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Aerosol–cloud–radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.

A terrestrial planet’s rotation period is one of the key parameters that determines its climate and habitability. Current methods for detecting the rotation period of exoplanets are not suitable for terrestrial exoplanets. Here we demonstrate that, under certain conditions, the rotation period of an Earth-like exoplanet will be detectable using direct-imaging techniques. We use a global climate model that includes clouds to simulate reflected starlight from an Earth-like exoplanet and explore how different parameters (e.g., orbital geometry, wavelength, time resolution) influence the detectability of the planet’s rotation period. We show that the rotation period of an Earth-like exoplanet is detectable using visible-wavelength channels with time-series monitoring at a signal-to-noise ratio (S/N) >20 with ∼5–15 rotation periods of data, while the rotation period of a planet with full ocean coverage is unlikely to be detectable. To better detect the rotation period, one needs to plan the observation so that each individual integration would yield a S/N >10, while keeping the integration time shorter than 1/6 to 1/4 of the rotation period of the planet. Our results provide important guidance for rotation period detection of Earth-like exoplanets in reflected light using future space telescopes.

Observations show that the Arctic sea ice cover has been shrinking at an unprecedented rate since the 1970s. Even though the accumulation of greenhouse gases in the atmosphere has been closely linked with the loss of Arctic sea ice, the role of atmospheric aerosols in past and future Arctic climate change remains elusive. Using a state-of-the-art fully coupled climate model, the authors assess the equilibrium responses of the Arctic sea ice to the different aerosol emission scenarios and investigate the pathways by which aerosols impose their influence in the Arctic. These sensitivity experiments show that the impacts of aerosol perturbations on the pace of sea ice melt effectively modulate the ocean circulation and atmospheric feedbacks. Because of the contrasting evolutions of particulate pollution in the developed and developing countries since the 1970s, the opposite aerosol forcings from different midlatitude regions are nearly canceled out in the Arctic during the boreal summer, resulting in a muted aerosol effect on the recent sea ice changes. Consequently, the greenhouse forcing alone can largely explain the observed Arctic sea ice loss up to the present. In the next few decades, the projected alleviation of particulate pollution in the Northern Hemisphere can contribute up to 20% of the total Arctic sea ice loss and 0.7°C surface warming over the Arctic. The authors’ model simulations further show that aerosol microphysical effects on the Arctic clouds are the major component in the total aerosol radiative forcing over the Arctic. Compared to the aerosol-induced energy imbalance in lower latitudes outside the Arctic, the local radiative forcing by aerosol variations within the Arctic, due to either local emissions or long-range transports, is more efficient in determining the sea ice changes and Arctic climate change.

Venus airglow emissions have been unambiguously detected in the wavelength ranges of 1.40–1.49 and 2.6–3.14 μm in limb observations by the Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) onboard the Venus Express (VEx) spacecraft and are attributed to the OH(2–0) and OH(1–0) Meinel band transitions. The integrated (limb slant path) emission rates for these bands were measured by Piccioni et al. (2008). Photochemical (Caltech/JPL KINETICS) and global circulation (Venus Thermospheric General Circulation Model - VTGCM) model calculations suggest the observed OH emission is produced primarily via the Bates-Nicolet mechanism, as on the Earth, although Venus' background atmosphere is different than that of the Earth, but the modeled contribution of the HO2 + O → OH(v) + O2 reaction increases in the lower portion of the OH airglow layer. An overall difference of ~2 km in the peak heights of the OH(1–0) and OH(2–0) layers is seen in both the KINETICS and VTGCM simulations as a result of this change in the relative importance of H + O3 → OH(v) + O2 versus HO2 + O → OH(v) + O2 reactions with altitude. First time 3-D simulations of the OH Δv = 1 nightglow limb slant emission calculate a peak intensity of ~0.6 ± 0.3 MegaRayleighs at ~102 km altitude, an intensity that is consistent with Venus Express VIRTIS observations (Gerard et al. 2010; Soret et al. 2010, 2012) and KINETICS results. Soret et al. (2010) reported the intensity of the peak OH airglow increased from 0.30 to 0.40 MR from dusk to dawn but noted the observations used are not uniformly distributed and the observed emission is extremely variable, so a more detailed assessment of the observations was not possible. Our simulations show a decrease in the average OH(1–0) emission is symmetric about the midnight meridian, but the simulations find an asymmetric decrease from the equator to the poles. Consideration of transport and chemical lifetimes suggests modeling of OH above ~96 km requires explicit description of transport and vibrational-state-dependent chemistry.

Nitrous oxide (N2O) is an important greenhouse gas contributing both to global radiative forcing and ozone depletion. Though N2O emissions are largely derived from agricultural activities, urban sources of N2O also contribute significantly to anthropogenic emissions, but are not well understood and difficult to quantify. This study employs a top-down approach to derive urban N2O emissions for the Los Angeles megacity using a unique dataset from a mountaintop remote sensing instrument, which has been observing greenhouse gas mixing ratios in LA since 2011. CLARS-FTS observations yield a weighted mean of 15.0 ± 0.1 ppb excess XN2O above background in the LA basin from 2013 to 2019. Time series of XN2Oxs show a seasonal cycle with a peak-to-peak amplitude of 5.6 ± 2.5 ppb, where greater XN2Oxs values are observed during the winter/spring and minima occur in late summer/early fall. A tracer-tracer ratio method is applied using XN2Oxs and XCO2,xs observations to estimate top-down N2O emissions for the LA basin during 2013–2018. Estimated monthly emissions range from 6 to 19 Gg N2O per month and exhibit a similar seasonal cycle to that observed in XN2Oxs. Estimated annual emissions fall within the range 124–144 Gg per year for the years 2014–2018. These top-down annual estimates are roughly 3 times the official statewide bottom-up inventory for the same time period, but consistent considering uncertainties with other top-down estimates for the LA basin. The discrepancy between top-down emission estimates and the statewide bottom-up inventory highlights the difficulty in constraining N2O emissions, especially for an urban environment.

We quantify the amount of nitrogen oxides (NOx) produced through lightning and photochemical processes in the Hadean atmosphere to be available in the Hadean ocean for the emergence of life. Atmospherically generated nitrate (NO_3−) and nitrite (NO_2−) are the most attractive high-potential electron acceptors for pulling and enabling crucial redox reactions of autotrophic metabolic pathways at submarine alkaline hydrothermal vents. The Hadean atmosphere, dominated by CO_2 and N_2, will produce nitric oxide (NO) when shocked by lightning. Photochemical reactions involving NO and H_2O vapor will then produce acids such as HNO, HNO_2, HNO_3, and HO_2NO_2 that rain into the ocean. There, they dissociate into or react to form nitrate and nitrite. We present new calculations based on a novel combination of early-Earth global climate model and photochemical modeling, and we predict the flux of NOx to the Hadean ocean. In our 0.1-, 1-, and 10-bar pCO_2 models, we calculate the NOx delivery to be 2.4 × 10^5, 6.5 × 10^8, and 1.9 × 10^8 molecules cm^(−2) s^(−1). After only tens of thousands to tens of millions of years, these NOx fluxes are expected to produce sufficient (micromolar) ocean concentrations of high-potential electron acceptors for the emergence of life.

