Author Correction: Space lidar observations constrain longwave cloud feedback.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Estimates of African Dust Deposition Along the Trans-Atlantic Transit Using the Decade-long Record of Aerosol Measurements from CALIOP, MODIS, MISR, and IASI.

Deposition of mineral dust into ocean fertilizes ecosystems and influences biogeochemical cycles and climate. In-situ observations of dust deposition are scarce, and model simulations depend on the highly parameterized representations of dust processes with few constraints. By taking advantage of satellites' routine sampling on global and decadal scales, we estimate African dust deposition flux and loss frequency (LF, a ratio of deposition flux to mass loading) along the trans-Atlantic transit using the three-dimensional distributions of aerosol retrieved by spaceborne lidar (CALIOP) and radiometers (MODIS, MISR, and IASI). On the basis of a ten-year (2007-2016) and basin scale average, the amount of dust deposition into the tropical Atlantic Ocean is estimated at 136 - 222 Tg yr-1. The 65-83% of satellite-based estimates agree with the in-situ climatology within a factor of 2. The magnitudes of dust deposition are highest in boreal summer and lowest in fall, whereas the interannual variability as measured by the normalized standard deviation with mean is largest in spring (28-41%) and smallest (7-15%) in summer. The dust deposition displays high spatial heterogeneity, revealing that the meridional shifts of major dust deposition belts are modulated by the seasonal migration of the intertropical convergence zone (ITCZ). On the basis of the annual and basin mean, the dust LF derived from the satellite observations ranges from 0.078 to 0.100 d-1, which is lower than model simulations by up to factors of 2 to 5. The most efficient loss of dust occurs in winter, consistent with the higher possibility of low-altitude transported dust in southern trajectories being intercepted by rainfall associated with the ITCZ. The satellite-based estimates of dust deposition can be used to fill the geographical gaps and extend time span of in-situ measurements, study the dust-ocean interactions, and evaluate model simulations of dust processes.

A New Look at the Daily Cycle of Trade Wind Cumuli.

A description of the daily cycle of oceanic shallow cumulus for undisturbed boreal winter conditions in the North Atlantic trades is presented. Modern investigation tools are used, including storm-resolving and large-eddy simulations, runover large domains in realistic configurations, and observations from in situ measurements and satellite-based retrievals. Models and observations clearly show pronounced diurnal variations in cloudiness, both near cloud base and below the trade inversion. The daily cycle reflects the evolution of two cloud populations: (i) a population of nonprecipitating small cumuli with weak vertical extent, which grows during the day and maximizes around sunset, and (ii) a population o deeper precipitating clouds with a stratiform cloud layer below the trade inversion, which grows during the night and maximizes just before sunrise. Previous studies have reported that cloudiness near cloud base undergoes weak variations on time scales longer than a day. However, here we find that it can vary strongly at the diurnal time scale. This daily cycle could serve as a critical test of the models' representation of the physical processes controlling cloudiness near cloud base, which is thought to be key for the determination of the Earth's climate response to warming.

Space lidar observations constrain longwave cloud feedback.

Some of the most challenging questions in atmospheric science relate to how clouds will respond as the climate warms. On centennial scales, the response of clouds could either weaken or enhance the warming due to greenhouse gas emissions. Here we use space lidar observations to quantify changes in cloud altitude, cover, and opacity over the oceans between 2008 and 2014, together with a climate model with a lidar simulator to also simulate these changes in the present-day climate and in a future, warmer climate. We find that the longwave cloud altitude feedback, found to be robustly positive in simulations since the early climate models and backed up by physical explanations, is not the dominant longwave feedback term in the observations, although it is in the model we have used. These results suggest that the enhanced longwave warming due to clouds might be overestimated in climate models. These results highlight the importance of developing a long-term active sensor satellite record to reduce uncertainties in cloud feedbacks and prediction of future climate.

Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations.

Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of tenuous aerosols. We conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.

Single scattering properties of non-spherical hydrosols modeled by spheroids.

The single scattering properties of hydrosols play an important role in the study of ocean optics, ocean color remote sensing, and ocean biogeochemistry research. Measurements show that hydrosols can be of various sizes and shapes, suggesting general non-spherical models should be considered for the study of single scattering properties of hydrosols. In this work, light scattering by non-spherical hydrosols are modeled by randomly oriented spheroids with the Amsterdam discrete dipole approximation (ADDA) code. We have defined two new parameters to quantify the degree of optical non-sphericity (DONS) and investigated the dependence of DONS on refractive index, size, and aspect ratio. For particles with non-unitary aspect ratios, the magnitude of DONS increases as the refractive index and particle size increase. The dependence of the backscattering fraction on the non-sphericity, size, and refractive index of hydrosols is also studied. It is found that the backscattering fraction is larger for smaller particles as well as for particles with higher refractive indices. Absorptive hydrosols generally have a lower backscattering fraction than non-absorptive hydrosols. This study of light scattering by non-spherical hydrosols would lead to better radiative transfer models in ocean waters and new remote sensing techniques of hydrosol compositions.

