ABSTRACT
Coupled atmosphere and ocean remote sensing retrievals of aerosol, cloud, and oceanic phytoplankton microphysical properties, such as those carried out by the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, involve single-scattering calculations that are time consuming. Lookup tables (LUTs) exist to speed up these calculations for aerosol and water droplets in the atmosphere. In our new Lorenz-Mie lookup table, we tabulate single scattering by an ensemble of coated isotropic spheres representing oceanic phytoplankton at wavelengths from 0.355 µm. The lookup table covers phytoplankton particles with radii in the range of 0.15-100 µm at an increase of up to 104 in computational speed compared to single-scattering calculations. The allowed complex refractive indices range from 1.05 to 1.24 for the shell's real part, from 10-7 to 0.3 for the shell's imaginary part, from 0 to 0.001 for the core's imaginary part, and equal to 1.02 for the core's real part. We show that we precisely compute inherent optical properties for the phytoplankton size distributions ranging up to 5 µm for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.355 to 1.065 µm and find that all the inherent optical properties of interest agree with the single-scattering calculations to within 1% for 99.9% of cases. We also provide an example of using the lookup table to reproduce the phytoplankton optical datasets listed in the PANGAEA database for synthetic hyperspectral algorithm development. The table together with C++, Fortran, MATLAB, and Python codes to apply different complex refractive indices and phytoplankton size distributions is freely available online.
ABSTRACT
In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.
ABSTRACT
Combined lidar and polarimeter retrievals of aerosol, cloud, and ocean microphysical properties involve single-scattering cloud calculations that are time consuming. We create a look-up table to speed up these calculations for water droplets in the atmosphere. In our new Lorenz-Mie look-up table we tabulate the light scattering by an ensemble of homogeneous isotropic spheres at wavelengths starting from 0.35 µm. The look-up table covers liquid water cloud particles with radii in the range of 0.001-500 µm while gaining an increase of up to 104 in computational speed. The covered complex refractive indices range from 1.25 to 1.36 for the real part and from 0 to 0.001 for the imaginary part. We show that we can precisely compute inherent optical properties for the particle size distributions ranging up to 100 µm for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.35 to 2.3 µm and find that the elements of the normalized scattering matrix as well as the asymmetry parameter, the absorption, backscatter, extinction, and scattering coefficients are precise to within 1% for 96.7%-100% of cases depending on the inherent optical property. We also provide an example of using the look-up table with in situ measurements to determine agreement with remote sensing. The table together with C++, Fortran, MATLAB, and Python codes to interpolate the complex refractive index and apply different particle size distributions are freely available online.
ABSTRACT
Biomass burning (BB) aerosol events were characterized over the U.S. East Coast and Bermuda over the western North Atlantic Ocean (WNAO) between 2005 and 2018 using a combination of ground-based observations, satellite data, and model outputs. Days with BB influence in an atmospheric column (BB days) were identified using criteria biased toward larger fire events based on anomalously high AERONET aerosol optical depth (AOD) and MERRA-2 black carbon (BC) column density. BB days are present year-round with more in June-August (JJA) over the northern part of the East Coast, in contrast to more frequent events in March-May (MAM) over the southeast U.S. and Bermuda. BB source regions in MAM are southern Mexico and by the Yucatan, Central America, and the southeast U.S. JJA source regions are western parts of North America. Less than half of the BB days coincide with anomalously high PM2.5 levels in the surface layer, according to data from 14 IMPROVE sites over the East Coast. Profiles of aerosol extinction suggest that BB particles can be found in the boundary layer and into the upper troposphere with the potential to interact with clouds. Higher cloud drop number concentration and lower drop effective radius are observed during BB days. In addition, lower liquid water path is found during these days, especially when BB particles are present in the boundary layer. While patterns are suggestive of cloud-BB aerosol interactions over the East Coast and the WNAO, additional studies are needed for confirmation.