The Principal Component Analysis (PCA)-based fast radiative transfer method has been shown to have at least an order of magnitude increase in computational speed while maintaining an overall accuracy of 0.01% (compared to line-by-line calculations) over narrow and broad spectral bands. In this paper, we describe several improvements made to the method and provide a discussion of the method’s performance over a diverse set of atmospheric profiles and land surface types. We also test the model over uniform pressure level profiles. The method is now capable of providing atmospheric spectra with residuals under 0.1%, calculated with respect to the continuum, throughout the shortwave region between 0.3−3μm at high resolution, which is substantial improvement over errors reported in earlier work. Future directions for applications and further optimization are examined.

We examine the middle atmospheric odd-hydrogen (HO_x) chemistry by comparing the Aura Microwave Limb Sounder (MLS) OH and HO_2 measurements with a photochemical model simulation. The model underestimates mesospheric OH and HO_2 concentrations if the standard chemical kinetic rates are used, whether the model H_2O and O_3 are constrained with observations or not. To resolve the discrepancies, we adjust the kinetic rate coefficients of three key reactions (O + OH → O_2 + H, OH + HO_2 → H_2O + O_2, and H + O_2 + M → HO_2 + M) and the O2photo absorption cross section at Lyman-α (121.57 nm) using the Bayesian optimal estimation. A much better model-observation agreement can be achieved if the kinetic rate coefficients for H + O_2 + M → HO_2 + M is increased by 134–310%, and the O_2 photo absorption cross section at Lyman-α is reduced by 33–54%, while the kinetic rate coefficients for O + OH → O_2 + H and OH + HO_2 → H_2O + O_2 remain consistent with the current laboratory values. The kinetic rate coefficient for H + O_2 + M → HO_2 + M requires a very large adjustment beyond the uncertainty limits recommended in the NASA Data Evaluation, suggesting the need for future laboratory measurements. An alternative explanation is that the radiative association reaction, H + O_2 → HO_2 + hν, plays a significant role, which has never been measured. Our results demonstrate that high quality satellite observations can be used to constrain photochemical parameters and help improve our understanding of atmospheric chemistry.

New Horizons has granted us an unprecedented glimpse at the structure and composition of Pluto's atmosphere, which is comprised mostly of N_2 with trace amounts of CH_4, CO, and the photochemical products thereof. Through photochemistry, higher-order hydrocarbons are generated, coagulating into aerosols and resulting in global haze layers. Here we present a state-of-the-art photochemical model for Pluto's atmosphere to explain the abundance profiles of CH_4, C_2H_2, C_2H_4, and C_2H_6, the total column density of HCN, and to predict the abundance profiles of oxygen-bearing species. The CH_4 profile can be best matched by taking a constant-with-altitude eddy diffusion coefficient K_(zz) profile of 1 × 10^3 cm^2 s^(–1) and a fixed CH_4 surface mixing ratio of 4 × 10^(–3). Condensation is key to fitting the C_2 hydrocarbon profiles. We find that C_2H_4 must have a much lower saturation vapor pressure than predicted by extrapolations of laboratory measurements to Pluto temperatures. We also find best-fit values for the sticking coefficients of C_2H_2, C_2H_4, C_2H_6, and HCN. The top three precipitating species are C_2H_2, C_2H_4, and C_2H_6, with precipitation rates of 179, 95, and 62 g cm^(–2) s^(–1), respectively.

Analyzing retrieval accuracy and precision is an important element of space‐based CO2 retrievals. However, this error analysis is sometimes challenging to perform rigorously because of the subtlety of Multivariate Statistics. To help address this issue, we revisit some fundamentals of Multivariate Statistics that help reveal the statistical essence of the associated error analysis. We show that the related statistical methodology is useful for revealing the intrinsic discrepancy and relation between the retrieval error for a nonzero‐variate CO2 state and that for a zero‐variate one. Our study suggests that the two scenarios essentially yield the same‐magnitude accuracy, while the latter scenario yields a better precision than the former. We also use this methodology to obtain a rigorous framework systematically and explore a broadly used approximate framework for analyzing CO2 retrieval errors. The approximate framework introduces errors due to an essential, but often forgotten, fact that a priori climatology in reality is never equal to the true state. Due to the nature of the problem considered, realistic numerical simulations that produce synthetic spectra may be more appropriate than remote sensing data for our specific exploration. As highlighted in our retrieval simulations, utilizing the approximate framework may not be universally satisfactory in assessing the accuracy and precision of Xco2 retrievals (with errors up to 0.17–0.28 ppm and 1.4–1.7 ppm, respectively, at SNR = 400). In situ measurements of CO2 are needed to further our understanding of this issue and related implications.

In this study, we propose a novel approach to describe the scattering effects of atmospheric aerosols in a complex urban environment using water vapor (H2O) slant column measurements in the near infrared. This approach is demonstrated using measurements from the California Laboratory for Atmospheric Remote Sensing Fourier Transform Spectrometer on the top of Mt. Wilson, California, and a two-stream-exact single scattering (2S-ESS) radiative transfer (RT) model. From the spectral measurements, we retrieve H2O slant column density (SCD) using 15 different absorption bands between 4000 and 8000 cm−1. Due to the wavelength dependence of aerosol scattering, large variations in H2O SCD retrievals are observed as a function of wavelength. Moreover, the variations are found to be correlated with aerosol optical depths (AODs) measured at the AERONET-Caltech station. Simulation results from the RT model reproduce this correlation and show that the aerosol scattering effect is the primary contributor to the variations in the wavelength dependence of the H2O SCD retrievals. A significant linear correlation is also found between variations in H2O SCD retrievals from different bands and corresponding AOD data; this correlation is associated with the asymmetry parameter, which is a first-order measure of the aerosol scattering phase function. The evidence from both measurements and simulations suggests that wavelength-dependent aerosol scattering effects can be derived using H2O retrievals from multiple bands. This understanding of aerosol scattering effects on H2O retrievals suggests a promising way to quantify the effect of aerosol scattering on greenhouse gas retrievals and could potentially contribute towards reducing biases in greenhouse gas retrievals from space.

We have derived homopause temperatures of 180–250 K for the 8-µm north-polar hot spot (8NPHS) of Jupiter by fitting CH_4 emission models to 3 and 8 µm spectra of the 8NPHS obtained 24 days apart in 2013. From the fits, we find that CH_4 mixing ratios at the 8NPHS are consistent with those reported by Kim et al. (2014) in equatorial regions. We propose possible mechanisms to account for the temperature of the 8NPHS homopause, which is relatively cool compared with the temperatures of other auroral regions, including locally-fixed and transient but energetic auroral particle precipitation.

