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This paper focuses on the analysis of stratified steady periodic water waves that contain stagnation points. The initial step involves transforming the free-boundary problem into a quasilinear pseudodifferential equation through a conformal mapping technique, resulting in a periodic function of a single variable. By utilizing the theorems developed by Crandall and Rabinowitz, we establish the existence and formal stability of small-amplitude steady periodic capillary-gravity water waves in the presence of stratified linear flows. Notably, the stability of bifurcation solution curves is strongly influenced by the stratified nature of the system. Additionally, as the Bernoulli's function $\beta$ approaches critical values, we observe that the linearized problem exhibits a two-dimensional kernel. Consequently, we apply a bifurcation theorem due to Kielh\"{o}fer that incorporates multiple-dimensional kernels and parameters, which enables us to establish the existence of two-mode water waves. As far as we know, the two-mode water waves in stratified flow are first constructed by us. Finally, we demonstrate the presence of internal stagnation points within these waves., Comment: 24pp

Objective. The distribution of equal states (DES) quantifies amplitude fluctuations in biomedical signals. However, under certain conditions, such as a high resolution of data collection or special signal processing techniques, equal states may be very rare, whereupon the DES fails to measure the amplitude fluctuations. Approach. To address this problem, we develop a novel threshold DES (tDES) that measures the distribution of differential states within a threshold. To evaluate the proposed tDES, we first analyze five sets of synthetic signals generated in different frequency bands. We then analyze sleep electroencephalography (EEG) datasets taken from the public PhysioNet. Main results. Synthetic signals and detrend-filtered sleep EEGs have no neighboring equal values; however, tDES can effectively measure the amplitude fluctuations within these data. The tDES of EEG data increases significantly as the sleep stage increases, even with datasets covering very short periods, indicating decreased amplitude fluctuations in sleep EEGs. Generally speaking, the presence of more low-frequency components in a physiological series reflects smaller amplitude fluctuations and larger DES. Significance.The tDES provides a reliable computing method for quantifying amplitude fluctuations, exhibiting the characteristics of conceptual simplicity and computational robustness. Our findings broaden the application of quantitative amplitude fluctuations and contribute to the classification of sleep stages based on EEG data.

GRB 221009A is the brightest gamma-ray burst ever detected since the discovery of this kind of energetic explosions. However, an accurate measurement of the prompt emission properties of this burst is very challenging due to its exceptional brightness. With joint observations of \textit{Insight}-HXMT and GECAM-C, we made an unprecedentedly accurate measurement of the emission during the first $\sim$1800 s of GRB 221009A, including its precursor, main emission (ME, which dominates the burst in flux), flaring emission and early afterglow, in the hard X-ray to soft gamma-ray band from $\sim$ 10 keV to $\sim$ 6 MeV. Based on the GECAM-C unsaturated data of the ME, we measure a record-breaking isotropic equivalent energy ($E_{\rm iso}$) of $\bf \sim 1.5 \times 10^{55}$ erg, which is about eight times the total rest-mass energy of the Sun. The early afterglow data require a significant jet break between 650 s and 1100 s, most likely at $\sim950$ s from the afterglow starting time $T_{AG}$, which corresponds to a jet opening angle of $\sim {0.7^\circ} \ (\eta_\gamma n)^{1/8}$, where $n$ is the ambient medium density in units of $\rm cm^{-3}$ and $\eta_\gamma$ is the ratio between $\gamma$-ray energy and afterglow kinetic energy. The beaming-corrected total $\gamma$-ray energy $E_{\gamma}$ is $\sim 1.15 \times10^{51} \ (\eta_\gamma n)^{1/4}$ erg, which is typical for long GRBs. These results suggest that this GRB may have a special central engine, which could launch and collimate a very narrowly beamed jet with an ordinary energy budget, leading to exceptionally luminous gamma-ray radiation per unit solid angle. Alternatively, more GRBs might have such a narrow and bright beam, which are missed by an unfavorable viewing angle or have been detected without distance measurement., Comment: Submitted to National Science Review. This paper is under press embargo, contact the corresponding author for details

