There are three devices operating at my home in east Tucson, Arizona, that continuously monitor the brightness of the night sky from my location and report their results on the web. Between these instruments, I have built up a dataset since mid-2017 that is useful for monitoring the evolution of skyglow at my site.
The location
My site, shown on the map below, is at the edge of the Tucson urban agglomeration. The map shows the Simplified Artificial Light Ratio (sALR) in false colors overlaid on an OpenStreetMap background. The colors range from dark blue to red in 32 steps of one unit of sALR per color.
The sALR is defined by Duriscoe et al. (2018). The overlay for 2024 was made by the U.S. National Park Service Natural Sounds and Night Skies Division from satellite measurements of nighttime lights. The sALR expresses by how much the artificial component of night sky brightness, averaged over the entire sky, compares to an assumed natural background level. sALR = 1, for example, means that there is as much artificial light in the night sky as there is natural light.
I have marked three particular values of the sALR on the map in colored contour lines. The red contour marks sALR = 10. Inside of this contour it is presumed the Milky Way is not visible to the unaided eye. As Milky Way invisibility is sometimes offered as an indication of significant skyglow, it's safe to say that the part of Tucson enclosed by the red contour is heavily light polluted.
The yellow contour marks the point where sALR = 2.0. Moore, Turina and White (2013) suggest this as a quality edge for "managed" night skies in U.S. national parks. Finally, the green contour (sALR = 0.33) is the upper limit for sky quality for a managed wilderness area. Note that in this view one has to travel roughly 100 km from the city center of Tucson to find such dark night skies; see the green contour line at extreme lower-left.
The full description of their suggested sky quality criteria is:
I have marked three particular values of the sALR on the map in colored contour lines. The red contour marks sALR = 10. Inside of this contour it is presumed the Milky Way is not visible to the unaided eye. As Milky Way invisibility is sometimes offered as an indication of significant skyglow, it's safe to say that the part of Tucson enclosed by the red contour is heavily light polluted.
The yellow contour marks the point where sALR = 2.0. Moore, Turina and White (2013) suggest this as a quality edge for "managed" night skies in U.S. national parks. Finally, the green contour (sALR = 0.33) is the upper limit for sky quality for a managed wilderness area. Note that in this view one has to travel roughly 100 km from the city center of Tucson to find such dark night skies; see the green contour line at extreme lower-left.
The full description of their suggested sky quality criteria is:
Sky Quality Class |
sALR |
NELM |
Bortle |
Zenith NSB (mpsa) |
Good |
0-0.33 |
> +6.8 |
1-3 |
> 21.90 |
Moderate ("threatened") |
0.33-2.0 |
+6.3 to +6.7 |
4 |
21.90-21.45 |
Poor ("for sensitive protected areas") |
2.0-10.0 |
+6.2 to +5.7 |
5 |
21.45-20.50 |
Milky Way invisible |
> 10.0 |
< +5.7 |
6-9 |
< 20.50 |
Here, "NELM" is the naked-eye limiting magnitude, which is the astronomical magnitude of the faintest star in the sky visible to the unaided eye; "Bortle" is the rating on the subjective Bortle Dark-Sky Scale; and "Zenith NSB" is the luminance of the zenith in 'astronomer' units (magnitudes per square arcsecond), in which a naturally dark night sky has a zenith value of about 22 mpsa.
My site is quite near the red contour line on the map. The measured value of sALR here is about 8; that is, the average value of the brightness of the night sky due to artificial skyglow is about 8 times higher than it would be were there no light pollution. This location is therefore properly characterized as Bortle 6 ("No trace of the zodiacal light can be seen, even on the best nights. Any indications of the Milky Way are apparent only toward the zenith. The sky within 35° of the horizon glows grayish white. Clouds anywhere in the sky appear fairly bright. You have no trouble seeing eyepieces and telescope accessories on an observing table. M33 is impossible to see without binoculars, and M31 is only modestly apparent to the unaided eye. The naked-eye limit is about 5.5, and a 32-cm telescope used at moderate powers will show stars at magnitude 14.0 to 14.5.")
The sALR estimate here is a little pessimistic; on clear, dark nights I can see the Milky Way easily from my backyard and follow it down to about 20° above the horizon when it rises in the southeast. Based on tests detailed on my Astronomical Visibility page, my NELM value is about +5, and with a 25-cm telescope I can see stars approaching magnitude +14.
My site is quite near the red contour line on the map. The measured value of sALR here is about 8; that is, the average value of the brightness of the night sky due to artificial skyglow is about 8 times higher than it would be were there no light pollution. This location is therefore properly characterized as Bortle 6 ("No trace of the zodiacal light can be seen, even on the best nights. Any indications of the Milky Way are apparent only toward the zenith. The sky within 35° of the horizon glows grayish white. Clouds anywhere in the sky appear fairly bright. You have no trouble seeing eyepieces and telescope accessories on an observing table. M33 is impossible to see without binoculars, and M31 is only modestly apparent to the unaided eye. The naked-eye limit is about 5.5, and a 32-cm telescope used at moderate powers will show stars at magnitude 14.0 to 14.5.")