Resolving spatially-varying exoplanet features from single-point light curves is essential for determining whether Earth-like worlds harbor geological features and/or climate systems that influence habitability. To evaluate the feasibility and requirements of this spatial feature resolving problem, we present an analysis of multi-wavelength single-point light curves of Earth, where it plays the role of a proxy exoplanet. Here, ~10,000 DSCOVR/EPIC frames collected over a two-year period were integrated over the Earth's disk to yield a spectrally-dependent point source and analyzed using singular value decomposition. We found that, between the two dominant principal components (PCs), the second PC contains surface-related features of the planet, while the first PC mainly includes cloud information. We present the first two-dimensional (2D) surface map of Earth reconstructed from light curve observations without any assumptions of its spectral properties. This study serves as a baseline for reconstructing the surface features of Earth-like exoplanets in the future., Accepted by ApJL, 7 pages, 4 figures

The formation of ice particles in the atmosphere strongly affects cloud properties and the climate. While mineral dust is known to be an effective ice nucleating particle, the role of aerosols from anthropogenic pollution in ice nucleation is still under debate. Here we probe the ice nucleation ability of different aerosol types by combining 11-year observations from multiple satellites and cloud-resolving model simulations. We find that, for strong convective systems, the ice particle effective radius near cloud top decreases with increasing loading of polluted continental aerosols, because the ice formation is dominated by homogeneous freezing of cloud droplets, which are smaller under more polluted conditions. By contrast, an increase in ice particle effective radius with polluted continental aerosols is found for moderate convection. Our model simulations suggest that this positive correlation is explained by enhanced heterogeneous ice nucleation and prolonged ice particle growth at higher aerosol loading, indicating that polluted continental aerosols contain a considerable fraction of ice nucleating particles. Similar aerosol–ice relationships are observed for dust aerosols, further corroborating the ice nucleation ability of polluted continental aerosols. By catalysing ice formation, aerosols from anthropogenic pollution could have profound impacts on cloud lifetime and radiative effect as well as precipitation efficiency. Polluted continental aerosols contain a considerable fraction of ice nucleating particles, suggest analyses of satellite observations and simulations with cloud-resolving models.

The interannual variability of tropical carbon monoxide from the Microwave Limb Sounder over 2004–2018 period is dominated by the quasi‐biennial oscillation (QBO). We simulate the carbon monoxide variability over this period using the 2‐D Caltech/JPL chemistry‐transport model. The chemistry‐transport model includes the photochemical sources and sinks and transport driven by a stream function and eddy diffusivity derived from the assimilated winds of National Centers for Environmental Prediction Reanalysis 2. The results show good agreement between model and Microwave Limb Sounder observations. We also investigate the anomalous period 2015–2016, when the QBO winds deviated significantly from their climatological values. The model simulations could capture the QBO features in agreement with observations for the anomalous period.

Aerosol effects on convective clouds and associated precipitation constitute an important open-ended question in climate research. Previous studies have linked an increase in aerosol concentration to a delay in the onset of rain, invigorated clouds and stronger rain rates. Here, using observational data, we show that the aerosol effect on convective clouds shifts from invigoration to suppression with increasing aerosol optical depth. We explain this shift in trend (using a cloud model) as the result of a competition between two types of microphysical processes: cloud-core-based invigorating processes vs. peripheral suppressive processes. We show that the aerosol optical depth value that marks the shift between invigoration and suppression depends on the environmental thermodynamic conditions. These findings can aid in better parameterizing aerosol effects in climate models for the prediction of climate trends.

We present recent results concerning the attractor landscape, memory, hysteresis and computation that can emerge in simple convective obstacle flows. In these systems a single phase fluid is heated from below and cooled from above. Small obstacles (one or two) are placed on the horizontal mid plane of the system and extract some fraction of the fluid’s horizontal or vertical momentum. Horizontal momentum sinks tend to attract convection plumes. Vertical momentum sinks are bistable; the obstacle will either align with a convection cell centre or convection plume depending on initial conditions and the history of the system. The resulting attractor landscape can be exploited to produce a single bit memory or even elementary Boolean logic.

The Alice spectrograph on New Horizons performed several far-ultraviolet (FUV) airglow observations during the July 2015 flyby of Pluto. One of these observations, named PColor2, was a short (226 s) scan across the dayside disk of Pluto from a range of ∼ 34 , 000 km, at about 40 minutes prior to closest approach. The brightest observed FUV airglow signal at Pluto is the Lyman alpha (Ly α ) emission line of atomic hydrogen, which arises primarily through the resonant scattering of solar Ly α by H atoms in the upper atmosphere, with a brightness of about 30 Rayleigh. Pluto appears dark against the much brighter ( ∼ 100 Rayleigh) sky background; this sky background is likewise the result of resonantly scattered solar Ly α , in this case by H atoms in the interplanetary medium (IPM). Here we use an updated photochemical model and a resonance line radiative transfer model to perform detailed simulations of the Ly α emissions observed in the Alice PColor2 scan. The photochemical models show that H and CH 4 abundances in Pluto’s upper atmosphere are a very strong function of the near-surface mixing ratio of CH 4 , and could provide a useful way to remotely monitor seasonal climate variations in Pluto’s lower atmosphere. The morphology of the PColor2 Ly α emissions provides constraints on the current abundance profiles of H atoms and CH 4 molecules in Pluto’s atmosphere, and indicate that the globally averaged near-surface mixing ratio of CH 4 is currently close to 0 . 4 % . This new result thus provides independent confirmation of one of the primary results from the solar occultation, also observed with the New Horizons Alice ultraviolet spectrograph.

Europa, one of the Galilean satellites, has a tenuous, oxygen-dominated atmosphere that is usually referred to as a collision-less exosphere. Coupled to the neutral atmosphere and in contact with Europa's surface, a tenuous ionosphere exists on Europa, whose presence has been revealed by multiple observations. Such an ionosphere is thought to be produced by solar photoionization and electron-impact ionization of the oxygen in the atmosphere. However, a recent study showed that the maximum ionosphere coincides with intermittent water plume on Europa, suggesting that water plays an important role in the formation of the ionosphere. Based on the assumption of horizontal uniformity in the middle of the plume, we use the Caltech/Jet Propulsion Laboratory one-dimensional KINETICS model to construct profiles of neutral and ionized species near the plume region. The simulation results, which show that the ionization reactions are initiated by water electron-impact ionization and photoionization and continued by charge transfer between water and oxygen molecules, have successfully reproduced the observations. We find that H2O+ is the dominant species only above the ionopause. Below the ionopause, the density of H2O+ is orders of magnitude lower than the density of O2+, which is the major composition below the ionopause. Our model has also been used to study the dissociation processes of water molecules from the plumes, which can be regarded as an alternative source for the oxygen in the atmosphere.

To have the capability for long‐term prediction of stratospheric ozone (O_3), chemistry‐climate models have often been tested against observations on decadal timescales. A model‐observation discrepancy in the tropical O_3 response to the 11 year solar cycle, first noted in 1993, persists for more than 20 years: While standard photochemical models predict a single‐peak response in the stratosphere, satellite observations show an unexpected double‐peak structure. Such discrepancy has led to the question of whether the current standard O_3 photochemistry is deficient. Various studies have explored uncertainties in photochemistry and dynamics but there has not been compelling evidence of model biases. Here we suggest that decadal satellite orbital drifts relative to the diurnal cycle could be the primary cause of the discrepancy. We show that the double‐peak structure can be reproduced by adding the A.M./P.M. diurnal difference to the single‐peak response predicted by the standard photochemistry. Thus we argue that the standard photochemistry is consistent with the observed solar cycle modulation in stratospheric O_3.