Quantum key distribution (QKD) can provide information theoretically secure key exchange even in the era of quantum computer. However, QKD requires the classical channel to be authenticated, and the current method is pre-sharing symmetric keys. For a QKD network of $n$ users, this method requires $C_n^2 = n(n-1)/2$ pairs of symmetric keys to realize pairwise interconnection. In contrast, with the help of mature public key infrastructure (PKI) and post-quantum cryptography (PQC) with quantum resistant security, each user only needs to apply for a digital certificate from certificate authority (CA) to achieve efficient and secure authentication for QKD. We only need to assume the short-term security of the PQC algorithm to achieve the long-term security of the distributed keys. Here, we experimentally verified the feasibility, efficiency and stability of the PQC algorithm in QKD authentication, and demonstrated the advantages when new users join the QKD network. Using PQC authentication we only need to believe the CA is safe, rather than all trusted relays. QKD combined with PQC authentication will greatly promote and extend the application prospects of quantum safe communication., Comment: 8 pages, 6 figures

Elastography ultrasound (EUS) provides additional bio-mechanical in-formation about lesion for B-mode ultrasound (BUS) in the diagnosis of breast cancers. However, joint utilization of both BUS and EUS is not popular due to the lack of EUS devices in rural hospitals, which arouses a novel modality im-balance problem in computer-aided diagnosis (CAD) for breast cancers. Current transfer learning (TL) pay little attention to this special issue of clinical modality imbalance, that is, the source domain (EUS modality) has fewer labeled samples than those in the target domain (BUS modality). Moreover, these TL methods cannot fully use the label information to explore the intrinsic relation between two modalities and then guide the promoted knowledge transfer. To this end, we propose a novel doubly supervised TL network (DDSTN) that integrates the Learning Using Privileged Information (LUPI) paradigm and the Maximum Mean Discrepancy (MMD) criterion into a unified deep TL framework. The proposed algorithm can not only make full use of the shared labels to effectively guide knowledge transfer by LUPI paradigm, but also perform additional super-vised transfer between unpaired data. We further introduce the MMD criterion to enhance the knowledge transfer. The experimental results on the breast ultra-sound dataset indicate that the proposed DDSTN outperforms all the compared state-of-the-art algorithms for the BUS-based CAD., Comment: Accepted by MICCAI 2020

We build a holographic $s$-wave conductor/superconductor model and an insulator/superconductor model in the four-dimensional conformal anomaly corrected~(CAC) AdS gravity. The effects of CAC parameter $\alpha$ are studied using both numerical and analytical methods in the probe approximation. Concretely, when the CAC parameter increases, the critical temperature increases for the conductor/superconductor phase transition, while the critical chemical potential decreases for the insulator/superconductor case, which suggests that the increasing CAC parameter enhances both superconducting phase transitions. Meanwhile, below the critical temperature or beyond the critical chemical potential, the scalar hair begins to condense, and the condensed phases are found to be thermodynamically stable. The critical behaviors obtained from numerics are confirmed by our analytical analysis. For the parameters we are considering, the energy gap in the conductor/superconductor model decreases monotonically by increasing the CAC parameter, while for the insulator/superconductor model the energy of quasiparticle excitations decreases with the CAC parameter., Comment: 24 pages, 6 figures

Metal powders with hierarchical nanostructures are always designed and fabricated by dealloying with or without combination of other manufacturing processes. However, they are mainly nanoporous metal powder and its derivations, and their monotonous nanostructures restrict their applications, so metal powders with novel nanostructures should be explored further for various applications. Herein, high energy mechanical milling and dealloying can be combined together for fabricating mass-produced metal powders with controllable nanostructures. As an example, a nanograins-attached and ultrathin Cu flake powder can be fabricated by high energy mechanical milling of a Cu-42wt.%Al powder mixture and subsequent dealloying. The dealloyed Cu powder particles have ultrathin flaky shapes with numerous Cu grains being attached to their surfaces, and the microstructure of the as-milled Cu-42wt.%Al powder particles and the dealloyed Cu particles is studied to elucidate the formation mechanism of the unique morphology of the dealloyed Cu powder.

The association of equal heartbeat intervals with cardiac conditions and the effect of the equality on permutation-based time irreversibility are investigated in this paper. We measure the distributions of equal heartbeat intervals under three conditions, namely congestive heart failure (CHF), healthy young and elderly, whose time irreversibility of heartbeats is detected by measuring the probabilistic difference between permutations instead of raw vectors. We demonstrate that heartbeats contain high rates of equal states, particularly the CHF with around 20% equalities, and the distributions of equal values discriminate the heartbeats at very short data length. The CHF have more equal values than the healthy young (p<1.47*10^{-15}) and elderly (p<2.48*10^{-11}), and the healthy young have less equalities than the elderly (p<3.16*10^{-4}). Time irreversibility considering equal values is promising to extract nonlinear behaviors of heartbeats, confirming the decreased nonlinear complexity of the diseased and aging heart rates, while that involving no equality leads to erroneous nonlinearity detection. In our contribution, we highlight the pathological or physiological information contained by the distribution of equal heartbeat intervals that might contribute to develop relevant biomarkers in the area of heart analysis, and demonstrate the effectiveness of equality-based time irreversibility in the nonlinearity detection of heartbeats.

