Reconstructing Spectral Scenes using Statistical Estimation to Enhance Space Situational Awareness

A new sensor, the Advanced Electro-Optical System (AEOS) Spectral Imaging Sensor (ASIS) has been developed at the Maui Space Surveillance Complex (MSSC). ASIS is capable of collecting resolved imagery of space objects in 10\u27s-100\u27s of spectral bands while using an adaptive optics system. However, the stringent requirements of collecting ground-based images requires a sensor that induces spectral blurring. Post-processing algorithms to remove this blurring are required to fully exploit these spectral images. This research focuses on developing the reconstruction algorithms, based on proven estimation theories, required to spectrally deblur the images collected from ASIS. Additionally, the research will expand the algorithm to also estimate the linear polarizations of the scene. The Cramer-Rao lower bounds on two key performance parameters, the spectral resolution and accuracy, of the reconstruction algorithm will also be calculated. Through the examination of these lower bounds a performance metric can be determined. This metric can be used to compare the ability of the algorithm to work on different spectral sensors

Unequal a priori Probability Multiple Hypothesis Testing in Space Domain Awareness with the Space Surveillance Telescope

This paper investigates the ability to improve Space Domain Awareness (SDA) by increasing the number of detectable Resident Space Objects (RSOs) from space surveillance sensors. With matched filter based techniques, the expected impulse response, or Point Spread Function (PSF), is compared against the received data. In the situation where the images are spatially undersampled, the modeled PSF may not match the received data if the RSO does not fall in the center of the pixel. This aliasing can be accounted for with a Multiple Hypothesis Test (MHT). Previously, proposed MHTs have implemented a test with an equal a priori prior probability assumption. This paper investigates using an unequal a priori probability MHT. To determine accurate a priori probabilities, three metrics are computed; they are correlation, physical distance, and empirical. Using the calculated a priori probabilities, a new algorithm is developed, and images from the Space Surveillance Telescope (SST) are analyzed. The number of detected objects by both an equal and unequal prior probabilities are compared while keeping the false alarm rate constant. Any additional number of detected objects will help improve SDA capabilities. Abstract © 2016 Optical Society of Americ

Detection of Water Vapor in the Thermal Spectrum of the Non-Transiting Hot Jupiter upsilon Andromedae b

The upsilon Andromedae system was the first multi-planet system discovered orbiting a main sequence star. We describe the detection of water vapor in the atmosphere of the innermost non-transiting gas giant ups~And~b by treating the star-planet system as a spectroscopic binary with high-resolution, ground-based spectroscopy. We resolve the signal of the planet's motion and break the mass-inclination degeneracy for this non-transiting planet via deep combined flux observations of the star and the planet. In total, seven epochs of Keck NIRSPEC $L$ band observations, three epochs of Keck NIRSPEC short wavelength $K$ band observations, and three epochs of Keck NIRSPEC long wavelength $K$ band observations of the ups~And~system were obtained. We perform a multi-epoch cross correlation of the full data set with an atmospheric model. We measure the radial projection of the Keplerian velocity ($K_P$ = 55 $\pm$ 9 km/s), true mass ($M_b$ = 1.7 $^{+0.33}_{-0.24}$ $M_J$), and orbital inclination \big($i_b$ = 24 $\pm$ 4$^{\circ}$\big), and determine that the planet's opacity structure is dominated by water vapor at the probed wavelengths. Dynamical simulations of the planets in the ups~And~system with these orbital elements for ups~And~b show that stable, long-term (100 Myr) orbital configurations exist. These measurements will inform future studies of the stability and evolution of the ups~And~system, as well as the atmospheric structure and composition of the hot Jupiter.Comment: Accepted to A

Ground- and Space-based Detection of the Thermal Emission Spectrum of the Transiting Hot Jupiter KELT-2Ab

We describe the detection of water vapor in the atmosphere of the transiting hot Jupiter KELT-2Ab by treating the star-planet system as a spectroscopic binary with high-resolution, ground-based spectroscopy. We resolve the signal of the planet's motion with deep combined flux observations of the star and the planet. In total, six epochs of Keck NIRSPEC $L$-band observations were obtained, and the full data set was subjected to a cross correlation analysis with a grid of self-consistent atmospheric models. We measure a radial projection of the Keplerian velocity, $K_P$, of 148 $\pm$ 7 km s$^{-1}$, consistent with transit measurements, and detect water vapor at 3.8$\sigma$. We combine NIRSPEC $L$-band data with $Spitzer$ IRAC secondary eclipse data to further probe the metallicity and carbon-to-oxygen ratio of KELT-2Ab's atmosphere. While the NIRSPEC analysis provides few extra constraints on the $Spitzer$ data, it does provide roughly the same constraints on metallicity and carbon-to-oxygen ratio. This bodes well for future investigations of the atmospheres of non-transiting hot Jupiters.Comment: accepted to A

