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NASA NTRSDate not supplied

Implementation of Interactive Sea Ice Radiative Transfer into the GISS GCM and Its Impact on Sea Ice Simulation

To improve the representation of solar radiation in sea ice in the Goddard Institute for Space Studies (GISS) climate model (ModelE), we have implemented an advanced radiative transfer (RT) scheme to interactively calculate the surface albedo and transmittance of the ice layer and the solar absorption within. The ice physical properties (temperature, salinity, and density), which are simulated by the thermodynamic module in ModelE, are directly used as the input of the RT scheme to determine the inherent optical properties (IOPs) of brine pockets and air bubbles in the ice layers. This provides a more sophisticated, accurate, and complete treatment of sea ice RT for ModelE. The sea ice RT model is also validated with measured spectral albedo and transmittance for different ice types. Compared with ModelE simulations with current radiative parameterization for sea ice, the new RT implementation will slightly increase the ice surface albedo in the summer in the Arctic and greatly increase the radiative transmittance. Consequently, the ice surface melting is reduced and the base melting is increased but the difference in the simulated ice area is small. The effect of this new RT implementation on the Antarctic ice is negligible. The observed decrease in Arctic sea ice extent is well captured by the ModelE simulation.

Sea ice↗

NASA NTRS2012

The HYSPIRI Decadal Survey Mission: Update on the Mission Concept and Science Objectives for Global Imaging Spectroscopy and Multi-Spectral Thermal Measurements

The NASA HyspIRI mission is planned to provide global solar reflected energy spectroscopic measurement of the terrestrial and shallow water regions of the Earth every 19 days will all measurements downlinked. In addition, HyspIRI will provide multi-spectral thermal measurements with a single band in the 4 micron region and seven bands in the 8 to 12 micron region with 5 day day/night coverage. A direct broadcast capability for measurement subsets is also planned. This HyspIRI mission is one of those designated in the 2007 National Research Council (NRC) Decadal Survey: Earth Science and Applications from Space. In the Decadal Survey, HyspIRI was recognized as relevant to a range of Earth science and science applications, including climate: "A hyperspectral sensor (e.g., FLORA) combined with a multispectral thermal sensor (e.g., SAVII) in low Earth orbit (LEO) is part of an integrated mission concept [described in Parts I and II] that is relevant to several panels, especially the climate variability panel." The HyspIRI science study group was formed in 2008 to evaluate and refine the mission concept. This group has developed a series of HyspIRI science objectives: (1) Climate: Ecosystem biochemistry, condition & feedback; spectral albedo; carbon/dust on snow/ice; biomass burning; evapotranspiration (2) Ecosystems: Global plant functional types, physiological condition, and biochemistry including agricultural lands (3) Fires: Fuel status, fire frequency, severity, emissions, and patterns of recovery globally (4) Coral reef and coastal habitats: Global composition and status (5) Volcanoes: Eruptions, emissions, regional and global impact (6) Geology and resources: Global distributions of surface mineral resources and improved understanding of geology and related hazards These objectives are achieved with the following measurement capabilities. The HyspIRI imaging spectrometer provides: full spectral coverage from 380 to 2500 at 10 nm sampling; 60 m spatial sampling with a 150 km swath; and fully downlinked coverage of the Earth's terrestrial and shallow water regions every 19 days to provide seasonal cloud-free coverage of the terrestrial surface. The HyspIRI Multi-Spectral Thermal instrument provides: 8 spectral bands from 4 to 12 microns; 60 m spatial sampling with a 600 km swath; and fully downlinked coverage of the Earth's terrestrial shallow water regions every 5 days (day/night) to provide nominally cloud-free monthly coverage. The HyspIRI mission also includes an on-board processing and direct broadcast capability, referred to as the Intelligent Payload Module (IPM), which will allow users with the appropriate antenna to download a subset of the HyspIRI data stream to a local ground station. These science and science application objectives are critical today and uniquely addressed by the combined imaging spectroscopy, thermal infrared measurements, and IPM direct broadcast capability of HyspIRI. Two key objectives are: (1) The global HyspIRI spectroscopic measurements of the terrestrial biosphere including vegetation composition and function to constrain and reduce the uncertainty in climate-carbon interactions and terrestrial biosphere feedback. (2) The global 8 band thermal measurements to provide improved constraint of fire related emissions. In this paper the current HyspIRI mission concept that has been reviewed and refined to its current level of maturity with a Data Products Symposium, Science Workshop and NASA HWorkshop is presented including traceability between the measurements and the science and science application objectives.

Green, Robert O.↗

NASA NTRS2004

An Initial Analysis of the Pixel-Level Uncertainties in Global MODIS Cloud Optical Thickness and Effective Particle Size Retrievals

Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical thickness and effective particle radius employ well-known solar reflectance techniques using pre-calculated reflectance look-up tables. We evaluate the quantitative uncertainty in simultaneous retrievals of cloud optical thickness and particle size for this type of algorithm. The technique uses sensitivity calculations derived from the reflectance look-up tables, coupled with estimates for the effect of various error terms on the uncertainty in inferring the actual cloud-top reflectance. The error terms include the effects of instrument calibration, surface spectral albedo, and atmospheric corrections on both water and ice cloud retrievals. Because particle shapes in ice clouds are highly variable, the effect of particle shape is analyzed separately with a more approximate method. Results will deal exclusively with pixel-level uncertainties associated with plane-parallel clouds; real-world radiative departures from a plane-parallel model are an additional consideration. While we demonstrate the uncertainty technique with operational 1 km MODIS retrievals from the Terra and Aqua satellite platforms, the technique is applicable to any reflectance-based satellite- or air-borne sensor retrieval using similar spectral channels.