Using eight years (2006–2014) of passive (MODIS/Aqua and OMI/Aura) and active (CALIOP/CALIPSO) satellite measurements of aerosols, we yield a three-dimensional (3D) distribution of the frequency of occurrence (FoO) of aerosols over China. As an indicator of the vertical heterogeneity of aerosol layers detected by CALIOP, two types of Most Probable Height (MPH), including MPH_FoO and MPH_AOD, are deduced. The FoO of “Total Aerosol” reveals significant geographical dependence. Eastern China showed much stronger aerosol FoD than northwestern China. The FoO vertical structures of aerosol layer are strongly dependent on altitudes. Among the eight typical ROIs analyzed, aerosol layers over the Gobi Desert have the largest occurrence probability located at an altitude as high as 2.83 km, as compared to 1.26 km over Beijing–Tianjin–Hebei. The diurnal variation (nighttime–daytime) in MPH_AOD varies from an altitude as low as 0.07 km over the Sichuan basin to 0.27 km over the Gobi Desert, whereas the magnitude of the diurnal variation in terms of MPH_AOD is six times as large as the MPH_FoO, mostly attributable to the day/night lidar SNR difference. Also, the 3D distribution of dust and smoke aerosols was presented. The multi-sensor synergized 3D observations of dust aerosols, frequently observed in the zonal belt of 38°N–45°N, is markedly different from that of smoke aerosols that are predominantly located in the eastern and southern parts. The 3D FoO distribution of dust indicates a west-to-east passageway of dust originating from the westernmost Taklimakan Desert all the way to North China Plain (NCP). The findings from the multi-sensor synergetic observations greatly improved our understanding on the long-range aerosol dispersion, transport and passageway over China.

Megacities are major sources of anthropogenic fossil fuel CO2 (FFCO2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO2 emission product, Hestia-LA, to simulate atmospheric CO2 concentrations across the LA megacity at spatial resolutions as fine as ∼ 1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO2 emission products to evaluate the impact of the spatial resolution of the CO2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO2 concentrations. We find that high spatial resolution in the fossil fuel CO2 emissions is more important than in the atmospheric model to capture CO2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO2 emissions monitoring in the LA megacity requires FFCO2 emissions modelling with ∼ 1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

We propose that C_4N_2 ice clouds observed in Titan's springtime polar stratosphere arise due to solid-state photochemistry occurring within extant ice cloud particles of HCN-HC_3N mixtures. This formation process resembles the halogen-induced ice particle surface chemistry that leads to condensed nitric acid trihydrate (NAT) particles and ozone depletion in Earth's polar stratosphere. As our analysis of the Cassini Composite Infrared Spectrometer 478 cm^(−1) ice emission feature demonstrates, this solid-state photochemistry mechanism eliminates the need for the relatively high C_4N_2 saturation vapor pressures required (even though they are not observed) when the ice is produced through the usual procedure of direct condensation from the vapor.

Accurate radiative transfer (RT) calculations are necessary for many earth-atmosphere applications, from remote sensing retrieval to climate modeling. A Principal Component Analysis (PCA)-based spectral binning method has been shown to provide an order of magnitude increase in computational speed while maintaining an overall accuracy of 0.01% (compared to line-by-line calculations) over narrow spectral bands. In this paper, we have extended the PCA method for RT calculations over the entire shortwave region of the spectrum from 0.3 to 3 microns. The region is divided into 33 spectral fields covering all major gas absorption regimes. We find that the RT performance runtimes are shorter by factors between 10-100, while root mean square errors are of order 0.01%.

Using data from the International Satellite Cloud Climatology Project (ISCCP), we examine how near-global (60°N–60°S) high cloud fraction varies over time in the past three decades. Our focus is on identifying dominant modes of variability and associated spatial patterns, and how they are related to sea surface temperature. By performing the principal component analysis, we find that the first two principal modes of high cloud distribution show strong imprints of the two types of El Nino–Southern Oscillation (ENSO)—the canonical ENSO and the ENSO Modoki. Comparisons between ISCCP data and 14 models from the Atmospheric Model Intercomparison Project Phase 5 (AMIP5) show that models simulate the spatial pattern and the temporal variations of high cloud fraction associated with the canonical ENSO very well but the magnitudes of the canonical ENSO vary among the models. Furthermore, the multi-model mean of the second principal mode in the AMIP5 simulations appears to capture the temporal behavior of the second mode but individual AMIP5 models show large discrepancies in capturing observed temporal variations. A new metric, defined by the relative variances of the first two principal components, suggests that most of the AMIP5 models overestimate the second principal mode of high clouds.

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO2 mole fractions and Δ14C and δ13C values of CO2 in the Los Angeles megacity observed in inland Pasadena (2006–2013) and coastal Palos Verdes peninsula (autumn 2009–2013), we have determined time series for CO2 contributions from fossil fuel combustion (Cff) for both sites and broken those down into contributions from petroleum and/or gasoline and natural gas burning for Pasadena. We find a 10 % reduction in Pasadena Cff during the Great Recession of 2008–2010, which is consistent with the bottom-up inventory determined by the California Air Resources Board. The isotopic variations and total atmospheric CO2 from our observations are used to infer seasonality of natural gas and petroleum combustion. The trend of CO2 contributions to the atmosphere from natural gas combustion is out of phase with the seasonal cycle of total natural gas combustion seasonal patterns in bottom-up inventories but is consistent with the seasonality of natural gas usage by the area's electricity generating power plants. For petroleum, the inferred seasonality of CO2 contributions from burning petroleum is delayed by several months relative to usage indicated by statewide gasoline taxes. Using the high-resolution Hestia-LA data product to compare Cff from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO2 reflect seasonal variations in wind direction. The seasonality of the local CO2 excess from fossil fuel combustion along the coast, on Palos Verdes peninsula, is higher in autumn and winter than spring and summer, almost completely out of phase with that from Pasadena, also because of the annual variations of winds in the region. Variations in fossil fuel CO2 signals are consistent with sampling the bottom-up Hestia-LA fossil CO2 emissions product for sub-city source regions in the LA megacity domain when wind directions are considered.