Evidence for the Direct Detection of the Thermal Spectrum of the Non-Transiting Hot Gas Giant HD 88133 b

We target the thermal emission spectrum of the non-transiting gas giant HD 88133 b with high-resolution near-infrared spectroscopy, by treating the planet and its host star as a spectroscopic binary. For sufficiently deep summed flux observations of the star and planet across multiple epochs, it is possible to resolve the signal of the hot gas giant's atmosphere compared to the brighter stellar spectrum, at a level consistent with the aggregate shot noise of the full data set. To do this, we first perform a principal component analysis to remove the contribution of the Earth's atmosphere to the observed spectra. Then, we use a cross-correlation analysis to tease out the spectra of the host star and HD 88133 b to determine its orbit and identify key sources of atmospheric opacity. In total, six epochs of Keck NIRSPEC L band observations and three epochs of Keck NIRSPEC K band observations of the HD 88133 system were obtained. Based on an analysis of the maximum likelihood curves calculated from the multi-epoch cross correlation of the full data set with two atmospheric models, we report the direct detection of the emission spectrum of the non-transiting exoplanet HD 88133 b and measure a radial projection of the Keplerian orbital velocity of 40 $\pm$ 15 km/s, a true mass of 1.02$^{+0.61}_{-0.28}M_J$, a nearly face-on orbital inclination of 15${^{+6}_{-5}}^{\circ}$, and an atmosphere opacity structure at high dispersion dominated by water vapor. This, combined with eleven years of radial velocity measurements of the system, provides the most up-to-date ephemeris for HD 88133.Comment: 9 pages, 6 figures; accepted for publication in Ap

Near-IR Direct Detection of Water Vapor in Tau Boötis b

We use high dynamic range, high-resolution L-band spectroscopy to measure the radial velocity (RV) variations of the hot Jupiter in the τ Boötis planetary system. The detection of an exoplanet by the shift in the stellar spectrum alone provides a measure of the planet's minimum mass, with the true mass degenerate with the unknown orbital inclination. Treating the τ Boo system as a high flux ratio double-lined spectroscopic binary permits the direct measurement of the planet's true mass as well as its atmospheric properties. After removing telluric absorption and cross-correlating with a model planetary spectrum dominated by water opacity, we measure a 6σ detection of the planet at K_p = 111 ± 5 km s^(−1), with a 1σ upper limit on the spectroscopic flux ratio of 10^(−4). This RV leads to a planetary orbital inclination of i=45^(+3)_(-4)° and a mass of M_p = 5.90^(+0.35)_(-0.20)M_Jup. We report the first detection of water vapor in the atmosphere of a non-transiting hot Jupiter, τ Boo b

Evidence for the Direct Detection of the Thermal Spectrum of the Non-Transiting Hot Gas Giant HD 88133 b

We target the thermal emission spectrum of the non-transiting gas giant HD 88133 b with high-resolution near-infrared spectroscopy, by treating the planet and its host star as a spectroscopic binary. For sufficiently deep summed flux observations of the star and planet across multiple epochs, it is possible to resolve the signal of the hot gas giant's atmosphere compared to the brighter stellar spectrum, at a level consistent with the aggregate shot noise of the full data set. To do this, we first perform a principal component analysis to remove the contribution of the Earth's atmosphere to the observed spectra. Then, we use a cross-correlation analysis to tease out the spectra of the host star and HD 88133 b to determine its orbit and identify key sources of atmospheric opacity. In total, six epochs of Keck NIRSPEC L-band observations and three epochs of Keck NIRSPEC K-band observations of the HD 88133 system were obtained. Based on an analysis of the maximum likelihood curves calculated from the multi-epoch cross-correlation of the full data set with two atmospheric models, we report the direct detection of the emission spectrum of the non-transiting exoplanet HD 88133 b and measure a radial projection of the Keplerian orbital velocity of 40 ± 15 km s^(−1), a true mass of 1.02^(+0.61)_(-0.28)M_J, a nearly face-on orbital inclination of 15^(+6o)_(-5), and an atmosphere opacity structure at high dispersion dominated by water vapor. This, combined with 11 years of radial velocity measurements of the system, provides the most up-to-date ephemeris for HD 88133

Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by −64 % but overestimates nitrate by +36 %. The largest underestimate in sulfate occurs during the pollution event, for which models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of 5 increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape, resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model, which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation, implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally produced sulfate increased from 1 % to 25 % of locally produced PM2.5, implying that local emissions controls could have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction, which affects the aerosol liquid water abundance and chemistry driving sulfate–nitrate–ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and this results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate + nitrate + ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements