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Currently there is a tremendous gap in observations of global air pressure fields although many satellite remote sensing techniques have been developed in measuring certain atmospheric variables such as temperature and moisture in last few decades. Air pressure is the key variable for the Earth's dynamic fields. This study explores the potential of global surface air pressure measurements using a satellite active microwave sensing technique, namely the Differential-absorption BArometric Radar (DiBAR), to improve weather forecasts, particularly severe weather such as typhoon predictions. The research team at NASA Langley has developed a prototype instrument and demonstrated its performance through ground and airborne experiments. Spacebome capability of this measurement approach will significantly improve typhoon and severe weather forecasts.

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Warming in the Arctic is larger than the global average. A primary reason for this Arctic Amplification is the albedo feedback. The contrasting albedo of sea ice and dark melted surface areas is the key component of albedo feedback. Cloud coverage over the changing surface and the response of the clouds to the changing surface conditions will modify the change in planetary albedo when sea ice melts. Space-based lidar measurements provide a unique opportunity for cloud measurements in the Arctic. The response of clouds to the changing sea ice concentration was directly observed. Based on CALIPSO satellite observations of cloud properties, this study found that cloud coverage in ice-free regions in the Arctic linearly increased with the area of ice-free water during the melt seasons in the past 10 years, while sea ice coverage varies significantly year-to-year. The observations suggest that when sea-ice retreats, cloud fraction of the ice-free region remains fixed at nearly 81%. The high cloud coverage over melted areas significantly reduces the albedo feedback. These results indicate that space-based lidar cloud and surface observations of the Arctic can help constrain and improve climate models.

Superthin clouds with optical depths smaller than ~ 0.3 exist globally and can seriously affect the remote sensing of aerosols, surface temperature, and atmospheric composition. Failing to detect these clouds, the sea-surface temperature retrieved from NASA's Atmospheric Infrared Sounder (AIRS) satellite data is ~ 5–10 K lower than true values at tropical and midlatitude regions, where these clouds frequently exist. Unfortunately, superthin clouds generally cannot be detected by passive satellite instruments that use only total intensity for measurements. Long-term global surveys of superthin clouds using space-borne lidars are limited by the large operational cost and narrow field of view of these active instruments. This chapter reviews the algorithm for remote sensing of superthin clouds based on our previous study results ( Sun et al., 2014 , Sun et al., 2015 ), which show that superthin clouds can be well detected by a polarimetric imager facing toward the backscattering direction of sunlight, exploiting a distinct, characterizing feature of the angle of linear polarization of the backscattered solar radiation (NASA Technology GSC-17392-1). If implemented for satellite remote sensing of the Earth-atmosphere system, this technology will greatly improve the detection of superthin clouds and tremendously impact the remote sensing of clouds, aerosols, surface temperature, atmospheric composition gases, and thus significantly improving data for climate modeling.

International audience; Earth observing systems have proven to be a unique source of long-term synoptic information on numerous physical, chemical and biological parameters on a global scale. Merging this information for integrated studies that peruse key questions about the ocean-atmosphere interface is, however, very challenging. Such studies require interdisciplinary frameworks and novel insights into ways to address the problem. We present here a perspective review on how current and emerging remote sensing technologies could help address two scientific questions within the Surface Ocean-Lower Atmosphere Study (SOLAS) science plan: (1) to what extent doesupper-ocean biology affect the composition and radiative properties of the marine boundary layer; and (2) to what extent does upper-ocean turbulence drive fluxes of mass and energy at the air-sea interface. We provide a thorough review of how these questions have been addressed and discuss novel potential avenues using multiplatform space-borne missions, from visible to microwave, active and passive sensors.

Forming parts from the flat fibre-metal laminates (FMLs) is very attractive to reduce the process cycle and labor cost. In this study, laser peen forming with the adaptability to produce large complex shapes is proposed to forming FMLs. Strip samples of glass laminate aluminum reinforced epoxy with different fibre orientations are prepared for experiments. The experimental results provide that the convex bending can be produced by the scanned high dynamic loading from laser irradiations. The bending is favorable to generate in the direction perpendicular to the unidirectional orientated fibres. Increasing the scanning times of arrayed laser shocks can increase the bending deformation to reach a very small saturated radius of curvature. But the risk of delamination failure is observed at the metal/fibre interface. By employing the chemical etching, the plastic deformation in the samples is found to generate in the top and bottom aluminum layers and the upper fibre layer. The study has demonstrated that the high dynamic loading of laser peen forming is a practical pathway to produce bending deformation with the sharp radius of curvature, which would be very attractive to various industrial applications.

