aads

Is dust what’s dimming Tabby’s Star?

Artist’s concept of a hypothetical uneven ring of dust causing the mysterious dimming of the star KIC 8462852, also known as Boyajian’s Star or Tabby’s Star. Image via NASA/JPL-Caltech.

Have you been following the strange case of KIC 8462852, also known as Tabby’s Star? It’s a star that behaves like no other ever seen, whose weird and dramatic dips in brightness have caused some astronomers to speculate about a possible Dyson sphere or megastructure around the star, built by an advanced civilization with the goal of large-scale energy harvesting. The Kepler space telescope has seen Tabby’s Star dim up to 20 percent over a matter of days, but the star also has much subtler, longer-term enigmatic dimming trends, with one continuing today. A new study announced on October 4, 2017 suggests an uneven dust cloud moving around the star as the cause of the long-term dimming. No Dyson sphere needed! But is it true?

The astronomers who published the study point to a smoking gun. They say their observations – using the Spitzer and Swift space missions, as well as the Belgian AstroLAB IRIS observatory – found less dimming in the infrared light from the star than in its ultraviolet light. Their statement explained:

Any object larger than dust particles [such as the great beams and girders of a Dyson sphere] would dim all wavelengths of light equally when passing in front of Tabby’s Star.

Huan Meng at the University of Arizona, Tucson is lead author of the new study, which also has as co-author Tabetha Boyajian at Yale University. She is the astronomer for whom Tabby’s Star is named, and also made this star famous in a 2016 TEDTalk about it. The study is published in the peer-reviewed Astrophysical Journal. Meng said:

This pretty much rules out the alien megastructure theory, as that could not explain the wavelength-dependent dimming. We suspect, instead, there is a cloud of dust orbiting the star with a roughly 700-day orbital period.

Andrew Siemion, director of the Berkeley SETI Research Center, explains the megastructure theory of Tabby’s Star. In this theory, the dimming of the star is caused by an alien-built structure. Image via UC Berkley/EarthSky.

These astronomers statement explained why they consider their explanation – the idea that the dimming is caused by dust – the best one:

We experience the uniform dimming of light often in everyday life: If you go to the beach on a bright, sunny day and sit under an umbrella, the umbrella reduces the amount of sunlight hitting your eyes in all wavelengths. But if you wait for the sunset, the sun looks red because the blue and ultraviolet light is scattered away by tiny particles.The new study suggests the objects causing the long-period dimming of Tabby’s Star can be no more than a few micrometers in diameter (about one ten-thousandth of an inch).

They explained that they observed Tabby’s Star in ultraviolet using Swift, and in infrared using Spitzer, from January to December 2016. Supplementing the space telescopes, researchers also observed the star in visible light during the same period using AstroLAB IRIS, a public observatory with a 27-inch-wide (68 centimeter) reflecting telescope located near the Belgian village of Zillebeke. Their statement said:

Based on the strong ultraviolet dip, [we] determined the blocking particles must be bigger than interstellar dust, small grains that could be located anywhere between Earth and the star. Such small particles could not remain in orbit around the star because pressure from its starlight would drive them farther into space. Dust that orbits a star, called circumstellar dust, is not so small it would fly away, but also not big enough to uniformly block light in all wavelengths.

This is currently considered the best explanation, although others are possible.

In their study, these astronomers are addressing the long-term dimming of Tabby’s Star. They did not address the shorter-term dimming events that happened in three-day spurts in 2017. They also did not confront the mystery of the major 20-percent dips in brightness that Kepler observed while studying the Cygnus field of its primary mission.

In other words, more mysteries remain. But isn’t that always the case?

Artist’s concept of cascading comets around a distant star. Previous research suggested a swarm of comets may be to blame for the short-period dimming of Tabby’s Star. Comets are also one of the most common sources of dust that orbits stars, and so could also be related to the long-period dimming studied by Meng and colleagues. Image via NASA/JPL/Caltech/Vanderbilt University.

Bottom line: A new study published in the Astrophysical Journal on October 4 suggests dust as the source for the long-term dimming of Tabby’s Star. Other dimming trends remain unexplained.



from EarthSky http://ift.tt/2xgRjLe

Artist’s concept of a hypothetical uneven ring of dust causing the mysterious dimming of the star KIC 8462852, also known as Boyajian’s Star or Tabby’s Star. Image via NASA/JPL-Caltech.

Have you been following the strange case of KIC 8462852, also known as Tabby’s Star? It’s a star that behaves like no other ever seen, whose weird and dramatic dips in brightness have caused some astronomers to speculate about a possible Dyson sphere or megastructure around the star, built by an advanced civilization with the goal of large-scale energy harvesting. The Kepler space telescope has seen Tabby’s Star dim up to 20 percent over a matter of days, but the star also has much subtler, longer-term enigmatic dimming trends, with one continuing today. A new study announced on October 4, 2017 suggests an uneven dust cloud moving around the star as the cause of the long-term dimming. No Dyson sphere needed! But is it true?

The astronomers who published the study point to a smoking gun. They say their observations – using the Spitzer and Swift space missions, as well as the Belgian AstroLAB IRIS observatory – found less dimming in the infrared light from the star than in its ultraviolet light. Their statement explained:

Any object larger than dust particles [such as the great beams and girders of a Dyson sphere] would dim all wavelengths of light equally when passing in front of Tabby’s Star.

Huan Meng at the University of Arizona, Tucson is lead author of the new study, which also has as co-author Tabetha Boyajian at Yale University. She is the astronomer for whom Tabby’s Star is named, and also made this star famous in a 2016 TEDTalk about it. The study is published in the peer-reviewed Astrophysical Journal. Meng said:

This pretty much rules out the alien megastructure theory, as that could not explain the wavelength-dependent dimming. We suspect, instead, there is a cloud of dust orbiting the star with a roughly 700-day orbital period.

Andrew Siemion, director of the Berkeley SETI Research Center, explains the megastructure theory of Tabby’s Star. In this theory, the dimming of the star is caused by an alien-built structure. Image via UC Berkley/EarthSky.