CALIPSO Lidar Calibration at 532 nm: Version 4 Nighttime Algorithm.

Data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP's other radiometric calibration procedures - i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime - depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30-34 km to 36-39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. As well, an enhanced strategy for filtering the radiation-induced noise from high energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved MERRA-2 model. An aerosol scattering ratio of 1.01 ± 0.01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2-3% lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne high spectral resolution lidar (HSRL) are reduced from 3.6% ± 2.2% in the version 3 data set to 1.6% ± 2.4 % in the version 4 release.

CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design.

The CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) level 3 aerosol profile product reports globally gridded, quality-screened, monthly mean aerosol extinction profiles retrieved by CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarization). This paper describes the quality screening and averaging methods used to generate the version 3 product. The fundamental input data are CALIOP level 2 aerosol extinction profiles and layer classification information (aerosol, cloud, and clear-air). Prior to aggregation, the extinction profiles are quality-screened by a series of filters to reduce the impact of layer detection errors, layer classification errors, extinction retrieval errors, and biases due to an intermittent signal anomaly at the surface. The relative influence of these filters are compared in terms of sample rejection frequency, mean extinction, and mean aerosol optical depth (AOD). The "extinction QC flag" filter is the most influential in preventing high-biases in level 3 mean extinction, while the "misclassified cirrus fringe" filter is most aggressive at rejecting cirrus misclassified as aerosol. The impact of quality screening on monthly mean aerosol extinction is investigated globally and regionally. After applying quality filters, the level 3 algorithm calculates monthly mean AOD by vertically integrating the monthly mean quality-screened aerosol extinction profile. Calculating monthly mean AOD by integrating the monthly mean extinction profile prevents a low bias that would result from alternately integrating the set of extinction profiles first and then averaging the resultant AOD values together. Ultimately, the quality filters reduce level 3 mean AOD by -24 and -31% for global ocean and global land, respectively, indicating the importance of quality screening.

The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm.

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) level 2 aerosol data products, released in November 2016, include substantial improvements to the aerosol subtyping and lidar ratio selection algorithms. These improvements are described along with resulting changes in aerosol optical depth (AOD). The most fundamental change in V4 level 2 aerosol products is a new algorithm to identify aerosol subtypes in the stratosphere. Four aerosol subtypes are introduced for the stratospheric aerosols: polar stratospheric aerosol (PSA), volcanic ash, sulfate/other, and smoke. The tropospheric aerosol subtyping algorithm was also improved by adding the following enhancements: (1) all aerosol subtypes are now allowed over polar regions, whereas the version 3 (V3) algorithm allowed only clean continental and polluted continental aerosols; (2) a new "dusty marine" aerosol subtype is introduced, representing mixtures of dust and marine aerosols near the ocean surface; and (3) the "polluted continental" and "smoke" subtypes have been renamed "polluted continental/smoke" and "elevated smoke", respectively. V4 also revises the lidar ratios for clean marine, dust, clean continental, and elevated smoke subtypes. As a consequence of the V4 updates, the mean 532 nm AOD retrieved by CALIOP has increased by 0.044 (0.036) or 52 % (40 %) for nighttime (daytime). Lidar ratio revisions are the most influential factor for AOD changes from V3 to V4, especially for cloud-free skies. Preliminary validation studies show that the AOD discrepancies between CALIOP and AERONET/MODIS (ocean) are reduced in V4 compared to V3.

Equivalence of internal and external mixture schemes of single scattering properties in vector radiative transfer.

Polarized radiation fields in a turbid medium are influenced by single-scattering properties of scatterers. It is common that media contain two or more types of scatterers, which makes it essential to properly mix single-scattering properties of different types of scatterers in the vector radiative transfer theory. The vector radiative transfer solvers can be divided into two basic categories: the stochastic and deterministic methods. The stochastic method is basically the Monte Carlo method, which can handle scatterers with different scattering properties explicitly. This mixture scheme is called the external mixture scheme in this paper. The deterministic methods, however, can only deal with a single set of scattering properties in the smallest discretized spatial volume. The single-scattering properties of different types of scatterers have to be averaged before they are input to deterministic solvers. This second scheme is called the internal mixture scheme. The equivalence of these two different mixture schemes of scattering properties has not been demonstrated so far. In this paper, polarized radiation fields for several scattering media are solved using the Monte Carlo and successive order of scattering (SOS) methods and scattering media contain two types of scatterers: Rayleigh scatterers (molecules) and Mie scatterers (aerosols). The Monte Carlo and SOS methods employ external and internal mixture schemes of scatterers, respectively. It is found that the percentage differences between radiances solved by these two methods with different mixture schemes are of the order of 0.1%. The differences of Q/I, U/I, and V/I are of the order of 10-5∼10-4, where I, Q, U, and V are the Stokes parameters. Therefore, the equivalence between these two mixture schemes is confirmed to the accuracy level of the radiative transfer numerical benchmarks. This result provides important guidelines for many radiative transfer applications that involve the mixture of different scattering and absorptive particles.