Time irreversibility (temporal asymmetry) is one of fundamental properties that characterize the nonlinearity of complex dynamical processes, and our brain is a typical complex dynamical system manifested with nonlinearity. Two subtraction-based parameters, Ys and X2, are employed to measure the probabilistic differences of permutations instead of raw vectors for the simplified quantification of time irreversibility, which is validated by chaotic and reversible processes and the surrogate data. We show that it is equivalent to quantify time irreversibility by measuring probabilistic difference between the forward and its backward processes and between the symmetric permutations. And we detect time irreversibility of two groups of epileptic EEGs, from the Nanjing General Hospital (NJGH) and from the public Bonn epileptic database. In our contribution, NJGH epileptic EEGs during seizure-free intervals of have lower time irreversibility than the control data while those of the Bonn data sets have higher nonlinearity than the healthy brain electrical activities. For the inconsistent results, we conduct multi-scale analysis and elucidate from the circadian rhythms in epileptic nonlinearity, however, more targeted researches are needed to verify our assumptions or to determine if there are other reasons leading to the inconsistency., Comment: The results in the original paper might be misleading and need further consideration. Therefore, we would like to withdraw this manuscript

Based on the dynamics of single scalar field slow-roll inflation and the theory of reheating, we investigate the generalized natural inflationary (GNI) model. Concretely, we give constraints on the scalar spectral index $n_{s}$ and tensor-to scalar ratio $r$ for $\Lambda$CDM $+r$ model according to the latest data from Plack 2018 TT,TE,EE+lowE+lensing (P18) and BICEP2/Keck 2015 season (BK15), i.e., $n_{s}=0.9659\pm0.0044$ at $68\%$ confidence level (CL) and $r<0.0623$ at $95\%$CL. We find that the GNI model is favored by P18 plus BK15 in the ranges of $\log_{10}(f/M_{p})=0.62^{+0.17}_{-0.18}$ and $m=0.35^{+0.13}_{-0.23}$ at $68\%$CL. In addition, the corresponding predictions of the general and two-phase reheating are respectively discussed. It follows that the parameter $m$ has the significant effect on the model behaviors., Comment: 15 pages, 15 figures, accepted for publication in CPC

A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth’s radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth’s climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near–real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.

Stakeholders and end users with diverse backgrounds in atmospheric science gathered to provide the state of the science and user needs for operational atmospheric composition measurements to inform future NOAA low-Earth-orbit satellite missions.

In the probe limit, we numerically build a holographic $p$-wave superfluid model in the four-dimensional Lifshitz black hole coupled to a Maxwell-complex vector field. We observe the rich phase structure and find that the Lifshitz dynamical exponent $z$ contributes evidently to the effective mass of the matter field and dimension of the gravitational background. Concretely, we obtain the Cave of Winds appeared only in the five-dimensional anti-de Sitter~(AdS) spacetime, and the increasing $z$ hinders not only the condensate but also the appearance of the first-order phase transition. Furthermore, our results agree with the Ginzburg-Landau results near the critical temperature. In addition, the previous AdS superfluid model is generalized to the Lifshitz spacetime., Comment: 14 pages,5 figures, and 1 table, accepted by Phys. Lett. B

In the probe limit, we numerically construct a holographic p-wave superfluid model in the 4D and 5D AdS black holes coupled to a Maxwell-complex vector field. We find that, for the condensate with the fixed superfluid velocity, the results are similar to the s-wave cases in both 4D and 5D spacetimes. In particular, "The Cave of Winds" and the phase transition always being the second order take place in the 5D case. Moreover, we find the second-first order translating point $\frac{S_y}{\mu}$ increases with the mass squared. Furthermore, for the supercurrent with the fixed temperature, the results agree with the GL prediction near the critical temperature. In addition, this complex vector superfluid model is still a generalization of the SU(2) superfluid model, and also provides a holographic realization of the $He_3$ superfluid system., Comment: Typos corrected;Published in Phys. Rev. D

