Remote Sensing of Column CO2, Atmospheric Pressure, and Vertical Distribution of Dust and Clouds on Mars using Differential Absorption Lidar at 1.96 µm on an Orbiter
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DIAL↗
SEARCH · Engineering Papers
Results for “remote sensing of clouds”
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Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing
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T. F. Eck↗
Organic Ices in Titan's Stratosphere
Titan’s stratospheric ice clouds are by far the most complex of any observed in the solar system, with over a dozen organic vapors condensing out to form a suite of pure and co-condensed ices, typically observed at high winter polar latitudes. Once these stratospheric ices are formed, they will diffuse throughout Titan’s lower atmosphere and most will eventually precipitate to the surface, where they are expected to contribute to Titan’s regolith. Early and important contributions were first made by the InfraRed Interferometer Spectrometer (IRIS) on Voyager 1, followed by notable contributions from IRIS’ successor, the Cassini Composite InfraRed Spectrometer (CIRS), and to a lesser extent, from Cassini’s Visible and Infrared Mapping Spectrometer (VIMS) and the Imaging Science Subsystem (ISS) instruments. All three remote sensing instruments made new ice cloud discoveries, combined with monitoring the seasonal behaviors and time evolution throughout Cassini’s 13-year mission tenure. A significant advance by CIRS was the realization that co-condensing chemical compounds can account for many of the CIRS-observed stratospheric ice cloud spectral features, especially for some that were previously puzzling, even though some of the observed spectral features are still not well understood. Relevant laboratory transmission spectroscopy efforts began just after the Voyager encounters, and have accelerated in the last few years due to new experimental efforts aimed at simulating co-condensed ices in Titan’s stratosphere. This review details the current state of knowledge regarding the organic ice clouds in Titan’s stratosphere, with perspectives from both observational and experimental standpoints.
Astronomy↗
Organic Ices in Titan's Stratosphere
Titan’s stratospheric ice clouds are by far the most complex of any observed in the solar system, with over a dozen organic vapors condensing out to form a suite of pure and co-condensed ices, typically observed at high winter polar latitudes. Once these stratospheric ices are formed, they will diffuse throughout Titan’s lower atmosphere and most will eventually precipitate to the surface, where they are expected to contribute to Titan’s regolith. Early and important contributions were first made by the InfraRed Interferometer Spectrometer (IRIS) on Voyager 1, followed by notable contributions from IRIS’ successor, the Cassini Composite InfraRed Spectrometer (CIRS), and to a lesser extent, from Cassini’s Visible and Infrared Mapping Spectrometer (VIMS) and the Imaging Science Subsystem (ISS) instruments. All three remote sensing instruments made new ice cloud discoveries, combined with monitoring the seasonal behaviors and time evolution throughout Cassini’s 13-year mission tenure. A significant advance by CIRS was the realization that co-condensing chemical compounds can account for many of the CIRS-observed stratospheric ice cloud spectral features, especially for some that were previously puzzling, even though some of the observed spectral features are still not well understood. Relevant laboratory transmission spectroscopy efforts began just after the Voyager encounters, and have accelerated in the last few years due to new experimental efforts aimed at simulating co-condensed ices in Titan’s stratosphere. This review details the current state of knowledge regarding the organic ice clouds in Titan’s stratosphere, with perspectives from both observational and experimental standpoints.
C. M. Anderson↗
Organic Ices in Titan’s Stratosphere
Titan’s stratospheric ice clouds are by far the most complex of any observed in the solar system, with over a dozen organic vapors condensing out to form a suite of pure and co-condensed ices, typically observed at high winter polar latitudes. Once these stratospheric ices are formed, they will diffuse throughout Titan’s lower atmosphere and most will eventually precipitate to the surface, where they are expected to contribute to Titan’s regolith. Early and important contributions were first made by the InfraRed Interferometer Spectrometer (IRIS) on Voyager 1, followed by notable contributions from IRIS’ successor, the Cassini Composite InfraRed Spectrometer (CIRS), and to a lesser extent, from Cassini’s Visible and Infrared Mapping Spectrometer (VIMS) and the Imaging Science Subsystem (ISS) instruments. All three remote sensing instruments made new ice cloud discoveries, combined with monitoring the seasonal behaviors and time evolution throughout Cassini’s 13-year mission tenure. A significant advance by CIRS was the realization that co-condensing chemical compounds can account for many of the CIRS-observed stratospheric ice cloud spectral features, especially for some that were previously puzzling, even though some of the observed spectral features are still not well understood. Relevant laboratory transmission spectroscopy efforts began just after the Voyager encounters, and have accelerated in the last few years due to new experimental efforts aimed at simulating co-condensed ices in Titan’s stratosphere. This review details the current state of knowledge regarding the organic ice clouds in Titan’s stratosphere, with perspectives from both an observational and experimental standpoint.