Satellite CO_2 retrievals from the Greenhouse gases Observing SATellite (GOSAT), Atmospheric Infrared Sounder (AIRS), and Tropospheric Emission Spectrometer (TES) and in situ measurements from the National Oceanic and Atmospheric Administration - Earth System Research Laboratory (NOAA-ESRL) Surface CO_2 and Total Carbon Column Observing Network (TCCON) are utilized to explore the CO_2 variability at different altitudes. A multiple regression method is used to calculate the CO_2 annual cycle and semiannual cycle amplitudes from different data sets. The CO_2 annual cycle and semiannual cycle amplitudes for GOSAT X_(CO2) and TCCON X_(CO2) are consistent but smaller than those seen in the NOAA-ESRL surface data. The CO_2 annual and semiannual cycles are smallest in the AIRS midtropospheric CO_2 compared with other data sets in the Northern Hemisphere. The amplitudes for the CO_2 annual cycle and semiannual cycle from GOSAT, TES, and AIRS CO_2 are small and comparable to each other in the Southern Hemisphere. Similar regression analysis is applied to the Model for OZone And Related chemical Tracers-2 and CarbonTracker model CO_2. The convolved model CO_2 annual cycle and semiannual cycle amplitudes are similar to those from the satellite CO_2 retrievals, although the models tend to underestimate the CO_2 seasonal cycle amplitudes in the Northern Hemisphere midlatitudes and underestimate the CO_2 semiannual cycle amplitudes in the high latitudes. These results can be used to better understand the vertical structures for the CO_2 annual cycle and semiannual cycle and help identify deficiencies in the models, which are very important for the carbon budget study.

Space‐based remote sensing of the column‐averaged methane dry air mole fraction (XCH_4) has greatly increased our understanding of the spatiotemporal patterns in the global methane cycle. The potential to retrieve multiple pieces of vertical profile information would further improve the quantification of CH_4 across space‐time scales. We conduct information analysis for channel selection and evaluate the prospects of retrieving multiple pieces of information as well as total column CH_4 from both ground‐based and space‐based near‐infrared remote sensing spectra. We analyze the degrees of freedom of signal (DOF) in the CH_4 absorption bands near 2.3 μm and 1.6 μm and select ∼1% of the channels that contain >95% of the information about the CH_4 profile. The DOF is around 4 for fine ground‐based spectra (resolution = 0.01 cm^(−1)) and 3 for coarse space‐based spectra (resolution = 0.20 cm^(−1)) based on channel selection and a signal‐to‐noise ratio (SNR) of 300. The DOF varies from 2.2 to 3.2 when SNR is between 100 and 300, and spectral resolution is 0.20 cm^(−1). Simulated retrieval tests in clear‐sky conditions using the selected channels reveal that the retrieved partial column‐averaged CH_4 values are not sensitive to the a priori profiles and can reflect local enhancements of CH_4 in different partial air columns. Both the total and partial column‐averaged retrieval errors in all tests are within 1% of the true state. These simulated tests highlight the possibility to retrieve up to three to four pieces of information about the vertical distribution of CH_4 in reality.

Atmospheric carbon monoxide (CO) is an effective tracer for monitoring atmospheric transport processes and for detecting pollution sources of anthropogenic origin. However, very few observation systems exist that are capable of providing measurements with high spatial and temporal resolution to identify hotspots for emission control purposes. Here we introduce a mountain-top remote sensing observatory, the California Laboratory for Atmospheric Remote Sensing (CLARS), for mapping the enhancement of CO column-averaged mixing ratio (XCO) over the Los Angeles (LA) megacity. Compared to conventional observation network, CLARS is unique in the following ways: (1) it mimics a geostationary satellite observatory for LA with approximately hourly- and kilometer-scale mapping capability; (2) the free tropospheric background atmosphere is simultaneously measured; and (3) the measurements are highly sensitive to anthropogenic emissions due to the long light path along the planetary boundary layer (PBL). The CO slant column density and XCO are retrieved from reflected sunlight measurements in the 2.3 μm CO band and the 1.27 μm oxygen (O2) band. Data filtering and corrections for aerosol scattering and geometric effects are then implemented to derive the XCO enhancement, which is the XCO excess in the PBL compared to the background value. In the LA megacity, the XCO enhancement shows a distinctive diurnal cycle primarily driven by changes in anthropogenic emissions and sea-breeze circulation. Such diurnal patterns can be reproduced by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The enhancement also shows a significant weekly cycle resulting from the weekly pattern in anthropogenic CO emissions. On average, the XCO enhancements on Sunday and Saturday are 16.1% and 4.4%, respectively, lower than weekday values. The weekly XCO enhancement patterns also show high correlation with traffic counts. A seasonal pattern of XCO enhancement with high (low) spatial contrast in summer (winter), resulting from changing sea-breeze circulation, can be observed. These diurnal, weekly, and seasonal patterns of XCO enhancement serve as tracers of the atmospheric pulse of the LA megacity. The CLARS observatory can serve as a testbed for future geostationary missions to track anthropogenic emissions in cities.

We have obtained Gemini/GNIRS 3.3–3.4 μm spectra of Jupiter at 65o North latitude over a range of longitudes roughly centered on the 8-μm CH4 north polar hot spot (8CNPHS). The spectra were measured on four occasions during a four-month period in 2018, in order to search for variability of the 3-μm emissions of CH₄ and C₂H₆. The observed locations of the brightest spots of the C₂H₆ and CH₄ emissions at 65oN differed in longitude typically by 20o during this period. The peak emission intensities of these species showed large variations, with the highest intensities 3–4 times greater than the lowest intensities. In addition, the brightest 3-μm CH₄ emissions and hottest temperatures at the 8CNPHS were significantly less than those at the 3-μm CH4 north polar hot spot (3CNPHS, Kim et al., 2015). Recently, Sinclair et al. (2019) reported a coincidence between solar wind dynamical pressure and the 8-μm brightening of the 8CNPHS. In contrast, we find lack of correlation in our data between the 3-μm hydrocarbon emission intensities at the 8CNPHS and the solar wind strength. We also find lack of correlation between H₃⁺ intensities and the solar wind strength during the period. However, due to the limited observational data, it is too early to conclude whether this lack of correlation indicates that the solar wind activity induced no significant changes in local temperatures (

The angle-dependent scattering effect of aerosols in the atmosphere can be used to infer their compositions, which in turn is important to understand their impacts of human health and Earth climate. The aerosol phase function, which characterizes the angular signature of scattering, has been continuously monitored from ground-based and space-borne observations. However, the range of scattering angles these instruments can sample is very limited. There is a dearth of research on the remote sensing of aerosol angular scattering effect at a city scale that analyzes diurnal variability and includes a wide range of scattering angles. Here, we quantify the aerosol angular scattering effect using measurements from a mountain-top remote sensing instrument: the California Laboratory for Atmospheric Remote Sensing Fourier Transform Spectrometer (CLARS-FTS). CLARS-FTS is located on top of the Mt. Wilson (1.67km above sea level) overlooking the Los Angeles (LA) megacity and receives reflected sunlight from targeted surface reflection points. The observational geometries of CLARS-FTS provide a wide range of scattering angles, from about 20 degrees (forward) to about 140 degrees (backward). The O2 ratio, which is the ratio of retrieved O2 Slant Column Density (SCD) to geometric O2 SCD, quantifies the aerosol transmission with a value of 1.0 represent aerosol-free and with a value closer to 0.0 represents stronger aerosol loadings. The aerosol transmission quantified by the O2 ratio from CLARS measurements provides an effective indicator of the aerosol scattering effect., Comment: 29 pages; 4 figures