Laser peen forming is a viable means for flexible shaping and adjusting of metal plate. The prestress is effective and useful to improve its formability. Experiments and numerical modeling are performed to investigate the effect of elastic prestress on the deformed shape generated by laser peen forming of aluminum alloy of 2024-T351. The experiments with prestressing laser peen forming are implemented in one direction of square samples by applying simple bending. A newly developed eigenstrain-based modeling procedure is introduced to simulate the prestress effects on the bending deformation and residual stresses. The boundary conditions of displacement are proposed to define in the explicit model to include the prestress effect. The numerical model is validated to be an effective and efficient tool for the predictions of deformed shape and residual stresses. Both experiments and model predictions provide that the radius of curvature in the direction of prebending can be greatly decreased by the increase of prebending curvature because much more in-plane plastic strains are generated during laser shocking. The scanning strategy is one important factor to generate the difference of bending in two directions besides prebending and spatial decay of shock pressure. The compressive residual stresses are observed to generate both at the top and at the bottom surfaces of samples. The increase of prebending curvature can increase the compressive residual stresses values at the top surface. And laser peen forming both with and without prestress is observed to have little effect on the surface roughness.

Sea level pressure (SLP) is an important variable in regulating hurricane motion. However, SLP generally cannot be measured in open oceans due to limited buoys. Because of the potential availability of an O 2 -band differential absorption radar for sea surface barometry, we investigate the value of assimilating various patterns of SLP from such a system on hurricane prediction using the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation system (3DVAR) based on Observing System Simulation Experiments (OSSEs). An important objective of this series of study is to explore the potential to use space and airborne sea surface air pressure measurements from an O 2 -band differential absorption radar currently under development for server weather including hurricane forecasts. The surface pressure patterns include an area of SLP, and a band of SLP either through the center or tangent to the hurricane position; the latter two distributions are similar to what could be obtained from the differential absorption radar system, which could be installed on spaceborne satellites and/or mounted on reconnaissance aircraft. In the banded pressure cases, we propose a vortex reconstruction technique based on surface pressure field. Assimilating observations from the reconstructed surface pressure leads to a better representation of initial SLP and vertical cross-section of wind, relative to the control where no data is assimilated and to the assimilation without vortex reconstruction. In eight of the nine OSSEs simulations on three hurricanes with three leading times of integration, which cover a wide range of initial minimum SLP from 951 to 1011 hPa, substantial improvements are found not only in the hurricane track and position, but also in the hurricane intensity, in terms of the SLP and maximum surface wind. The only case without significant improvement is resulted from the very weak initial condition (SLP 1011 hPa), which had no clear indication of tropical disturbance at the stage for initialization. The improvements of assimilation are generally enhanced for the stronger hurricanes whose differences in initial minimum SLP between nature run and control are larger.

This is the second part on assessing the impacts of assimilating various distributions of sea-level pressure (SLP) on hurricane simulations, using the Weather and Research Forecast (WRF) three dimensional variational data assimilation system (3DVAR). One key purpose of this series of study is to explore the potential of using remotely sensed sea surface barometric data from O2-band differential absorption radar system currently under development for server weather including hurricane forecasts. In this part II we further validate the conclusions of observational system simulation experiments (OSSEs) in the part I using observed SLP for three hurricanes that passed over the Florida peninsula. Three SLP patterns are tested again, including all available data near the Florida peninsula, and a band of observations either through the center or tangent to the hurricane position. Before the assimilation, a vortex SLP reconstruction technique is employed for the use of observed SLP as discussed in the part I. In agreement with the results from OSSEs, the performance of assimilating SLP is enhanced for the two hurricanes with stronger initial minimum SLP, leading to a significant improvement in the track and position relative to the control where no data are assimilated. On the other hand, however, the improvement in the hurricane intensity is generally limited to the first 24–48 h of integration, while a high resolution nested domain simulation, along with assimilation of SLP in the coarse domain, shows more profound improvement in the intensity. A diagnostic analysis of the potential vorticity suggests that the improved track forecasts are attributed to the combined effects of adjusting the steering wind fields in a consistent manner with having a deeper vortex, and the associated changes in the convective activity.