The sALR estimate here is a little pessimistic; on clear, dark nights I can see the Milky Way easily from my backyard and follow it down to about 20° above the horizon when it rises in the southeast. Based on tests detailed on my Astronomical Visibility page, my NELM value is about +5, and with a 25-cm telescope I can see stars approaching magnitude +14.
The photometers
The devices I use were built by two teams at universities in Spain. They were developed as part of light pollution research campaigns with the goal of delivering instruments that were low in cost and durable in field conditions for long periods of time yet able to make accurate measurements of night sky brightness. They were intended as autonomous monitors that would operate with a minimum of human intervention, relaying their measurements through wireless connections.
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Telescope Encoder and Sky Sensor - WiFi (TESS-W)
The TESS-W is one of the outputs of the STARS4ALL, a project funded by the European Union Horizon 2020 Programme during 2014-2020. It is a compact device that runs on a 5V USB power connection and collects measurements of the night sky brightness using a light-to-frequency counter with a wide optical passband. It senses the presence of clouds by measuring the temperature difference between a sky-facing thermal IR sensor and a thermistor that measures the inside of the case. A lens over the sensor restricts the acceptance cone to 20º. Read the TESS instrument paper here.
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Telescope Encoder and Sky Sensor - WiFi - Four Color (TESS-W4C)
The TESS-W4C is a close relative of the TESS-W, but it provides color information that the TESS-W panchromatic sensor/filter combination doesn't. The package contains four light-to-frequency counters with optics yielding the same beamwidth as in the TESS-W. The sensors are equipped with optical filters to measure four passbands simultaneously: a wide panchromatic band; a slightlh narrower panchromatic band, and "R" and "B" channels. Differences between the bands are used to synthesize "G" and a kind of longwave red labeled "IR". Also like TESS-W, its enclosure contains a sky-facing thermal IR sensor and a thermistor. A report on these filters can be found here.
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SkyGlow Wireless Autonomous Sensor (SG-WAS)The SG-WAS also uses a light-to-frequency counter and a lens to narrow its field of view, but it also handles multiple wireless communication protocols (LoRa, WiFi, or LTE-M) and derives its electrical power from solar photovoltaic cells and rechargeable batteries. Like the TESS-W, it includes a thermal IR sensor for measuring the "temperature" of the sky, which it uses to make a first-order guess about whether the sky is clear or cloudy. It can report for up to 20 days on a full battery charge, and if powered off can 'hibernate' for as long as four months. Read the SG-WAS instrument paper here.
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Photometric passbands
The TESS-W(4C) and SG-WAS have different passbands, each of which is different to that of the most popular portable night sky photometer on the market, the Sky Quality Meter. The plot below (adapted in part from Figure 5 in reference [1]) shows the wide panchromatic passbands of TESS-W (solid purple line) and SG-WAS (solid red line), and the narrower panchromatic passband of the TESS-4C (wide black line) along with the passband of the popular Sky Quality Meter (solid yellow line). The TESS-W4C "B" and "R" passbands are shown in the solid blue and red lines, respectively, as are the synthetic "G" and "IR" passbands in dashed green and dark maroon lines. The purple dotted line represents a reference night sky spectrum, showing the principal airglow lines of [OI] and Na I ("D"), as well as emission due to ro-vibrational transitions of the OH molecule. The thin gray line shows the spectrum of skyglow over Tucson obtained in October 2019.
The color discrimination of the TESS-W4C is useful for discerning different sources of light in the night sky and can be helpful in understanding long-term trends. Its B band sees the strongest contribution from the "blue spike" in the white LED spectral power distribution at around 450 nm. The synthetic "G" band contains most of the spectral power in the Tucson light dome. The synthetic "IR" band has relatively little contribution from skyglow but picks up the OH airflow lines from around 700-750 nm.
The figure below provided by Prof. Jaime Zamorano (Complutense University of Madrid), shows a more accurate representation of the TESS-W panchromatic passband (solid purple line). It again compares it to the SQM passband (dashed black line) and the BVR passbands. The solid black line shows, as a point of comparison, the spectral power distribution of the night sky over the high-altitude Calar Alto Observatory site in southeast Spain. It again shows the large difference in instrumental sensitivity between TESS and the SQM at longer wavelengths.
Both the TESS and SG-WAS passbands transmit more light at long wavelengths than the SQM passband, the latter of which was chosen to mimic the response of the human visual system. In particular, TESS is more sensitive to the OH bands than either the SQM or SG-WAS, and it often reads brighter than them under the same conditions. The SQM has more short-wavelength sensitivity than either the TESS or SG-WAS, meaning that it reacts differently under twilight conditions in particular.
