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On 8 May 1997 vertical profiles of over 30 different gases were measured remotely in solar occultation by the JPl MkIV Interferometer during a balloon flight launched from Fairbanks, Alaska.
From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations cover large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite data sets. The development and deployment of SMARTCOMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile facilities are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instruments fall into three categories: flux radiometer, radiance sensor and in-situ probe. In this paper, we will demonstrate the capability of SMART-COMMIT in recent field campaigns (e.g., CRYSTAL-FACE, UAE 2, BASEASIA, NAMMA) that were designed and executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., biomass-burning smoke, airborne dust) and cirrus clouds. We envision robust approaches in which well-collocated ground-based measurements and space-borne observations will greatly advance our knowledge of extensive aerosols and clouds.
One outgrowth of the Convection and Precipitation/Electrification (CaPE) experiment that took place in central Florida during July and August 1991 was the creation of the CaPE Hydrometeorology Project (CHymP). The principal goal of this project is to investigate the daily water cycle of the CaPE experimental area by analyzing the numerous land and atmosphere in situ and remotely sensed data sets that were generated during the 40-days of observations. The water cycle comprises the atmospheric branch. In turn, the atmospheric branch comprises precipitation leaving the base of the atmospheric volume under study, evaporation and transpiration entering the base, the net horizontal fluxes of water vapor and cloud water through the volume and the conversion of water vapor to cloud water and vice-versa. The sum of these components results in a time rate of change in the water and liquid water (or ice) content of the atmospheric volume. The components of the land branch are precipitation input to and evaporation and transpiration output from the surface, net horizontal fluxes of surface and subsurface water, the sum of which results in a time rate of change in surface and subsurface water mass. The objective of CHymP is to estimate these components in order to determine the daily water budget for a selected area within the CaPE domain. This work began in earnest in the summer of 1992 and continues. Even estimating all the budget components for one day is a complex and time consuming task. The discussions below provides a short summary of the rainfall quality assessment procedures followed by a plan for estimating the horizontal moisture flux.
One of the technical challenges within the Atmospheric Environment Safety Technologies (AEST) Project of the Aviation Safety Program was to "improve and expand remote sensing and mitigation of hazardous atmospheric environments and phenomena"1. In 2012, the author performed an analysis comparing various characteristics of accidents associated with different types of atmospheric hazard environments2. This document reports an update to that analysis which was done in preparation for presenting these findings at the 2015 annual meeting of the Transportation Research Board. Specifically, an additional three years of data were available, and a time-trend analysis was added.
The NASA/NOAA/AMS Earth Science Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to Florida and the KSC Visitor's Center. Go back to the early weather satellite images from the 1960s see them contrasted with the latest International global satellite weather movies including killer hurricanes and tornadic thunderstorms. See the latest spectacular images from NASA and the National Oceanic and Atmospheric Administration (NOAA) remote sensing missions like the Geostationary Operational Environmental Satellites (GOES), NOAA, Tropical Rainfall Measuring Mission (TRMM), SeaWiFS, Landsat7, and new Terra which will be visualized with state-of-the art tools. Shown in High Definition TV resolution (2048 x 768 pixels) are visualizations of hurricanes Lenny, Floyd, Georges, Mitch, Fran, and Linda. See visualizations featured on covers of magazines like Newsweek, TIME, National Geographic, Popular Science, and on National and International Network TV. New Digital Earth visualization tools allow us to roam and zoom through massive global images including a Landsat tour of the US, with drill-downs into major cities using one meter resolution spy-satellite technology from the Space Imaging IKONOS satellite. Spectacular new visualizations of the global atmosphere and oceans are shown. See massive dust storms sweeping across Africa. See ocean vortexes and currents that bring up the nutrients to feed tiny plankton and draw the fish, giant whales and fisherman. See the how the ocean blooms in response to these currents and El Nino/La Nina climate changes. The demonstration is interactively driven by a SGI Octane Graphics Supercomputer with dual CPUs, 5 Gigabytes of RAM and Terabyte disk using two projectors across the super sized Universe Theater panoramic screen.