Hyperspectral observations have become one of the most popular and powerful methods for atmospheric remote sensing, and are widely used for temperature, gas, aerosol, and cloud retrievals. However, accurate forward radiative transfer simulations are computationally expensive since typical line-by-line approaches involve a large number of monochromatic radiative transfer calculations. This study explores the feasibility of machine learning techniques (using neural network (NN) as an example) for fast hyperspectral radiative transfer simulations, by performing calculations at a small fraction of hyperspectral wavelengths and extending them across the entire spectral range. Results from the NN model are compared with those from a principal component analysis (PCA) model, which uses a similar principle of dimensionality reduction. We consider hyperspectral radiances from both actual satellite observations and accurate line-by-line simulations. The NN model can alleviate the computational burden by two to three orders of magnitude, and generate radiances with small relative errors (generally less than 0.5% compared to exact calculations); the performance of the NN model is better than that of the PCA model. The model can be further improved by optimizing the training procedure and parameters, the representative wavelengths, and the machine learning technique itself.

Quantifying the vertical distribution of atmospheric aerosols is crucial for estimating their impact on the Earth's energy budget and climate, improving forecast of air pollution in cities, and reducing biases in the retrieval of greenhouse gases (GHGs) from space. However, to date, passive remote sensing measurements have provided limited information about aerosol extinction profiles. In this study, we propose the use of a spectral sorting approach to constrain the aerosol vertical structure using spectra of reflected sunlight absorption within the molecular oxygen (O2) A-band collected by the Orbiting Carbon Observatory-2 (OCO-2). The effectiveness of the approach is evaluated using spectra acquired over the western Sahara coast by comparing the aerosol profile retrievals with lidar measurements from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Using a radiative transfer model to simulate OCO-2 measurements, we found that high-resolution O2 A-band measurements have high sensitivity to aerosol optical depth (AOD) and aerosol layer height (ALH). Retrieved estimates of AOD and ALH based on a look up table technique show good agreement with CALIPSO measurements, with correlation coefficients of 0.65 and 0.53, respectively. The strength of the proposed spectral sorting technique lies in its ability to identify spectral channels with high sensitivity to AOD and ALH and extract the associated information from the observed radiance in a straightforward manner. The proposed approach has the potential to enable future passive remote sensing missions to map the aerosol vertical distribution on a global scale.

16 págs., 15 figs., 1 tab., 1 app., Odd oxygen (O, O(D), O) abundance and its variability in the Martian atmosphere results from complex physical and chemical interactions among atmospheric species, which are driven mainly by solar radiation and atmospheric conditions. Although our knowledge of Mars’ ozone distribution and variability has been significantly improved with the arrival of several recent orbiters, the data acquired by such missions is not enough to properly characterize its diurnal variation. Thus, photochemical models are useful tools to assist in such a characterization. Here, both the Martian ozone vertical distribution and its diurnal variation for equatorial latitudes are studied, using the JPL/Caltech one-dimensional photochemical model and diurnally-variable atmospheric profiles. The chosen equatorial latitude-region is based on the recent and future plans of NASA and other agencies to study this region by different surface missions. A production and loss analysis is performed in order to characterize the chemical mechanisms that drive odd oxygen's diurnal budget and variability on Mars making use of the comprehensive chemistry implemented in the model. The diurnal variation shows large differences in the abundance between daytime and nighttime; and variable behavior depending on the atmospheric layer. The photolysis-driven ozone diurnal profile is obtained at the surface, whilst a sharp decrease is obtained in the upper troposphere at daytime, which originates from the large differences in atomic oxygen abundances between atmospheric layers. Finally, no clear anticorrelation between ozone and water vapor is found in the diurnal cycle, contrary to the strong correlation observed by orbiters on a seasonal timescale., This research has been supported by the Spanish Ministry of Economy and Competiveness(MINECO), under projects ESP2014-54256-C4-1-R and ESP2016-79612-C3-1-R.

This study attempts to infer aerosol vertical structure in the urban boundary layer using passive hyperspectral measurements. A spectral sorting technique is developed to retrieve total aerosol optical depth (AOD) and effective aerosol layer height (ALH) from hyperspectral measurements in the 1.27‐μm oxygen absorption band by the mountaintop Fourier Transform Spectrometer at the California Laboratory for Atmospheric Remote Sensing instrument (1,673 m above sea level) overlooking the LA basin. Comparison to AOD measurements from Aerosol Robotic Network and aerosol backscatter profile measurements from a Mini MicroPulse Lidar shows agreement, with coefficients of determination (r^2) of 0.74 for AOD and 0.57 for effective ALH. On average, the AOD retrieval has an error of 24.9% and root‐mean‐square error of 0.013, while the effective ALH retrieval has an error of 7.8% and root‐mean‐square error of 67.01 m. The proposed method can potentially be applied to existing and future satellite missions with hyperspectral oxygen measurements to constrain aerosol vertical distribution on a global scale.

The recently discovered TRAPPIST-1 system is exciting due to the possibility of several rocky, Earth-sized planets harboring liquid water on their surface. To assess the detectability of oceans on these planets, we model the disk-integrated phase curves and polarization signals for planets in this system for reflected starlight. We examine four cases: (1) dry planet, (2) cloud-covered planet, (3) planet with regional-scale oceans, and (4) planet with global oceans. Polarization signals are strongest for optically thin (≾ 0.1) atmospheres over widespread oceans, with the degree of polarization being up to 90% for a single planet or on the order of 100 parts per billion for the star–planet system. In cases where reflected light from different planets in a tightly packed system cannot be separated, observing in polarized light allows for up to a tenfold increase in star–planet contrast compared to photometric observations alone. However, polarization from other sources, such as atmospheric scattering and cloud variability, will pose major challenges to the detection of glint (specularly reflected starlight) polarization signals. Planned telescopes like LUVOIR may be capable of observing glint from Earth-like planets around Sun-like stars, and if equipped with a polarimeter can significantly improve our ability to detect and study oceans on rocky exoplanets.

Even though it was not designed as an exoplanetary research mission, the Deep Space Climate Observatory (DSCOVR) has been opportunistically used for a novel experiment, in which Earth serves as a proxy exoplanet. More than two years of DSCOVR Earth images were employed to produce time series of multi-wavelength, single-point light sources, in order to extract information on planetary rotation, cloud patterns, surface type, and orbit around the Sun. In what follows, we assume that these properties of the Earth are unknown, and instead attempt to derive them from first principles. These conclusions are then compared with known data about our planet. We also used the DSCOVR data to simulate phase angle changes, as well as the minimum data collection rate needed to determine the rotation period of an exoplanet. This innovative method of using the time evolution of a multi-wavelength, reflected single-point light source, can be deployed for retrieving a range of intrinsic properties of an exoplanet around a distant star.