Intercomparison
Given that the devices are running at the same location under identical conditions, I have compared their output to obtain a rough calibration. In the plot below, measurements are shown in the blue points. A linear least-squares fit is shown as a blue solid line with 95% confidence intervals in the blue shaded area. The solid black line represents where the measurements would fall if there were a perfect 1:1 correspondence between the devices.
Over much of this range, which roughly represents the range of sky brightnesses typical of my site during astronomical darkness, SG_088 reads consistently brighter than stars19 by about half a magnitude. This seems to indicate a constant zeropoint offset rather than reflecting the devices' different passbands; under most circumstances, stars19 should read a little brighter by virtue of its wider passband. Accounting for the zeropoint difference, the two track each other well with a slope that differs only slightly from one (1.032). Accounting for random measurement errors, the devices are fairly comparable over several magnitudes.
TESS-W stars19 live output
The following plots represent live outputs from stars19. The first shows data for the past 24 hours. Three quantities are overplotted simultaneously: the measured zenith brightness (green), the "temperature" of the sky radiation (cyan) and the temperature of a thermistor inside the case (orange).
The next plot shows a week's worth of sky brightness data. The shape of the trace each night changes according to the moon phase and how clear the sky was.
The next plot shows the local altitude of the Sun (green) and Moon (orange) during the past week. It is positioned on the same temporal axis at the previous plot so the two line up horizontally. The Moon's percent illumination is shown in cyan.
The next plot shows a histogram of all data collected at the site since May 2017 under astronomically dark conditions (Sun at least 18 degrees below the horizon) and during times when the sky was probably clear (a large difference in temperature between the air and sky, indicating radiative cooling).
TESS-W4C stars1429 live output
The following plots represent live outputs from stars1429. The first shows data for the past 24 hours. Four quantities are overplotted simultaneously: the measured zenith brightness in (1) the wide panchromatic TESS-W passband (purple); (2) a narrower panchromatic band (black); (3) the "R" band (red); and (4) the "B" band (blue).
Below are "dashboard"-style outputs for the four channels of stars1429 showing current values of the zenith brightness in units of magnitudes per square arcsecond.
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Analysis and statistics
The Internet of Things EELab (IOT-EELab) provides some simple, interactive analysis tools for both the TESS-W and SG-WAS photometers. The following plots are specific to stars19 due to the length of its dataset (~8 years as of this writing). The data were filtered according to these criteria:
Variable |
Value |
Dates |
2017-05-02 to 2025-06-30 |
Sun altitude |
< -18º |
Moon altitude |
< -5º |
Clouds |
σ (mag) < 0.01 |
Galactic latitude in zenith |
|b| > 40º |
Ecliptic coordinates of Sun and zenith |
Variable, depending on the ecliptic longitude of the Sun and the ecliptic latitude of the zenith (see Fig. 6a in Alarcon et al. 2021) |
Outlier rejection |
3σ |
That leaves 18204 measurements represented in the plots below. First, a histogram of measurements in this filtered set:
Descriptive statistics on the set are as follows:
Parameter |
Value (mag/arcsec²) |
Mean |
20.296 |
Median |
20.308 |
P50 |
20.300 |
P99 |
20.610 |
σ |
0.130 |
Brightest measurement |
19.86 |
Darkest measurement |
20.64 |
1st quartile |
20.23 |
3rd quartile |
20.37 |
The next plot shows a histogram of all measurements showing the effect of applying the filters. The colors of each trace indicate the distribution of remaining measurements after each cut. The influences of the Sun, Moon and clouds account for almost of the non-Gaussianity of the distributions.
The next plot is a so-called "jellyfish plot" of all measurements. This is a kind of densitogram that plots the number of measurements in each of a set of bins of (time of night, night sky brightness). Warmer colors mean more measurements fall into a given bin, and the time axis is aligned so that local midnight always falls along the center of the x-axis.
The bulk of the points fall roughly along a horizontal line near the typical clear-sky sky brightness (~20.3 magnitudes per square arcsecond). The "arms" of the jellyfish on either end represent the changing length of the night during the seasons, with shorter temporal sequences in summer and longer ones in winter. Cyan-colored pixels below the main bulk indicate nights with cloud and/or moonlight interference (or both). Since my site is located in a light-polluted area, clouds brighten the night sky rather than making it darker than the natural background level.
Also note the slight slant in the plotted points. That's a real effect, and it shows that the night sky gets a little darker in the hours after midnight. Again, being in an urban area, this is a reflection of human activity patterns. In any near cities, outdoor lighting tends to dominate the budget of light in the night sky and control the measured brightness in clear-sky conditions.
