Assimilating spaceborne lidar dust extinction can improve dust forecasts

Atmospheric mineral dust has a rich tri-dimensional spatial and temporal structure that is poorly constrained in forecasts and analyses when only column-integrated aerosol optical depth (AOD) is assimilated. At present, this is the case of most operational global aerosol assimilation products. Aerosol vertical distributions obtained from spaceborne lidars can be assimilated in aerosol models, but questions about the extent of their benefit upon analyses and forecasts along with their consistency with AOD assimilation remain unresolved. Our study thoroughly explores the added value of assimilating spaceborne vertical dust profiles, with and without the joint assimilation of dust optical depth (DOD). We also discuss the consistency in the assimilation of both sources of information and analyse the role of the smaller footprint of the spaceborne lidar profiles in the results. To that end, we have performed data assimilation experiments using dedicated dust observations for a period of 2 months over northern Africa, the Middle East, and Europe. We assimilate DOD derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) on board Suomi National Polar-Orbiting Partnership (SUOMI-NPP) Deep Blue and for the first time Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP)-based LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies (LIVAS) pure-dust extinction coefficient profiles on an aerosol model. The evaluation is performed against independent ground-based DOD derived from AErosol RObotic NETwork (AERONET) Sun photometers and ground-based lidar dust extinction profiles from the Cyprus Clouds Aerosol and Rain Experiment (CyCARE) and PREparatory: does dust TriboElectrification affect our ClimaTe (Pre-TECT) field campaigns. Jointly assimilating LIVAS and Deep Blue data reduces the root mean square error (RMSE) in the DOD by 39 % and in the dust extinction coefficient by 65 % compared to a control simulation that excludes assimilation. We show that the assimilation of dust extinction coefficient profiles provides a strong added value to the analyses and forecasts. When only Deep Blue data are assimilated, the RMSE in the DOD is reduced further, by 42 %. However, when only LIVAS data are assimilated, the RMSE in the dust extinction coefficient decreases by 72 %, the largest improvement across experiments. We also show that the assimilation of dust extinction profiles yields better skill scores than the assimilation of DOD under an equivalent sensor footprint. Our results demonstrate the strong potential of future lidar space missions to improve desert dust forecasts, particularly if they foresee a depolarization lidar channel to allow discrimination of desert dust from other aerosol types.

Interstellar Extinction and Elemental Abundances: Individual Sight Lines

While it is well recognized that both the Galactic interstellar extinction curves and the gas-phase abundances of dust-forming elements exhibit considerable variations from one sight line to another, as yet most of the dust extinction modeling efforts have been directed to the Galactic average extinction curve, which is obtained by averaging over many clouds of different gas and dust properties. Therefore, any details concerning the relationship between the dust properties and the interstellar environments are lost. Here we utilize the wealth of extinction and elemental abundance data obtained by space telescopes and explore the dust properties of a large number of individual sight lines. We model the observed extinction curve of each sight line and derive the abundances of the major dust-forming elements (i.e., C, O, Si, Mg, and Fe) required to be tied up in dust (i.e., dust depletion). We then confront the derived dust depletions with the observed gas-phase abundances of these elements and investigate the environmental effects on the dust properties and elemental depletions. It is found that for the majority of the sight lines the interstellar oxygen atoms are fully accommodated by gas and dust and therefore there does not appear to be a “missing oxygen” problem. For those sight lines with an extinction-to-hydrogen column density A V /N H ≳ 4.8 × 10−22 mag cm2 H−1 there are shortages of C, Si, Mg, and Fe elements for making dust to account for the observed extinction, even if the interstellar C/H, Si/H, Mg/H, and Fe/H abundances are assumed to be protosolar abundances augmented by Galactic chemical evolution.

Anomalous Hydrogen Recombination Line Ratios in Ultraluminous Infrared Galaxies

We conducted systematic observations of the H i Brα (4.05 μm) and Brβ (2.63 μm) lines in 52 nearby (z < 0.3) ultraluminous infrared galaxies (ULIRGs) with AKARI. Among 33 ULIRGs wherein the lines are detected, 3 galaxies show anomalous Brβ/Brα line ratios (∼1.0), which are significantly higher than those for case B (0.565). Our observations also show that ULIRGs have a tendency to exhibit higher Brβ/Brα line ratios than those observed in Galactic H ii regions. The high Brβ/Brα line ratios cannot be explained by a combination of dust extinction and case B since dust extinction reduces the ratio. We explore possible causes for the high Brβ/Brα line ratios and show that the observed ratios can be explained by a combination of an optically thick Brα line and an optically thin Brβ line. We simulated the H ii regions in ULIRGs with the Cloudy code, and our results show that the high Brβ/Brα line ratios can be explained by high-density conditions, wherein the Brα line becomes optically thick. To achieve a column density large enough to make the Brα line optically thick within a single H ii region, the gas density must be as high as n ∼ 108 cm−3. We therefore propose an ensemble of H ii regions, in each of which the Brα line is optically thick, to explain the high Brβ/Brα line ratio.