Data from hyperspectral infrared sounders are routinely ingested worldwide by National Weather Centers (NWCs). The cloud-free fraction of this data is used for initializing forecasts which include profiles of temperature, water vapor, water cloud and ice cloud profiles on a global grid. Although the data from these sounders are sensitive to the vertical distribution of ice and liquid water in clouds, this information is not fully utilized. In the future, this information could be used for validating clouds in NWC models and for initializing forecasts. We evaluate how well the calculated radiances from hyperspectral Radiative Transfer Models (RTMs) compare to cloudy radiances observed by AIRS and to one another. Vertical profiles of the clouds, temperature and water vapor from ECMWF (European Center for Medium-range Weather Forecasting) were used as input for the RTMs. For non-frozen ocean day and night data, the histograms derived from the calculations by several RTMs at 900 cm(exp -1)have a better than 0.95 correlation with the histogram derived from the AIRS observations, with a bias relative to AIRS of typically less than 2 K. Differences in the cloud physics and cloud overlap assumptions result in little bias between the RTMs, but the standard deviation of the differences ranges from 6 to 12 K. Results at 2616 cm(exp -1) at night are reasonably consistent with results at 900 cm(exp -1). Except for RTMs which use full scattering calculations, the bias and histogram correlations at 2616 cm(exp -1) are inferior to those at 900 cm(exp -1) for daytime calculations.

The Alice instrument on NASA's New Horizons spacecraft observed an ultraviolet solar occultation by Pluto's atmosphere on 2015 July 14. The transmission vs. altitude was sensitive to the presence of N_2, CH_4, C_2H_2, C_2H_4, C_2H_6, and haze. We derived line-of-sight abundances and local number densities for the 5 molecular species, and line-of-sight optical depth and extinction coefficients for the haze. We found the following major conclusions: (1) We confirmed temperatures in Pluto's upper atmosphere that were colder than expected before the New Horizons flyby, with upper atmospheric temperatures near 65–68 K. The inferred enhanced Jeans escape rates were (3–7) × 10^(22) N_2 s^(−1) and (4–8) × 10^(25) CH_4 s^(−1) at the exobase (at a radius of ∼ 2900 km, or an altitude of ∼1710 km). (2) We measured CH_4 abundances from 80 to 1200 km above the surface. A joint analysis of the Alice CH_4 and Alice and REX N_2 measurements implied a very stable lower atmosphere with a small eddy diffusion coefficient, most likely between 550 and 4000 cm^2 s^(−1). Such a small eddy diffusion coefficient placed the homopause within 12 km of the surface, giving Pluto a small planetary boundary layer. The inferred CH_4 surface mixing ratio was ∼ 0.28–0.35%. (3) The abundance profiles of the “C_2H_x hydrocarbons” (C_2H_2, C_2H_4, C_2H_6) were not simply exponential with altitude. We detected local maxima in line-of-sight abundance near 410 km altitude for C_2H_4, near 320 km for C_2H_2, and an inflection point or the suggestion of a local maximum at 260 km for C_2H_6. We also detected local minima near 200 km altitude for C_2H_4, near 170 km for C_2H_2, and an inflection point or minimum near 170–200 km for C_2H_6. These compared favorably with models for hydrocarbon production near 300–400 km and haze condensation near 200 km, especially for C_2H_2 and C_2H_4 (Wong et al., 2017). (4) We found haze that had an extinction coefficient approximately proportional to N_2 density.

International audience; Recent measurements of methane (CH4) by the Mars Science Laboratory (MSL) now confront us with robust data that demand interpretation. Thus far, the MSL data have revealed a baseline level of CH4 (*0.4 parts per billion by volume [ppbv]), with seasonal variations, as well as greatly enhanced spikes of CH4 with peak abundances of *7 ppbv. What do these CH4 revelations with drastically different abundances and temporal signatures represent in terms of interior geochemical processes, or is martian CH4 a biosignature? Discerning how CH4 generation occurs on Mars may shed light on the potential habitability of Mars. There is no evidence of life on the surface of Mars today, but microbes might reside beneath the surface. In this case, the carbon flux represented by CH4 would serve as a link between a putative subterranean biosphere on Mars and what we can measure above the surface. Alternatively, CH4 records modern geochemical activity. Here we ask the fundamental question: how active is Mars, geochemically and/or biologically? In this article, we examine geological, geochemical, and biogeo- chemical processes related to our overarching question. The martian atmosphere and surface are an over- whelmingly oxidizing environment, and life requires pairing of electron donors and electron acceptors, that is, redox gradients, as an essential source of energy. Therefore, a fundamental and critical question regarding the possibility of life on Mars is, ‘‘Where can we find redox gradients as energy sources for life on Mars?’’ Hence, regardless of the pathway that generates CH4 on Mars, the presence of CH4, a reduced species in an oxidant-rich environment, suggests the possibility of redox gradients supporting life and habitability on Mars. Recent missions such as ExoMars Trace Gas Orbiter may provide mapping of the global distribution of CH4. To discriminate between abiotic and biotic sources of CH4 on Mars, future studies should use a series of diagnostic geochemical analyses, preferably performed below the ground or at the ground/atmosphere interface, including measurements of CH4 isotopes, methane/ethane ratios, H2 gas concentration, and species such as acetic acid. Advances in the fields of Mars exploration and instrumentation will be driven, augmented, and supported by an improved un- derstanding of atmospheric chemistry and dynamics, deep subsurface biogeochemistry, astrobiology, planetary geology, and geophysics. Future Mars exploration programs will have to expand the integration of complementary areas of expertise to generate synergistic and innovative ideas to realize breakthroughs in advancing our under- standing of the potential of life and habitable conditions having existed on Mars. In this spirit, we conducted a set of interdisciplinary workshops. From this series has emerged a vision of technological, theoretical, and meth- odological innovations to explore the martian subsurface and to enhance spatial tracking of key volatiles, such as CH4.

The Geostationary Fourier Transform Spectrometer (GeoFTS) is designed to measure high-resolution spectra of reflected sunlight in three near-infrared bands centered around 0.76, 1.6, and 2.3 μm and to deliver simultaneous retrievals of column-averaged dry air mole fractions of CO2, CH4, CO, and H2O (denoted XCO2, XCH4, XCO, and XH2O, respectively) at different times of day over North America. In this study, we perform radiative transfer simulations over both clear-sky and all-sky scenes expected to be observed by GeoFTS and estimate the prospective performance of retrievals based on results from Bayesian error analysis and characterization. We find that, for simulated clear-sky retrievals, the average retrieval errors and single-measurement precisions are < 0.2% for XCO2, XCH4, and XH2O, and < 2% for XCO, when the a priori values have a bias of 3% and an uncertainty of 3%. In addition, an increase in the amount of aerosols and ice clouds leads to a notable increase in the retrieval errors and slight worsening of the retrieval precisions. Furthermore, retrieval precision is a strong function of signal-to-noise ratio and spectral resolution. This simulation study can help guide decisions on the design of the GeoFTS observing system, which can result in cost-effective measurement strategies while achieving satisfactory levels of retrieval precisions. The simultaneous retrievals at different times of day will be important for more accurate estimation of carbon sources and sinks on fine spatiotemporal scales and for studies to better understand the close coupling between the carbon and water cycles.

