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The role of lidar in atmospheric studies concerned with radiative energy transfer and remote sensing is summarized. The application of lidar to climatic change investigations is proposed.
The convenient availability and simplicity of the Lorenz-Mie theory has resulted in a widespread practice of treating nonspherical particles (especially those in random orientation) as if they were spheres to which Lorenz-Mie results are applicable. However, the assumption of sphericity is rarely made after first having studied the effects of nonsphericity and having concluded that they are negligible. On the contrary, overwhelming evidence suggests that scattering properties of nonspherical particles, including those in random orientation, can significantly differ from those of volume- or surface-equivalent spheres. Hence, the last few decades have demonstrated major research efforts aimed at a significantly better understanding of the effects of particle shape and morphology on electromagnetic scattering. The goal of this presentation is to provide a concise summary of these efforts. The recent availability of theoretical techniques for computing single and multiple scattering of light by realistic polydispersions of spherical and nonspherical particles and the strong dependence of the Stokes scattering matrix on particle size, shape, and refractive index make polarization and depolarization measurements a powerful particle characterization tool. This presentation will focus on recent applications of photopolarimetric and lidar depolarization measurements to remote sensing characterization of tropospheric aerosols, polar stratospheric clouds (PSCs) and contrails. The talk will include (1) a short theoretical overview of the effects of particle microphysics on particle single-scattering characteristics; (2) the use of multi-angle multi-spectral photopolarimetry to retrieve the optical thickness, size distribution, refractive index, and number concentration of tropospheric aerosols over the ocean surface; and (3) the application of the T-matrix method to constraining the PSC and contrail particle microphysics using multi-spectral measurements of lidar backscatter and depolarization
The recent availability of theoretical techniques for computing single and multiple scattering of light by realistic polydispersions of spherical and nonspherical particles and the strong dependence of the Stokes scattering matrix on particle size, shape, and refractive index make polarization and depolarization measurements a powerful particle characterization tool. In this presentation I will describe recent applications of photopolarimetric and lidar depolarization measurements to remote sensing characterization of tropospheric aerosols, polar stratospheric clouds (PSCs), and contrails. The talk will include (1) a short theoretical overview of the effects of particle microphysics on particle single-scattering characteristics; (2) the use of multi-angle multi-spectral photopolarimetry to retrieve the optical thickness, size distribution, refractive index, and number concentration of tropospheric aerosols over the ocean surface; and (3) the application of the T-matrix method to constraining the PSC and contrail particle microphysics using multi-spectral measurements of lidar backscatter and depolarization.
We have measured the CO2 volume mixing ratio (VMR) within the planetary boundary layer (PBL) using cloud slicing with an airborne pulsed integrated path differential absorption (IPDA) lidar from flight altitudes of up to 13 km. During a flight over Iowa in summer 2011, simultaneous measurement of the optical range and CO2 absorption to clouds and the ground were made using time-resolved detection of pulse echoes from each scattering surface.We determined the CO2 absorption in the PBL by differencing the two lidar-measured absorption line shapes, one to a broken shallow cumulus cloud layer located at the top of the PBL and the other to the ground. Solving for the CO2 VMR in the PBL and that of the free troposphere, we measured a ≈15 ppm (4%) drawdown in the PBL. Both CO2 VMRs were within ≈3 ppm of in situ CO2 profile measurements. We have also demonstrated cloud slicing using scatter from thin, diffuse cirrus clouds and cumulus clouds, which allowed solving for the CO2 VMR for three vertical layers. The technique and retrieval algorithm are applicable to a space-based lidar instrument as well as to lidar IPDA measurements of other trace gases. Thus, lidar cloud slicing also offers promise toward space-based remote sensing of vertical trace gas profiles in the atmosphere using a variety of clouds.
Scanning holographic lidar receivers are currently in use in two operational lidar systems, PHASERS (Prototype Holographic Atmospheric Scanner for Environmental Remote Sensing) and now HARLIE (Holographic Airborne Rotating Lidar Instrument Experiment). These systems are based on volume phase holograms made in dichromated gelatin (DCG) sandwiched between 2 layers of high quality float glass. They have demonstrated the practical application of this technology to compact scanning lidar systems at 532 and 1064 nm wavelengths, the ability to withstand moderately high laser power and energy loading, sufficient optical quality for most direct detection systems, overall efficiencies rivaling conventional receivers, and the stability to last several years under typical lidar system environments. Their size and weight are approximately half of similar performing scanning systems using reflective optics. The cost of holographic systems will eventually be lower than the reflective optical systems depending on their degree of commercialization. There are a number of applications that require or can greatly benefit from a scanning capability. Several of these are airborne systems, which either use focal plane scanning, as in the Laser Vegetation Imaging System or use primary aperture scanning, as in the Airborne Oceanographic Lidar or the Large Aperture Scanning Airborne Lidar. The latter class requires a large clear aperture opening or window in the aircraft. This type of system can greatly benefit from the use of scanning transmission holograms of the HARLIE type because the clear aperture required is only about 25% larger than the collecting aperture as opposed to 200-300% larger for scan angles of 45 degrees off nadir.