The next plot is a jellyfish plot of only filtered measurements according to the criteria listed above.
Also note the slight slant in the plotted points. That's a real effect, and it shows that the night sky gets a little darker in the hours after midnight. Again, being in an urban area, this is a reflection of human activity patterns. In any near cities, outdoor lighting tends to dominate the budget of light in the night sky and control the measured brightness in clear-sky conditions.
The next plot is a jellyfish plot of only filtered measurements according to the criteria listed above.
Now the distribution of remaining values reflects "ideal" conditions that best characterize the site.
The next plot is a heatmap of all measurements where the color of a cell indicates the measured zenith brightness on that date and time. Cooler colors mean darker night skies and warmer colors mean brighter skies.
The next plot is a heatmap of all measurements where the color of a cell indicates the measured zenith brightness on that date and time. Cooler colors mean darker night skies and warmer colors mean brighter skies.
The "wavy" appearance of this plot again reflects the changing length of the night throughout the seasons. During summer, the distribution narrows in the vertical direction; in winter it widens as the nights get longer.
The next plot is a heatmap of filtered measurements:
The next plot is a heatmap of filtered measurements:
This plot tells us something about local meteorological conditions as well as the latitude of my site (around 32ºN). After removing all points from the raw dataset that include interference from the Sun, Moon, clouds and the Milky Way, the darkest months of the year are revealed: February to June. The swaths of points tend to get more dense as the months progress, as our weather is on average most consistently clear in late spring and early summer. At our latitude, one of the most dense parts of the Milky Way is in the zenith during much of the night from around June to September; on the other hand, the North Galactic Cap is in our zenith in around March and April.
The last plot is a "sky chart" of all measurements:
The last plot is a "sky chart" of all measurements:
In this representation of the data, the field of view of the TESS-W is shown on a Mercator projection of the celestial sphere. The declination in our zenith is roughly equal to our latitude, so the data are indicated by the continuous strip of color in the upper third of the plot. The colors represent the zenith brightness as a function of right ascension. Because the declination of the North Galactic Pole (+27.4°) is similar to the latitude at my site, the sky appears to get a little darker in around April and May because the influence of light from the Milky Way is least during that time. This is particularly evident if the same type of plot is made that includes only the filtered data:
Application: Skyglow amplification by clouds
The photometers can infer the presence of clouds by looking at the difference between the ambient temperature of the air around the devices and the "temperature" of the radiation field of the night sky (the "sky temperature"). They do this with the use of an auxiliary sensor that records the intensity of thermal infrared radiation coming from the direction toward the zenith. When there is a large difference between these numbers, it means the sky is clear and the land is efficiently cooling by radiating heat toward the "cold" night sky. Here is an example of this from stars1429 data obtained on the night of UT 2025 May 27. The plotting window runs from sunset on the left to sunrise on the following day on the right.
Here the orange trace is the air temperature and the blue trace is the sky temperature, both in units of degrees Celsius. They start off separated by almost 36° C. Late in the night, just before the onset of air heating by the Sun after local sunrise, they have coasted to a separation of about 25° C. At that point the land and the lower atmosphere are nearly in thermodynamic equilibrium locally (to the extent that ever happens!)
On the other hand, here's what (part of) a cloudy night looks like, the night of UT 2026 February 17:
On the other hand, here's what (part of) a cloudy night looks like, the night of UT 2026 February 17:
During this two-hour span, the observed conditions at my site were very nearly uniform overcast. Note how, although the air temperature (orange trace) decreases by nearly 1° C over this interval, the sky temperature (blue trace) hardly changes. This is an indication that radiative cooling has pretty much stalled completely because clouds are frustrating the infrared photon paths as they try to make their way to space.
Now, looking at the sky brightness on overcast versus clear nights, one finds that the difference in zenith brightness from completely cloudy to completely clear conditions changes by a little more than three magnitudes (3.25, to be a little more exact). That is a factor of 2.512^3.25 ~ 20 (using Pogson's Ratio) difference in brightness. It also indicates the amount by which clouds "amplify" skyglow as seen from my location. That is to say that cloudy nights are literally 20 times brighter at the zenith than are clear nights. The extra light comes from the city (Tucson), and the clouds reflect it back down to the ground with much more efficacy than under clear conditions when reflection is considerably lower.
This also has an effect on the flux of light reaching the ground. This is connected to the brightness of the night sky via what is known as the Posch Ratio, named in honor of our departed colleague, Dr. Thomas Posch (1974-2019). It is the ratio of night sky radiance (L) to the horizontal irradiance (E) and has a value of around π (≈ 3.14159...) Under light-polluted conditions a clear sky is closer to 2.25π, or about 7. Clouds lower it to around 4 (see Jechow, Kyba and Hölker 2020). Using this number for the ratio gives E = 4L. So if the sky radiance changes by a factor of 20, the horizontal irradiance changes by a factor of about 4×20 = 80. For plants and animals that expect dark nighttime conditions in nature, elevating the (already bright) ground illumination level by a factor of 80 presents some big challenges.