Results are presented for a study intended to develop a general remote sensing-aided cost-effective procedure to estimate watershed-wide water loss to the atmosphere via evapotranspiration and to estimate net solar radiation over the watershed. Evapotranspiration estimation employs a basic two-stage two-phase sample of three information resolution levels. Net solar radiation is taken as one of the variables at each level of evapotranspiration modeling. The input information for models requiring spatial information will be provided by Landsat digital data, environmental satellite data, ground meteorological data, ground sample unit information, and topographic data. The outputs of the sampling-estimation/data bank system will be in-place maps of evapotranspiration on a data resolution element basis, watershed-wide evapotranspiration isopleths, and estimates of watershed and subbasin total evapotranspiration with associated statistical confidence bounds. The methodology developed is being tested primarily on the Spanish Creek Watershed Plumas County, California.
The gas giants (Jupiter and Saturn) and icy giants (Uranus and Neptune) are fluid planets with atmospheres primarily made of hydrogen and helium. The part of their atmospheres accessible to remote sensing occupies only a small fraction of their radii (0.05%). Clouds and hazes form around the 1 bar altitude pressure level and extend vertically, according to the thermochemical models, in a layer with a thickness of 200_500 km where temperature increases with depth (usually known as the "weather layer"). Clouds made of NH3, NH4SH, H2O (in Jupiter and Saturn), with the addition of CH4 (in Uranus and Neptune), cover the planet in stratified layers that are mixed with unknown hromophore agents. Dynamical phenomena in the weather layer shape different cloud patterns that define the visible appearance of these planets. In the thermal part of the spectrum clouds act as opacity sources providing brightness contrasts. The ensemble of cloud morphologies in terms of shapes, sizes and albedos allows their use as tracers of the atmospheric motions in the weather layer (Fig. 4.1). This is the main tool employed so far to study the winds on these fourplanets.
In recent years, some remote-sensing applications require advanced airborne multi-sensor systems to provide high performance reflective and emissive spectral imaging measurement rapidly over large areas. The key or unique problem of characteristics is associated with a black box back-end system that operates a suite of cutting-edge imaging sensors to collect simultaneously the high throughput reflective and emissive spectral imaging data with precision georeference. This back-end system needs to be portable, easy-to-use, and reliable with advanced onboard processing. The innovation of the black box backend is a miniaturized airborne imaging central server system (MAICSS). MAICSS integrates a complex embedded system of systems with dedicated power and signal electronic circuits inside to serve a suite of configurable cutting-edge electro- optical (EO), long-wave infrared (LWIR), and medium-wave infrared (MWIR) cameras, a hyperspectral imaging scanner, and a GPS and inertial measurement unit (IMU) for atmospheric and surface remote sensing. Its compatible sensor packages include NASA s 1,024 1,024 pixel LWIR quantum well infrared photodetector (QWIP) imager; a 60.5 megapixel BuckEye EO camera; and a fast (e.g. 200+ scanlines/s) and wide swath-width (e.g., 1,920+ pixels) CCD/InGaAs imager-based visible/near infrared reflectance (VNIR) and shortwave infrared (SWIR) imaging spectrometer. MAICSS records continuous precision georeferenced and time-tagged multisensor throughputs to mass storage devices at a high aggregate rate, typically 60 MB/s for its LWIR/EO payload. MAICSS is a complete stand-alone imaging server instrument with an easy-to-use software package for either autonomous data collection or interactive airborne operation. Advanced multisensor data acquisition and onboard processing software features have been implemented for MAICSS. With the onboard processing for real time image development, correction, histogram-equalization, compression, georeference, and data organization, fast aerial imaging applications, including the real time LWIR image mosaic for Google Earth, have been realized for NASA fs LWIR QWIP instrument. MAICSS is a significant improvement and miniaturization of current multisensor technologies. Structurally, it has a complete modular and solid-state design. Without rotating hard drives and other moving parts, it is operational at high altitudes and survivable in high-vibration environments. It is assembled from a suite of miniaturized, precision-machined, standardized, and stackable interchangeable embedded instrument modules. These stackable modules can be bolted together with the interconnection wires inside for the maximal simplicity and portability. Multiple modules are electronically interconnected as stacked. Alternatively, these dedicated modules can be flexibly distributed to fit the space constraints of a flying vehicle. As a flexibly configurable system, MAICSS can be tailored to interface a variety of multisensor packages. For example, with a 1,024x1,024 pixel LWIR and a 8,984x6,732 pixel EO payload, the complete MAICSS volume is approximately 7x9x11 in. (=18x23x28 cm), with a weight of 25 lb (=11.4 kg).