The top-of-atmosphere (TOA) radiation field from a coupled atmosphere-ocean system (CAOS) includes contributions from the atmosphere, surface, and water body. Atmospheric correction of ocean color imagery is to retrieve water-leaving radiance from the TOA measurement, from which ocean bio-optical properties can be obtained. Knowledge of the absolute and relative magnitudes of water-leaving signal in the TOA radiation field is important for designing new atmospheric correction algorithms and developing retrieval algorithms for new ocean biogeochemical parameters. In this paper we present a systematic sensitivity study of water-leaving contribution to the TOA radiation field, from 340 nm to 865 nm, with polarization included. Ocean water inherent optical properties are derived from bio-optical models for two kinds of waters, one dominated by phytoplankton (PDW) and the other by non-algae particles (NDW). In addition to elastic scattering, Raman scattering and fluorescence from dissolved organic matter in ocean waters are included. Our sensitivity study shows that the polarized reflectance is minimized for both CAOS and ocean signals in the backscattering half plane, which leads to numerical instability when calculating water leaving relative contribution, the ratio between polarized water leaving and CAOS signals. If the backscattering plane is excluded, the water-leaving polarized signal contributes less than 9% to the TOA polarized reflectance for PDW in the whole spectra. For NDW, the polarized water leaving contribution can be as much as 20% in the wavelength range from 470 to 670 nm. For wavelengths shorter than 452 nm or longer than 865 nm, the water leaving contribution to the TOA polarized reflectance is in general smaller than 5% for NDW. For the TOA total reflectance, the water-leaving contribution has maximum values ranging from 7% to 16% at variable wavelengths from 400 nm to 550 nm from PDW. The water leaving contribution to the TOA total reflectance can be as large as 35% for NDW, which is in general peaked at 550 nm. Both the total and polarized reflectances from water-leaving contributions approach zero in the ultraviolet and near infrared bands. These facts can be used as constraints or guidelines when estimating the water leaving contribution to the TOA reflectance for new atmospheric correction algorithms for ocean color imagery.

Satellite passive ocean color instruments have provided an unbroken ∼20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

Regular photon sieve (PS) may only have up to ~25% transmission of light. The low transmission limits its applications in many fields such as satellite remote sensing when the reflected light incident on the PS is relatively weak. Binary PS was developed to overcome the low transmission problem of PS. However, binary PS which involves using different optical materials/thicknesses in different zones of the PS at a nanometer or micron scale, is not easy to manufacture. Therefore, in this study, we developed a fully transparent PS concept. We can use laser photolithography to simply make holes on a sheet of fully transparent material. With specifically designed optical thickness and PS-patterned pinholes, the transparent sheet can effectively focus light to its focal point. This concept is validated both by the finite-difference time domain (FDTD) modeling and by laboratory prototypes in this study.

Lidar remote sensing based on visible wavelength is one of the only way to penetrate the water surface and to obtain range resolved information of the ocean surface mixed layer at the synoptic scale. Accurate measurement of the mixed layer properties is important for ocean weather forecast and to assist the optimal deployment of military assets. Turbulence within the mixed layer also plays an important role in climate variability as it also influences ocean heat storage and algae photosynthesis (Sverdrup 1953, Behrenfeld 2010). As of today, mixed layer depth changes are represented in the models through various parameterizations constrained mostly by surface properties like wind speed, surface salinity and sea surface temperature. However, cooling by wind and rain can create strong gradients (0.5C) of temperature between the submillimeter surface layer and the subsurface layer (Soloviev and Lukas, 1997) which will manifest itself as a low temperature bias in the observations. Temperature and salinity profiles are typically used to characterize the mixed layer variability (de Boyer Montegut et al. 2004) and are both key components of turbulence characterization (Hou 2009). Recently, several research groups have been investigating ocean temperature profiling with laser remote sensing based either on Brillouin (Fry 2012, Rudolf and Walther 2014) or Raman scattering (Artlett and Pask 2015, Lednev et al. 2016). It is the continuity of promising research that started decades ago (Leonard et al. 1979, Guagliardo and Dufilho 1980, Hirschberg et al. 1984) and can benefit from the current state of laser and detector technology. One aspect of this research that has not been overlooked (Artlett and Pask 2012) but has yet to be revisited is the impact of temperature on vibrational Raman polarization (Chang and Young, 1972). The TURBulence Ocean Lidar is an experimental system, aimed at characterizing underwater turbulence by examining various Stokes parameters. Its multispectral capability in both emission (based on an optical parametric oscillator) and detection (optical filters) provide flexibility to measure the polarization signature of both elastic and inelastic scattering. We will present the characteristics of TURBOL and several results from our laboratory and field experiments with an emphasis on temperature profiling capabilities based on vibrational Raman polarization. We will also present other directions of research related to this activity.

International audience; This paper describes the development and validation of a method to accurately identify snow/ice cover, surface melting, land surface and open water in polar regions using polar-orbiting Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar measurements from the Cloud and Aerosol Lidar and Infrared Pathfinder Observation (CALIPSO) mission. The technique is based on the relationship between integrated attenuated backscatter color ratio and integrated depolarization ratio, and is proven to efficiently separate snow/ice cover and surface melting from open water and land surfaces. The method has been applied to 10 years (2006–2016) of CALIOP data to study the seasonal and inter-annual variability of Arctic sea ice cover and its declining trend. Results show that the area fraction of snow cover over land at latitudes > 60°N varied between 0.9 during winter and 0.1 in summer. The CALIOP observations of Arctic sea ice cover exhibit a strong seasonal cycle and significant inter-annual variability, which are consistent with the passive microwave-based sea ice results. The > 10 years of CALIOP continuous observations of the snow/ice cover will benefit the communities modeling snow/ice melting and climate change.