Now, looking at the sky brightness on overcast versus clear nights, one finds that the difference in zenith brightness from completely cloudy to completely clear conditions changes by a little more than three magnitudes (3.25, to be a little more exact). That is a factor of 2.512^3.25 ~ 20 (using Pogson's Ratio) difference in brightness. It also indicates the amount by which clouds "amplify" skyglow as seen from my location. That is to say that cloudy nights are literally 20 times brighter at the zenith than are clear nights. The extra light comes from the city (Tucson), and the clouds reflect it back down to the ground with much more efficacy than under clear conditions when reflection is considerably lower.
This also has an effect on the flux of light reaching the ground. This is connected to the brightness of the night sky via what is known as the Posch Ratio, named in honor of our departed colleague, Dr. Thomas Posch (1974-2019). It is the ratio of night sky radiance (L) to the horizontal irradiance (E) and has a value of around π (≈ 3.14159...) Under light-polluted conditions a clear sky is closer to 2.25π, or about 7. Clouds lower it to around 4 (see Jechow, Kyba and Hölker 2020). Using this number for the ratio gives E = 4L. So if the sky radiance changes by a factor of 20, the horizontal irradiance changes by a factor of about 4×20 = 80. For plants and animals that expect dark nighttime conditions in nature, elevating the (already bright) ground illumination level by a factor of 80 presents some big challenges.
Application: Influence of the 11-year solar cycle
With over eight years of data in hand from TESS-W stars19, I looked at whether it was possible to detect the influence of the solar cycle on the brightness of the night sky from my moderately light-polluted site. The Sun's magnetic activity waxes and wanes with a periodicity of about 11 years for reasons that solar physicists are still trying to understand. During periods when its activity is high, the Sun generally emits more ultraviolet and x-ray light that can dissociate molecules and ionize atoms in the upper atmosphere on Earth's daytime side. When the components find each other on the night side, they recombine and emit faint light. This 'night airglow' is usually the strongest influence on the brightness of the night sky in places not affected by light pollution.
There also instances in which very energetic magnetic events on the Sun unleash streams of charged particles directed toward the Earth. When these particles slam into the constituents of the upper atmosphere they cause it to emit generally brighter light than the night airglow. These aurorae are most common at high latitudes, but on rare occasions we also see them here in the Arizona desert. Here is an example captured in a photograph taken at my site in October 2024:
There also instances in which very energetic magnetic events on the Sun unleash streams of charged particles directed toward the Earth. When these particles slam into the constituents of the upper atmosphere they cause it to emit generally brighter light than the night airglow. These aurorae are most common at high latitudes, but on rare occasions we also see them here in the Arizona desert. Here is an example captured in a photograph taken at my site in October 2024:
The reddish light low in the northern sky is due to atomic oxygen in the 1D excited state. We only see it coming from atoms at altitudes above 300 km because the transition is "quenched" at lower altitudes where the air is more dense and collisions with other atmospheric constituents are more likely. The plot below shows the detection of the aurora (red arrow) at the local zenith during the intense geomagnetic storm of UT 11 May 2024. During this event, which lasted about two hours, the zenith brightened by about 15%.
Anecdotally, I noticed that the darkest clear nights in around 2024-2025, near the peak of the current Solar Cycle 25, were brighter by a comparable amount compared to the darkest nights at the minimum of the cycle in 2019-2020. I set out to determine if that was clearly indicated in the data by writing some Python code to perform a time series analysis on the data. Almost 4 million individual data points were filtered, as described above, to remove data points contaminated by twilight, moonlight, clouds, the Milky Way, and the zodiacal light.
That leaves only natural sources like the airglow and the artificial light from Tucson. Sure enough, the results plotted against time show the expected sinusoidal variation:
Bear in mind that this is a subtle effect at my location. The skyglow signal is sufficient to swamp that of smaller natural effects. This analysis is a little like trying to find the proverbial needle in a very noisy haystack.
So far the outcome is suggestive if perhaps not conclusive. The next question is whether individual zenith brightness measurements correlate with other measures of solar activity. Among those is the solar 10.7-cm radio flux, which Space Weather Canada calls "currently one of the best indices of solar activity we have," and that it "correlates with indices of solar activity such as sunspot number and total sunspot area, with the advantage over those indices that the measurements are completely objective, and can be made under almost any weather conditions." It reflects the slowly varying component of solar radio emission and therefore is good at detecting long-term trends. SWC has daily records of the 10.7-cm radio flux going back decades, making it a good source of data for this analysis.
