Thesis

Numerical prediction of the night sky quality

Details

  • Call:

    IDPASC Portugal - PHD Programme 2017

  • Academic Year:

    2017 / 2018

  • Domain:

    Astrophysics

  • Supervisor:

    Rui Salgado

  • Co-Supervisor:

    Raul Lima

  • Institution:

    Universidade de Évora

  • Host Institution:

    Universidade de Évora

  • Abstract:

    Artificial light at night from ground sources produces light pollution and is the cause of skyglow. Part of the light emitted from those sources, either directly or by reflection off the ground, propagates horizontally and upward. The resulting brightening of the night sky is detectable up to dozens or hundreds of kilometres from the sources compromising, together with the transparency of the atmosphere, astronomical and astrophysical observations. A model of light propagation that can predict the effect of a ground source at a known distance relies on a thorough knowledge of the diffusion of the light on the atmosphere. The scattering of the light from ground sources depends on the molecules and aerosols present on the atmospheric layers, on cloud cover and air humidity. Some of these physical parameters are operationally anticipated by the Numerical Weather Prediction (NWP) systems. The main objective of this PhD programme is the study of the predictability of the nocturnal darkness and of the atmospheric transparency by linking a nocturnal light propagation tested model (Kocifaj, 2007) with a NWP model and a scheme to compute the moon brightness. The work-plan includes the study of the dependence of the scattering of the light on the local atmospheric characteristics. Measuring simultaneously, in situ, both night sky brightness and the concentration of aerosols and molecules, would allow the refinement of current light diffusion models. As we know, it will be the first attempt to get sky quality forecasts based on NWP, which will be of high interest to astronomers and astrophysicists. The Dark Sky Alqueva Reserve, in Alentejo, will be the field laboratory to test the methodologies. As it was the first Starlight Tourism Destination in the world, the Alqueva reserve has optimal conditions to perform such a study, taking advantage of previous studies (Lima, Pinto da Cunha, Peixinho, 2016) and of the development of a new project (ALOP: ALT20-03-0145-FEDER-000004), in which a meteorological station will be installed together with a Sky Quality Meter. STATE OF THE ART The definition of “Light pollution” (LP) is ambiguous, but many authors (Elliott, 2009; Gallaway, Olsen & Mitchell, 2010; Cinzano & Falchi, 2014; and others) agree on that LP is the alteration of the natural quantity of light in the night environment produced by the introduction of manmade light. LP interferes with wildlife and astronomical observations, may trigger potentially harmful health effects, wastes energy and leads to unnecessary consumption of natural resources to generate light, among other effects. In the context of the study for this work, LP will be assumed as a perceptible and mostly continuous degradation of the natural dark sky brightness conditions. The “Declaration in Defence of the Night Sky and the Right to Starlight” (stated by the conjoint UNESCO, UNWTO and IAU) considers that the degradation of the night sky must be regarded as a fundamental loss and its preservation should be considered an inalienable right. Also, intelligent use of artificial lighting that minimizes sky glow and avoids obtrusive visual impact on both humans and wildlife should be promoted, plus this is a strategy that would involve a more efficient use of energy to meet the wider commitments made on climate change, and for the protection of the environment (Starlight, 2007). Astronomical observatories are considerably affected by light pollution, therefore site testing is crucial for new and planned observatories, not only for current conditions but also to prospective light pollution increase in the large vicinity (McInnes & Walker, 1974). Thus, it is of extreme importance to foresee the evolution of LP in sites of interest as it is the Dark Sky® Alqueva Reserve, in Portugal, the first Starligh Tourist Destination in the world (Lima, 2015). Recently, Falchi et al (2016) published the New World Atlas of Artificial Night Sky Brightness mapping the current state of the artificial night sky brightness and showing the continuous increase of light pollution on a worldwide scale. To understand the evolution of LP