Some recent studies reported expansion of the Earth׳s tropical regime in the past few decades. The poleward expansion of the Hadley cell is a strong indication of the warming of the globe. The extent of Hadley cell also has very important implications to the climate of dry subtropical regions because of the prevalence of precipitation in the deep tropical belt. Determination of the Hadley circulation especially its extent has great significance for monitoring global climate change and for the subtropical climate studies. Although many methods have been developed in recent years, reliable measurement of the extent of Hadley cell is still an issue in climate studies. This letter shows that the extent of the Hadley cell could reliably be estimated by measuring the height of the uppermost super-thin clouds in the troposphere with space-borne lidar. Through consecutive multi-year measurements of the height of the uppermost super-thin clouds, a good estimation of the expansion of the Hadley cell could be obtained.

Laser peen texturing (LPT), which is a new surface texturing technology, was proposed to fabricate micro-dimple arrays on copper surface. Pin-on-disk experiments were conducted under different normal loads and sliding speeds to investigate friction and wear behaviors of untextured and textured samples in starved lubrication. It was found that friction performance of the surface is improved significantly after LPT. Microscope observation and EDS analysis showed that textured surface could reduce both abrasive and adhesive wear as compared to untextured surface. Results also indicated that an optimum texture density might exist at which surface shows the best friction and wear behavior.

Multi-platform and multi-sensor observations are used to study the impacts of mineral dust on ice clouds of tropical deep convection systems based on one massive Sahara dust event. The comparisons of cloud properties between dust-laden and dust-free conditions support the hypothesis that the presence of large concentrations of mineral dust produces more ice particles at warmer temperature through heterogeneous nucleation processes. Water vapor competition limits ice particles' growth and results in relatively small sizes of ice particles and a narrow distribution of effective particle diameter in non-precipitating ice clouds, particularly at upper layer with temperatures colder than − 40 to − 50 °C. On the other hand, precipitating ice clouds with sufficient water vapor supply have greater ice water paths under dust-laden conditions than under dust-free conditions. The results also suggest that mineral dusts may invigorate the convection and enhance water vapor supply in deep convective precipitating clouds, lifting ice particles to higher altitudes. Additional study illustrates that the observed microphysical changes of ice clouds in the deep convection systems are not simply due to the differences of large-scale dynamics and thermodynamics.

Optical and microphysical properties for optically thin ice clouds are retrieved from one year of collocated Aqua/MODIS and CALIPSO/CALIOP measurements in 2008. The values of optical thickness τ and effective particle size Deff are inferred from MODIS measurements at three infrared (IR) bands located at 8.5, 11, and 12 µm in conjunction with collocated CALIOP cloud boundary altitudes and the MERRA atmospheric profile datasets. The τ values inferred from MODIS IR window measurements are insensitive to the pre-assumed particle and habit distributions. Based on near-IR measurements at 1.38 μm and the IR-based τ, a new method is developed to infer the scattering phase functions over both ocean and land. A comparison between theoretically calculated phase functions and the retrieved counterparts demonstrates that roughened solid columns provide the best match for cirrus clouds over ocean, whereas droxtals may exist in optically thin cirrus clouds. The best-fitted phase functions are generated using appropriate habit mixtures to match the inferred phase functions. The phase function resulting from a mixture of 55% severely roughened solid columns, 35% severely roughened droxtals, and 10% smooth aggregates almost perfectly matches the mean phase function value retrieved over ocean. The asymmetry factor based on the oceanic best-fitted phase functions is 0.778 at a wavelength of 0.65 μm. However, it is difficult to find an appropriate habit recipe to fit the inferred phase function over land. This may be caused by the relatively large uncertainties associated with τ retrievals over land. The retrieval of Deff shows that optically thin cirrus clouds consist of smaller ice particles in comparison with optically thicker ice clouds. The mean Deff values of optically thin ice clouds over land and ocean are 41 μm and 48 μm, respectively.

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

Laser peen forming (LPF) is a novel flexible process by utilizing pulse laser to induce mechanical deformation on the specimen surface. It is of great importance to quantitatively evaluate the geometry effect on deforming behavior in LPF for both shape forming and distortion correction. This is very helpful for process planning to improve the shaping efficiency and accuracy. In this study, analytical modeling and numerical simulation are carried out to investigate the geometry effect of axis with a simplified shape. Considering that plate deformation by uniformed LPF can be assumed as beam bending with an arc shape, an analytical model is proposed to analyze its geometry effect by utilizing equivalent bending moment. The model is validated by the numerical model of LPF developed based on the eigenstrain. The result shows the developed analytical model can provide a consistent prediction of axis geometry effect, but the accuracy is depending on the initial radius of axis arc. By using the analytical modeling of LPF, the bending characteristic of LPF on the double curvature plate is studied. The prediction is more accurate when the radius of axis arc is large. When the radius of axis arc is less than 5000 mm, the axis has some effect on the bending of LPF, with the increase of the axis radius, the geometry effect of axis is gradually decreased.