When I plot the brightness of my zenith (after filtering out contaminated measurements) against the 10.7-cm radio flux, I get a correlation that is weak but fairly clear:
So far the outcome is suggestive if perhaps not conclusive. The next question is whether individual zenith brightness measurements correlate with other measures of solar activity. Among those is the solar 10.7-cm radio flux, which Space Weather Canada calls "currently one of the best indices of solar activity we have," and that it "correlates with indices of solar activity such as sunspot number and total sunspot area, with the advantage over those indices that the measurements are completely objective, and can be made under almost any weather conditions." It reflects the slowly varying component of solar radio emission and therefore is good at detecting long-term trends. SWC has daily records of the 10.7-cm radio flux going back decades, making it a good source of data for this analysis.
When I plot the brightness of my zenith (after filtering out contaminated measurements) against the 10.7-cm radio flux, I get a correlation that is weak but fairly clear:
Importantly, the darkest nights in the time series never happen when the 10.7-cm radio flux is high.
Given this simple empirical correspondence between solar magnetic activity and zenith sky brightness, it is reasonable to model and subtract that influence. Doing so reveals any underlying trend in the data that is presumably the result of changes to artificial light emissions here in Tucson that ultimately control the brightness of my night sky (at least at the zenith). Here are the results:
Given this simple empirical correspondence between solar magnetic activity and zenith sky brightness, it is reasonable to model and subtract that influence. Doing so reveals any underlying trend in the data that is presumably the result of changes to artificial light emissions here in Tucson that ultimately control the brightness of my night sky (at least at the zenith). Here are the results:
What's left, particularly after the data gap in 2019, certainly looks like "no change". Other than the solar cycle influence, that matches my own intuition about the city lights around me. (In fairness, the recent population trend in Tucson is growth averaging less than 0.5% per year, so one doesn't expect a lot of new lighting.)
How does this compare to trends in the amount of light emitted on the ground that determines my zenith brightness? To answer that question involves first determining where that light comes from. Most artificial light at an observer's zenith originates within a few kilometers, but the 'reach' of outdoor lighting depends on a number of factors including the technical specifications of luminaires and light-scattering properties of the local atmosphere (see more about that below).
Tucson itself clearly dominates artificial light emissions in my vicinity. Below is plotted the summed upward radiance from within the corporate boundaries of the city (634 square kilometers in all) from 2017-2025. And, somewhat surprisingly, there is a clear increase in that radiance since about the year 2023. Lately the city's total radiance has increased by about five percent per year.
How does this compare to trends in the amount of light emitted on the ground that determines my zenith brightness? To answer that question involves first determining where that light comes from. Most artificial light at an observer's zenith originates within a few kilometers, but the 'reach' of outdoor lighting depends on a number of factors including the technical specifications of luminaires and light-scattering properties of the local atmosphere (see more about that below).
Tucson itself clearly dominates artificial light emissions in my vicinity. Below is plotted the summed upward radiance from within the corporate boundaries of the city (634 square kilometers in all) from 2017-2025. And, somewhat surprisingly, there is a clear increase in that radiance since about the year 2023. Lately the city's total radiance has increased by about five percent per year.
The data used in this plot were extracted from Radiance Light Trends, for which I gladly thank the site developer, Jurij Stare. The radiances come from the Visible Infrared Imaging Radiometer Suite Day-Night Band, which is deployed on several satellites operated by the United States National Oceanic and Atmospheric Administration.
Why am I not seeing this increase in my time-series data after correcting for the influence of the solar cycle? There are a few reasons. Maybe I actually have seen an increase in my zenith brightness due to higher light emissions from Tucson, which are happening at a rate that coincidentally follows the solar cycle in phase. As a result, in the previous step I may have simply removed the city signal instead of the solar signal. An indicator of this would be if, in coming years, my zenith stays bright even as solar activity declines toward the next solar minimum in around 2030. Alternately, maybe the growth in Tucson light emissions is happening far from my location on the opposite side of the city, which would yield a proportionally lower effect at my zenith. To sort this out, I will continue to follow both the solar cycle and city light emissions in the next several years. This kind of application shows the power of the kinds of time series that devices like the TESS photometers can provide.
Why am I not seeing this increase in my time-series data after correcting for the influence of the solar cycle? There are a few reasons. Maybe I actually have seen an increase in my zenith brightness due to higher light emissions from Tucson, which are happening at a rate that coincidentally follows the solar cycle in phase. As a result, in the previous step I may have simply removed the city signal instead of the solar signal. An indicator of this would be if, in coming years, my zenith stays bright even as solar activity declines toward the next solar minimum in around 2030. Alternately, maybe the growth in Tucson light emissions is happening far from my location on the opposite side of the city, which would yield a proportionally lower effect at my zenith. To sort this out, I will continue to follow both the solar cycle and city light emissions in the next several years. This kind of application shows the power of the kinds of time series that devices like the TESS photometers can provide.
