to some extent. The results showed that there is a sharp drop in radiation ratios, specifically in the years1980and 1990. As for the extent of the relationship for solar radiation with temperature levels throughout the study period, it was found that there is an inverse relationship between them, and this confirms that the cause of high temperatures is not because of increased solar radiation, but it may rather due to other reasons such as increased greenhouse gases.

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A Neural Network Post-processing Approach to Improving NWP Solar Radiation Forecasts

Energy Procedia ◽

10.1016/j.egypro.2014.10.089 ◽

2014 ◽

Vol 57 ◽

pp. 1044-1052 ◽

Cited By ~ 15

Author(s):

Philippe Lauret ◽

Maïmouna Diagne ◽

Mathieu David

Keyword(s):

Neural Network ◽

Solar Radiation ◽

Post Processing ◽

Processing Approach

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An updated review on recent trends in observational surface atmospheric variables and their extremes over Spain

Cuadernos de Investigación Geográfica ◽

10.18172/cig.3134 ◽

2017 ◽

Vol 43 (1) ◽

pp. 209 ◽

Cited By ~ 16

Author(s):

S.M. Vicente-Serrano ◽

E. Rodríguez-Camino ◽

F. Domínguez-Castro ◽

A. El Kenawy ◽

C. Azorín-Molina

Keyword(s):

Wind Speed ◽

Solar Radiation ◽

Air Temperature ◽

Heat Waves ◽

Extreme Weather ◽

Extreme Weather Events ◽

Weather Events ◽

Recent Trends ◽

The Mean ◽

Atmospheric Variables

This article reviewed state-of-the-art findings on recent trends in observed atmospheric variables and their extremes in Spain. Our study screened peer-reviewed articles, published within the last decade, on recent climate variability in Spain, with a particular focus on a range of the essential atmospheric variables. The review focusses on the recent evolution of precipitation and air temperature, but also on other meteorological variables such as solar radiation, wind speed, surface humidity and evapotranspiration. While this review highlights results on changes in the mean state of climate in Spain, it also gives equal attention to findings on extreme weather events (e.g. rainstorms, heat waves and droughts). This paper also reviews trends of the most extreme events, like rainstorms, heat waves and droughts. A detailed review of studies focusing on recent changes in the surface climate of Spain revealed some key findings. Studies demonstrate an overall increase of solar radiation since the 1980s. A similar behaviour was observed for surface air temperature since the 1960s, on the order of +0.3ºC decade-1, with rapid warming rates during summer. Different seasonal trend patterns of wind speed were noted over Spain, with declines in winter-spring and increases in summer-autumn. A remarkable decrease (-5%) in relative humidity was observed from 1961 to 2011. For precipitation, studies suggested a strong variability over both space and time, with a moderate decrease of the annual total precipitation. In accordance with changes in the mean conditions of climate, studies of extreme weather events stressed a notable warming in warm extremes, while changes in cold extremes were generally insignificant.

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Direct Solar Radiation Prediction Based on Soft-Computing Algorithms Including Novel Predictive Atmospheric Variables

Intelligent Data Engineering and Automated Learning – IDEAL 2013 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-41278-3_39 ◽

2013 ◽

pp. 318-325 ◽

Cited By ~ 7

Author(s):

S. Salcedo-Sanz ◽

C. Casanova-Mateo ◽

A. Pastor-Sánchez ◽

D. Gallo-Marazuela ◽

A. Labajo-Salazar ◽

...

Keyword(s):

Solar Radiation ◽

Soft Computing ◽

Direct Solar Radiation ◽

Atmospheric Variables

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Development of Climate Services for Renewable Energy: Statistical Post-processing of Solar Radiation Seasonal Forecast Over the Indonesian Region

10.5194/ems2021-319 ◽

2021 ◽

Author(s):

Yesi Sianturi ◽

Ardhasena Sopaheluwakan ◽

Tamima Amin ◽

Kwarti A. Sartika ◽

Andhika Hermawanto ◽

...