Vector radiative transfer model for coupled atmosphere and ocean systems including inelastic sources in ocean waters.

Inelastic scattering plays an important role in ocean optics. The main inelastic scattering mechanisms include Raman scattering, fluorescence by colored dissolved organic matter (FDOM), and fluorescence by chlorophyll. This paper reports an implementation of all three inelastic scattering mechanisms in the exact vector radiative transfer model for coupled atmosphere and ocean Systems (CAOS). Simulation shows that FDOM contributes to the water radiation field in the broad visible spectral region, while chlorophyll fluorescence is limited in a narrow band centered at 685 nm. This is consistent with previous findings in the literature. The fluorescence distribution as a function of depth and viewing angle is presented. The impacts of fluorescence to the degree of linear polarization (DoLP) and orientation of the polarization ellipse (OPE) are studied. The DoLP is strongly influenced by inelastic scattering at wavelengths with strong inelastic scattering contribution. The OPE is less affected by inelastic scattering but it has a noticeable impact, in terms of the angular region of positive polarization, in the backward direction. This effect is more apparent for deeper water depth.

Quantifying the low bias of CALIPSO's column aerosol optical depth due to undetected aerosol layers.

The CALIOP data processing scheme only retrieves extinction profiles in those portions of the return signal where cloud or aerosol layers have been identified by the CALIOP layer detection scheme. In this study we use two years of CALIOP and MODIS data to quantify the aerosol optical depth of undetected weakly backscattering layers. Aerosol extinction and column-averaged lidar ratio is retrieved from CALIOP Level 1B (Version 4) profile using MODIS AOD as a constraint over oceans from March 2013 to February 2015. To quantify the undetected layer AOD (ULA), an unconstrained retrieval is applied globally using a lidar ratio of 28.75 sr estimated from constrained retrievals during the daytime over the ocean. We find a global mean ULA of 0.031 ± 0.052. There is no significant difference in ULA between land and ocean. However, the fraction of undetected aerosol layers rises considerably during daytime, when the large amount of solar background noise lowers the signal to noise ratio (SNR). For this reason, there is a difference in ULA between day (0.036 ± 0.066) and night (0.025 ± 0.021). ULA is larger in the northern hemisphere and relatively larger at high latitudes. Large ULA for the Polar Regions is strongly related to the cases where the CALIOP Level 2 Product reports zero AOD. This study provides an estimate of the complement of AOD that is not detected by lidar, and bounds the CALIOP AOD uncertainty to provide corrections for science studies that employ the CALIOP Level 2 AOD.

Emerging Technologies and Synergies for Airborne and Space-Based Measurements of Water Vapor Profiles.

A deeper understanding of how clouds will respond to a warming climate is one of the outstanding challenges in climate science. Uncertainties in the response of clouds, and particularly shallow clouds, have been identified as the dominant source of the discrepancy in model estimates of equilibrium climate sensitivity. As the community gains a deeper understanding of the many processes involved, there is a growing appreciation of the critical role played by fluctuations in water vapor and the coupling of water vapor and atmospheric circulations. Reduction of uncertainties in cloud-climate feedbacks and convection initiation as well as improved understanding of processes governing these effects will result from profiling of water vapor in the lower troposphere with improved accuracy and vertical resolution compared to existing airborne and space-based measurements. This paper highlights new technologies and improved measurement approaches for measuring lower tropospheric water vapor and their expected added value to current observations. Those include differential absorption lidar and radar, microwave occultation between low-Earth orbiters, and hyperspectral microwave remote sensing. Each methodology is briefly explained, and measurement capabilities as well as the current technological readiness for aircraft and satellite implementation are specified. Potential synergies between the technologies are discussed, actual examples hereof are given, and future perspectives are explored. Based on technical maturity and the foreseen near-mid-term development path of the various discussed measurement approaches, we find that improved measurements of water vapor throughout the troposphere would greatly benefit from the combination of differential absorption lidar focusing on the lower troposphere with passive remote sensors constraining the upper-tropospheric humidity.