ABSTRACT
Improved characterization of ambient PM2.5 mass concentration and chemical speciation is a topic of interest in air quality and climate sciences. Over the past decades, considerable efforts have been made to improve ground-level PM2.5 using remotely sensed data. Here we present two new approaches for estimating atmospheric PM2.5 and chemical composition based on the High Spectral Resolution Lidar (HSRL)-retrieved aerosol extinction values and types and Creating Aerosol Types from Chemistry (CATCH)-derived aerosol chemical composition. The first methodology (CMAQ-HSRL-CH) improves EPA's Community Multiscale Air Quality (CMAQ) predictions by applying variable scaling factors derived using remotely-sensed information about aerosol vertical distribution and types and the CATCH algorithm. The second methodology (HSRL-CH) does not require regional model runs and can provide atmospheric PM2.5 mass concentration and chemical speciation using only the remotely sensed data and the CATCH algorithm. The resulting PM2.5 concentrations and chemical speciation derived for NASA DISCOVER-AQ (Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality) Baltimore-Washington, D.C. Corridor (BWC) Campaign (2011) are compared to surface measurements from EPA's Air Quality Systems (AQS) network. The analysis shows that the CMAQ-HSRL-CH method leads to considerable improvement of CMAQ's predicted PM2.5 concentrations (R2 value increased from 0.37 to 0.63, the root mean square error (RMSE) was reduced from 11.9 to 7.2 µg m-3, and the normalized mean bias (NMB) was lowered from -46.0 to 4.6%). The HSRL-CH method showed statistics (R2=0.75, RMSE=8.6 µgm-3, and NMB=24.0%), which were better than the CMAQ prediction of PM2.5 alone and analogous to CMAQ-HSRL-CH. In addition to mass concentration, HSRL-CH can also provide aerosol chemical composition without specific model simulations. We expect that the HSRL-CH method will be able to make reliable estimates of PM2.5 concentration and chemical composition where HSRL data are available.
ABSTRACT
Every night across the world's oceans, numerous marine animals arrive at the surface of the ocean to feed on plankton after an upward migration of hundreds of metres. Just before sunrise, this migration is reversed and the animals return to their daytime residence in the dark mesopelagic zone (at a depth of 200-1,000 m). This daily excursion, referred to as diel vertical migration (DVM), is thought of primarily as an adaptation to avoid visual predators in the sunlit surface layer1,2 and was first recorded using ship-net hauls nearly 200 years ago3. Nowadays, DVMs are routinely recorded by ship-mounted acoustic systems (for example, acoustic Doppler current profilers). These data show that night-time arrival and departure times are highly conserved across ocean regions4 and that daytime descent depths increase with water clarity4,5, indicating that animals have faster swimming speeds in clearer waters4. However, after decades of acoustic measurements, vast ocean areas remain unsampled and places for which data are available typically provide information for only a few months, resulting in an incomplete understanding of DVMs. Addressing this issue is important, because DVMs have a crucial role in global ocean biogeochemistry. Night-time feeding at the surface and daytime metabolism of this food at depth provide an efficient pathway for carbon and nutrient export6-8. Here we use observations from a satellite-mounted light-detection-and-ranging (lidar) instrument to describe global distributions of an optical signal from DVM animals that arrive in the surface ocean at night. Our findings reveal that these animals generally constitute a greater fraction of total plankton abundance in the clear subtropical gyres, consistent with the idea that the avoidance of visual predators is an important life strategy in these regions. Total DVM biomass, on the other hand, is higher in more productive regions in which the availability of food is increased. Furthermore, the 10-year satellite record reveals significant temporal trends in DVM biomass and correlated variations in DVM biomass and surface productivity. These results provide a detailed view of DVM activities globally and a path for refining the quantification of their biogeochemical importance.