and plan the actions to take in order to minimise it and prevent its growth, analysis based on LP modelling has to be done. Several modelling studies have been made, most of them based on population number and distance to the populated centres (Olsen, Gallaway & Mitchell, 2013) (Walker, 1970, 1977). Nevertheless, this approach has revealed limitations given to the absence of direct data on light pollution, unreliable source of data on population number and distribution, thus this model procedures had to be abandoned (Lima, 2015). A model of light diffusion proposed by Garstang uses various atmospheric parameters along with geographical characteristics, such as the elevation angle of the city (emmiter) relative to the observer (Garstang, 1986). Garstang’s model was the base of subsequent models such as Pierantonio Cinzano’s (Cinzano, 2000), that later, in a pioneering study, (Cinzano et al, 2001) created the first world atlas of the artificial night sky brightness, combining radiance from the US Air Force Defense Meteorological Satellite Program Operational Linescan System (DMSP OLS) satellite data with a model based on Garstang’s model, that takes into account all available radiance data whether produced by a populated centre, by an industrial centre, or any other source, which was a remarkable improvement over all previous models. More recently, other authors – Kocifaj’s (2007), Luginbuhl et al (2009), Aubé & Kocifaj (2012), Cinzano & Falchi (2013), (Kocifaj, 2014) – introduced improvements in the allowed atmospheric parameters, on the radiative transfer problem, and in the numerical codes, models that are known as extended Garstang models (EGM). The Kocifaj’s model (Kocifaj, 2007), also used in (Lima, 2015) applied to the Alqueva Reserve, is the proposed model to be the tested in this work. The Kocifaj’s model will be used linked to a Numerical Weather Prediction model (NWP) and a scheme to compute the moon brightness. Plus, in situ measurements of the night sky brightness and concentration of aerosols and molecules will allow the refinement of the current light diffusion models. Nowadays, NWP models produce realistic forecasts, at 10 km resolution in the case of the global ECMWF’s Integrated Forecasting System (IFS, 2016), or 2.5 km, for Portugal, in the case of AROME (Applications of Research to Operations at Mesoscale, Seity, 2016). In addition to the most common weather variables, NWP models produce a wide range of quantities that can be used to support various human activities. Specifically for the description of solar radiation, this two model uses the ‘‘McRad’’ radiation model (Morcrette et al., 2007), which allows to predict values of various radiative components, including direct normal irradiance, DNI, which is currently being tested for support concentrating solar projects (Troccoli and Morcrette, 2014). The advances in radiative modelling, weather forecast, and aerosol assimilation in combination with light diffusion schemes allow us to suppose that it is possible to take further forecast steps, including the prediction of night darkness. WORKPLAN The PhD programme includes the following tasks/objectives: 1. Investigate the state of the art of nocturnal artificial light propagations models and possible advantages of use of NWP results as input parameters. 2. Participation in the installation and test of a Sky Quality Meter in a meteorological station. 3. Monitoring and control the operation of the Sky Quality Meter and processing of the collected data. 4. Use calibrated satellite remote sensing information in order to map night light sources in the region of interest. 5. Study the relationships between night sky brightness and the local concentration of aerosols and molecules and use this information to introduce refinements in current light diffusion models. 6. Learning how to use a numerical weather prediction model. The Meso-NH research model (Lafore et al., 1998) will be the model to be used in the case studies simulations. 7. Carry out the (one way) coupling of the nocturnal light propagation model to the Meso-NH model. 8. Perform and analyse numerical simulations of well documented real case studies, using the coupled NWP-Night-Darkness model. 9. Based on the above results, investigate the feasibility of the use of operational weather forecast information currently made available for Portugal by the IPMA (based on IFS and AROME models) in predicting the sky quality for astronomers and astrophysics. 