Since 1997 NASA has been successfully launching a series of satellites - the Earth Observing System (EOS) - to intensively study, and gain a better understanding of, the Earth as an integrated system. Space-borne remote sensing observations, however, are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. Through numerous participations, particularly but not limited to the EOS remote-sensing/retrieval and validation projects over the years, NASA/GSFC has developed and continuously refined ground-based networks and mobile observatories that proved to be vital in providing high temporal measurements, which complement and enrich the satellite observations. These are: the AERO NET (AErosol RObotic NETwork) a federation of ground-based globally distributed network of spectral sun-sky photometers; the MPLNET (Micro-Pulse Lidar NETwork, a similarly organized network of micro-pulse lidar systems measuring aerosol and cloud vertical structure continuously; and the SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere, mobile observatories, a suite of spectral radiometers and in-situ probes acquiring supersite measurements. Most MPLNET sites are collocated with those of AERONET, and both networks always support the deployment of SMART-COMMIT worldwide. These data products follow the data structure of EOS conventions: Level-0, instrument archived raw data; Level-1 (or 1.5), real-time data with no (or limited) quality assurance; Level-2, not real high temporal and spectral resolutions. In this talk, we will present NASA/GSFC groundbased facilities, serving as network or supersite observations, which have been playing key roles in major international research projects over diverse aerosol regimes to complement and enrich the EOS scientific research.
The atmospheric boundary layer (ABL) height plays a key role in many atmospheric processes as one of the dominant flow length scales. However, a systematic quantification of the ABL height over the entire range of scales (i.e., with periods ranging from one minute to one year) is still lacking in literature. In this work, the ABL height is quantified based on high-resolution measurements collected by a scanning pulsed Doppler LiDAR during the recent American WAKE experimeNt (AWAKEN) campaign. The high availability of ABL height estimates (≈2200 collected over one year and each of them based on 10-min averaged statistics) allows to robustly assess five different ABL height models, i.e., one for convective thermal conditions and four for stable conditions. Thermal condition is quantified by a stability parameter spanning three orders of magnitude and probed by near-ground 3D sonic anemometry. The free-atmosphere stability, quantified by the Brunt–Väisälä frequency, is both calculated from simultaneous radiosonde measurements and obtained from the best fit of two of the chosen ABL height models. Good agreement is found between the data and three of the chosen models, quantified by mean absolute errors on the ABL height between 281 and 585 m. Furthermore, the seasonal variability of the convective ABL height model parameters (−15% to +23% with respect to the year baseline) agrees with the variability of buoyancy-generated turbulence caused by the variation in solar radiation throughout the year.
Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.