Platnick, S.↗

NASA NTRS1984

Snow reflectance from Landsat-4 Thematic Mapper

In California 75 percent of the agricultural water supply comes from the melting Sierra Nevada snowpack. Basin-wide spectral albedo measurements from the Landsat-4 Thematic Mapper (TM) could be used to better forecast the timing of the spring runoff, because these data can be combined with solar radiation calculations to estimate the net radiation balance. The TM is better-suited for this purpose than the Multispectral Scanner because of its larger dynamic range. Saturation still occurs in bands 1-4, but is severe only in TM1 (0.45-0.52 micron). Snow reflectance in TM2 (0.43-0.61 micron) is typical of the visible wavelength region, where reflectance is almost insensitive to crystal size but sensitive to contamination. TM4 (0.78-0.90 micron) allows estimation of effective optical grain size and thereby spectral extension throughout the near-infrared. TM5 (1.57-1.78 microns) can discriminate clouds from snow.

Dozier, J.↗

DOE OSTI2024

An Examination of Water-Related Melt Processes in Arctic Snow on Tundra and Sea-Ice

From April through June in 2019 and 2022, we monitored snow melt at three sites near Utqiaġvik, Alaska. Along 200-m lines we measured snow depth, density, stratigraphy, snow-covered area, and spectral albedo. Site 1 (ARM) was sloped tundra drained by water tracks. Site 2 (BEO) was flat polygonal tundra. Site 3 (ICE) was on undeformed landfast sea ice. All three sites were within a 6 km radius. Despite similar pre-melt snow distributions and weather, the melt progression differed markedly between sites. In 2019, by mid-melt, there was 40% less snow-covered area at ARM versus ICE, and 34% less snow-covered area at ARM versus BEO. The 2022 melt started 2 weeks later than in 2019 and was rapid, so smaller differences in snow-covered areas developed. In both years meltout dates varied by up to 25 days between sites, and more than 20 days within sites, with melt rates at locations only meters apart differing by up to a factor of seven. This melt diachroneity led to highly heterogeneous meltout patterns at all three sites. Our measurements and observations indicate that, in addition to reductions in snow reflective properties and wind-driven heat advection, the fate of meltwater plays a key role in producing melt diachroneity. We identify seven snow-water mechanisms that can enhance or inhibit melt rates, all largely controlled by the local topography and the nature of the substrate. These mechanisms are important because the most rapid changes in albedo coincide with the peak of water-snow melt interactions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1971

Galilean satellites - Narrowband photometry 0.30 to 1.10 microns

Jupiter Galilean satellites narrowband photometric data, observing albedos, spectral reflectivity, rotational phase, and brightness variations

Johnson, T. V.↗

NASA NTRS1975

The composition of the ultraviolet dark markings on Venus

The ultraviolet dark clouds are an ephemeral phenomenon in the Venus atmosphere, apparently just near the limit of stability. The UV dark material is moderately abundant, perhaps 10%, since the contrasts between light and dark material are some 20%. The material should absorb light between 3000-4000 A, and ideally should also have visible absorptions in the blue, as the overall spectral albedo of Venus indicates. Such a material is bromine dissolved in hydrobromic acid. Solar radiation near 2500 A is sufficient to partially photolyze HBr into Br2. HBr in the Venus atmosphere is inferred to have a mixing ratio of 0.0001 versus CO2. With a water vapor mixing ratio of 0.001, droplets of hydrobromic acid are possible. These droplets would eventually evaporate in the drier upper atmosphere. The refractive index of these hydrobromic acid droplets of 52% (by weight) composition is 1.46, within the limits set by polarization studies of Venus.

Sill, G. T.↗

NASA NTRS1979

Infrared radiometer for the Pioneer Venus orbiter. I - Instrument description

A ten-channel IR radiometer for the Pioneer Venus orbiter is described. The experimental techniques used and the design of the instrumentation by which they were implemented are considered. Emphasis is placed on temperature sounding, limb sounding, limb darkening, zenith scanning, cloud top temperature, spectral albedo and water vapor measurements. Instrumentation description is also given including optics, detectors, and electronics. Attention is given to data acquisition and handling, calibration, and in-flight performance.

Taylor, F. W.↗

NASA NTRS1984

LANDSAT-D investigations in snow hydrology

Thematic mapper radiometric characteristics, snow/cloud reflectance, and atmospheric correction are discussed with application to determining the spectral albedo of snow. The geometric characterics of TM and digital elevation data are examined. The geometric transformations and resampling required to coregister these data are discussed.