High-energy 2-microns lasers have been incorporated in a breadboard coherent Doppler lidar to test component technologies and explore applications for remote sensing of the atmosphere. Design of the lidar is presented including aspects in the laser transmitter, receiver, photodetector, and signal processing. Sample data is presented on wind profiling and CO2 concentration measurements.
High-energy 2-micrometer wavelength lasers have been incorporated in a prototype coherent Doppler lidar to test component technologies and explore applications for remote sensing of the atmosphere. Design of the lidar is presented including aspects in the laser transmitter, receiver, photodetector, and signal processing. Calibration tests and sample atmospheric data are presented on wind and aerosol profiling.
The development of an eye-safe, airborne LIDAR that exploits the decorrelation of the heterodyne signal to detect clear air turbulence is reported. A one watt average power transmitter is capable of detecting clear air turbulence to over 20 km is subvisual cirrus (an environment highly correlated with instabilities of sratified shear layers). In the absence of subvisual cirrus, a 4 km detection range is maintained. A table depicting the warning time in seconds with respect to the aircraft speed and instrument range (in kilometers) is presented.
A region of thermal enhancement of the mesosphere has been detected on numerous occasions by in situ measurements, remote sensing from space, and lidar techniques. The source of these 'temperature inversion layers' has been attributed in the literature to the dissipation relating to dynamical forcing by gravity wave or tidal activity. However, evidence that gravity wave breaking can produce the inversion layer with amplitude as large as that observed in lidar measurements has been limited to results of numerical modeling. An alternative source for the production of the thermal inversion layer in the mesosphere is the direct deposition of heat by exothermic chemical reactions. Two-dimensional modeling combining a comprehensive model of the mesosphere photochemistry with the dynamical transport of long-lived species shows that the region from 80 to 95 km may be heated as much as 3 to 10 K/d during the night and half this rate during the day. Given the uncertainties in our understanding of the dynamics and chemistry for the mesopause region, separating the two sources by passive observations of the mesosphere thermal structure looks to be difficult. Therefore we have considered an active means for producing a mesopause thermal layer, namely the release of ozone into the upper mesosphere from a rocket payload. The induced effects would include artificial enhancements of the OH and Na airglow intensities as well as the mesopause thermal structure. The advantages of the rocket release of ozone is that detection of these effects by ground-based imaging, radar, and lidar systems and comparison of these effects with model predictions would help quantify the partition of the artificial inversion layer production into sources of dynamical and chemical forcing.
Profiling of atmospheric carbon dioxide (CO2) is important for understanding the natural carbon cycle on Earth and its influence on global warming and climate change. Differential absorption lidar is a powerful remote sensing technique used for profiling and monitoring atmospheric constituents. Recently there has been an interest to apply this technique, at the 2 m wavelength, for investigating atmospheric CO2. This drives the need for high quality detectors at this wavelength. Although 2 m detectors are commercially available, the quest for a better detector is still on. The detector performance, regarding quantum efficiency, gain and associated noise, affects the DIAL signal-to-noise ratio and background signal, thereby influencing the instrument sensitivity and dynamic range. Detectors based on the III-V based compound materials shows a strong potential for such application. In this paper the detector requirements for a long range CO2 DIAL profiles will be discussed. These requirements were compared to newly developed III-V compound infrared detectors. The performance of ternary InGaSb pn junction devices will be presented using different substrates, as well as quaternary InGaAsSb npn structure. The performance study was based on experimental characterization of the devices dark current, spectral response, gain and noise. The final results are compared to the current state-of-the-art InGaAs technology. Npn phototransistor structure showed the best performance, regarding the internal gain and therefore the device signal-to-noise ratio. 2-micrometers detectivity as high as 3.9 x 10(exp 11) cmHz(sup 1/2)/W was obtained at a temperature of -20 C and 4 V bias voltage. This corresponds to a responsivity of 2650 A/W with about 60% quantum efficiency.