These astronomers statement explained why they consider their explanation – the idea that the dimming is caused by dust – the best one:

We experience the uniform dimming of light often in everyday life: If you go to the beach on a bright, sunny day and sit under an umbrella, the umbrella reduces the amount of sunlight hitting your eyes in all wavelengths. But if you wait for the sunset, the sun looks red because the blue and ultraviolet light is scattered away by tiny particles.The new study suggests the objects causing the long-period dimming of Tabby’s Star can be no more than a few micrometers in diameter (about one ten-thousandth of an inch).

They explained that they observed Tabby’s Star in ultraviolet using Swift, and in infrared using Spitzer, from January to December 2016. Supplementing the space telescopes, researchers also observed the star in visible light during the same period using AstroLAB IRIS, a public observatory with a 27-inch-wide (68 centimeter) reflecting telescope located near the Belgian village of Zillebeke. Their statement said:

Based on the strong ultraviolet dip, [we] determined the blocking particles must be bigger than interstellar dust, small grains that could be located anywhere between Earth and the star. Such small particles could not remain in orbit around the star because pressure from its starlight would drive them farther into space. Dust that orbits a star, called circumstellar dust, is not so small it would fly away, but also not big enough to uniformly block light in all wavelengths.

This is currently considered the best explanation, although others are possible.

In their study, these astronomers are addressing the long-term dimming of Tabby’s Star. They did not address the shorter-term dimming events that happened in three-day spurts in 2017. They also did not confront the mystery of the major 20-percent dips in brightness that Kepler observed while studying the Cygnus field of its primary mission.

In other words, more mysteries remain. But isn’t that always the case?

Artist’s concept of cascading comets around a distant star. Previous research suggested a swarm of comets may be to blame for the short-period dimming of Tabby’s Star. Comets are also one of the most common sources of dust that orbits stars, and so could also be related to the long-period dimming studied by Meng and colleagues. Image via NASA/JPL/Caltech/Vanderbilt University.

Bottom line: A new study published in the Astrophysical Journal on October 4 suggests dust as the source for the long-term dimming of Tabby’s Star. Other dimming trends remain unexplained.



from EarthSky http://ift.tt/2xgRjLe

More applications of computed NMR spectra

In this post I cover two papers discussing application of computed NMR chemical shifts to structure identification and (yet) another review of computational techniques towards NMR structure prediction.

Grimblat, Kaufman, and Sarotti1 take up the structure of rubriflordilactone B 1, which was isolated from Schisandra rubriflora. The compound was then synthesized and its x-ray structure reported, however its NMR did not match with the natural extract. It was suggested that there were actually two compounds in the extract, the minor one was less soluble and is the crystallized 1, and a second compound responsible for the NMR signal.

The authors looked at all stereoisomers of this molecule keeping the three left-most rings intact. The low energy rotamers of these 32 stereoisomers were then optimized at B3LYP/6-31G* and the chemical shifts computed at PCM(pyridine)/mPW1PW91/6-31+G**. To benchmark the method, DP4+ was used to identify which stereoisomer best matches with the observed NMR of authentic 1; the top fit (92.6% probability) was the correct structure.

The 32 stereoisomers were then tested against the experimental NMR of the natural extract. DP4+ with just the proton shifts suggested structure 2 (99.8% probability); however, the 13C chemical shifts predicted a different structure. Re-examination of the reported chemical shifts identifies some mis-assigned signals, which led to a higher C-DP4+ prediction. When all 128 stereoisomers were tested, structure 2 had the highest DP4+ prediction (99.5%), but the C-DP4+ prediction remained problematic (10.8%). Analyzing the geometries of all reasonable alternative for agreement with the NOESY spectrum confirmed 2. These results underscore the importance of using all data sources.

Reddy and Kutateladze point out the importance of using coupling constants along with chemical shifts in structure identification.2 They examined cordycepol A 3, obtained from Cordyceps ophioglossoides. They noted that the computed chemical shifts and coupling constants of originally proposed structure 3a differed dramatically from the experimental values.

They first proposed that the compound has structure 3b. The computed coupling constants using their relativistic force field.3 The experimental coupling constants for the proton H1 are 13.4 and 7.1 Hz. The computed values for 3a are 8.9 and 1.6 Hz, and this structure is clearly incorrect. The coupling constants are improved with 3b, but the 13C chemical shifts are in poor agreement with experiment. So, they proposed structure 3c, the epimer at both C1 and C11 of the original structure.

They optimized four conformations of 3c at B3LYP/6-31G(d) and obtained Boltzmann-weighted chemical shifts at mPW1PW91/6-311+G(d,p). The RMS deviation of the computed 13C chemical shifts relative to the experiment is only 1.54 ppm, and more importantly, the computed coupling constants of 13.54 and 6.90 Hz are in excellent agreement with the experiment values.

Lastly, Grimblat and Sarotti present a review of a number of methods for using computed NMR chemical shifts towards structure prediction.4 These methods include CP3, DP4, DP4+ (all of which I have posted on in the past) and an artificial neural network approach of their own design. They discuss a number of interesting cases where each of these methods has been crucial in identifying the correct chemical structure.

References

1. Grimblat, N.; Kaufman, T. S.; Sarotti, A. M., "Computational Chemistry Driven Solution to Rubriflordilactone B." Org. Letters 2016, 18, 6420-6423, DOI: 10.1021/acs.orglett.6b03318.

2. Reddy, D. S.; Kutateladze, A. G., "Structure Revision of an Acorane Sesquiterpene Cordycepol A." Org. Letters 2016, 18, 4860-4863, DOI: 10.1021/acs.orglett.6b02341.

3. (a) Kutateladze, A. G.; Mukhina, O. A., "Minimalist Relativistic Force Field: Prediction of Proton–Proton Coupling Constants in 1H NMR Spectra Is Perfected with NBO Hybridization Parameters." J. Org. Chem. 2015, 80, 5218-5225, DOI: 10.1021/acs.joc.5b00619; (b) Kutateladze, A. G.; Mukhina, O. A., "Relativistic Force Field: Parametrization of 13C–1H Nuclear Spin–Spin Coupling Constants." J. Org. Chem. 2015, 80, 10838-10848, DOI: 10.1021/acs.joc.5b02001.

4. Grimblat, N.; Sarotti, A. M., "Computational Chemistry to the Rescue: Modern Toolboxes for the Assignment of Complex Molecules by GIAO NMR Calculations." Chem. Eur. J. 2016, 22, 12246-12261, DOI: h10.1002/chem.201601150.