Concentrations of particulate aerosols and their vertical placement in the atmosphere determine their interaction with the Earth system and their impact on air quality. Space-based lidar, such as the Cloud–Aerosol Transport System (CATS) technology demonstration instrument, is well-suited for determining the vertical structure of these aerosols and their diurnal cycle. Through the implementation of aerosol-typing algorithms, vertical layers of aerosols are assigned a type, such as marine, dust, and smoke, and a corresponding extinction-to-backscatter (lidar) ratio. With updates to the previous aerosol-typing algorithms, we find that CATS, even as a technology demonstration, observed the documented seasonal cycle of aerosols, comparing favorably with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) space-based lidar and the NASA Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) model reanalysis. By leveraging the unique orbit of the International Space Station, we find that CATS can additionally resolve the diurnal cycle of aerosol altitude as observed by ground-based instruments over the Maritime Continent of Southeast Asia.

In the probe limit, we study the holographic $p$-wave phase transition in the Gauss-Bonnet gravity via numerical and analytical methods. Concretely, we study the influences of the external magnetic field on the Maxwell complex vector model in the five-dimensional Gauss-Bonnet-AdS black hole and soliton backgrounds, respectively. For the two backgrounds, the results show that the magnetic field enhances the superconductor phase transition in the case of the lowest Landau level, while the increasing Gauss-Bonnet parameter always hinders the vector condensate. Moreover, the Maxwell complex vector model is a generalization of the SU(2) Yang-Mills model all the time. In addition, the analytical results backup the numerical results. Furthermore, this model might provide a holographic realization for the QCD vacuum instability., Comment: 19 pages, 8 figures

The generalized $f(R)$ gravity with curvature-matter coupling in five-dimensional (5D) spacetime can be established by assuming a hypersurface-orthogonal spacelike Killing vector field of 5D spacetime, and it can be reduced to the 4D formulism of FRW universe. This theory is quite general and can give the corresponding results to the Einstein gravity, $f(R)$ gravity with both no-coupling and non-minimal coupling in 5D spacetime as special cases, that is, we would give the some new results besides previous ones given by Ref.\cite{60}. Furthermore, in order to get some insight into the effects of this theory on the 4D spacetime, by considering a specific type of models with $f_{1}(R)=f_{2}(R)=\alpha R^{m}$ and $B(L_{m})=L_{m}=-\rho$, we not only discuss the constraints on the model parameters $m$, $n$, but also illustrate the evolutionary trajectories of the scale factor $a(t)$, the deceleration parameter $q(t)$ and the scalar field $\epsilon(t)$, $\phi(t)$ in the reduced 4D spacetime. The research results show that this type of $f(R)$ gravity models given by us could explain the current accelerated expansion of our universe without introducing dark energy., Comment: arXiv admin note: text overlap with arXiv:0912.4581, arXiv:gr-qc/0411066 by other authors

By numerical and analytical methods, we study in detail the effects of the Lifshitz dynamical exponent $z$ on the vector condensate induced by an applied magnetic field in the probe limit. Concretely, in the presence of the magnetic field, we obtain the Landau level independent of $z$, and also find the critical value by coupling a Maxwell complex vector field and SU(2) field into a (3+1)-dimensional Lifshitz black hole, respectively. The research results show that for both two models with the lowest Landau level, the increasing $z$ improves the response of the critical temperature to the applied magnetic field even without the charge density, and the analytical results uphold the numerical results. In addition, we find even in the Lifshitz black hole, the Maxwell complex vector model is still a generalization of the SU(2) Yang-Mills model. Furthermore, we construct the square vortex lattice and discuss the implications of these results., Comment: Some arguments add; Small errors corrected; Fig.9 replotted; Published in PRD

Via numerical and analytical methods, the effects of the Lifshitz dynamical exponent $z$ on holographic superconductors are studied in some detail, including $s$ wave and $p$ wave models. Working in the probe limit, we find that the behaviors of holographic models indeed depend on concrete value of $z$. We obtain the condensation and conductivity in both Lifshitz black hole and soliton backgrounds with general $z$. For both $s$ wave and $p$ wave models in the black hole backgrounds, as $z$ increases, the phase transition becomes more difficult and the growth of conductivity is suppressed. For the Lifshitz soliton backgrounds, when $z$ increases ($z=1,~2,~3$), the critical chemical potential decreases in the $s$ wave cases but increases in the $p$ wave cases. For $p$ wave models in both Lifshitz black hole and soliton backgrounds, the anisotropy between the AC conductivity in different spatial directions is suppressed when $z$ increases. The analytical results uphold the numerical results., Comment: Typos corrected; Footnote added; References added; To be published in Nuclear Physics B