Keyword(s):

Solar Radiation ◽

Solar Energy ◽

Energy Input ◽

Transfer Functions ◽

Seasonal Forecast ◽

Model Output ◽

Post Processing ◽

Short Term ◽

Radiation Data ◽

Observation Network

Indonesia is one of the tropical regions with strong solar radiation exposure throughout the year, and this indicates the large potential for solar energy utilization in the country. Nevertheless, the utilization of solar energy in Indonesia until 2020 had only reached 10 MWp, as reported by the Ministry of Energy and Mineral Resources (ESDM), which is very small compared to the total potential of solar energy in Indonesia (approximately 112,000 GWp). One of the challenges for the development of solar energy in Indonesia is the weather and climate factors, as several weather parameters can cause intermittency in solar energy input in this region.In the solar energy sector, a reliable forecast of potential energy input is of great importance in designing operational plans, whether it is a short-term, annual, or longer-term work plan. Global horizontal irradiance is an important quantity to determine the power generated from photovoltaic devices, and different resources are used to generate global radiation forecasts all over the world, ranging from ground-observed radiation, remote sensing observation, to numerical weather models. The European Centre for Medium-Range Weather Forecasts (ECMWF) provides solar radiation forecasts for various timescales, from hourly forecast to monthly and seasonal forecast. Whilst short-term solar radiation forecast is provided by other standard weather forecasting models, forecasts in the longer timescale are less commonly available and thus the seasonal forecast becomes a valuable information in making long-term operational plans.A new solar radiation observation network has been installed in a number of locations across Indonesia in recent years, which allows the evaluation and modification of the seasonal forecast generated by the model. To improve the performance of the forecast, a statistical post-processing approach is implemented, by making use of measurements provided by the radiation observation network and ERA5 reanalysis dataset. To generate historical solar radiation data in all parts of Indonesia, a co-kriging interpolation of the ground-observed solar radiation is executed, using reanalysis data as an external drift in the interpolation process. The new gridded solar radiation data is then utilized to create transfer functions that represent the relationship between the statistical moments of both the numerical model output and observed radiation based on its probabilistic distributions. The transfer functions are generated in the training period, which will then be used to modify the model output in the forecast period. The implementation of the bias-correction process applied in this explorative study is aimed to provide the foundation of solar radiation prediction information that will support the operational activities of solar energy production in Indonesia.

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Performance Analysis of Short-Term Electricity Demand with Atmospheric Variables

Energies ◽

10.3390/en11040818 ◽

2018 ◽

Vol 11 (4) ◽

pp. 818 ◽

Cited By ~ 6

Author(s):

Kamal Chapagain ◽

Somsak Kittipiyakul

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Solar Radiation ◽

Cloud Cover ◽

Demand Forecasting ◽

Electricity Demand ◽

Short Term ◽

Electricity Demand Forecasting ◽

Model C ◽

Atmospheric Variables

The quality of short-term electricity demand forecasting is essential for the energy market players for operation and trading activities. Electricity demand is significantly affected by non-linear factors, such as climatic conditions, calendar components and seasonal behavior, which have been widely reported in the literature. This paper considers parsimonious forecasting models to explain the importance of atmospheric variables for hourly electricity demand forecasting. Many researchers include temperature as a major weather component. If temperature is included in a model, other weather components, such as relative humidity and wind speed, are considered as less effective. However, several papers mention that there is a significant impact of atmospheric variables on electricity demand. Therefore, the main purpose of this study is to investigate the impact of the following atmospheric variables: rainfall, relative humidity, wind speed, solar radiation, and cloud cover to improve the forecasting accuracy. We construct three different multiple linear models (Model A, Model B, and Model C) including the auto-regressive moving average with exogenous variables (ARMAX) with the mentioned exogenous weather variables to compare the performances for Hokkaido Prefecture, Japan. The Bayesian approach is applied to estimate the weight of each variable with Gibbs sampling to approximate the estimation of the coefficients. The overall mean absolute percentage error (MAPE) performances of Model A, Model B, and Model C are estimated as 2.43%, 1.98% and 1.72%, respectively. This means that the accuracy is improved by 13.4% by including rainfall, snowfall, solar radiation, wind speed, relative humidity, and cloud cover data. The results of the statistical test indicate that these atmospheric variables and the improvement in accuracy are statistically significant in most of the hours. More specifically, they are significant during highly fluctuating and peak hours.

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