Application: Aerosol detection
The brightness of the night sky in and near cities is usually dominated by artificial skyglow. This is particularly true in the case of bigger cities, where always contributes more to night sky brightness than any natural source of light. However, natural influences can modulate the amount of skyglow by changing the light-scattering properties of the lower atmosphere. The research group led by Prof. Miroslav Kocifaj (Slovak Academy of Sciences) has published important work on this subject in recent years; see references 2-4, below. More information about this effect is on my Skyglow research page.
The bottom line is that when the concentration of aerosols — small solid particles suspended in the air — is high, the air becomes less transparent to light. Aerosols scatter light in many directions, and sometimes that means light is directed back down to the ground. The result is often a brighter night sky. Time-series photometry of the night sky shows changes in sky brightness that mirror changes in the atmospheric aerosol concentration.
For much of the year, our air is quite clear; that is, the aerosol concentration is relatively low. This is reflected in measurements of the aerosol optical depth (AOD), a number that characterizes the concentration of aerosol particles in terms of how much they attenuate the strength of a light ray passing through them. That number is sensitive to the wavelength of light, so it is often quoted with respect to some specified wavelength.
A NASA program called AERONET deploys AOD measurement devices around the world, one of which is located in Tucson. These devices measure AOD values for a number of fiducial wavelengths. On the clearest days, which often happen here in winter, the AOD numbers reach their minimum possible values. I tend to look specifically at the AOD value at 500 nanometers ("AOD_500") since that wavelength falls nearly in the middle of the visual spectrum. AOD_500 reaches a global minimum of around 0.020 on days like this.
In the late spring, we often see very windy days in southern Arizona. The wind pushes dust from the desert floor and lofts it to altitudes of up to a few thousand meters where it remains suspended for hours to days. The dust particles are made of very fine grains of mostly silicates with some organic matter mixed in. Very dusty days in spring can see AOD_500 values approaching 0.100.
Below are examples of these situations, very clear and and very dusty; notice the difference in the scales on the vertical axes of the two plots. The first is a particularly clear day in December 2019. On the night that followed this day, TESS-W stars19 reported a darkest reading of 20.47 magnitudes per square arcsecond at 5:25am local time — a typically dark reading near solar minimum. The second AERONET plot is for a dusty day in May 2020. On that night the darkest reading was about 0.1 magnitude brighter. All other things being equal, it's likely that the dust suspended in the air of the second night made for a brighter night sky (by about 10%).
The bottom line is that when the concentration of aerosols — small solid particles suspended in the air — is high, the air becomes less transparent to light. Aerosols scatter light in many directions, and sometimes that means light is directed back down to the ground. The result is often a brighter night sky. Time-series photometry of the night sky shows changes in sky brightness that mirror changes in the atmospheric aerosol concentration.
For much of the year, our air is quite clear; that is, the aerosol concentration is relatively low. This is reflected in measurements of the aerosol optical depth (AOD), a number that characterizes the concentration of aerosol particles in terms of how much they attenuate the strength of a light ray passing through them. That number is sensitive to the wavelength of light, so it is often quoted with respect to some specified wavelength.
A NASA program called AERONET deploys AOD measurement devices around the world, one of which is located in Tucson. These devices measure AOD values for a number of fiducial wavelengths. On the clearest days, which often happen here in winter, the AOD numbers reach their minimum possible values. I tend to look specifically at the AOD value at 500 nanometers ("AOD_500") since that wavelength falls nearly in the middle of the visual spectrum. AOD_500 reaches a global minimum of around 0.020 on days like this.
In the late spring, we often see very windy days in southern Arizona. The wind pushes dust from the desert floor and lofts it to altitudes of up to a few thousand meters where it remains suspended for hours to days. The dust particles are made of very fine grains of mostly silicates with some organic matter mixed in. Very dusty days in spring can see AOD_500 values approaching 0.100.
Below are examples of these situations, very clear and and very dusty; notice the difference in the scales on the vertical axes of the two plots. The first is a particularly clear day in December 2019. On the night that followed this day, TESS-W stars19 reported a darkest reading of 20.47 magnitudes per square arcsecond at 5:25am local time — a typically dark reading near solar minimum. The second AERONET plot is for a dusty day in May 2020. On that night the darkest reading was about 0.1 magnitude brighter. All other things being equal, it's likely that the dust suspended in the air of the second night made for a brighter night sky (by about 10%).
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The most extreme cases are when our daytime skies are dimmed by smoke from regional wildfires, something that's becoming more common during summer months. For several days in September 2020, Arizona was blanketed by thick smoke from forest fires in California. The 11th saw some of the worst smoke from the event. This is what it looked like in NOAA visible satellite imagery:
Instead of clear blue skies we experienced daytime skies ranging in color from white to gray to brown:
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The Sun was heavily extincted, especially when near the horizon.