InChIs

1: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19+,20-,21-,22+,24-,25-,28+/m0/s1
InChIKey=JGSLSHOXBXVVTQ-NEUKEVNNSA-N

2: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19-,20-,21-,22+,24+,25-,28+/m0/s1
InChIKey=JGSLSHOXBXVVTQ-WQIRXNRDSA-N

3c: InChI=1S/C16H28O2/c1-6-11(2)9-14-16(5)12(3)7-8-13(16)15(4,17)10-18-14/h9,12-14,17H,6-8,10H2,1-5H3/b11-9-/t12-,13-,14-,15-,16+/m0/s1
InChIKey=WPQIVUHVYBQTBG-AWEVENECSA-N



from Computational Organic Chemistry http://ift.tt/2xU0237

In this post I cover two papers discussing application of computed NMR chemical shifts to structure identification and (yet) another review of computational techniques towards NMR structure prediction.

Grimblat, Kaufman, and Sarotti1 take up the structure of rubriflordilactone B 1, which was isolated from Schisandra rubriflora. The compound was then synthesized and its x-ray structure reported, however its NMR did not match with the natural extract. It was suggested that there were actually two compounds in the extract, the minor one was less soluble and is the crystallized 1, and a second compound responsible for the NMR signal.

The authors looked at all stereoisomers of this molecule keeping the three left-most rings intact. The low energy rotamers of these 32 stereoisomers were then optimized at B3LYP/6-31G* and the chemical shifts computed at PCM(pyridine)/mPW1PW91/6-31+G**. To benchmark the method, DP4+ was used to identify which stereoisomer best matches with the observed NMR of authentic 1; the top fit (92.6% probability) was the correct structure.

The 32 stereoisomers were then tested against the experimental NMR of the natural extract. DP4+ with just the proton shifts suggested structure 2 (99.8% probability); however, the 13C chemical shifts predicted a different structure. Re-examination of the reported chemical shifts identifies some mis-assigned signals, which led to a higher C-DP4+ prediction. When all 128 stereoisomers were tested, structure 2 had the highest DP4+ prediction (99.5%), but the C-DP4+ prediction remained problematic (10.8%). Analyzing the geometries of all reasonable alternative for agreement with the NOESY spectrum confirmed 2. These results underscore the importance of using all data sources.

Reddy and Kutateladze point out the importance of using coupling constants along with chemical shifts in structure identification.2 They examined cordycepol A 3, obtained from Cordyceps ophioglossoides. They noted that the computed chemical shifts and coupling constants of originally proposed structure 3a differed dramatically from the experimental values.

They first proposed that the compound has structure 3b. The computed coupling constants using their relativistic force field.3 The experimental coupling constants for the proton H1 are 13.4 and 7.1 Hz. The computed values for 3a are 8.9 and 1.6 Hz, and this structure is clearly incorrect. The coupling constants are improved with 3b, but the 13C chemical shifts are in poor agreement with experiment. So, they proposed structure 3c, the epimer at both C1 and C11 of the original structure.

They optimized four conformations of 3c at B3LYP/6-31G(d) and obtained Boltzmann-weighted chemical shifts at mPW1PW91/6-311+G(d,p). The RMS deviation of the computed 13C chemical shifts relative to the experiment is only 1.54 ppm, and more importantly, the computed coupling constants of 13.54 and 6.90 Hz are in excellent agreement with the experiment values.

Lastly, Grimblat and Sarotti present a review of a number of methods for using computed NMR chemical shifts towards structure prediction.4 These methods include CP3, DP4, DP4+ (all of which I have posted on in the past) and an artificial neural network approach of their own design. They discuss a number of interesting cases where each of these methods has been crucial in identifying the correct chemical structure.

References

1. Grimblat, N.; Kaufman, T. S.; Sarotti, A. M., "Computational Chemistry Driven Solution to Rubriflordilactone B." Org. Letters 2016, 18, 6420-6423, DOI: 10.1021/acs.orglett.6b03318.

2. Reddy, D. S.; Kutateladze, A. G., "Structure Revision of an Acorane Sesquiterpene Cordycepol A." Org. Letters 2016, 18, 4860-4863, DOI: 10.1021/acs.orglett.6b02341.

3. (a) Kutateladze, A. G.; Mukhina, O. A., "Minimalist Relativistic Force Field: Prediction of Proton–Proton Coupling Constants in 1H NMR Spectra Is Perfected with NBO Hybridization Parameters." J. Org. Chem. 2015, 80, 5218-5225, DOI: 10.1021/acs.joc.5b00619; (b) Kutateladze, A. G.; Mukhina, O. A., "Relativistic Force Field: Parametrization of 13C–1H Nuclear Spin–Spin Coupling Constants." J. Org. Chem. 2015, 80, 10838-10848, DOI: 10.1021/acs.joc.5b02001.

4. Grimblat, N.; Sarotti, A. M., "Computational Chemistry to the Rescue: Modern Toolboxes for the Assignment of Complex Molecules by GIAO NMR Calculations." Chem. Eur. J. 2016, 22, 12246-12261, DOI: h10.1002/chem.201601150.

InChIs

1: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19+,20-,21-,22+,24-,25-,28+/m0/s1
InChIKey=JGSLSHOXBXVVTQ-NEUKEVNNSA-N

2: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19-,20-,21-,22+,24+,25-,28+/m0/s1
InChIKey=JGSLSHOXBXVVTQ-WQIRXNRDSA-N

3c: InChI=1S/C16H28O2/c1-6-11(2)9-14-16(5)12(3)7-8-13(16)15(4,17)10-18-14/h9,12-14,17H,6-8,10H2,1-5H3/b11-9-/t12-,13-,14-,15-,16+/m0/s1
InChIKey=WPQIVUHVYBQTBG-AWEVENECSA-N



from Computational Organic Chemistry http://ift.tt/2xU0237

Global climate impacts of a potential volcanic eruption of Mount Agung

Guest post by: 

Flavio Lehner (flehner@ucar.edu) and John Fasullo

National Center for Atmospheric Research, Boulder, CO, USA

An example of a stratovolcano eruption (note: not Mt. Agung). On July 13, 2015, the Operational Land Imager (OLI) on Landsat 8 took a close up of Mount Raung's summit caldera (on the Indonesian island of Java). Visible is afternoon cloud cover and an eruption plume. Image courtesy of NASA.