Ices↗
Advancing Technologies for Climate Observation
Climate research needs Accurate global cloud ice measurements Cloud ice properties are fundamental controlling variables of radiative transfer and precipitation Cost-effective, sensitive instruments for diurnal and wide-swath coverage Mature technology for space remote sensing IceCube objectivesDevelop and validate a flight-qualified 883 GHz receiver for future use in ice cloud radiometer missions Raise TRL (57) of 883 GHz receiver technology Reduce instrument cost and risk by developing path to space for COTS sub-mm-wave receiver systems Enable remote sensing of global cloud ice with advanced technologies and techniques
radiative transfer↗
IceCube: Spaceflight Demonstration of 883-GHz Cloud Radiometer for Future Science
Cloud ice play important roles in Earth’s climate and weather systems through their interactions with atmospheric radiation, dynamics, energy and precipitation processes. Submillimeter (submm) wave remote sensing at 200-1000 GHz is able to provide the sensitivity not covered by visible (VIS)/infrared (IR) and low-frequency microwave (MW) sensors (10-183 GHz), and measure cloud ice in the middle-to-upper troposphere. The IceCube 883-GHz cloud radiometer is the latest of NASA’s efforts to advance the technology readiness level (TRL) of submm-wave receiver technology for future compact, low-cost implementation of Earth observing systems. Emerging CubeSat opportunities allow a fast-track development and spaceflight demonstration of IceCube on a 3-U CubeSat. Funded by NASA’s In-Space Validation of Earth Science Technologies (InVEST) program and Science Mission Directorate (SMD), IceCube is the first CubeSat developed and flown by Goddard Space Flight Center (GSFC) in 2.5 years, using commercial off-the-shelf (COTS) components and subsystems. It was successfully released from International Space Station (ISS) in May 2017, acquired 15-month science data and produced the first global map of the 883-GHz cloud ice. It achieved all mission objectives and provided a pathway for future cost-effective cloud observations from CubeSat constellation.
Submm-wave remote sensing↗
On the Retrieval of Ice Cloud Particle Shapes from POLDER Measurements
Shapes of ice crystals can significantly affect the radiative transfer in ice clouds. The angular distribution of the polarized reflectance over ice clouds strongly depends on ice crystal shapes. Although the angular-distribution features of the total or polarized reflectance over ice clouds implies a possibility of retrieving ice cloud particle shapes by use of remote sensing data, the accuracy of the retrieval must be evaluated. In this study, a technique, which applies single ice crystal habit and multidirectional polarized radiance to retrieve ice cloud particle shapes, is assessed. Our sensitivity studies show that the retrieved particle shapes &om this algorithm can be considered good approximations to those in actual clouds in calculation of the phase matrix elements. Although a fractal poly-crystal shape or an inhomogeneous hexagonal column may also produce this type of phase functions, more representative single-scattering properties from combinations of natural particle shapes and size distributions may still be necessary in accurate retrieval of other cloud properties such as optical thickness and particle size.
Sun, W.↗
Cloud Detection over Snow and Ice with Oxygen A- and B-band Observations from the Earth Polychromatic Imaging Camera (EPIC)
Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.
EPIC↗
Fog and Cloud Induced Aerosol Modification Observed by AERONET
Large fine mode (sub-micron radius) dominated aerosols in size distributions retrieved from AERONET have been observed after fog or low-altitude cloud dissipation events. These column-integrated size distributions have been obtained at several sites in many regions of the world, typically after evaporation of low altitude cloud such as stratocumulus or fog. Retrievals with cloud processed aerosol are sometimes bimodal in the accumulation mode with the larger size mode often approx.0.4 - 0.5 microns radius (volume distribution); the smaller mode typically approx.0.12 to aprrox.0.20 microns may be interstitial aerosol that were not modified by incorporation in droplets and/or aerosol that are less hygroscopic in nature. Bimodal accumulation mode size distributions have often been observed from in situ measurements of aerosols that have interacted with clouds, and AERONET size distribution retrievals made after dissipation of cloud or fog are in good agreement with particle sizes measured by in situ techniques for cloud-processed aerosols. Aerosols of this type and large size range (in lower concentrations) may also be formed by cloud processing in partly cloudy conditions and may contribute to the shoulder of larger size particles in the accumulation mode retrievals, especially in regions where sulfate and other soluble aerosol are a significant component of the total aerosol composition. Observed trends of increasing aerosol optical depth (AOD) as fine mode radius increased suggests higher AOD in the near cloud environment and therefore greater aerosol direct radiative forcing than typically obtained from remote sensing, due to bias towards sampling at low cloud fraction.