As fundamental parameters for polarized-radiative-transfer calculations, the single-scattering phase matrix of irregularly shaped aerosol particles must be accurately modeled. In this study, a scattered-field finite-difference time-domain (FDTD) model and a scattered-field pseudo-spectral time-domain (PSTD) model are developed for light scattering by arbitrarily shaped dielectric aerosols. The convolutional perfectly matched layer (CPML) absorbing boundary condition (ABC) is used to truncate the computational domain. It is found that the PSTD method is generally more accurate than the FDTD in calculation of the single-scattering properties given similar spatial cell sizes. Since the PSTD can use a coarser grid for large particles, it can lower the memory requirement in the calculation. However, the Fourier transformations in the PSTD need significantly more CPU time than simple subtractions in the FDTD, and the fast Fourier transform requires a power of 2 elements in calculations, thus using the PSTD could not significantly reduce the CPU time required in the numerical modeling. Furthermore, because the scattered-field FDTD/PSTD equations include incident-wave source terms, the FDTD/PSTD model allows for the inclusion of an arbitrarily incident wave source, including a plane parallel wave or a Gaussian beam like those emitted by lasers usually used in laboratory particle characterizations, etc. The scattered-field FDTD and PSTD light-scattering models can be used to calculate single-scattering properties of arbitrarily shaped aerosol particles over broad size and wavelength ranges.

Generating compressive residual stresses at the critical stress locations can result in prevention or delay of structural component failure. Laser peening is a well known method for inducing compressive residual stresses. The plastic deformation created by the planar shock waves near the surface regions is the major cause for the generation of compressive residual stresses. Apart from the planar waves, release waves at the border of impact are generated that act against the plastic deformation created by planar waves. This decrease of plastic deformation reduces the compressive residual stress generated near the surface regions of peened components. Laser peening of curved geometries creates compressive residual stresses—which are dissimilar to flat geometry—because of the influence of release waves on different curvatures. This research investigates the effects of reduction in the amount of plasticity in convex, concave, and flat geometries using plastic dissipation energy as the measure of plastic deformation imparted on the component. Three dimensional finite element models are created in Abaqus to predict the effects of reduced plasticity in residual stresses generated on curved geometries of laser peened components.

[1] Global ocean phytoplankton biomass (Cphyto) and total particulate organic carbon (POC) stocks have largely been characterized from space using passive ocean color measurements. A space-based light detection and ranging (lidar) system can provide valuable complementary observations for Cphyto and POC assessments, with benefits including day-night sampling, observations through absorbing aerosols and thin cloud layers, and capabilities for vertical profiling through the water column. Here we use measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to quantify global Cphyto and POC from retrievals of subsurface particulate backscatter coefficients (bbp). CALIOP bbp data compare favorably with airborne, ship-based, and passive ocean data and yield global average mixed-layer standing stocks of 0.44 Pg C for Cphyto and 1.9 Pg for POC. CALIOP-based Cphyto and POC data exhibit global distributions and seasonal variations consistent with ocean plankton ecology. Our findings support the use of spaceborne lidar measurements for advancing understanding of global plankton systems.

International audience; We analyzed different models to estimate absorption at W-band by gaseous species by taking advantage of the collocated CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. We used the power backscattered by the surface in the green visible wavelength of the lidar of CALIPSO as a reference to infer CloudSat's 94-GHz ocean surface backscatter in clear air and infer the attenuation introduced by gaseous absorption. Different millimeter-wave propagation models (MPMs) and different sources to determine the profile of atmospheric thermodynamic state are used to estimate CloudSat attenuation. These estimates are compared to the observations to calculate the residual dispersion. We show here that we need to adjust the empirical constants of preexisting water vapor absorption models to minimize the dispersion. Our results indicate an overestimation of absorption by the water vapor continuum at 94 GHz in Liebe-based MPM. We also propose a new empirical model to better represent the absorption of the water vapor continuum near 94 GHz. When this model is used in combination with the Advanced Microwave Scanning Radiometer for the Earth Observing System water vapor path and the Global Modeling and Assimilation Office water vapor vertical profile distribution, it leads to the lowest dispersion of the data on a statistical basis (global data over one month). The improved model is expected to optimize water vapor correction applied to CloudSat data and, potentially, also to improve interpretation of brightness temperature measurements in the W-band (e.g., 85- and 98-GHz radiometric channels).