Recent weeks have seen an increase in the number of earthquakes happening below Mount Agung, a 9,944ft (3,031m) high volcano in eastern Bali, Indonesia. Authorities have evacuated nearly 50,000 people in the vicinity of the volcano in light of a potential eruption. In addition to concern for people’s lives and infrastructure, the tourism industry fears the potential for disrupted flight plans.

Mount Agung erupted last in 1963, killing over 1,000 people. As is common with large explosive eruptions, it also injected significant amounts of sulfur dioxide into the stratosphere (at least 16-18km above the surface). There, sulfur dioxide combined with water to form sulfuric acid aerosols. These aerosols reflect incoming solar radiation, causing cooling of the Earth’s climate. In fact, volcanic eruptions have been the most important external driver of interannual to decadal variability in global mean surface temperature for at least the past millennium1.

The cooling of global mean temperature from the 1963 eruption amounted to about 0.2 to 0.3°C, although it is difficult to precisely quantify from the noisy observational record where temperature variations unrelated to the volcanic eruption can occur simultaneously2. After such eruptions, global temperature eventually recovers to pre-eruption levels, but both the peak cooling and the recovery time depend on the magnitude and evolution of the eruption; that is, the amount of sulfur dioxide that is emitted and the duration of the eruption.

The second half of the 20th century has seen only two other large eruptions of comparable magnitude: El Chichón in 1982, and Pinatubo in 1991. As with the 1963 Agung eruption, all left significant imprints on climate, most prominently in global temperature but also in global ocean heat content and sea level3, the carbon cycle4, precipitation and streamflow5.

Scientists have been analyzing the precious data that emerged from these rare events for decades. For example, these eruptions serve as test beds for climate models and their ability to simulate the response to energy balance perturbations such as those arising from the reduced incoming solar radiation after volcanic eruptions6. However, it has been over 26 years since the last large eruption and the observing systems in place at that time were relatively primitive. Now, there are a number of new observing systems in place (most notably satellites such as the NASA A-Train and ARGO floats that measure ocean conditions at depth) that have never been tested during such an eruption. These systems could provide critical new measurements to improve our understanding of volcanic impacts on climate and the Earth system, which in turn will serve as an important test of climate models.

Coincidently, the three major eruptions since 1950 were contemporaneous with the warm phase of the El Niño-Southern Oscillation (ENSO), called El Niño events. During these natural events, large amounts of energy are redistributed from the tropical Pacific Ocean around the world, typically leading to a bump in global temperature of about +0.1 to 0.2°C.

While it remains debated whether volcanic eruptions themselves are able to trigger El Niño events, scientists recognized the tendency for volcanic cooling to be balanced by a warming El Niño event in the last about 60 years. Using climate models, such confounding effects have been estimated and removed7,8, revealing that when such effects are taken into account, climate models are significantly better at simulating the global temperature response to eruptions than was previously thought8.

So what should we expect global temperature to do if Mount Agung erupts again within the coming months? While the general forecasting of volcanic eruptions has improved greatly over recent decades – saving many lives like on Bali today – we still cannot predict when exactly an eruption will occur, what its strength will be, and how long it will last. These are all critical factors that determine the response of temperature and other climate aspects to a potential eruption and thus we cannot currently make reliable climate forecasts associated with it. We can think through possible scenarios, though.

The NOAA Climate Prediction Center in its latest ENSO forecast advisory (2nd October 2017) gave a 55-60% chance for the development of a La Niña during this coming winter. La Niña is the counterpart to El Niño and typically causes global mean temperature to be lower than it would be if ENSO conditions were neutral.

One scenario to think through could thus be a major eruption occurring during a La Niña this coming winter. Using the Community Earth System Model Large Ensemble9 (CESM) we can estimate, at least with a climate model, how much the volcanic cooling might be amplified through the coincidental occurrence of a La Niña. The CESM simulations consist of 40 historical simulations, all of which include a representation of the three volcanic eruptions as they occurred in 1963, 1982, and 1991. While imperfect, the CESM does a decent job of simulating the global mean temperature response to recent volcanic eruptions8. We then subsample the 40 historical simulations of the CESM according to whether the eruptions occurred during an El Niño or a La Niña.

Here we use the model information from all three late 20th Century eruptions even though Pinatubo and El Chichón are obviously located in different parts of the world, and erupted with somewhat different strength than Agung. However, they are all located in the tropics close to the Equator, which allows the sulfur dioxide injected into the stratosphere to spread easily across the hemisphere, thus maximizing its impact on global climate. Research has shown that the location and season of an eruption can also influence the characteristics of its climate impact, although decisively less than the eruption strength and duration10,11.

As expected, the CESM suggests that an eruption comparable in magnitude to the 1963 Mount Agung eruption occurring during a La Niña would lead to significantly more cooling than if ENSO neutral conditions coincided with it (Figure 1). Similarly, such an eruption would cool significantly less if it happened during an El Niño. The CESM on average suggests almost 0.3°C cooling for an eruption during a La Niña and less than 0.1°C during an El Niño.

The model also suggests that for an eruption of this strength, global temperature should return to pre-eruption levels within about 5 years, irrespective of which ENSO state prevails during the eruption (Figure 1).

 

Figure 1: (Left) Composite global mean surface temperature anomaly from the Community Earth System Model Large Ensemble (CESM) during the three volcanic eruptions Agung 1963, El Chichón 1982, and Pinatubo 1991. Anomalies are relative to the 5-year mean preceding the eruption. The CESM simulations have 40 members, yielding 120 simulations of the 3 eruptions. Once the 120 simulations are subsampled according to ENSO state during the eruption, they reveal how El Niños dampen and La Niñas exacerbate the volcanic cooling. Time series are filtered with a 1-2-1 filter, the shading shows 5-95% uncertainty range, the lines are the ensemble mean, and the blue and red bars indicate when the ‘El Niño’ and ‘La Niña’ cases differ significantly from the ‘All’ cases. (Right) Scenarios of annual mean global temperature evolution if an Agung­-like eruption occurred in 2017, constructed by adding the ensemble of temperature anomalies from the left panel to random ensemble members from CESM in 2017. Observations are from the Berkley Earth Surface Temperature (BEST) dataset.