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AOD was almost off the chart on these days. On the 11th, AOD_500 peaked at about 2.8 — some 140 times higher than on the clearest days.
These different aerosol conditions were very evident in the stars19 night-sky brightness data from these nights, shown below.
There are a few remarkable aspects of this plot. One is how very much brighter the September night with smoke (blue points) was compared to the clear night in December (magenta points). Near solar midnight (around 12:20am local time), the difference was -1.6 magnitudes, or a factor of almost 4.4 higher in brightness. Accounting for the differences in the length of the night between December and September, the difference is roughly constant between the two traces. Note, however, how variable the sky brightness is in September. The smoke is rarely anything approaching a uniform layer; rather, it comes in waves of varying density. If AOD values for the overnight hours were available, one would expect the sky brightness to vary more or less in lockstep with AOD.
The other notable feature of the plot is how similar the traces are for December and May (orange points) with one important difference. Notice how the traces mostly follow each other but diverge from about -3 to +1 hours relative to midnight, that is, from 8pm-1am local time. The December trace is darker during that time, but afterward (until the start of morning twilight in May) the traces come into alignment. The difference in the earlier hours shows that dust is pretty efficient at scattering the city lights and making the sky brighter. That is until a little after midnight, at which point quite a few lights are routinely turned off; see reference [5] below for more about that.
The other notable feature of the plot is how similar the traces are for December and May (orange points) with one important difference. Notice how the traces mostly follow each other but diverge from about -3 to +1 hours relative to midnight, that is, from 8pm-1am local time. The December trace is darker during that time, but afterward (until the start of morning twilight in May) the traces come into alignment. The difference in the earlier hours shows that dust is pretty efficient at scattering the city lights and making the sky brighter. That is until a little after midnight, at which point quite a few lights are routinely turned off; see reference [5] below for more about that.
References
1. Alarcon, M. R., Puig-Subirà, M., Serra-Ricart, M., Lemes-Perera, S., Mallorquín, M., & López, C. (2021). SG-WAS: A New Wireless Autonomous Night Sky Brightness Sensor. Sensors, Vol. 21, Issue 16, p. 5590. https://doi.org/10.3390/s21165590
2. Kocifaj, M., & Bará, S. (2020). Night-time monitoring of the aerosol content of the lower atmosphere by differential photometry of the anthropogenic skyglow. Monthly Notices of the Royal Astronomical Society: Letters, Vol. 500, Issue 1, pp. L47–L51. https://doi.org/10.1093/mnrasl/slaa181
3. Kocifaj, M., & Barentine, J. C. (2021). Air pollution mitigation can reduce the brightness of the night sky in and near cities. Scientific Reports, Vol. 11, Issue 1, Article 14622. https://doi.org/10.1038/s41598-021-94241-1
4. Wallner, S., & Kocifaj, M. (2023). Aerosol impact on light pollution in cities and their environment. Journal of Environmental Management, Vol. 335, p. 117534. https://doi.org/10.1016/j.jenvman.2023.117534
5. Barentine, J. C., Kundracik, F., Kocifaj, M., Sanders, J. C., Esquerdo, G. A., Dalton, A. M., Foott, B., Grauer, A., Tucker, S., & Kyba, C. C. M. (2020). Recovering the city street lighting fraction from skyglow measurements in a large-scale municipal dimming experiment. Journal of Quantitative Spectroscopy and Radiative Transfer, Vol. 253, p. 107120. https://doi.org/10.1016/j.jqsrt.2020.107120
2. Kocifaj, M., & Bará, S. (2020). Night-time monitoring of the aerosol content of the lower atmosphere by differential photometry of the anthropogenic skyglow. Monthly Notices of the Royal Astronomical Society: Letters, Vol. 500, Issue 1, pp. L47–L51. https://doi.org/10.1093/mnrasl/slaa181
3. Kocifaj, M., & Barentine, J. C. (2021). Air pollution mitigation can reduce the brightness of the night sky in and near cities. Scientific Reports, Vol. 11, Issue 1, Article 14622. https://doi.org/10.1038/s41598-021-94241-1
4. Wallner, S., & Kocifaj, M. (2023). Aerosol impact on light pollution in cities and their environment. Journal of Environmental Management, Vol. 335, p. 117534. https://doi.org/10.1016/j.jenvman.2023.117534
5. Barentine, J. C., Kundracik, F., Kocifaj, M., Sanders, J. C., Esquerdo, G. A., Dalton, A. M., Foott, B., Grauer, A., Tucker, S., & Kyba, C. C. M. (2020). Recovering the city street lighting fraction from skyglow measurements in a large-scale municipal dimming experiment. Journal of Quantitative Spectroscopy and Radiative Transfer, Vol. 253, p. 107120. https://doi.org/10.1016/j.jqsrt.2020.107120