Seasonally Transported Aerosol Layers over Southeast Atlantic are Closer to Underlying Clouds than Previously Reported.

From June to October, low-level clouds in the Southeast (SE) Atlantic often underlie seasonal aerosol layers transported from African continent. Previously, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) 532 nm lidar observations have been used to estimate the relative vertical location of the above-cloud aerosols (ACA) to the underlying clouds. Here, we show new observations from NASA's Cloud-Aerosol Transport System (CATS) lidar. Two seasons of CATS 1064 nm observations reveal that the bottom of the ACA layer is much lower than previously estimated based on CALIPSO 532nm observations. For about 60% of CATS nighttime ACA scenes, the aerosol layer base is within 360 m distance to the top of the underlying cloud. Our results are important for future studies of the microphysical indirect and semi-direct effects of ACA in the SE Atlantic region.

Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors.

We estimated global fine particulate matter (PM2.5) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically based satellite-derived PM2.5 estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998-2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM2.5 estimates were highly consistent (R(2) = 0.81) with out-of-sample cross-validated PM2.5 concentrations from monitors. The global population-weighted annual average PM2.5 concentrations were 3-fold higher than the 10 µg/m(3) WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM2.5 data sources can yield valuable improvements to PM2.5 characterization on a global scale.

Contribution of Raman scattering to polarized radiation field in ocean waters.

We have implemented Raman scattering in a vector radiative transfer model for coupled atmosphere and ocean systems. A sensitivity study shows that the Raman scattering contribution is greatest in clear waters and at longer wavelengths. The Raman scattering contribution may surpass the elastic scattering contribution by several orders of magnitude at depth. The degree of linear polarization in water is smaller when Raman scattering is included. The orientation of the polarization ellipse shows similar patterns for both elastic and inelastic scattering contributions. As polarimeters and multipolarization-state lidars are planned for future Earth observing missions, our model can serve as a valuable tool for the simulation and interpretation of these planned observations.

Inherent optical properties of the coccolithophore: Emiliania huxleyi.

A realistic nonspherical model for Emiliania huxleyi (EHUX) is built, based on electron micrographs of coccolithophore cells. The Inherent Optical Properties (IOP) of the EHUX are then calculated numerically by using the discrete dipole approximation. The coccolithophore model includes a near-spherical core with the refractive index of 1.04 + m(i)j, and a carbonate shell formed by smaller coccoliths with refractive index of 1.2 + m(i)j, where m(i) = 0 or 0.01 and j(2) = -1. The reported IOP are the Mueller scattering matrix, backscattering probability, and depolarization ratio. Our calculation shows that the Mueller matrices of coccolithophores show different angular dependence from those of coccoliths.

Method for reconstructing atmospheric optical parameters from the data of polarization lidar sensing.

Inversion of polarization lidar sensing data based on the form of the lidar sensing equation with allowance for contributions from multiple-scattering calls for a priori information on the scattering phase matrix. In the present study the parameters of the Stokes vectors for various propagation media, including those with the scattering phase matrices that vary along the measuring range, are investigated. It is demonstrated that, in spaceborne lidar sensing, a simple parameterization of the multiple-scattering contribution is applicable and the polarization signal's characteristics depend mainly on the lidar and depolarization ratios, whereas differences in the angular dependences of the matrix components are no longer determining factors. An algorithm for simultaneous reconstruction of the profiles of the backscattering coefficient and depolarization and lidar ratios in an inhomogeneous medium is suggested. Specific features of the methods are analyzed for the examples of interpretation of lidar signal profiles calculated by the Monte Carlo method and are measured experimentally.

Sensitivity of the backscattering Mueller matrix to particle shape and thermodynamic phase.

The Mueller matrix (M) corresponding to the phase matrix in the backscattering region (scattering angles ranging from 175 degrees to 180 degrees) is investigated for light scattering at a 0.532-microm wavelength by hexagonal ice crystals, ice spheres, and water droplets. For hexagonal ice crystals we assume three aspect ratios (plates, compact columns, and columns). It is shown that the contour patterns of the backscattering Mueller matrix elements other than M11, M44, M14, and M41 depend on particle geometry; M22 and M33 are particularly sensitive to the aspect ratio of ice crystals. The Mueller matrix for spherical ice particles is different from those for nonspherical ice particles. In addition to discriminating between spherical and nonspherical particles, the Mueller matrix may offer some insight as to cloud thermodynamic phase. The contour patterns for large ice spheres with an effective size of 100 microm are substantially different from those associated with small water droplets with an effective size of 4 microm.