Eck, T. F.↗
Ice-Over-Water Cloud Properties in an Artificial Neural Network Approach
Clouds are a crucial component of the atmospheric energy system, particularly the radiative balance within, above, and below the troposphere. The vertical distribution of cloud mass and phase determines layer heating rates, the loss of radiation to space, and the amount of radiative heating at the surface. Thus, it is important to know how clouds are distributed both vertically and horizontally at all times of day. Satellite remote sensing is the only approach available to monitor clouds day and night around the globe. In this paper several artificial neural network (ANN) algorithms, employing several Aqua MODIS infrared channels, profiles of relative humidity and temperature from GMAO numerical weather analyses, and the retrieved total cloud visible optical depth, are trained to detect multilayer ice-over-water cloud systems and to retrieve some of their properties as identified by a year of 2008 Aqua MODIS data matched with CloudSat and CALIPSO (CC) cloud profiles. The CC lidar and radar profiles provide the vertical structure that serves as output truth for the multilayer algorithm. The neural networks were trained using one year (2008) of cloud top height data from the CC dataset, with correlation around 0.94 (0.95) and MAE as low as 0.82 (0.81) km for nonpolar regions during the day (night). Applying the trained ANN to independent year 2009 MODIS data resulted in a combined ML and single layer hit rate of 86.4% (85.1%) for nonpolar regions during the day (night). Since the ANN is trained using near-nadir MODIS pixels, infrared radiance corrections were developed as a function of view zenith angle from MODIS and applied to off-nadir pixels when processing MODIS swath data. The multilayer amount derived with the ANN is relatively invariant with increasing view zenith angle compared to the multilayer amount without the corrections.
MODIS↗
Atmospheric Carbon and Transport – America (ACT-America) Data Sets: Description, Management, and Delivery
The ACT-America project is a NASA Earth Venture Suborbital-2 mission designed to study the transport and fluxes of greenhouse gases. The open and freely available ACT-America data sets provide airborne in situ measurements of atmospheric carbon dioxide, methane, trace gases, aerosols, clouds, and meteorological properties, airborne remote sensing measurements of aerosol backscatter, atmospheric boundary layer height and columnar content of atmospheric carbon dioxide, tower-based measurements, and modeled atmospheric mole fractions and regional carbon fluxes of greenhouse gases over the Central and Eastern United States. In this study, we conducted 121 research flights during five campaigns in four seasons during 2016–2019 over three regions of the US (Mid-Atlantic, Midwest and South) using two NASA research aircraft (B-200 and C-130). We performed three flight patterns (fair weather, frontal crossings, and OCO-2 underflights) and collected more than 1,140 h of airborne measurements via level-leg flights in the atmospheric boundary layer, lower, and upper free troposphere and vertical profiles spanning these altitudes. We also merged various airborne in situ measurements onto a common standard sampling interval, which brings coherence to the data, creates geolocated data products, and makes it much easier for the users to perform holistic analysis of the ACT-America data products. Here, we report on detailed information of data sets collected, the workflow for data sets including storage and processing of the quality controlled and quality assured harmonized observations, and their archival and formatting for users. Finally, we provide some important information on the dissemination of data products including metadata and highlights of applications of ACT-America data sets.
54 ENVIRONMENTAL SCIENCES↗
Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) Field Campaign Report
The Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted successfully between 1 December 2019 and 31 May 2020 around the Norwegian Sea. COMBLE deployed the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) first Mobile Facility (AMF1) along the coast of northern Scandinavia, at an arctic latitude (70°N), and an array of additional instruments on Bear Island (75°N) in the Norwegian Sea. The instruments deployed at these two sites collected a large array of in situ and remote-sensing observations of atmospheric conditions, clouds, precipitation, and aerosol. The main objective of COMBLE is to quantify the properties of shallow convective clouds that develop as part of an air-mass transformation process when cold air blows over open water. The two COMBLE sites are located at ~1,200 km and ~500 km from the cold source, i.e., arctic ice edge, respectively.
54 ENVIRONMENTAL SCIENCES↗
Analysis of ER-2 radiometer and lidar observations from the 1987 marine stratus experiment
Extensive remote sensing observations of marine stratus clouds were acquired from the NASA ER-2 aircraft during the 1987 FIRE stratus field experiment. The observations included high spatial resolution imaging radiometry at eighteen wavelengths and active lidar cloud top profiling. Analysis of these data can provide results to both enhance and extend aircraft in-situ cloud physics observations. For the spectral imaging radiometry observations of the marine stratus, a potentially useful result was obtained. For near infrared wavelengths, a large number of the bidirectional reflectance observations included persistent and significant single scattering features. With few exceptions, the features were not correspondingly observed at visible wavelengths. An initial comparison to direct cloud physics measurements give a good agreement (Spinhirne and Nakajima, 1989). The analysis of lidar returns from marine stratus cloud tops were shown to be potentially valuable for study of the microphysical and dynamic characteristics of the clouds (Boers et al., 1988, Spinhirne et al., 1989). Analysis involving cloud top water content and height spectra was applied to some of the extensive lidar observations of the 1987 field experiment. Derivation of cloud top radiative parameters and comparison to in-situ observations are planned.