HO_2 and OH, also known as HO_x, play an important role in controlling middle atmospheric O_3. Due to their photochemical production and short chemical lifetimes, HO_x are expected to respond rapidly to solar irradiance changes, resulting in O_3 variability. While OH solar cycle signals have been investigated, HO_2 studies have been limited by the lack of reliable observations. Here we present the first evidence of HO_2 variability during solar 27 day cycles by investigating the recently developed HO_2 data from the Aura Microwave Limb Sounder (MLS). We focus on 2012–2015, when solar variability is strong near the peak of Solar Cycle 24. The features of HO_2 variability, with the strongest signals at 0.01–0.068 hPa, correlate well with those of solar Lyman α. When continuous MLS OH observations are not available, the new HO_2 data could be a promising alternative for investigating HO_x variability and the corresponding impacts on O_3 and the climate.

We have obtained 3.3–3.4-μm spectro-images of Jupiter including CH_4 and H_3^+ emission lines from both polar regions at the Gemini North telescope. We find that the peak of the 3-μm CH_4 northern bright spot is located at ∼200° (SysIII) longitude, ∼20° west of the center of the 8-μm north-polar bright spot, and does not coincide with the 3-μm H_3^+ bright spot. We derive high temperatures (500–850 K) from CH_4 rotational lines on the bright spots of both polar regions, above the 1-μbar pressure level, while we find cooler temperatures (

Observations from Pioneer Venus and from SPICAV/SOIR aboard Venus Express (VEx) have shown the upper haze (UH) of Venus to be highly spatially and temporally variable, and populated by multiple particle size modes. Previous models of this system (e.g., Gao et al., 2014. Icarus 231, 83–98), using a typical temperature profile representative of the atmosphere (viz., equatorial VIRA profile), did not investigate the effect of temperature on the UH particle distributions. We show that the inclusion of latitude-dependent temperature profiles for both the morning and evening terminators of Venus helps to explain how the atmospheric aerosol distributions vary spatially. In this work we use temperature profiles obtained by two instruments onboard VEx, VeRa and SPICAV/SOIR, to represent the latitudinal temperature dependence. We find that there are no significant differences between results for the morning and evening terminators at any latitude and that the cloud base moves downwards as the latitude increases due to decreasing temperatures. The UH is not affected much by varying the temperature profiles; however, the haze does show some periodic differences, and is slightly thicker at the poles than at the equator. We also find that the sulphuric acid “rain” seen in previous models may be restricted to the equatorial regions of Venus, such that the particle size distribution is relatively stable at higher latitudes and at the poles.

The California Laboratory for Atmospheric Remote Sensing Fourier transform spectrometer (CLARS‐FTS) deployed at Mount Wilson, California, has been measuring column abundances of greenhouse gases in the Los Angeles (LA) basin in the near‐infrared spectral region since August 2011. CLARS‐FTS measures reflected sunlight and has high sensitivity to absorption and scattering in the boundary layer. In this study, we estimate the retrieval biases caused by aerosol scattering and present a fast and accurate approach to correct for the bias in the CLARS column averaged CO2 mixing ratio product, X_(CO2). The high spectral resolution of 0.06 cm^(−1) is exploited to reveal the physical mechanism for the bias. We employ a numerical radiative transfer model to simulate the impact of neglecting aerosol scattering on the CO_2 and O_2 slant column densities operationally retrieved from CLARS‐FTS measurements. These simulations show that the CLARS‐FTS operational retrieval algorithm likely underestimates CO_2 and O_2 abundances over the LA basin in scenes with moderate aerosol loading. The bias in the CO_2 and O_2 abundances due to neglecting aerosol scattering cannot be canceled by ratioing each other in the derivation of the operational product of X_(CO2). We propose a new method for approximately correcting the aerosol‐induced bias. Results for CLARS X_(CO2) are compared to direct‐Sun X_(CO2) retrievals from a nearby Total Carbon Column Observing Network (TCCON) station. The bias‐correction approach significantly improves the correlation between the X_(CO2) retrieved from CLARS and TCCON, demonstrating that this approach can increase the yield of useful data from CLARS‐FTS in the presence of moderate aerosol loading.

The Los Angeles megacity, which is home to more than 40% of the population in California, is the second largest megacity in the United States and an intense source of anthropogenic greenhouse gases (GHGs). Quantifying GHG emissions from the megacity and monitoring their spatiotemporal trends are essential to be able to understand the effectiveness of emission control policies. Here we measure carbon dioxide (CO2) and methane (CH4) across the Los Angeles megacity using a novel approach – ground-based remote sensing from a mountaintop site. A Fourier transform spectrometer (FTS) with agile pointing optics, located on Mount Wilson at 1.67 km above sea level, measures reflected near-infrared sunlight from 29 different surface targets on Mount Wilson and in the Los Angeles megacity to retrieve the slant column abundances of CO2, CH4 and other trace gases above and below Mount Wilson. This technique provides persistent space- and time-resolved observations of path-averaged dry-air GHG concentrations, XGHG, in the Los Angeles megacity and simulates observations from a geostationary satellite. In this study, we combined high-sensitivity measurements from the FTS and the panorama from Mount Wilson to characterize anthropogenic CH4 emissions in the megacity using tracer–tracer correlations. During the period between September 2011 and October 2013, the observed XCH4 : XCO2 excess ratio, assigned to anthropogenic activities, varied from 5.4 to 7.3 ppb CH4 (ppm CO2)−1, with an average of 6.4 ± 0.5 ppb CH4 (ppm CO2)−1 compared to the value of 4.6 ± 0.9 ppb CH4 (ppm CO2)−1 expected from the California Air Resources Board (CARB) bottom-up emission inventory. Persistent elevated XCH4 : XCO2 excess ratios were observed in Pasadena and in the eastern Los Angeles megacity. Using the FTS observations on Mount Wilson and the bottom-up CO2 emission inventory, we derived a top-down CH4 emission of 0.39 ± 0.06 Tg CH4 year−1 in the Los Angeles megacity. This is 18–61% larger than the state government's bottom-up CH4 emission inventory and consistent with previous studies.

Our observational study revealed that the precipitation increased over the wet area and decreased over the dry area during the past two decades. Here, we further investigate whether the current atmospheric models can quantitatively capture the characteristics of precipitation from the observation. The NASA Goddard Institute for Space Studies (GISS) model is used to examine the historic simulation of the precipitation, in which the historic greenhouse gases and aerosols are included in the radiative forcing. The consistency between the historic GISS simulation and the Global Precipitation Climatology Project (GPCP) precipitation suggests that the model can qualitatively capture the temporal trends of precipitation over the wet and dry areas. However, the precipitation trends are weaker in the model than in the observation. The observed trends of precipitation do not appear in the control simulation with the fixed concentrations of greenhouse gases and aerosols, which suggests that the global warming due to anthropogenic forcing can influence the temporal variations of precipitation over the wet and dry areas. Diagnostic studies of other variables from the model further suggest that enhanced rising air can increase the precipitation over the wet area.