These cooling estimates need to be kept in mind when we turn to other comparisons of climate models with reality. For example, in the heated debate over whether climate models are overestimating the global warming response to increased greenhouse gas concentrations, such nuances become important. CMIP5 and the last IPCC assessment were based on simulations that were forced, among other things, with observed volcanic eruptions up until 2005. At the time, that was all that was available and climate models did not therefore include volcanic eruptions after 2005. In reality, however, a number of smaller eruptions did occur after 2005 and thus caused some expected discrepancy with the model simulations12.

To address this issue, scientists are now producing climate projections that include hypothetical future volcanic eruptions, which enables us to answer more quantitatively the question of whether we should expect the effect of volcanic eruptions on climate to be different in a warmer future compared to the past13,14.

Current forecasts, whether statistical or dynamical, as to how warm the years 2017 and 2018 will be, would clearly be affected by a new eruption of Mount Agung (at least if it is similar in strength and duration to the three largest late 20th century eruptions). As illustrated in Figure 1, global temperatures within the next two years could easily drop as low as what they were in 2012 at the end of the infamous "global warming slowdown". Further, given the recovery time of global temperature after an eruption, some discrepancies with CMIP5 model projections until the beginning of the 2020s might also be expected.

This example also shows that global temperature, albeit popular, is not the most robust quantity to measure changes in Earth’s climate. Even absent a strong external forcing, global temperature can vary substantially from year to year, making it difficult to separate the signal from the noise in case of a volcanic eruption or increasing greenhouse gas concentrations. Instead, scientists propose to look at quantities such as global sea level or ocean heat content to take the pulse of our planet15. Those quantities integrate the response of the climate system over very large volumes, thus beating down the noise relative to the signal.

References

1. Schurer, A. P., Hegerl, G. C., Mann, M. E., Tett, S. F. B. & Phipps, S. J. Separating forced from chaotic climate variability over the past millennium. J. Clim. 26, 6954–6973 (2013).

2. Thompson, D. W. J., Wallace, J. M., Jones, P. D. & Kennedy, J. J. Identifying signatures of natural climate variability in time series of global-mean surface temperature: Methodology and insights. J. Clim. 22, 6120–6141 (2009).

3. Fasullo, J. T., Nerem, R. S. & Hamlington, B. Is the detection of accelerated sea level rise imminent? Sci. Rep. 6, 31245 (2016).

4. Frölicher, T. L., Joos, F., Raible, C. C. & Sarmiento, J. L. Atmospheric CO2 response to volcanic eruptions: The role of ENSO, season, and variability. Global Biogeochem. Cycles 27, 239–251 (2013).

5. Iles, C. E. & Hegerl, G. C. Systematic change in global patterns of streamflow following volcanic eruptions. Nat. Geosci. 8, 838–842 (2015).

6. Hansen, J., Wang, W. & Lacis, A. Mount Agung Eruption Provides Test of a Global Climatic Perturbation. Science 199, 1065–1068 (1978).

7. Kirchner, I. & Graf, H.-F. Volcanos and El Niño: signal separation in Northern Hemisphere winter. Climate Dynamics 11, 341–358 (1995).

8. Lehner, F., Schurer, A. P., Hegerl, G. C., Deser, C. & Frölicher, T. L. The importance of ENSO phase during volcanic eruptions for detection and attribution. Geophysical Research Letters (2016). doi:10.1002/2016GL067935

9. Kay, J. E. et al. The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability. Bull. Am. Meteorol. Soc. 141119125353005 (2014). doi:10.1175/BAMS-D-13-00255.1

10. Colose, C. M., LeGrande, A. N. & Vuille, M. Hemispherically asymmetric volcanic forcing of tropical hydroclimate during the last millennium. Earth Syst. Dyn. 7, 681–696 (2016).

11. Stevenson, S., Fasullo, J. T., Otto-Bliesner, B. L., Tomas, R. A. & Gao, C. Role of eruption season in reconciling model and proxy responses to tropical volcanism. Proc. Natl. Acad. Sci. 114, 201612505 (2017).

12. Santer, B. D. et al. Volcanic contribution to decadal changes in tropospheric temperature. Nat. Geosci. 7, 185–189 (2014).

13. Bethke, I. et al. Potential volcanic impacts on future climate variability. Nat. Clim. Chang. (2017). doi:10.1038/nclimate3394

14. Fasullo, J. T. et al. The Amplifying Influence of Increased Ocean Stratification on A Future Year Without A Summer. Nat. Commun. (2017).

15. Cheng, L. et al. Taking the pulse of the planet. Eos (Washington. DC). 98, (2017).

 



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Guest post by: 

Flavio Lehner (flehner@ucar.edu) and John Fasullo

National Center for Atmospheric Research, Boulder, CO, USA

An example of a stratovolcano eruption (note: not Mt. Agung). On July 13, 2015, the Operational Land Imager (OLI) on Landsat 8 took a close up of Mount Raung's summit caldera (on the Indonesian island of Java). Visible is afternoon cloud cover and an eruption plume. Image courtesy of NASA.

Recent weeks have seen an increase in the number of earthquakes happening below Mount Agung, a 9,944ft (3,031m) high volcano in eastern Bali, Indonesia. Authorities have evacuated nearly 50,000 people in the vicinity of the volcano in light of a potential eruption. In addition to concern for people’s lives and infrastructure, the tourism industry fears the potential for disrupted flight plans.

Mount Agung erupted last in 1963, killing over 1,000 people. As is common with large explosive eruptions, it also injected significant amounts of sulfur dioxide into the stratosphere (at least 16-18km above the surface). There, sulfur dioxide combined with water to form sulfuric acid aerosols. These aerosols reflect incoming solar radiation, causing cooling of the Earth’s climate. In fact, volcanic eruptions have been the most important external driver of interannual to decadal variability in global mean surface temperature for at least the past millennium1.

The cooling of global mean temperature from the 1963 eruption amounted to about 0.2 to 0.3°C, although it is difficult to precisely quantify from the noisy observational record where temperature variations unrelated to the volcanic eruption can occur simultaneously2. After such eruptions, global temperature eventually recovers to pre-eruption levels, but both the peak cooling and the recovery time depend on the magnitude and evolution of the eruption; that is, the amount of sulfur dioxide that is emitted and the duration of the eruption.