Subject(s)
Animal Migration , Animals , Oceans and Seas , Satellite Communications , Time FactorsABSTRACT
We evaluate the retrieval performance of the automated, unsupervised inversion algorithm, Tikhonov Advanced Regularization Algorithm (TiARA), which is used for the autonomous retrieval of microphysical parameters of anthropogenic and natural pollution particles. TiARA (version 1.0) has been developed in the past 10 years and builds on the legacy of a data-operator-controlled inversion algorithm used since 1998 for the analysis of data from multiwavelength Raman lidar. The development of TiARA has been driven by the need to analyze in (near) real time large volumes of data collected with NASA Langley Research Center's high-spectral-resolution lidar (HSRL-2). HSRL-2 was envisioned as part of the NASA Aerosols-Clouds-Ecosystems mission in response to the National Academy of Sciences (NAS) Decadal Study mission recommendations 2007. TiARA could thus also serve as an inversion algorithm in the context of a future space-borne lidar. We summarize key properties of TiARA on the basis of simulations with monomodal logarithmic-normal particle size distributions that cover particle radii from approximately 0.05 µm to 10 µm. The real and imaginary parts of the complex refractive index cover the range from non-absorbing to highly light-absorbing pollutants. Our simulations include up to 25% measurement uncertainty. The goal of our study is to provide guidance with respect to technical features of future space-borne lidars, if such lidars will be used for retrievals of microphysical data products, absorption coefficients, and single-scattering albedo. We investigate the impact of two different measurement-error models on the quality of the data products. We also obtain for the first time, to the best of our knowledge, a statistical view on systematic and statistical uncertainties, if a large volume of data is processed. Effective radius is retrieved to 50% accuracy for 58% of cases with an imaginary part up to 0.01i and up to 100% of cases with an imaginary part of 0.05i. Similarly, volume concentration, surface-area concentration, and number concentrations are retrieved to 50% accuracy in 56%-100% of cases, 99%-100% of cases, and 54%-87% of cases, respectively, depending on the imaginary part. The numbers represent measurement uncertainties of up to 15%. If we target 20% retrieval accuracy, the numbers of cases that fall within that threshold are 36%-76% for effective radius, 36%-73% for volume concentration, 98%-100% for surface-area concentration, and 37%-61% for number concentration. That range of numbers again represents a spread in results for different values of the imaginary part. At present, we obtain an accuracy of (on average) 0.1 for the real part. A case study from the ORCALES field campaign is used to illustrate data products obtained with TiARA.
ABSTRACT
Comprehensive polarimetric closure is demonstrated using observations from two in-situ polarimeters and Vector Radiative Transfer (VRT) modeling. During the Ship-Aircraft Bio-Optical Research (SABOR) campaign, the novel CCNY HyperSAS-POL polarimeter was mounted on the bow of the R/V Endeavor and acquired hyperspectral measurements from just above the surface of the ocean, while the NASA GISS Research Scanning Polarimeter was deployed onboard the NASA LaRC's King Air UC-12B aircraft. State-of-the-art, ancillary measurements were used to characterize the atmospheric and marine contributions in the VRT model, including those of the High Spectral Resolution Lidar (HSRL), the AErosol RObotic NETwork for Ocean Color (AERONET-OC), a profiling WETLabs ac-9 spectrometer and the Multi-spectral Volume Scattering Meter (MVSM). An open-ocean and a coastal scene are analyzed, both affected by complex aerosol conditions. In each of the two cases, it is found that the model is able to accurately reproduce the Stokes components measured simultaneously by each polarimeter at different geometries and viewing altitudes. These results are mostly encouraging, considering the different deployment strategies of RSP and HyperSAS-POL, which imply very different sensitivities to the atmospheric and ocean contributions, and open new opportunities in above-water polarimetric measurements. Furthermore, the signal originating from each scene was propagated to the top of the atmosphere to explore the sensitivity of polarimetric spaceborne observations to changes in the water type. As expected, adding polarization as a measurement capability benefits the detection of such changes, reinforcing the merits of the full-Stokes treatment in modeling the impact of atmospheric and oceanic constituents on remote sensing observations.
ABSTRACT
Satellite passive ocean color instruments have provided an unbroken â¼20-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.
Subject(s)
Ecosystem , Oceanography , Oceans and Seas , Satellite Imagery , Atmosphere , Lasers , PlanktonABSTRACT
Passive ocean observing sensors are unable to detect subsurface structure in ocean properties, resulting in errors in water column integrated phytoplankton biomass and net primary production (NPP) estimates. Active lidar (light detection and ranging) sensors make quantitative measurements of depth-resolved backscatter (bbp) and diffuse light attenuation (Kd) coefficients in the ocean and can provide critical measurements for biogeochemical models. Sub-surface phytoplankton biomass, light, chlorophyll, and NPP fields were characterized using both in situ measurements and coincident airborne high spectral resolution lidar (HSRL-1) measurements collected as part of the SABOR (Ship-Aircraft Bio-Optical Research) field campaign. We found that depth-resolved data are critical for calculating phytoplankton stocks and NPP, with improvements in NPP estimates up to 54%. We observed strong correlations between coincident HSRL-1 and in situ IOP measurements of both bbp (r = 0.94) and Kd (r = 0.90).
