This document discusses models for analyzing artificial sky brightness. It begins by defining sky brightness and noting that it is highly variable due to changing atmospheric conditions and light emissions. It then outlines several models for predicting night sky brightness, including two-stream approximation and iterative radiative transfer equation approaches. The document also discusses using analysis models to enable prediction and lists challenges for the future, such as extending measurement networks, using multispectral satellites, agreeing on common descriptors, developing parametric models, and issuing recommendations.

1. Salva Bará
salva.bara@usc.es
Área de Óptica, Dept. Física Aplicada. Facultade de Óptica e Optometría
Universidade de Santiago de Compostela. Galicia.
http://webspersoais.usc.es/persoais/salva.bara/
Models for the analysis of
artificial sky brightness

2. DISCLAIMER
This presentation is intended for
educational, non-commercial use.
Trademarks, models and publications are
quoted here merely for informative
purposes, without any explicit or implicit
endorsement by the Universidade de
Santiago de Compostela (USC).
(c) Images may have external copyright.

3. 1. "Sky brightness": what is it?
2. A highly variable magnitude
3. Modeling the night sky brightness
4. Challenges for the next years

4. 1. "Sky brightness": what is it?

5. "Brightness"

6. propagation
scattering
absorption
MEDIATED BY:
Molecules
Aerosols
NATURAL SOURCES
including airglow
ARTIFICIAL
SOURCES

7. Analyzing artificial
sky brightness
Measuring TOTAL sky
brightness and
subtracting the
NATURAL one
Computing the
ARTIFICIAL sky
brightness with LP
propagation models

8. 2. A highly variable magnitude

9. Variable light
emissions

10. Variable light
emissions
Changing atmospheric conditions

11. Variable light
emissions
Changing atmospheric conditions
Changes in
recorded
brightness

16. Parameter(s) of choice...?
- Significant magnitude m1/3

17. Parameter(s) of choice...?
- Significant magnitude m1/3
- Moonlight modulation factor

18. Parameter(s) of choice...?
- Significant magnitude m1/3
- Moonlight modulation factor

19. 3. Modeling the night sky brightness

20. A. Models for predicting the NSB
• Two-stream approximation
• Iterative approach to Radiative Transfer
Equation (RTE)
• Successive Orders of Scattering

21. Falchi et al, 2016

22. Fernando Patat, http://cosmicdiary.org/fpatat/2009/12/02/the-shadow-of-the-earth-lombra-della-terra/
Multiple scattering: the shadow of the Earth

23. Fernando Patat, http://cosmicdiary.org/fpatat/2009/12/02/the-shadow-of-the-earth-lombra-della-terra/
Multiple scattering: the shadow of the Earth
credit: Sky and Telescope

24. Kocifaj, 2018

26. B. Models for
analyzing the NSB

27. C. Using the analysis for prediction (1)

28. C. Using the analysis for prediction (2)

29. C. Using the analysis for prediction (3)

30. 4. Challenges for the next years

31. 4. Challenges for the next years
• Extending the measurement networks

32. Rede
Galega
de Medida
do Brillo
do Ceo
Nocturno

33. • (Re)Conocer la extensión del problema

34. 4. Challenges for the next years
• Extending the measurement networks
• Multispectral satellite platforms

35. (c) NASA-suomi NPP Oct.2012 (VIIRS)

37. ISS Jul. 26, 2014. Nikon D3S/24mm.

38. 4. Challenges for the next years
• Extending the measurement networks
• Multispectral satellite platforms
• Agreeing common NSB descriptors

39. 4. Challenges for the next years
• Extending the measurement networks
• Multispectral satellite platforms
• Agreeing common NSB descriptors
• Developing parametric NSB models

40. 4. Challenges for the next years
• Extending the measurement networks
• Multispectral satellite platforms
• Agreeing common NSB descriptors
• Developing parametric NSB models
• Issuing recommendations and ordinances