The second half of the 20th century has seen only two other large eruptions of comparable magnitude: El Chichón in 1982, and Pinatubo in 1991. As with the 1963 Agung eruption, all left significant imprints on climate, most prominently in global temperature but also in global ocean heat content and sea level3, the carbon cycle4, precipitation and streamflow5.

Scientists have been analyzing the precious data that emerged from these rare events for decades. For example, these eruptions serve as test beds for climate models and their ability to simulate the response to energy balance perturbations such as those arising from the reduced incoming solar radiation after volcanic eruptions6. However, it has been over 26 years since the last large eruption and the observing systems in place at that time were relatively primitive. Now, there are a number of new observing systems in place (most notably satellites such as the NASA A-Train and ARGO floats that measure ocean conditions at depth) that have never been tested during such an eruption. These systems could provide critical new measurements to improve our understanding of volcanic impacts on climate and the Earth system, which in turn will serve as an important test of climate models.

Coincidently, the three major eruptions since 1950 were contemporaneous with the warm phase of the El Niño-Southern Oscillation (ENSO), called El Niño events. During these natural events, large amounts of energy are redistributed from the tropical Pacific Ocean around the world, typically leading to a bump in global temperature of about +0.1 to 0.2°C.

While it remains debated whether volcanic eruptions themselves are able to trigger El Niño events, scientists recognized the tendency for volcanic cooling to be balanced by a warming El Niño event in the last about 60 years. Using climate models, such confounding effects have been estimated and removed7,8, revealing that when such effects are taken into account, climate models are significantly better at simulating the global temperature response to eruptions than was previously thought8.

So what should we expect global temperature to do if Mount Agung erupts again within the coming months? While the general forecasting of volcanic eruptions has improved greatly over recent decades – saving many lives like on Bali today – we still cannot predict when exactly an eruption will occur, what its strength will be, and how long it will last. These are all critical factors that determine the response of temperature and other climate aspects to a potential eruption and thus we cannot currently make reliable climate forecasts associated with it. We can think through possible scenarios, though.

The NOAA Climate Prediction Center in its latest ENSO forecast advisory (2nd October 2017) gave a 55-60% chance for the development of a La Niña during this coming winter. La Niña is the counterpart to El Niño and typically causes global mean temperature to be lower than it would be if ENSO conditions were neutral.

One scenario to think through could thus be a major eruption occurring during a La Niña this coming winter. Using the Community Earth System Model Large Ensemble9 (CESM) we can estimate, at least with a climate model, how much the volcanic cooling might be amplified through the coincidental occurrence of a La Niña. The CESM simulations consist of 40 historical simulations, all of which include a representation of the three volcanic eruptions as they occurred in 1963, 1982, and 1991. While imperfect, the CESM does a decent job of simulating the global mean temperature response to recent volcanic eruptions8. We then subsample the 40 historical simulations of the CESM according to whether the eruptions occurred during an El Niño or a La Niña.

Here we use the model information from all three late 20th Century eruptions even though Pinatubo and El Chichón are obviously located in different parts of the world, and erupted with somewhat different strength than Agung. However, they are all located in the tropics close to the Equator, which allows the sulfur dioxide injected into the stratosphere to spread easily across the hemisphere, thus maximizing its impact on global climate. Research has shown that the location and season of an eruption can also influence the characteristics of its climate impact, although decisively less than the eruption strength and duration10,11.

As expected, the CESM suggests that an eruption comparable in magnitude to the 1963 Mount Agung eruption occurring during a La Niña would lead to significantly more cooling than if ENSO neutral conditions coincided with it (Figure 1). Similarly, such an eruption would cool significantly less if it happened during an El Niño. The CESM on average suggests almost 0.3°C cooling for an eruption during a La Niña and less than 0.1°C during an El Niño.

The model also suggests that for an eruption of this strength, global temperature should return to pre-eruption levels within about 5 years, irrespective of which ENSO state prevails during the eruption (Figure 1).

 

Figure 1: (Left) Composite global mean surface temperature anomaly from the Community Earth System Model Large Ensemble (CESM) during the three volcanic eruptions Agung 1963, El Chichón 1982, and Pinatubo 1991. Anomalies are relative to the 5-year mean preceding the eruption. The CESM simulations have 40 members, yielding 120 simulations of the 3 eruptions. Once the 120 simulations are subsampled according to ENSO state during the eruption, they reveal how El Niños dampen and La Niñas exacerbate the volcanic cooling. Time series are filtered with a 1-2-1 filter, the shading shows 5-95% uncertainty range, the lines are the ensemble mean, and the blue and red bars indicate when the ‘El Niño’ and ‘La Niña’ cases differ significantly from the ‘All’ cases. (Right) Scenarios of annual mean global temperature evolution if an Agung­-like eruption occurred in 2017, constructed by adding the ensemble of temperature anomalies from the left panel to random ensemble members from CESM in 2017. Observations are from the Berkley Earth Surface Temperature (BEST) dataset.

These cooling estimates need to be kept in mind when we turn to other comparisons of climate models with reality. For example, in the heated debate over whether climate models are overestimating the global warming response to increased greenhouse gas concentrations, such nuances become important. CMIP5 and the last IPCC assessment were based on simulations that were forced, among other things, with observed volcanic eruptions up until 2005. At the time, that was all that was available and climate models did not therefore include volcanic eruptions after 2005. In reality, however, a number of smaller eruptions did occur after 2005 and thus caused some expected discrepancy with the model simulations12.

To address this issue, scientists are now producing climate projections that include hypothetical future volcanic eruptions, which enables us to answer more quantitatively the question of whether we should expect the effect of volcanic eruptions on climate to be different in a warmer future compared to the past13,14.

Current forecasts, whether statistical or dynamical, as to how warm the years 2017 and 2018 will be, would clearly be affected by a new eruption of Mount Agung (at least if it is similar in strength and duration to the three largest late 20th century eruptions). As illustrated in Figure 1, global temperatures within the next two years could easily drop as low as what they were in 2012 at the end of the infamous "global warming slowdown". Further, given the recovery time of global temperature after an eruption, some discrepancies with CMIP5 model projections until the beginning of the 2020s might also be expected.

This example also shows that global temperature, albeit popular, is not the most robust quantity to measure changes in Earth’s climate. Even absent a strong external forcing, global temperature can vary substantially from year to year, making it difficult to separate the signal from the noise in case of a volcanic eruption or increasing greenhouse gas concentrations. Instead, scientists propose to look at quantities such as global sea level or ocean heat content to take the pulse of our planet15. Those quantities integrate the response of the climate system over very large volumes, thus beating down the noise relative to the signal.