We will extend the study of the new generalized Chaplygin gas (NGCG) based on [JCAP 0601(2006)003]. Concretely, we will not only discuss the change rates of the energy densities and the energy transfer of this model, but also perform the $Om$ diagnostic to differentiate the $\Lambda$CDM model from the NGCG and the GCG models. Furthermore, in order to consider the influence of dark energy on the structure formation, we also present the evolution of growth index in this scenario with interaction., Comment: 9 pages, 5 figures

This work serves as the second of a two-part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multi satellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multichemical transport model (CTM) (GEOS-Chem, WRF-Chem, and CMAQ) outputs, and ground observations. In Part I of the study, an ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over non rural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125–300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and non rural areas, referred to as “extended ground truth” or EGT, for the present day. Lastly, we applied the KF technique to reduce the forecast bias for next day using the EGT. Our results find that the ensemble of bias-corrected daily PM2.5 from three CTMs for both today and next day show the best performance. Together, the two-part study develops a multimodel and multi-AOD bias-correction technique that has the potential to improve PM2.5 forecasts in both rural and non rural areas in near real time, and be readily implemented at state levels.

The widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Dark-Target (DT) aerosol product fails to accurately retrieve Aerosol Optical Depth (AOD) over shallow and turbid Coastal Waters (CWs). To fill in gaps, and to improve land to ocean AOD continuity, we developed a coastal water retrieval algorithm at a spatial resolution of 1 km (CW-1km). CW-1km relies on observed top-of-atmosphere reflectance at 2.1 μm (ρ2.1), both to derive AOD and to perform a spatial variation test that enhances the existing DT masks for clouds and land. We show that the CW-1km improves spatial continuity of AOD between land, coast, and open ocean, while also increasing AOD product availability by 47.0%. Comparing with 15 years of marine aerosol network measurements, CW-1km AODs are validated to have a normalized mean bias of 1.0%, which is much smaller than 17.6% for the original DT product.

The National Air Quality Forecast Capability (NAQFC) operated in U.S.’s National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matters with aerodynamic diameters less than 2.5μm (PM2.5) over the contiguous 48 U.S. states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions ( CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to the CMAQ’s Carbon Bond 5 (CB05)-Aero6 species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015.The simulated PM2.5 was improved from 0.18 to 0.37 and the mean bias was reduced from -6.74 μg/m3 to -2.96 μg/m3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study, and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the global model CLBCs, such as GEOS CLBCs, are not available.

This paper describes the third part of a series of investigations to develop algorithms for simultaneous retrieval of aerosol parameters and surface spectral reflectance from the data measured by GEOstationary Trace gas and Aerosol Sensor Optimization (GEO-TASO) instrument. Since the algorithm is designed for future hyperspectral and geostationary satellite sensors, such as Tropospheric Emissions: Monitoring of Pollution (TEMPO), it is applied to GEO-TASO data measured over the same area by different flights as part of the Korea-United Stated Air Quality Study (KORUS-AQ) field campaign in 2016. While GEO-TAOS has a spectral sampling interval of ~0.28 nm in the visible, its data is thinned through a band selection approach with consideration of atmospheric transmittance and different surface types, which yields 20 common spectral bands to be used by the algorithm. The algorithm starts with 4 common principal components (PCs) for surface spectral reflectance extracted from various spectral libraries, and the constraints of surface reflectance parameters and aerosol scattering models respectively from k- means clustering analysis of the Rayleigh-corrected GEO-TASO spectra and AERONET data. The algorithm then proceeds iteratively with an optimal estimation approach to update PCs and retrieve aerosol optical depth (AOD) until the best match between simulated and GEOS-TASO measured spectra is achieved. The spectral AODs are compared between those retrieved from GEO-TASO (x) and 7 AERONETS (y) in 440, 550, 550, 675 nm, respectively. The comparison reveals that iterative updates of surface spectral PCs (and so surface reflectance) yield significant enhancement in AOD retrievals, improving the mean linear fitting equations from y = 0.735x + 0.088 (without update of PCs) to y = 1.055x+ 0.01, and the Pearson correlation coefficient (𝑅𝑅2) from 0.54 to 0.76, respectively. Move case studies are need to further evaluate the algorithm for its application to TEMPO that carries a enhanced version of GEO-TASO instrument.