Dozier, J.↗

NASA NTRS1986

Reply

A reply is made on behalf of the authors of Wiscombe et al. (1984) to comments of Hegg (1986) to the effect that the optically effective cloud drop radius r(eff) values used by Wiscombe are shown by more recent data to be underestimated. It is presently noted that cloud radiation studies have often not just used comparably small r(eff) values, but ignored large drops in calculations altogether, on the grounds that large drops must fall out of clouds very rapidly. Attention is given to total shortwave absorptivity, spectral albedo, and IR cooling rate near cloud tops.

Wiscombe, W.↗

NASA NTRS1985

Modelisation of the optical scattering behaviour of the vegetation canopies

The three dimensional model of Kimes (1984) which can treat three dimensional variability in heterogeneous scenes, was used to test and expand physical scattering mechanisms involved in reflectance distribution dynamics by analyzing modeling and field data. The major physical phenomena causing the directional scattering behavior of vegetation canopies are presented. These include the strong anisotropic properties of the soil, and the anisotropic scattering properties of the vegetation as described by the phase function of the leaves and the geometric effects caused by vertical layers of leaves. This knowledge serves as a basis for defining optimum directional view angles for remote sensing strategies. An example on using knowledge of the scattering behavior of vegetation to develop techniques for extracting vegetation parameters (spectral albedo) from directional reflectance data is presented.

Kimes, D. S.↗

NASA NTRS1986

Asteroid team

Work on asteroid classification continued was rewarded with the discovery of two Earth-approaching M asteroids. The M class is rare and these are the first found among the near-Earth asteroids to have the spectral albedo characteristic of this class. The two asteroids are newly discovered 1986 DA and 1986 EB which were observed at N and Q bandpasses (i.e., 10 and 20 microns) with the 3 m IRTF telescope and at five wavelengths from 0.36 to 0.85 microns from Kitt peak National Observatory's 0.36 m telescope. The derived diameters are about 2 km for both objects. In the asteroid radiometry program N or Q photometry was obtained for more than 40 asteroids in Feb. 1986. Radiometric diameter calibration support were provided for stellar occultations of stars by 230 Athamantis and 129 Antigone. The data were reduced but not analyzed. Infrared spectra (0.8 to 2.6 microns) of 60 asteroids were reduced and are now ready for compositional analysis.

Matson, D. L.↗

NASA NTRS1991

Urban heat island

The phenomenon of urban heat island was investigated by the use of LANDSAT Thematic Mapper data sets collected over the metropolitan area of Washington DC (U.S.). By combining the retrieved spectral albedos and temperatures, urban modification on radiation budgets of five surface categories were analyzed. The surface radiation budget imagery of the area show that urban heating is attributable to a large heat flux from the rapidly heating surfaces of asphalt, bare soil and short grass. In summer, symptoms of diurnal heating begin to appear by mid morning and can be about 10 degrees warmer than nearby woodlands in summer.

Hongsuk H. Kim↗

NASA NTRS1994

Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change.

Steffen, K.↗

NASA NTRS1994

The effect of sea ice on the solar energy budget in the astmosphere-sea ice-ocean system: A model study

A coupled one-dimensional multilayer and multistream radiative transfer model has been developed and applied to the study of radiative interactions in the atmosphere, sea ice, and ocean system. The consistent solution of the radiative transfer equation in this coupled system automatically takes into account the refraction and reflection at the air-ice interface and allows flexibility in choice of stream numbers. The solar radiation spectrum (0.25 micron-4.0 micron) is divided into 24 spectral bands to account adequately for gaseous absorption in the atmosphere. The effects of ice property changes, including salinity and density variations, as well as of melt ponds and snow cover variations over the ice on the solar energy distribution in the entire system have been studied quantitatively. The results show that for bare ice it is the scattering, determined by air bubbles and brine pockets, in just a few centimeters of the top layer of ice that plays the most important role in the solar energy absorption and partitioning in the entire system. Ice thickness is important to the energy distribution only when the ice is thin, while the absorption in the atmosphere is not sensitive to ice thickness exceeds about 70 cm. The presence of clouds moderates all the sensitivities of the absorptive amounts in each layer to the variations in the ice properties and ice thickness. Comparisons with observational spectral albedo values for two simple ice types are also presented.

Jin, Z.↗

NASA NTRS1996

Assessment of Climate Variability of the Greenland Ice Sheet: Integration of In Situ and Satellite Data

Steffen, K.↗

NASA NTRS1996

Subpixel Snow-Covered-Area and Snow Grain Size From Mixture Analysis with AVIRIS Data

Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made. Snow grain size, SWE and snow impurities determine the spectral albedo of snow, which controls the net solar flux at the snowpack surface. Snow albedo is of the utmost importance in snowmelt modeling, yet the difficulty with which grain size, SWE, and impurities are mapped has left the spatial distribution of snow albedo in alpine catchments poorly understood. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been used to estimate sub-pixel snow-covered-area and snow grain size independently. In this paper we present a technique which improves estimates of both snow parameters by treating their mapping simultaneously.

Green Robert O.↗

NASA NTRS1998

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

Kimes, Daniel S.↗