ABSTRACT
We present an investigation of some important mathematical and numerical features related to the retrieval of microphysical parameters [complex refractive index, single-scattering albedo, effective radius, total number, surface area, and volume concentrations] of ambient aerosol particles using multiwavelength Raman or high-spectral-resolution lidar. Using simple examples, we prove the non-uniqueness of an inverse solution to be the major source of the retrieval difficulties. Some theoretically possible ways of partially compensating for these difficulties are offered. For instance, an increase in the variety of input data via combination of lidar and certain passive remote sensing instruments will be helpful to reduce the error of estimation of the complex refractive index. We also demonstrate a significant interference between Aitken and accumulation aerosol modes in our inversion algorithm, and confirm that the solutions can be better constrained by limiting the particle radii. Applying a combination of an analytical approach and numerical simulations, we explain the statistical behavior of the microphysical size parameters. We reveal and clarify why the total surface area concentration is consistent even in the presence of non-unique solution sets and is on average the most stable parameter to be estimated, as long as at least one extinction optical coefficient is employed. We find that for selected particle size distributions, the total surface area and volume concentrations can be quickly retrieved with fair precision using only single extinction coefficients in a simple arithmetical relationship.
ABSTRACT
This paper developed a new retrieval framework of external mixing of the dust and non-dust aerosol to predict the lidar ratio of the external mixing aerosols and to separate the contributions of non-spherical aerosols by using different depolarization ratios among dust, sea salt, smoke, and polluted aerosols. The detailed sensitivity tests and case study with the new method showed that reliable dust information could be retrieved even without prior information about the non-dust aerosol types. This new method is suitable for global dust retrievals with satellite observations, which is critical for better understanding global dust transportation and for model improvements.
Subject(s)
Aerosols/analysis , Dust/analysis , Light , Computer Simulation , Environmental Monitoring/methods , Infrared Rays , Satellite Communications , Scattering, Radiation , Sodium Chloride/analysisABSTRACT
During a Stratospheric Aerosol and Gas (SAGE)-III Ozone Loss and Validation Experiment (SOLVE)-II science flight on 4 February 2003, a mother-of-pearl cloud over Iceland was underflown by the NASA DC-8 and measured with the lidars onboard. In addition, color photos were taken during the approach. Aided by extensive modeling of cloud coloration, the main results of the analysis of this unique data set are: (1) the polar stratospheric cloud was mountain wave-induced and of type II; (2) the spectacular color display was caused by ice particles with sizes around 2 µm.
ABSTRACT
We present the results of a feasibility study in which a simple, automated, and unsupervised algorithm, which we call the arrange and average algorithm, is used to infer microphysical parameters (complex refractive index, effective radius, total number, surface area, and volume concentrations) of atmospheric aerosol particles. The algorithm uses backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm as input information. Testing of the algorithm is based on synthetic optical data that are computed from prescribed monomodal particle size distributions and complex refractive indices that describe spherical, primarily fine mode pollution particles. We tested the performance of the algorithm for the "3 backscatter (ß)+2 extinction (α)" configuration of a multiwavelength aerosol high-spectral-resolution lidar (HSRL) or Raman lidar. We investigated the degree to which the microphysical results retrieved by this algorithm depends on the number of input backscatter and extinction coefficients. For example, we tested "3ß+1α," "2ß+1α," and "3ß" lidar configurations. This arrange and average algorithm can be used in two ways. First, it can be applied for quick data processing of experimental data acquired with lidar. Fast automated retrievals of microphysical particle properties are needed in view of the enormous amount of data that can be acquired by the NASA Langley Research Center's airborne "3ß+2α" High-Spectral-Resolution Lidar (HSRL-2). It would prove useful for the growing number of ground-based multiwavelength lidar networks, and it would provide an option for analyzing the vast amount of optical data acquired with a future spaceborne multiwavelength lidar. The second potential application is to improve the microphysical particle characterization with our existing inversion algorithm that uses Tikhonov's inversion with regularization. This advanced algorithm has recently undergone development to allow automated and unsupervised processing; the arrange and average algorithm can be used as a preclassifier to further improve its speed and precision. First tests of the performance of arrange and average algorithm are encouraging. We used a set of 48 different monomodal particle size distributions, 4 real parts and 15 imaginary parts of the complex refractive index. All in all we tested 2880 different optical data sets for 0%, 10%, and 20% Gaussian measurement noise (one-standard deviation). In the case of the "3ß+2α" configuration with 10% measurement noise, we retrieve the particle effective radius to within 27% for 1964 (68.2%) of the test optical data sets. The number concentration is obtained to 76%, the surface area concentration to 16%, and the volume concentration to 30% precision. The "3ß" configuration performs significantly poorer. The performance of the "3ß+1α" and "2ß+1α" configurations is intermediate between the "3ß+2α" and the "3ß."