Over forty scientists from six countries convened in Raleigh, NC on June 4-6 2012 to review the status and prospects of sea spray aerosol research. Participants were researchers from the oceanography and atmospheric science communities, including academia, private industry, and government agencies. The recommendations from the working groups are summarized in a science prioritization matrix that is meant to prioritize the research agenda and identify areas of investigation by the magnitude of their impact on proposed science questions. Str

Land surface hydrology is important to regional climate, ecosystem, agriculture, and even human activities. Changes in soil moisture can produce considerable impacts on socioeconomics. Analysis of assimilation model results, especially those from the Community Land Model, shows that soil moisture over Oklahoma region is continuously reduced from 1980 to 2009. The potential drying trend in the Oklahoma region is evaluated by observations taken during last three decades in this study. Satellite data from Global Precipitation Climatology Project exhibit a clear precipitation decrease in the Oklahoma region during the last decade or so compared with those of two or three decades ago. Accompanying with the precipitation variation, land surface net radiation and temperature over the region are found increases by satellite and/or in-situ measurements. These changes in regional climate conditions also likely result in reduction of regional evaporation and enhancement of sensible heat transport from land surface into the atmosphere as indicated in assimilated data. These observed and modeled evidences of the changes in regional water and energy cycles lead us to conclude that the soil moisture over the Oklahoma region was reduced during the last decade. This soil moisture drop could increase a risk in water shortage for agriculture in the Oklahoma state if the dry period continues. Further investigations on the drying in the Oklahoma State or even entire Southern Great Plains are needed to mitigate potential droughts, reductions in vegetation products, and other socioeconomic impacts.

Submerged objects viewed through wavy water surfaces appear distorted by refraction. An imaging system exploiting this effect is implemented using a submerged planar light source designed so that color images reveal features of small-amplitude waves in a wind-wave tank. The system is described by a nonlinear model of image formation based on the geometry of refraction, spectral emission from the light source, radiative transfer through the water and surface, and camera spectral response. Surface normal vector components are retrieved from the color image data using an iterative solution to the nonlinear model. The surface topography is then retrieved using a linear model that combines surface normal data with a priori constraints on elevation and curvature. The high-resolution topographic data reveal small-amplitude waves spanning wavelength scales from capillary through short gravity wave regimes. The system capabilities are demonstrated in the retrieval of test surfaces, and of a case of wind-driven waves, using data collected at high spatial and temporal resolution in a wave tank. The approach of using a physical model of image formation with inverse solution methods provides an example of how surface topography can be retrieved and may be applicable to data from other similar instruments.

Five years of CALIPSO lidar layer products are used to study transpacific transport of Asian dust. We focus on possible changes to dust intrinsic optical properties during the course of transport, with specific emphasis on changes to particulate depolarization ratio (PDR). PDR distributions for Asian dust transported across the Pacific are compared to previously reported PDR distributions for African dust transported across the Atlantic. African dust shows a slight decreasing trend in PDR during westward transport across the Atlantic during its most active long-range transport season in summer. Asian dust, on the other hand, shows some spatial variability in PDR over the Pacific during its most active long-range transport season in spring. The dust PDR is generally smaller over the ocean than over the Tarim basin and nearby downwind regions. PDR also shows a decreasing trend with latitude moving northward toward the Arctic, together with an increasing trend in the dust aerosol optical depth (AOD) when passing over polluted Asian regions. Possible explanations include (i) the mixing of dust externally or internally with other types of aerosol over the heavily developed industrial regions in East Asia, and (ii) the downstream mixing of dust plumes from different source regions (i.e., Tarim and Gobi). Dust from different source regions exhibits relatively large differences in PDR, with mean values of 0.34±0.07, 0.28±0.06, and 0.30±0.08, respectively, over the Tarim basin, Gobi Desert and Northwest African source regions. Different transport mechanisms are seen for African dust and Asian dust. Asian dust transport is originated by cold fronts and driven by westerly jets. In contrast, summer African transatlantic dust transport is driven by trade winds and is generally well confined in altitude in the free troposphere throughout the tropics and subtropics.

We have built an aerosol retrieval algorithm which combines the Look Up Table (LUT) and least squares fitting methods. The algorithm is based on the multi-angle multi-wavelength polarized reflectance at the Top Of the Atmosphere (TOA) measured by the Research Scanning Polarimeter (RSP). The aerosol state parameters are the aerosol particle effective radius, effective variance, complex index of refraction, and aerosol column number density. Monomodal aerosol size distribution is assumed. The Cost Function (CF) of the least squares fitting is designed in consideration of the RSP instrumental characteristics. The aerosol retrieval algorithm inherently assumes one layer of aerosols within the atmosphere. Synthetic polarized radiance data at the TOA have been created assuming either one or two layers of aerosols using the vector radiative transfer code based on successive order of scattering method. Test cases for one-layer aerosol systems show great performance. Around 90% of the total 1200 test cases have CF values smaller than 50. For these cases, the correlation coefficients of the input and retrieved parameters are generally around or larger than 0.98. The effective variance is slightly worse with the correlation coefficient of 0.76938. On the other hand, test cases for two-layer aerosol systems show that only 50% of the total (also 1200) tested cases have final CFs smaller than 50. Among these successful cases ( CF ≤ 50 ), the retrieved optical depth can still be interpreted as the total column optical depth, though the correlation coefficient is decreased in comparison with the one-layer aerosol cases. We propose to interpret other retrieved aerosol parameters as the average of corresponding parameters for each layer weighted by its optical depth at 865 nm. The retrieved effective radius and complex refractive index can be explained by this scheme (correlation coefficient around 0.9). The effective variance, however, shows decreased performance with the correlation coefficient of 0.46421. This may be due to the strong nonlinearity dependence of the scattering properties on the effective variance.