Spinhirne, James D.↗
Scientific goals of the Cooperative Multiscale Experiment (CME)
Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.
Cotton, William↗
Analysis of measurements for solid state laser remote lidar system
The merits of using lidar systems for remote measurements of various atmospheric processes such as wind, turbulence, moisture, and aerosol concentration are widely recognized. Although the lidar technology has progressed considerably over the past two decades, significant research particularly in the area of solid state lidars remains to be conducted in order to fully exploit this technology. The work performed by the UAH (University of Alabama in Huntsville) personnel under this Delivery Order concentrated on analyses of measurements required in support of solid state laser remote sensing lidar systems which are to be designed, deployed, and used to measure atmospheric processes and constituents. UAH personnel has studied and recommended to NASA/MSFC the requirements of the optical systems needed to characterize the detection devices suitable for solid state wavelengths and to evaluate various heterodyne detection schemes. The 2-micron solid state laser technology was investigated and several preliminary laser designs were developed and their performance for remote sensing of atmospheric winds and clouds from a spaceborne platform were specified. In addition to the laser source and the detector, the other critical technologies necessary for global wind measurements by a spaceborne solid state coherent lidar systems were identified to be developed and demonstrated. As part of this work, an analysis was performed to determine the atmospheric wind velocity estimation accuracy using the line-of-sight measurements of a scanning coherent lidar. Under this delivery order, a computer database of materials related to the theory, development, testing, and operation of lidar systems was developed to serve as a source of information for lidar research and development.
Amzajerdian, Farzin↗
Airborne Studies in the Arctic in Support of FIRE-III
This grant supported (i) the participation of the University of Washington's (UW) Cloud and Aerosol Research Group (CARG), with its Convair-580 research aircraft, in the FIRE-ACE field study in the Arctic; (ii) analyses of portions of the data collected; (iii) presentation of results at conferences and workshops; (iv) formal publication of results; and, (v) archiving of the data collected by the UW/CARG. The UW/CARG Convair-580 flew twenty-three research flights, totaling over 97 research hours, in the FIRE-ACE field study during the period 19 May through 24 June 1998. Six flights were beneath the NASA ER-2 aircraft, eight flights over the instrumented SHEBA ship, and eleven flights over the DOE ARM site in Barrow, Alaska. Measurements of cloud radiative properties and cloud structures were obtained in stratus, altocumulus and cirrus clouds. Aerosol measurements were obtained in polluted arctic haze, and in very clean conditions. Several new instruments were flown on the UW Convair-580, including the Gerber g-meter, the NASA/Goddard spectral full-scanning radiometer, and the SPEC cloud particle imager (CPI). A complete listing of all of the UW Convair-580 flights in FIRE-ACE is given in the report by Hobbs listed as (ii) in Section 3 below. The UW/CARG focussed its own analyses of these data on the airborne in situ measurements of clouds and aerosols. This resulted in five formal publications, covering topics ranging from the production of aerosols by clouds and aerosol effects on surface heating in the arctic, to the structures of arctic clouds and comparisons of in situ measurements of cloud structures with deductions from remote sensing measurements.
Hobbs, Peter V.↗
Spatially Complete Global Spectral Surface Albedos: Value-Added Datasets Derived from Terra MODIS Land Products
Land surface albedo is an important parameter in describing the radiative properties of the earth s surface as it represents the amount of incoming solar radiation that is reflected from the surface. The amount and type of vegetation of the surface dramatically alters the amount of radiation that is reflected; for example, croplands that contain leafy vegetation will reflect radiation very differently than blacktop associated with urban areas. In addition, since vegetation goes through a growth, or phenological, cycle, the amount of radiation that is reflected changes over the course of a year. As a result, albedo is both temporally and spatially dependant upon global location as there is a distribution of vegetated surface types and growing conditions. Land surface albedo is critical for a wide variety of earth system research projects including but not restricted to remote sensing of atmospheric aerosol and cloud properties from space, ground-based analysis of aerosol optical properties from surface-based sun/sky radiometers, biophysically-based land surface modeling of the exchange of energy, water, momentum, and carbon for various land use categories, and surface energy balance studies. These projects require proper representation of the surface albedo s spatial, spectral, and temporal variations, however, these representations are often lacking in datasets prior to the latest generation of land surface albedo products.
Moody, Eric G.↗