Assimilating spaceborne lidar dust extinction improves dust forecasts

Atmospheric mineral dust has a rich tri-dimensional spatial and temporal structure that is poorly constrained in forecasts and analyses when only column-integrated aerosol optical depth (AOD) is assimilated. At present, this is the case of most operational global aerosol assimilation products. Aerosol vertical distributions obtained from space-borne lidars can be assimilated in aerosol models, but questions about the extent of their benefit upon analyses and forecasts along with their consistency with AOD assimilation remain unresolved. Our study thoroughly explores the added value of assimilating space-borne vertical dust profiles, with and without the joint assimilation of dust optical depth (DOD). We also discuss the consistency in the assimilation of both sources of information and analyse the role of the smaller footprint of the space-borne lidar profiles upon the results. To that end, we have performed data assimilation experiments using dedicated dust observations for a period of two months over Northern Africa, the Middle East and Europe. We assimilate DOD derived from VIIRS/SUOMI-NPP Deep Blue, and for the first time CALIOP-based LIVAS pure-dust extinction coefficient profiles on an aerosol model. The evaluation is performed against independent ground-based DOD derived from AERONET Sun photometers and ground-based lidar dust extinction profiles from field campaigns (CyCARE and Pre-TECT). Jointly assimilating LIVAS and Deep Blue data reduces the root mean square error (RMSE) in the DOD by 39 % and in the dust extinction coefficient by 65 % compared to a control simulation that excludes assimilation. We show that the assimilation of dust extinction coefficient profiles provides a strong added value to the analyses and forecasts. When only Deep Blue data are assimilated the RMSE in the DOD is reduced further, by 42 %. However, when only LIVAS data are assimilated the RMSE in the dust extinction coefficient decreases by 72 %, the largest improvement across experiments. We also show that the assimilation of dust extinction profiles yields better skill scores than the assimilation of DOD under equivalent sensor footprint. Our results demonstrate the strong potential of future lidar space missions to improve desert dust forecasts, particularly if they foresee a depolarization lidar channel to allow discriminating desert dust from other aerosol types.

The IRX–β relation of high-redshift galaxies

ABSTRACT The relation between infrared excess (IRX) and UV spectral slope (βUV) is an empirical probe of dust properties of galaxies. The shape, scatter, and redshift evolution of this relation are not well understood, however, leading to uncertainties in estimating the dust content and star formation rates (SFRs) of galaxies at high redshift. In this study, we explore the nature and properties of the IRX–βUV relation with a sample of z = 2–6 galaxies ($M_*\approx 10^9\!-\!10^{12}\, \mathrm{M}_\odot$) extracted from high-resolution cosmological simulations (MassiveFIRE) of the Feedback in Realistic Environments (FIRE) project. The galaxies in our sample show an IRX–βUV relation that is in good agreement with the observed relation in nearby galaxies. IRX is tightly coupled to the UV optical depth, and is mainly determined by the dust-to-star geometry instead of total dust mass, while βUV is set both by stellar properties, UV optical depth, and the dust extinction law. Overall, much of the scatter in the IRX–βUV relation of our sample is found to be driven by variations of the intrinsic UV spectral slope. We further assess how the IRX–βUV relation depends on viewing direction, dust-to-metal ratio, birth-cloud structures, and the dust extinction law and we present a simple model that encapsulates most of the found dependencies. Consequently, we argue that the reported ‘deficit’ of the infrared/sub-millimetre bright objects at z ≳ 5 does not necessarily imply a non-standard dust extinction law at those epochs.

Hα fluxes and extinction distances for planetary nebulae in the IPHAS survey of the Northern Galactic Plane

We report Hα filter photometry for 197 northern hemisphere planetary nebulae (PNe) obtained using imaging data from the IPHAS survey. Hα+[N ii] fluxes were measured for 46 confirmed or possible PNe discovered by the IPHAS survey and for 151 previously catalogued PNe that fell within the area of the northern Galactic Plane surveyed by IPHAS. After correcting for [N ii] emission admitted by the IPHAS Hα filter, the resulting Hα fluxes were combined with published radio free-free fluxes and Hβ fluxes, in order to estimate mean optical extinctions to 143 PNe using ratios involving their integrated Balmer line fluxes and their extinction-free radio fluxes. Distances to the PNe were then estimated using three different 3D interstellar dust extinction mapping methods, including the IPHAS-based H-MEAD algorithm of Sale (2014). These methods were used to plot dust extinction versus distance relationships for the lines of sight to the PNe; the intercepts with the derived dust optical extinctions allowed distances to the PNe to be inferred. For 17 of the PNe in our sample reliable Gaia DR2 distances were available and these have been compared with the distances derived using three different extinction mapping algorithms as well as with distances from the nebular radius vs. Hα surface brightness relation of Frew et al. (2016). That relation and the H-MEAD extinction mapping algorithm yielded the closest agreement with the Gaia DR2 distances.