We apply the iteration of source function (IOSF) philosophy to the successive order of scattering method for solving the vector radiative transfer equation in the coupled atmosphere and ocean system. A major class of radiative transfer solvers only provides the radiation field at discrete viewing zenith angles. The radiation field at other angles is found by interpolation. The iteration of source matrix method integrates the product of the radiation field and source matrix at quadrature points to obtain the radiation field at arbitrary viewing angles. The resultant solution includes the radiation contributions from all scattering orders higher than one. The analytical single scattering solution is then added to find the total radiation field. The proposed scheme includes the benefits of both the IOSF interpolation and the analytical single scattering solution. Boundary conditions for a flat air–sea interface are fully considered. A test case of a coupled atmosphere and ocean system shows that this combined method improves the polarized radiation field greatly in comparison with the regular polynomial interpolation method.

International audience; A new approach has been proposed to determine ocean subsurface particulate backscattering coefficient b from CALIOP 30° off-nadir lidar measurements. The new method also provides estimates of the particle volume scattering function at the 180° scattering angle. The CALIOP based layer-integrated lidar backscatter and particulate backscattering coefficients are compared with the results obtained from MODIS ocean color measurements. The comparison analysis shows that ocean subsurface lidar backscatter and particulate backscattering coefficient bbp can be accurately obtained from CALIOP lidar measurements, thereby supporting the use of space-borne lidar measurements for ocean subsurface studies.

Laser peen forming (LPF) is a promising method to fabricate fiber metal laminates (FMLs) with its design flexibility to produce complex shapes. Eigenstrain-based modeling is a helpful method to predict deformation after LPF, while determining eigenstrain is very difficult because of its complex constituents and high-dynamic loading of process. An effective experiment-based method is proposed in this work to obtain eigenstrain induced by LPF in metal layers of FMLs. An analytical beam model is developed to relate the deflection profile generated by specific scanning strategy to equivalent bending moment. Based on the determined bending moment from the measured deflection profiles, the generated eigenstrain can be inversely calculated by the proposed beam model describing the relationship between the eigenstrain and the bending moment. Chemical etching to remove sheets layer by layer is used to obtain the relaxed deflection profile to calculate the eigenstrain in each metal layer. Furthermore, an approximate model of plate is established to predict deformation after LPF based on determined eigenstrain. The results show that the predictive deformed shape agrees very well with both experiments and finite model prediction.

Electromagnetic (EM) beams with orbital angular momentum (OAM) may have great potential applications in communication technology and in remote sensing of the Earth-atmosphere system and outer planets. Study of their interaction with optical lenses and dielectric or metallic objects, or scattering of them by particles in the Earth-atmosphere system, is a necessary step to explore the advantage of the OAM EM beams. In this study, the 3-dimensional (3D) scattered-field (SF) finite-difference time domain (FDTD) technique with the convolutional perfectly matched layer (CPML) absorbing boundary conditions (ABC) is applied to calculate the scattering of the purely azimuthal (the radial mode number is assumed to be zero) Laguerre-Gaussian (LG) beams with the OAM by dielectric particles. We found that for OAM beam's interaction with dielectric particles, the forward-scattering peak in the conventional phase function (P 11 ) disappears, and light scattering peak occurs at a scattering angle of ∼ 15–45°. The disappearance of forward-scattering peak means that, in laser communications most of the particle-scattered noise cannot enter the receiver, thus the received light is optimally the original OAM-encoded signal. This feature of the OAM beam also implies that in lidar remote sensing of the atmospheric particulates, most of the multiple-scattering energy will be off lidar sensors, and this may result in an accurate profiling of particle layers in the atmosphere or in the oceans by lidar, or even in the ground when a ground penetration radar (GPR) with the OAM is applied. This far-field characteristics of the scattered OAM light also imply that the optical theorem, which is derived from plane-parallel wave scattering case and relates the forward scattering amplitude to the total cross section of the scatterer, is invalid for the scattering of OAM beams by dielectric particles.