10. Writing papers and the thesis. REFERENCES Aubé, Martin, & Kocifaj, Miroslav (2012). Using two light-pollution models to investigate artificial sky radiances at Canary Islands observatories. Monthly Notices of the Royal Astronomical Society, 422(1), pp. 819–830. doi:10.1111/j.1365-2966.2012.20664.x Cinzano, Pierantonio (2000). The Propagation of Light Pollution in Diffusely Urbanised Areas. In Cinzano, P. (Ed.) Measuring and Modelling Light Pollution. Memoria della Società Astronomica Italiana/Journal of the Italian Astronomical Society, 71(1), pp. 93-112. Cinzano, Pierantonio, & Falchi, Fabio (2013). The propagation of light pollution in the atmosphere. Monthly Notices of the Royal Astronomical Society, 427(4), pp. 3337–3357. doi:10.1111/j.1365-2966.2012.21884.x Cinzano, Pierantonio, & Falchi, Fabio (2014). Quantifying light pollution. Journal of Quantitative Spectroscopy & Radiative Transfer, 139, pp. 13– 20. Cinzano, Pierantonio, Falchi, Fabio, & Elvidge, Christopher D. (2001). The first World Atlas of the artificial night sky brightness. Monthly Notices of the Royal Astronomical Society, 328(3), pp. 689–707. doi:10.1046/j.1365- 8711.2001.04882.x Elliott, Kevin C. (2009) Pollution. In Callicott, J. B., and Frodeman, R. (Eds.). Encyclopedia of Environmental Ethics and Philosophy - Vol. 2., pp. 158. Farmington Hills, MI: Gale. Falchi, Fabio, Cinzano, Pierantonio, Duriscoe, Dan, Kyba, Christopher CM, Elvidge, Christopher D, Baugh, Kimberly, Portnov, Boris A, Rybnikova, Nataliya A, Furgoni, Riccardo. (2016). The new world atlas of artificial night sky brightness Science advances 10 jun: Vol. 2, no. 6, e1600377. doi: 10.1126/sciadv.1600377 Gallaway, T., Olsen, R. N., & Mitchell, D. M. (2010). The economics of global light pollution. Ecological Economics, 69(3), pp. 658–665. doi:10.1016/j.ecolecon.2009.10.003 Garstang, Roy H. (1986). Model for Artificial Night-Sky Illumination. Publications of The Astronomical Society of the Pacific, 98, pp. 364–375. IFS (2016). IFS Documentation – Cy41r2. Part III: Dynamics and numerical procedures, ECMWF, 2016. Lafore JP, Stein J, Asencio N, Bougeault P, Ducrocq V, Duron J, Fischer C, Héreil P, Mascart P, Masson V, Pinty JP, Redelsperger JL, Richard E, Vilà-Guerau de Arellano J. 1998. The Meso-NH Atmospheric Simulation System. Part I: adiabatic formulation and control simulations. Annales Geophysicae. 16: 90-109. DOI: 10.1007/s00585-997-0090-6 Kocifaj, M (2007). Light-pollution model for cloudy and cloudless night skies with ground-based light sources. Applied Optics, 46(15), pp. 3013–3022. Kocifaj, M (2014). Modeling the night-sky radiances and inversion of multiangle and multi-spectral radiance data. Journal of Quantitative Spectroscopy & Radiative Transfer, 139, pp. 35–42. Lima, R (2015). Light pollution: measuring and modelling skyglow: an application in two portuguese reserves. Coimbra [s.n.]. Tese de doutoramento. http://hdl.handle.net/10316/28773. Lima, R, Pinto da Cunha, J, Peixinho, N. 2016. Light Pollution: Assessment of Sky Glow on two Dark Sky Regions of Portugal. J Toxicol Environ Health A. 2016;79(7):307-19. doi: 10.1080/15287394.2016.1153446. Epub 2016 Mar 30 Morcrette, J.-J., and Coauthors, 2007: Recent advances in radiation transfer parameterizations. ECMWF Tech. Memo. 539, 52 pp. Olsen, Reed N., Gallaway, Terrel, & Mitchell, David. (2013). Modelling US light pollution. Journal of Environmental Planning and Management, 57(6), pp. 883–903. doi:10.1080/09640568.2013.774268 Seity, Y., P. Brosseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, and V. Mason, 2011: The AROME-France convective-scale operational model. Mon. Wea. Rev., 139,976–991, doi:10.1175/2010MWR3425.1 Starlight. (2007). Declaration in Defence of the Night Sky and the Right to Starlight (La Palma Declaration). In Marín, Cipriano & Jafari, Jafar (Eds.) Starlight: A common heritage. La Palma: Starlight Initiative and Instituto de Astrofísica de Canarias (IAC), pp. 455-457. Available from: http://www.starlight2007.net/pdf/StralightCommonHeritage.pdf. Troccoli A and Morcrette J-J. Skill of direct solar radiation predicted by the ECMWF global atmospheric model over Australia. J. Appl. Meteorol. Climatol. 2014;53:2571–88. Walker, Merle F. (1970). The California Site Survey. Publications of The Astronomical Society of the Pacific. 314, pp. 672-698. Walker, Merle F. (1977). The effects of urban lighting on the brightness of the night sky. Publications of The Astronomical Society of the Pacific, 89, pp. 405–409.