Solar irradiance, climatic indicators and climate change – An empirical analysis

Bhargawa, Asheesh; Singh, Ashok K.

doi:10.1016/j.asr.2019.03.018

Cited by 22 publications

(9 citation statements)

References 26 publications

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“…These three parameters are: climate change, natural capital depletion rates and pollution (Table 1). Potential quantitative indicators for climate change could be atmospheric CO2 concentration, global surface temperature, global sea ice extent, global mean sea level, global precipitation anomaly and possibly total solar irradiance (Bhargawa and Singh, 2019). Likewise, potential quantitative indicators for natural capital depletion rates could be reserves to production ratios of non-renewable energy resources, rare earth minerals et cetera.…”

Section: Environmental Dimensionmentioning

confidence: 99%

Green growth or degrowth? Evaluating the potential of technology for sustainability

Pyakurel¹

2021

Economics and Policy of Energy and the Environment

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The raging debate between green growth and degrowth continues. Technology is a focal point in this debate as the advocates of green growth and degrowth have contradictory views on the roles and impacts of technology on environment and society. Green growth advocates believe that technology can allow indefinite growth while simultaneously ensuring environmental and societal sustainability, whereas the degrowth advocates argue that technological progress cannot allow indefinite growth. These views are largely opinion based rather than informed by objective and systematic analyses because comprehensive tools to evaluate the roles and impacts of technology on environment and society do not yet exist. This paper develops a much-needed framework to comprehensively evaluate the roles of technology on environment and society by analysing the interactions among the dimensions of technology, environment, economy and society. Key parameters that characterise technology are proposed for its evaluation and the policy implications of technological evaluations are examined. Finally, potential future research directions are explored. The technological evaluation approach proposed in this paper has a potential to significantly advance the green growth versus degrowth debate.

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Section: Environmental Dimensionmentioning

confidence: 99%

Green growth or degrowth? Evaluating the potential of technology for sustainability

Pyakurel¹

2021

Economics and Policy of Energy and the Environment

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“…Many studies across the world have been carried out for highlighting the changes, trends and variability analysis of the solar irradiance and temperature. [12][13][14][15][16][17][18], but the problem is that little or no study has focused on the regional variations of a country, this study in particular is unique in that it focuses on all major cities (stations) in a country like Nigeria. The assumption is that locations in the same region have the same variation, but this may not be entirely so as latitudes, elevation, and other local meteorological factors vary.…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis and Distribution of Global Solar Radiation and Temperature Over Southern Nigeria

Okono

Agbo

Ekah

et al. 2022

J. Nig. Soc. Phys. Sci.

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The intensity of solar energy that is received by a particular location is affected by most meteorological conditions including, the solar irradiance received by the location, precipitation, extreme heat as a result of the surface or ambient temperature, etc. We obtain the monthly global solar irradiation and ambient temperature for the three (3) eco-climatic zones in the south of Nigeria (17 locations) for 12 years (2005 - 2016) from the Photovoltaic Geographical Information System (PVGIS) Satellite. The goal of this study is to understand how regional meteorological conditions affect radiation and temperature reception. Monthly and annual trends were plotted and compared for both variables in each region to show the similarity or dichotomy in their trends. The Mann-Kendall (M-K) trend test has been adopted to reveal that the changes in the variations on an annual basis, and results showed that the trend were not significant for both variables. Box plots have been used to give a better description of the data, and compared to show similarities and differences. Finally, we adopted the Gaussian (normal) distribution to show, understand and compare the data distribution. Linear regression plots for each zone shows that the relationship between the solar irradiation and temperature is high. Results show that the climate and vegetation of a region contributes majorly to the variation of radiation and temperature. Inhomogeneityof data or results for locations in the same zones may be attributed to local meteorological conditions. The results obtained here will prove vital in decision making relating to the adoption of solar energy technologies in the region. Results show that the climate and vegetation of a region contributes majorly to the variation of radiation and temperature. Inhomogeneity of data or results for locations in the same zones may be attributed to local meteorological conditions.

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“…Most of these studies were based on physical modeling with strict boundary conditions and initial settings 11,12 . In the last few decades, data-driven methods utilizing time series analysis and machine learning models have been increasingly adopted to forecast global surface temperature or sea level 7,8,[13][14][15][16][17][18][19][20] and local climate 21 . In 2021, we published the rst work 9 on pathway analysis of global warming and sea level rise utilizing monthly historical data.…”

Section: Introductionmentioning

confidence: 99%

Data Driven Pathway Analysis and Forecast of Global Warming and Sea Level Rise

Song

Tong

Chao

et al. 2022

Preprint

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Climate change remains a top concern for the world, with its causes, pathways, and forecasts, still subject to debate. In this paper, we present a novel data driven pathway analysis framework to identify the key processes behind the mean global temperature and sea level rise, and to forecast the magnitude of the increases between now and 2100. Based on historical data and dynamic statistical modeling alone, we have confirmed the causal pathways from increased greenhouse gas emissions to increased global mean temperature and sea level, with its intermediate links including humidity, sea ice coverage and glacier volume, but not sunspot numbers. Our results indicate that, if no action is taken to rein in anthropogenic greenhouse gas emissions, the global average temperature is estimated to be 2.79°C higher than its pre-industrial level and the global sea level is expected to be 604 mm above its 2021 mean by 2100. However, if the global community would adhere to the greenhouse gas emission regulations outlined in the 2021 United Nations Conference on Climate Change (COP26), the global temperature would increase to a less threatening 1.58°C above its pre-industrial level, while the sea level increase would reduce to 455 mm above its 2021 mean.

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Solar irradiance, climatic indicators and climate change – An empirical analysis

Cited by 22 publications

References 26 publications

Green growth or degrowth? Evaluating the potential of technology for sustainability

Green growth or degrowth? Evaluating the potential of technology for sustainability

Statistical Analysis and Distribution of Global Solar Radiation and Temperature Over Southern Nigeria

Data Driven Pathway Analysis and Forecast of Global Warming and Sea Level Rise

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