Vicarious calibration approaches using in-situ measurements are key techniques applied to on-orbit remote sensors. The in-situ measurements have advantages in terms of traceability and quantifiable accuracy that make them ideal for inter-consistency studies of on-orbit sensors. The Committee on Earth Observation Satellites Working Group on Calibration and Validation Infrared Visible Optical Sensors initiated the Radiometric Calibration Network (RadCalNet) to provide automated surface and top-of-atmosphere (TOA) reflectance data from multiple participating ground sites to the worldwide user community. RadCalNet standardizes protocols for collecting data, processes TOA reflectance, and provides International System of Units traceable uncertainty budgets for the five currently operating sites. RadCalNet data from the Railroad Valley Playa, Nevada, site was used to provide an SI-traceable, absolute radiometric calibration of the Enhanced MODIS Airborne Simulator as part of an overflight of opportunity during the FIREX-AQ campaign. The results shown here demonstrate the utility of RadCalNet data for absolute radiometric calibration of airborne imagers making flights of opportunity without the need for coordination with a field validation team.
The mid-wave infrared (MWIR) spectrum contains a wealth of invaluable information including the spectral ‘fingerprint’ of many chemical species and has applications in remote sensing and astronomical imaging. Traditionally, filtering for the MWIR is achieved by means of passive multilayer interference (dichroic) filters, Fabry-Perot-based micro-electro-mechanical system (MEMS) filters, liquid crystal tunable filters, and focal plane array (FPA) filters. For accurate multispectral imaging applications, these approaches suffer from various limitations such as: having moving parts; exhibiting slow response times, and; having limited spectral bandwidth / resolution. Recently, there has been significant interest toward ‘active’ spectral imaging technologies, whereby the ability to provide electrically tunable narrowband filtering—spanning the entire MWIR—is highly desirable. In this work we introduce a new spectral imaging technology, namely actively tunable optical transmission filters using the phase-change material (PCM) GexSbyTez (GST). The GST exhibits a large, reversible change in its refractive index across the MWIR upon a phase transition (from amorphous to crystalline). This refractive index modulation governs the filter’s optical characteristics. Through an optical stimulus or applied voltage—which changes the GST state from amorphous to crystalline—one can actively tune the filter with MHz speed. We incorporate GST into optimized guided mode resonance (GMR) and plasmonic nanohole array (PNA) device architectures, enabling <10nm spectral resolution and tunable operation across 3~5µm. Our proposed PCM-MWIR filter will be able to extract the maximum amount of ‘useful’ information within the atmosphere for remote Earth sensing measurements at operational speeds orders of magnitude faster than current airborne-based sensors. Moreover, it may enable affordable SmallSat-based MWIR instrumentation which is complimentary to other observation systems. The MISSE (Materials International Space Station Experiment-Flight Facility) experiment has been proposed as a testbed for a PCM-based tunable MWIR filter module to allow exposure of the module to the low Earth orbit space environment. This will provide valuable data regarding the robustness of the filter to withstand the radiation and atomic oxygen environment and allow assessment of the technology for use in space applications.
There is renewed interest in using optical remote sensing techniques for measuring and monitoring airborne toxins. Many instruments have been used to measure traces of atmospheric molecular species. Some optical remote sensing technology is in use for measuring or monitoring toxic or pollutant gases. The examples in this article provide a number of lessons that may be of use in the new field of optical remote sensing of toxic gases. Topics covered include the following: atmospheric properties, Fourier transform spectrometry, gas-filter correlation, differential absorption laser systems, aircraft missions, laser long-path instruments, differential optical absorption spectrometry, and ozone measurement.
Multi-angle polarimetric (MAP) measurements can enable detailed characterization of aerosol microphysical and optical properties and improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere–ocean system. Theoretical pixel-wise retrieval uncertainties based on error propagation have been used to quantify retrieval performance and determine the quality of data products. However, standard error propagation techniques in high-dimensional retrievals may not always represent true retrieval errors well due to issues such as local minima and the nonlinear dependence of the forward model on the retrieved parameters near the solution. In this work, we analyze these theoretical uncertainty estimates and validate them using a flexible Monte Carlo approach. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on efficient neural network forward models, is used to conduct the retrievals and uncertainty quantification on both synthetic HARP2 (Hyper-Angular Rainbow Polarimeter 2) and AirHARP (airborne version of HARP2) datasets. In addition, for practical application of the uncertainty evaluation technique in operational data processing, we use the automatic differentiation method to calculate derivatives analytically based on the neural network models. Both the speed and accuracy associated with uncertainty quantification for MAP retrievals are addressed in this study. Pixel-wise retrieval uncertainties are further evaluated for the real AirHARP field campaign data. The uncertainty quantification methods and results can be used to evaluate the quality of data products, as well as guide MAP algorithm development for current and future satellite systems such as NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission.