ABSTRACT
High spectral resolution lidars (HSRLs) have shown great value in aircraft aerosol remote sensing application and are planned for future satellite missions. A compact, robust, quasi-monolithic tilted field-widened Michelson interferometer is being developed as the spectral discrimination filter for an second-generation HSRL(HSRL-2) at NASA Langley Research Center. The Michelson interferometer consists of a cubic beam splitter, a solid arm and an air arm. Piezo stacks connect the air arm mirror to the body of the interferometer and can tune the interferometer within a small range. The whole interferometer is tilted so that the standard Michelson output and the reflected complementary output can both be obtained. In this paper, the transmission ratio is proposed to evaluate the performance of the spectral filter for HSRL. The transmission ratios over different types of system imperfections, such as cumulative wavefront error, locking error, reflectance of the beam splitter and anti-reflection coatings, system tilt, and depolarization angle are analyzed. The requirements of each imperfection for good interferometer performance are obtained.
Subject(s)
Aerosols/chemistry , Atmosphere/chemistry , Interferometry/instrumentation , Interferometry/methods , Meteorology/instrumentation , Meteorology/methods , Air Pollutants/chemistry , Aircraft , Models, TheoreticalABSTRACT
Mice that are ets variant gene 5 (ETV5) null (Etv5(-/-)) undergo the first wave of spermatogenesis but lose all spermatogonial stem cells (SSCs) during this time. The SSC loss in Etv5(-/-) mice begins during the neonatal period, suggesting a role for ETV5 in SSC self-renewal during this period. Herein, we show that Etv5 mRNA was present in perinatal mouse testis and that ETV5 was expressed in fetal Sertoli cells and by germ cells and Sertoli cells during the neonatal period. Transplantation of Etv5(-/-) germ cells failed to establish spermatogenesis in W/W(v) mice testes, indicating that germ cell ETV5 has a key role in establishment or self-renewal of transplanted SSCs. The SSC self-renewal is stimulated by glial cell-derived neurotrophic factor (GDNF) acting through the RET/GDNF family receptor alpha 1 (GFRA1) receptor complex in SSCs. Immunohistochemistry, quantitative PCR, and laser capture microdissection revealed decreased RET mRNA and protein expression in spermatogonia of neonatal Etv5(-/-) mice by Postnatal Days 4-8, indicating that disrupted GDNF/RET/GFRA1 signaling may occur before initial spermatogonial stem/progenitor cell decrease. Etv5(-/-) spermatogonia had reduced proliferation in vivo and in vitro. Decreased cell proliferation may cause the observed decreases in the number of type A spermatogonia (Postnatal Day 17) and daily sperm production (Postnatal Day 30) in Etv5(-/-) mice, indicating quantitative impairments in the first wave of spermatogenesis. In conclusion, ETV5 is expressed beginning in fetal Sertoli cells and can potentially have effects on neonatal Sertoli cells and germ cells. In addition, ETV5 has critical effects on neonatal spermatogonial proliferation, which may involve impaired signaling through the RET receptor.