An accurate estimation of biomass burning emissions is 1 partially limited by the lack of knowledge of fire burning phase (smoldering vs. flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in nighttime scenes. In contrast, VIIRS 4 m moderate resolution band #13 (M13), though capable of detecting fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered by their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to the footprint of M-band pixels, accounting for onboard detector aggregation schemes and bowtie effect removals. The visible energy fraction (VEF) is subsequently introduced as an indicator of fire burning phase VEF is calculated as the ratio of visible light power (VLP) to FRP for each fire pixel retrieved from the VIIRS 750 m active fire product. A global distribution of VEF values, and thereby the fire phase, is quantitatively obtained, showing smaller VEF values in regions with mostly smoldering wildfires, such as peatland fires in Indonesia, larger VEF values in regions with flaming wildfires over grasslands and savannas in the sub-Sahelian region, and the largest VEF values associated with gas flaring in the Middle East. Mean VEF for different land cover types or regions is highly correlated with modified combustion efficiency (MCE). These results, together with a case study of the 2018 California Camp Fire, show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.

We present an algorithm for retrieving aerosol layer height (ALH) and aerosol optical depth (AOD) for smoke over vegetated land and water surfaces from measurements of the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). The algorithm uses Earth-reflected radiances in six EPIC bands in the visible and near-infrared and incorporates flexible spectral fitting that accounts for specifics of land and water surface reflectivity. The fitting procedure first determines AOD using EPIC atmospheric window bands (443 nm, 551 nm, 680nm, and 780 nm), then uses oxygen (O2) A and B bands (688 nm and 764 nm) to derive ALH, which represents an optical centroid altitude. ALH retrieval over vegetated surface primarily takes advantage of measurements in the O2B band. We applied the algorithm to EPIC observations of several biomass burning events over the United States and Canada in August 2017. We found that the algorithm can be used to obtain AOD and ALH multiple times daily over water and vegetated land surface. Validation is performed against aerosol extinction profiles detected by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and against AOD observed at nine Aerosol Robotic Network (AERONET) sites, showing, on average, an error of 0.58 km and a bias of -0.13 km in retrieved ALH and an error of 0.05 and a bias of 0.03 in retrieved AOD. Additionally, we show that the aerosol height information retrieved by the present algorithm can potentially benefit the retrieval of aerosol properties from EPIC’s ultraviolet (UV) bands.

Surface full-sky erythemal dose rate (EDR) from the Ozone Monitoring Instrument (OMI) at both satellite overpass time and local noon time is evaluated against ground measurements at 31 sites from the US Department of Agriculture's (USDA) UV-B Monitoring and Research Program (UVMRP) over the period of 2005–2017. We find that both OMI overpass and solar noon time EDR are highly correlated with the measured counterparts (with a linear correlation coefficient of 0.90 and 0.88, respectively). Although the comparison statistics are improved with a longer time window (0.5–1.0 h) for pairing surface and OMI measurements, both OMI overpass and local noon time EDRs have 7 % overestimation that is larger than 6 % uncertainty in the ground measurements and show different levels of dependence on solar zenith angle (SZA) and to lesser extent on cloud optical depth. The ratio of EDR between local noon and OMI overpass time is often (95 % in frequency) larger than 1 with a mean of 1.18 in the OMI product; in contrast, the same ratio from surface observation is normally distributed with 22 % of the times less than 1 and a mean of 1.38. This contrast in part reflects the deficiency in the OMI surface UV algorithm that assumes constant atmospheric conditions between overpass and noon time. The probability density functions (PDFs) for both OMI and ground measurements of noontime EDR are in statistically significant agreement, showing dual peaks at ∼20 and ∼200 mW/sq. m, respectively; the latter is lower than 220 mW/ sq. m, the value at which the PDF of daily EDR from ground measurements peaks, and this difference indicates that the largest EDR value for a given day may not often occur at local noon. Lastly, statistically significant positive trends of EDR are found in the northeastern US in OMI data, but opposite trends are found within ground-based data (regardless of sampling for either noontime or daily averages). While positive trends are consistently found between OMI and surface data for EDR over the southern Great Plains (Texas and Oklahoma), their values are within the uncertainty of ground measurements. Overall, no scientifically sound trends can be found among OMI data for aerosol total and absorbing optical depth, cloud optical depth and total ozone to explain coherently the surface UV trends revealed either by OMI or ground-based estimates; these data also cannot reconcile trend differences between the two estimates (of EDR from OMI and surface observations). Future geostationary satellites with better spatiotemporal resolution data should help overcome spatiotemporal sampling issues inherent in OMI data products and therefore improve the estimates of surface UV flux and EDR from space.