References

1. Schurer, A. P., Hegerl, G. C., Mann, M. E., Tett, S. F. B. & Phipps, S. J. Separating forced from chaotic climate variability over the past millennium. J. Clim. 26, 6954–6973 (2013).

2. Thompson, D. W. J., Wallace, J. M., Jones, P. D. & Kennedy, J. J. Identifying signatures of natural climate variability in time series of global-mean surface temperature: Methodology and insights. J. Clim. 22, 6120–6141 (2009).

3. Fasullo, J. T., Nerem, R. S. & Hamlington, B. Is the detection of accelerated sea level rise imminent? Sci. Rep. 6, 31245 (2016).

4. Frölicher, T. L., Joos, F., Raible, C. C. & Sarmiento, J. L. Atmospheric CO2 response to volcanic eruptions: The role of ENSO, season, and variability. Global Biogeochem. Cycles 27, 239–251 (2013).

5. Iles, C. E. & Hegerl, G. C. Systematic change in global patterns of streamflow following volcanic eruptions. Nat. Geosci. 8, 838–842 (2015).

6. Hansen, J., Wang, W. & Lacis, A. Mount Agung Eruption Provides Test of a Global Climatic Perturbation. Science 199, 1065–1068 (1978).

7. Kirchner, I. & Graf, H.-F. Volcanos and El Niño: signal separation in Northern Hemisphere winter. Climate Dynamics 11, 341–358 (1995).

8. Lehner, F., Schurer, A. P., Hegerl, G. C., Deser, C. & Frölicher, T. L. The importance of ENSO phase during volcanic eruptions for detection and attribution. Geophysical Research Letters (2016). doi:10.1002/2016GL067935

9. Kay, J. E. et al. The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability. Bull. Am. Meteorol. Soc. 141119125353005 (2014). doi:10.1175/BAMS-D-13-00255.1

10. Colose, C. M., LeGrande, A. N. & Vuille, M. Hemispherically asymmetric volcanic forcing of tropical hydroclimate during the last millennium. Earth Syst. Dyn. 7, 681–696 (2016).

11. Stevenson, S., Fasullo, J. T., Otto-Bliesner, B. L., Tomas, R. A. & Gao, C. Role of eruption season in reconciling model and proxy responses to tropical volcanism. Proc. Natl. Acad. Sci. 114, 201612505 (2017).

12. Santer, B. D. et al. Volcanic contribution to decadal changes in tropospheric temperature. Nat. Geosci. 7, 185–189 (2014).

13. Bethke, I. et al. Potential volcanic impacts on future climate variability. Nat. Clim. Chang. (2017). doi:10.1038/nclimate3394

14. Fasullo, J. T. et al. The Amplifying Influence of Increased Ocean Stratification on A Future Year Without A Summer. Nat. Commun. (2017).

15. Cheng, L. et al. Taking the pulse of the planet. Eos (Washington. DC). 98, (2017).

 



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Marines Corps Evaluates Virtual Decision Kit to Supplement Training

The Marine Corps has developed a technology that allows Marines and Sailors to train virtually on or off duty, and test their decision-making skills from the barracks.

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The Marine Corps has developed a technology that allows Marines and Sailors to train virtually on or off duty, and test their decision-making skills from the barracks.

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International Observe the Moon Night

Image via InOMN.

NASA’s Lunar Reconnaissance Orbiter – with support from NASA’s Solar System Exploration Research Virtual Institute (SSERVI) and the Lunar and Planetary Institute – are sponsoring an International Observe the Moon Night (InOMN) on October 28, 2017. Go to the InOMN website to find information about how to host, register, and evaluate your InOMN event, look for an InOMN event near you, and share pictures and highlights from InOMN. The website says it’s:

… an annual worldwide public event that encourages observation, appreciation, and understanding of our moon and its connection to NASA planetary science and exploration, as well as the cultural and personal connections we all have with Earth’s nearest neighbor. Everyone on Earth is invited to join the celebration by hosting or attending an InOMN event — and uniting on one day each year to look at and learn about the moon together …

In 2017, we are encouraging an eclipse-focus for the event, celebrating the total solar eclipse that crossed the United States in August, a lunar eclipse that will occur in January, and past and future eclipses visible around the world …

Though we encourage everyone to participate in International Observe the Moon Night on a specified day each year, we understand that this date may not work for everyone. If it does not work for you this year, you are welcome to host your event on a different day, as close to October 28 as possible.

Click here to register your event for International Observe the Moon Night

Go to the event’s website to look for an InOMN event near you

Moon phase on October 28, 2017 (waxing gibbous). Generate an image of how the moon’s phase will appear from the Northern Hemisphere, or Southern Hemisphere, on any day in 2017 using the Scientific Visualization Studio’s Dial-a-Moon online app. Image via InOMN.

Bottom line: Info about International Observe the Moon Night 2017.

EarthSky tees are back! Learn how your purchase helps support worthy causes, and use code ESFRIENDS for $5 off.



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Image via InOMN.

NASA’s Lunar Reconnaissance Orbiter – with support from NASA’s Solar System Exploration Research Virtual Institute (SSERVI) and the Lunar and Planetary Institute – are sponsoring an International Observe the Moon Night (InOMN) on October 28, 2017. Go to the InOMN website to find information about how to host, register, and evaluate your InOMN event, look for an InOMN event near you, and share pictures and highlights from InOMN. The website says it’s:

… an annual worldwide public event that encourages observation, appreciation, and understanding of our moon and its connection to NASA planetary science and exploration, as well as the cultural and personal connections we all have with Earth’s nearest neighbor. Everyone on Earth is invited to join the celebration by hosting or attending an InOMN event — and uniting on one day each year to look at and learn about the moon together …

In 2017, we are encouraging an eclipse-focus for the event, celebrating the total solar eclipse that crossed the United States in August, a lunar eclipse that will occur in January, and past and future eclipses visible around the world …

Though we encourage everyone to participate in International Observe the Moon Night on a specified day each year, we understand that this date may not work for everyone. If it does not work for you this year, you are welcome to host your event on a different day, as close to October 28 as possible.