Sunlight contamination dominates the backscatter noise in space-based lidar measurements during daytime. The background scattered sunlight is highly variable and dependent upon the surface and atmospheric albedo. The scattered sunlight contribution to noise increases over land and snow surfaces where surface albedos are high and thus overwhelm lidar backscatter from optically thin atmospheric constituents like aerosols and thin clouds. In this work, we developed a novel lidar remote sensing concept that potentially can eliminate sunlight induced noise. The new lidar concept requires: (1) a transmitted laser light that carries orbital angular momentum (OAM); and (2) a photon sieve (PS) diffractive filter that separates scattered sunlight from laser light backscattered from the atmosphere, ocean and solid surfaces. The method is based on numerical modeling of the focusing of Laguerre-Gaussian (LG) laser beam and plane-wave light by a PS. The model results show that after passing through a PS, laser light that carries the OAM is focused on a ring (called “focal ring” here) on the focal plane of the PS filter, very little energy arrives at the center of the focal plane. However, scattered sunlight, as a plane wave without the OAM, focuses at the center of the focal plane and thus can be effectively blocked or ducted out. We also find that the radius of the “focal ring” increases with the increase of azimuthal mode (L) of LG laser light, thus increasing L can more effectively separate the lidar signal away from the sunlight noise.

Fibre metal laminates are new sorts of composite materials with superior fatigue and impact properties. Forming parts from FMLs is very attractive to reduce the process cycle and labor cost. Laser peen forming (LPF) is a promising method to form FMLs with its design flexibility and adaptability to produce complex shapes. To predict the deformed shape of FMLs after laser peen forming, eigenstrain-based modelling is a helpful method with advantage in spending less computational time, but it is difficult to precisely determine eigenstrain distribution regarding material with layered structure. In the present research, an efficient and effective experiment-based method is proposed to determine eigenstrain in the metal layer of FMLs, which can avoid the complicated numerical simulation. The determined eigenstrain is assumed to be uniformly distributed in each metal layer while no plastic deformation is generated in composite layer due to its high strength yield. An analytical model is developed to relate the bending deformation to eigenstrain field. Firstly, the equivalent external bending moment applied on the samples is deduced from eigenstrain, and then the relation of deformation and bending moment is provided by a beam bending model. Chemical etching is utilized to remove metal layer by layer to calculate eigenstrain in each layer. With removal of each metal layer, the bending profiles will spring back or bend further due to change of applied moment and bending stiffness. The eigenstrain in each layer can be inversely determined by matching the residual bending profile after each etching with the developed bending model. One scanning strategy of LPF with reciprocating line and 50% overlapping rate is performed in experiments to apply laser shocks on the entire top surface of strip samples, which are prepared from glass laminate aluminum reinforced epoxy with a unidirectional orientation. Eigenstrain in the top and bottom metal layer is successively determined by the proposed analytical model and chemical etching. Finite element analysis is utilized to verify the determined eigenstrain by comparing the simulated shape with experiments and good agreement is obtained.

In a previous study we evaluated the above-cloud aerosol optical depth (AOD) retrieval at 532 nm in the CALIOP version 3 (V3) data products for two selected spatial domains along the Saharan dust transport pathway and African smoke transport pathway. In that study we rescaled the V3 level-1 (L1) data to compensate for known V3 calibration biases, and then derived aerosol intrinsic properties such as lidar ratio (Sa) and particulate depolarization ratio (PDR) for comparison with the CALIOP dust and smoke aerosol models. The calibration of the recently released version 4 (V4) CALIPSO L1 data product is significantly improved over V3. So in this paper we repeat our previous analysis using the new V4 L1 data. A comparison shows that our rescaled V3 and the new V4 data are different only by ~1% in the two selected spatial domains. The retrieved AOD values decrease by ~2.6% in both domains from V3 to V4. When the data is screened to exclude weakly scattering layers, the median Sa retrieved from the V4 L1 data in the dust transport region is reduced by 1.4 sr to 43.0±8.3 sr. The median Sa value in the smoke transport region is increased by 0.8 sr to 71.2±15.1 sr. The PDR values remain almost unchanged for the screened data.

The canopy height is an important parameter in aboveground biomass estimation. Lidar remote sensing from airborne or satellite platforms, has a unique capability for forestry applications. This study introduces an innovative concept to estimate canopy height using CALIOP two wavelengths lidar measurements. One main advantage is that the concept proposed here is dependent on the penetration depths at two wavelengths without making assumption about the last peak of waveform as the ground location, and it does not require the ancillary Digital Elevation Model (DEM) data in order to obtain the slope information of terrain. Canopy penetration depths at two wavelengths indicate moderately strong relationships for estimating the canopy height. Results show that the CALIOP-derived canopy heights were highly correlated with the ICESat/GLAS-derived values with a mean RMSE of 3.4 m and correlation coefficient (R) of 0.89. Our findings present a relationship between the penetration difference and canopy height, which can be used as another metrics for canopy height estimation, except the full waveforms.

Reflected solar radiation from Earth’s ocean–atmosphere system can be significantly polarized by Earth’s surface and by atmospheric components such as air molecules and aerosols. Measurements of many satellite radiometric instruments have some dependence on the polarization state of the reflected light.