Earth's high-latitude regions show a considerable amount of cloud coverage, which significantly affects global radiation budgets. Here, in this study, we examine ground- and ship-based remote sensing observations from two Atmospheric Radiation Measurement (ARM) field campaigns conducted in the high-latitude regions of Northern and Southern Hemispheres (NH and SH). A comparison of macrophysical properties for low, mid-level, high, and deep clouds shows that the cloud top heights and thickness values are higher in the Arctic for each cloud type compared with the Southern Ocean and Antarctic regions, possibly due to higher sea surface temperatures in the north Atlantic. The Arctic also shows lower ice phase occurrence frequencies compared with the SH high latitudes for low clouds. For high, mid-level and deep clouds, the cloud phase distributions as a function of temperature show small geographical variabilities. The observations are then compared with the Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) to evaluate the representations of these cloud properties. Here, the results show that the model captures cloud base and top heights well and reproduces the differences in cloud macrophysical properties between the two hemispheres. But the model underestimates ice phase frequencies for all cloud types. Such model cloud phase bias is strongly correlated with positive relative humidity biases and negative aerosol number concentration biases, indicating an important role of relative humidity and aerosols in modulating cloud phase partitioning in the model.
Supercooled fogs can have an important radiative impact at the surface of the Greenland Ice Sheet, but they are difficult to detect and our understanding of the factors that control their lifetime and radiative properties is limited by a lack of observations. This study demonstrates that spectrally resolved measurements of downwelling longwave radiation can be used to generate retrievals of fog microphysical properties (phase and particle effective radius) when the fog visible optical depth is greater than ~0.25. For 12 cases of fog under otherwise clear skies between June and September 2019 at Summit Station in central Greenland, nine cases were mixed-phase. The mean ice particle (optically-equivalent sphere) effective radius was 24.0 ± 7.8 µm, and the mean liquid droplet effective radius was 14.0 ± 2.7 µm. These results, combined with measurements of aerosol particle number concentrations, provide evidence supporting the hypotheses that (a) low surface aerosol particle number concentrations can limit fog liquid water path, (b) fog can act to increase near-surface aerosol particle number concentrations through enhanced mixing, and (c) multiple fog events in quiescent periods gradually deplete near-surface aerosol particle number concentrations.
Observing thermodynamic profiles within the planetary boundary layer is essential to understanding and predicting atmospheric phenomena because of the significant exchange of sensible and latent heat between the land and atmosphere within that layer. The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based infrared spectrometer used to obtain the vertical profiles of temperature and water vapor mixing ratio. Most AERIs are only capable of zenith views, although the Marine AERI (M-AERI) has a design that allows it to view various elevation angles. In this study, we quantify the improvement in the information content and accuracy of the retrieved profiles when nonzenith angles are included, as is common with microwave radiometer profilers. The impacts of the additional scan angles are quantified through both a synthetic study and with M-AERI observations from the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) campaign. Furthermore, the simulation study shows that low elevation angles contain more information content for temperature whereas high elevation angles have more information content for water vapor. Outside of very humid environments, the addition of low elevation angles also results in lower root-mean-square errors when compared with high angles for both temperature and water vapor mixing ratio, although this is primarily a result of averaging multiple observations together to reduce instrument noise. Real-world results from the ACAPEX dataset indicate similar results as were found for the simulation study, although not all predicted benefits are realized because of the small sample size and observational uncertainties.