Click here to register your event for International Observe the Moon Night

Go to the event’s website to look for an InOMN event near you

Moon phase on October 28, 2017 (waxing gibbous). Generate an image of how the moon’s phase will appear from the Northern Hemisphere, or Southern Hemisphere, on any day in 2017 using the Scientific Visualization Studio’s Dial-a-Moon online app. Image via InOMN.

Bottom line: Info about International Observe the Moon Night 2017.

EarthSky tees are back! Learn how your purchase helps support worthy causes, and use code ESFRIENDS for $5 off.



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Watch ISS spacewalk October 5

In this May 2017 photo, NASA astronaut Jack Fischer works outside the U.S. Destiny laboratory module of the International Space Station. Image via NASA.

EarthSky tees are back! Learn how your purchase helps support worthy causes, and use code ESFRIENDS for $5 off.

On Thursday (October 5, 2017) three American astronauts aboard the International Space Station (ISS) will perform the first of a trio of spacewalks in October. The other spacewalks are scheduled for October 10 and 18.

NASA TV coverage of Thursday’s spacewalk will begin at 6:30 a.m. EDT (10:30 UTC) and the spacewalk itself is scheduled to start at approximately 8:05 a.m. EDT (12:05 UTC); however, the spacewalks might begin earlier if the crew is running ahead of schedule. Translate to your timezone.

Watch here.

Expedition 53 Commander Randy Bresnik of NASA will lead all three spacewalks, joined on October 5 and 10 by Flight Engineer Mark Vande Hei, also of NASA. Flight Engineer Joe Acaba of NASA will join Bresnik on October 18 for the third spacewalk.

The goal of the spacewalks is to perform station maintenance. According to a NASA statement:

During the first spacewalk, Bresnik and Vande Hei will replace one of two Latching End Effectors (LEE) on the station’s robotic arm, Canadarm2. One of the Canadarm2 grappling mechanisms experienced a stall of its motorized latches last month, but the problem has had no effect on planned station operations. A spare LEE is stored outside on the station’s truss. Canadarm2 has two identical Latching End Effectors used to grapple visiting cargo vehicles and payloads, provide data and telemetry to the rest of the Canadian-built Mobile Base System and the unique capability to “walk” from one location on the station’s truss to another.

The second and third spacewalks will be devoted to lubricating the newly replaced Canadarm2 end effector and replacing cameras on the left side of the station’s truss and the right side of the station’s U.S. Destiny laboratory.

Bottom line: Three ISS spacewalks are scheduled for October 2017. How to watch.

Read more from NASA



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In this May 2017 photo, NASA astronaut Jack Fischer works outside the U.S. Destiny laboratory module of the International Space Station. Image via NASA.

EarthSky tees are back! Learn how your purchase helps support worthy causes, and use code ESFRIENDS for $5 off.

On Thursday (October 5, 2017) three American astronauts aboard the International Space Station (ISS) will perform the first of a trio of spacewalks in October. The other spacewalks are scheduled for October 10 and 18.

NASA TV coverage of Thursday’s spacewalk will begin at 6:30 a.m. EDT (10:30 UTC) and the spacewalk itself is scheduled to start at approximately 8:05 a.m. EDT (12:05 UTC); however, the spacewalks might begin earlier if the crew is running ahead of schedule. Translate to your timezone.

Watch here.

Expedition 53 Commander Randy Bresnik of NASA will lead all three spacewalks, joined on October 5 and 10 by Flight Engineer Mark Vande Hei, also of NASA. Flight Engineer Joe Acaba of NASA will join Bresnik on October 18 for the third spacewalk.

The goal of the spacewalks is to perform station maintenance. According to a NASA statement:

During the first spacewalk, Bresnik and Vande Hei will replace one of two Latching End Effectors (LEE) on the station’s robotic arm, Canadarm2. One of the Canadarm2 grappling mechanisms experienced a stall of its motorized latches last month, but the problem has had no effect on planned station operations. A spare LEE is stored outside on the station’s truss. Canadarm2 has two identical Latching End Effectors used to grapple visiting cargo vehicles and payloads, provide data and telemetry to the rest of the Canadian-built Mobile Base System and the unique capability to “walk” from one location on the station’s truss to another.

The second and third spacewalks will be devoted to lubricating the newly replaced Canadarm2 end effector and replacing cameras on the left side of the station’s truss and the right side of the station’s U.S. Destiny laboratory.

Bottom line: Three ISS spacewalks are scheduled for October 2017. How to watch.

Read more from NASA



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Goodbye to the dark side

This view looks toward the sunlit side of the rings from about 7 degrees above the ring plane. The image was taken in visible light with the wide-angle camera on NASA’s Cassini spacecraft on June 7, 2017, at a distance of approximately 751,000 miles (1.21 million kilometers) from Saturn. Image via NASA/JPL-Caltech/Space Science Institute.

Views of planet Saturn’s night side, like the image above, are only possible thanks to spacecraft emissaries like Cassini – whose mission ended on September 15, 2017 with an intentional dive into Saturn. That’s because Earth is closer to the sun than Saturn, so observers here on Earth only see Saturn’s day side. With spacecraft, we can capture views (and data) that simply aren’t possible from Earth, even with the largest telescopes.

EarthSky tees are back! Learn how your purchase helps support worthy causes, and use code ESFRIENDS for $5 off.

Bottom line: Image of Saturn’s dark side, taken by the Cassini spacecraft.

Read more from NASA



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This view looks toward the sunlit side of the rings from about 7 degrees above the ring plane. The image was taken in visible light with the wide-angle camera on NASA’s Cassini spacecraft on June 7, 2017, at a distance of approximately 751,000 miles (1.21 million kilometers) from Saturn. Image via NASA/JPL-Caltech/Space Science Institute.

Views of planet Saturn’s night side, like the image above, are only possible thanks to spacecraft emissaries like Cassini – whose mission ended on September 15, 2017 with an intentional dive into Saturn. That’s because Earth is closer to the sun than Saturn, so observers here on Earth only see Saturn’s day side. With spacecraft, we can capture views (and data) that simply aren’t possible from Earth, even with the largest telescopes.

EarthSky tees are back! Learn how your purchase helps support worthy causes, and use code ESFRIENDS for $5 off.

Bottom line: Image of Saturn’s dark side, taken by the Cassini spacecraft.

Read more from NASA



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adds 2