Subject(s)
Cell Proliferation , DNA-Binding Proteins/metabolism , Germ Cells/metabolism , Proto-Oncogene Proteins c-ret/metabolism , Spermatogenesis , Testis/growth & development , Transcription Factors/metabolism , Animals , Animals, Newborn , Cells, Cultured , DNA-Binding Proteins/deficiency , DNA-Binding Proteins/genetics , Fibroblast Growth Factor 2/administration & dosage , Fibroblast Growth Factor 2/metabolism , Gene Expression Regulation, Developmental , Germ Cells/cytology , Germ Cells/transplantation , Glial Cell Line-Derived Neurotrophic Factor/administration & dosage , Glial Cell Line-Derived Neurotrophic Factor Receptors/administration & dosage , Glial Cell Line-Derived Neurotrophic Factor Receptors/genetics , Glial Cell Line-Derived Neurotrophic Factor Receptors/metabolism , Immunohistochemistry , Male , Mice , Mice, Knockout , Microdissection , Proto-Oncogene Proteins c-ret/genetics , RNA, Messenger/metabolism , Recombinant Fusion Proteins/administration & dosage , Recombinant Fusion Proteins/metabolism , Sertoli Cells/cytology , Sertoli Cells/metabolism , Spermatogenesis/genetics , Spermatogonia/cytology , Spermatogonia/metabolism , Testis/embryology , Testis/metabolism , Transcription Factors/deficiency , Transcription Factors/geneticsABSTRACT
A compact, highly robust airborne High Spectral Resolution Lidar (HSRL) that provides measurements of aerosol backscatter and extinction coefficients and aerosol depolarization at two wavelengths has been developed, tested, and deployed on nine field experiments (over 650 flight hours). A unique and advantageous design element of the HSRL system is the ability to radiometrically calibrate the instrument internally, eliminating any reliance on vicarious calibration from atmospheric targets for which aerosol loading must be estimated. This paper discusses the design of the airborne HSRL, the internal calibration and accuracy of the instrument, data products produced, and observations and calibration data from the first two field missions: the Joint Intercontinental Chemical Transport Experiment--Phase B (INTEX-B)/Megacity Aerosol Experiment--Mexico City (MAX-Mex)/Megacities Impacts on Regional and Global Environment (MILAGRO) field mission (hereafter MILAGRO) and the Gulf of Mexico Atmospheric Composition and Climate Study/Texas Air Quality Study II (hereafter GoMACCS/TexAQS II).
ABSTRACT
The transcription factor Ets-variant gene 5 (ETV5) is essential for spermatogonial stem cell (SSC) self-renewal, as the targeted deletion of the Etv5 gene in mice (Etv5(-/-)) results in only the first wave of spermatogenesis. Reciprocal transplants of neonatal germ cells from wild-type (WT) and Etv5(-/-) testes were performed to determine the role of ETV5 in Sertoli cells and germ cells. ETV5 appears to be needed in both cell types for normal spermatogenesis. In addition, Etv5(-/-) recipients displayed increased interstitial inflammation and tubular involution after transplantation. Preliminary studies suggest that the blood-testis barrier (Sertoli-Sertoli tight junctional complex) is abnormal in the Etv5(-/-) mouse.
Subject(s)
Blood-Testis Barrier/physiology , DNA-Binding Proteins/physiology , Immunity, Innate/genetics , Spermatogenesis/genetics , Testis/immunology , Transcription Factors/physiology , Animals , Blood-Testis Barrier/immunology , DNA-Binding Proteins/genetics , Male , Mice , Mice, Knockout , Models, Biological , Tight Junctions/immunology , Tight Junctions/physiology , Transcription Factors/geneticsABSTRACT
A technique we refer to as Elevation Information in Tail (EIT) has been developed to provide improved lidar altimetry from CALIPSO lidar data. The EIT technique is demonstrated using CALIPSO data and is applicable to other similar lidar systems with low-pass filters. The technique relies on an observed relation between the shape of the surface return signals (peak shape) and the detector photo-multiplier tube transient response (transient response tail). Application of the EIT to CALIPSO data resulted in an order of magnitude or better improvement in the CALIPSO land surface 30-meter elevation measurements. The results of EIT compared very well with the National Elevation Database (NED) high resolution elevation maps, and with the elevation measurements from the Shuttle Radar Topography Mission (SRTM).