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Aerosol overlying marine stratocumulus clouds is a persistent feature in the southeast Atlantic during the biomass burning season, July through November. We sampled aerosol and cloud from an airborne research platform, the NASA P3, during the deployments of ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) encompassing the peak biomass burning season. We used the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) to quantify the aerosol’s optical properties, notably the aerosol optical depth (AOD) by directly measuring the amount of light attenuation. We present an overview of very recent AOD measurements and contrast those to previous deployments. We observed an average AOD at 500 nm of 0.33 (0.30) in September 2016 (August 2017), with similar spatial dependence as observed by the MODIS instrument on board the TERRA and AQUA satellites. We also show full spectral vertical dependence of AOD from flight profiles, which compares favorably to the integrated aerosol extinction profile obtained by the active remote sensing High Spectral Resolution Lidar-2 (HSRL-2). We also present a quantification of the gap extent separating cloud top and aerosol layer bottom. Using hyperspectral transmitted light measurements from 4STAR, in conjunction with hyperspectral hemispheric irradiance measurements from the Solar Spectral Flux Radiometers (SSFR), we retrieved aerosol intensive properties (asymmetry parameter, single scattering albedo), aerosol size distributions, cloud optical depth (COD), cloud particle effective radius, and cloud thermodynamic phase. Cloud properties, also presented here, are obtained from 4STAR measurements of scattered light below clouds.
The NASA Langley Research Center’s High Spectral Resolution Lidar with Differential Absorption Lidar (HSRL-DIAL) instrument was flown on the NASA DC-8 aircraft during the Fire Influence on Region to Global Environments and Air Quality (FIREX-AQ; https://www.esrl.noaa.gov/csl/projects/firex-aq/) field campaign. The airborne HSRL-DIAL system retrieves aerosol backscatter and depolarization at 3 wavelengths (355, 532, and 1064 nm), aerosol extinction at 532 nm, and ozone concentration (differential at 290 and 300 nm). Additionally, the HSRL-DIAL system incorporates both a zenith and nadir telescope allowing for retrievals from in-smoke sampling to be integrated through the plume. During the first portion of the FIREX-AQ campaign, the DC8 aircraft sampled more than ten large-scale fires with varying fuels, combustion stages, and metrological conditions, with some fires being sampled multiple times across separate days. This presentation focuses on the retrievals of aerosol backscatter (at 532 and 1064 nm), aerosol depolarization (at 532 nm and 1064 nm), aerosol optical thickness (at 532 nm), lidar ratio, and color ratio to examine the changes in these properties in the smoke plume as they are advected downwind.
When aerosol overlie bright clouds, their radiative impact on the incident light can be either positive or negative. This difference in radiative impact promotes difficulties in remote sensing aerosol properties, which have shown biases in aerosol optical depth (AOD) retrievals when clouds are underneath. To better constrain this quantity, we have measured aerosols above clouds over the course of 3 years in the southeast Atlantic as part of the ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES). These directly measured AOD above clouds are used to build and improve upon the current Near-Real-Time MODACAERO algorithm for above cloud AOD from MODIS, into a continuity product for NASA EOS/SNPP/JPSS. Here we present a summary of the above cloud aerosol optical depth measured during ORACLES, and that will be used for porting the MODACAERO algorithm to the continuity product. We use aerosol optical depth measured directly from sunlight attenuation using the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) and compare it to the active remote sensing, High Spectral Resolution Lidar-2 (HSRL-2). We present a combination of all 3 years of measurements during peak biomass burning season. We have observed average above cloud aerosol optical depth at 500 nm ranging from 0.28 to 0.37, with the maximum in August 2017. We emphasize the use of improved aerosol absorption and scattering models based on airborne measurements during ORACLES.
A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth’s radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth’s climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near–real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.
Mexico is one of the countries with great potential for the UN's Reducing Emissions from Deforestation and Forest Degradation (REDD+) program, a key nature-based solution for the forest sector. To monitor carbon stock changes, there is a growing demand for unbiased Monitoring Reporting Verification (MRV) systems to facilitate effective forest management and climate change mitigation strategies. Remote sensing-based national aboveground biomass density (AGBD) estimation over Mexico is scarce and often limited to one-time static mapping, leading to spatiotemporal inconsistency in inputs. As an effort under NASA's Carbon Monitoring System (CMS) program, we have developed a remote sensing-based approach to create consistent historical AGBD maps of Mexico using multi-stream remote sensing data, including spaceborne lidar GEDI and long-term Landsat time series, as well as topographic information. We employ the continuous change detection and classification (CCDC) algorithm for temporal modeling of Landsat surface reflectance, followed by the inference of forest AGBD using a random forest machine learning algorithm with the temporal information of land surface dynamics extracted by the CCDC as input. GEDI provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. In this presentation, we share the progress made in developing a spatially explicit mapping of historical AGBD changes associated with land surface changes and post-disturbance landscapes.
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