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At least 73 records · Page 4

CloudSat Reflectivity Data Visualization Inside Hurricanes

Animations and other outreach products have been created and released to the public quickly after the CloudSat spacecraft flew over hurricanes. The automated script scans through the CloudSat quicklook data to find significant atmospheric moisture content. Once such a region is found, data from multiple sources is combined to produce the data products and the animations. KMZ products are quickly generated from the quicklook data for viewing in Google Earth and other tools. Animations are also generated to show the atmospheric moisture data in context with the storm cloud imagery. Global images from GOES satellites are shown to give context. The visualization provides better understanding of the interior of the hurricane storm clouds, which is difficult to observe directly. The automated process creates the finished animation in the High Definition (HD) video format for quick release to the media and public.

visualization↗

CloudSat Reflectivity Data Visualization Inside Hurricanes

We have presented methods to rapidly produce visualization and outreach products from CloudSat data for science and the media These methods combine data from several sources in the product generation process In general, the process can be completely automatic, producing products and notifying potential users

remote science↗

Deformable Mirrors Capture Exoplanet Data, Reflect Lasers

To image and characterize exoplanets, Goddard Space Flight Center turned to deformable mirrors (DMs). Berkeley, California-based Iris AO, Inc. worked with Goddard through the SBIR program to improve the company’s microelectromechanical DMs, which are now being evaluated and used for biological research, industrial applications, and could even be used by drug manufacturers.

Source record↗

Deriving Polarization Properties of Desert-Reflected Solar Spectra with PARASOL Data

Reflected solar radiation from desert is strongly polarized by sand particles. To date, there is no reliable desert surface reflection model to calculate desert reflection matrix. In this study, the PARASOL data are used to retrieve physical properties of desert. These physical properties are then used in the ADRTM to calculate polarization of desert-reflected light for the whole solar spectra.

Sun, Wenbo↗

Estimation of shortwave hemispherical reflectance (albedo) from bidirectionally reflected radiance data

An equation for estimating albedo from bidirectional reflectance data is proposed. The estimates of albedo are found to be greater than values obtained with simultaneous pyranometer measurements. Particular attention is given to potential sources of systematic errors including extrapolation of bidirectional reflectance data out to a view zenith angle of 90 deg, the use of inappropriate weighting coefficients in the numerator of the albedo equation, surface shadowing caused by the A-frame instrumentation used to measure the incoming and outgoing radiation fluxes, errors in estimates of the denominator of the proposed albedo equation, and a 'hot spot' contribution in bidirectional data measured by a modular multiband radiometer.

Starks, Patrick J.↗

On the spectral reflectance properties of materials exposed at the Viking landing sites

Reflectance data derived from Viking Lander multispectral data were used to characterize the types of soils and blocks exposed at the landing sites and to search for evidence of relatively unaltered igneous rocks. A comprehensive effort was mounted to examine multispectral data that combines testing of camera radiometric calibrations, explicitly removing the effects of atmospheric attenuation and skylight, and quantitatively comparing the corrected data to reflectance data from laboratory materials. Bi-directional reflectances for blue, green and red channels were determined for 31 block and soil exposures at Viking landing sites.

Guinness, E.↗

Early Evaluation of the VIIRS Calibration, Cloud Mask and Surface Reflectance Earth Data Records

Surface reflectance is one of the key products fromVIIRS and as withMODIS, is used in developing several higherorder land products. The VIIRS Surface Reflectance (SR) Intermediate Product (IP) is based on the heritageMODIS Collection 5 product (Vermote, El Saleous, & Justice, 2002). The quality and character of surface reflectance depend on the accuracy of the VIIRS Cloud Mask (VCM), the aerosol algorithms and the adequate calibration of the sensor. The focus of this paper is the early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system, the Interface Data Processing System (IDPS). After a brief introduction, the paper presents the calibration performance and the role of the surface reflectance in calibration monitoring. The analysis of the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions) shows typical problems over bright surfaces and high elevation sites. Also discussed is the performance of the aerosol input used in the atmospheric correction and in particular the artifacts generated by the use of the Navy Aerosol Analysis and Prediction System. Early quantitative results of the performance of the SR product over the AERONET sites showthatwith the fewadjustments recommended, the accuracy iswithin the threshold specifications. The analysis of the adequacy of the SR product (Land PEATE adjusted version) in applications of societal benefits is then presented. We conclude with a set of recommendations to ensure consistency and continuity of the JPSS mission with the MODIS Land Climate Data Record.

Surface reflectance↗

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classification models that can require substantial ground truth datasets for training. We explore the potential of an unsupervised approach, autoencoders, to extract meaningful traits from plant hyperspectral reflectance data using measurements of the reflectance of 2151 individual wavelengths of light from the leaves of maize ( Zea mays ) plants harvested from 1658 field plots in a replicated field trial. A subset of autoencoder‐derived variables exhibited significant repeatability, indicating that a substantial proportion of the total variance in these variables was explained by difference between maize genotypes, while other autoencoder variables appear to capture variation resulting from changes in leaf reflectance between different batches of data collection. Several of the repeatable latent variables were significantly correlated with other traits scored from the same maize field experiment, including one autoencoder‐derived latent variable (LV8) that predicted plant chlorophyll content modestly better than a supervised model trained on the same data. In at least one case, genome‐wide association study hits for variation in autoencoder‐derived variables were proximal to genes with known or plausible links to leaf phenotypes expected to alter hyperspectral reflectance. In aggregate, these results suggest that an unsupervised, autoencoder‐based approach can identify meaningful and genetically controlled variation in high‐dimensional, high‐throughput phenotyping data and link identified variables back to known plant traits of interest.

Tross, Michael C.↗

Learning class descriptions from a data base of spectral reflectance of soil samples

Consideration is given to a program developed to learn class descriptions from positive and negative training examples of spectral reflectance data of bare soils. It is a combination of 'learning by example' and the generate-and-test paradigm and is designed to provide a robust learning environment that can handle error-prone data. The program was tested by having it learn class descriptions of various categories of organic carbon content, iron oxide content, and particle size distribution in soils. These class descriptions were then used to classify an array of targets. The program found the sequence of relationships between bands that contained the most important information to distinguish the classes. Physical explanations for the class descriptions obtained are presented.

Kimes, D. S.↗

A TM Tasseled Cap equivalent transformation for reflectance factor data

A transformation of TM-waveband reflectance-factor data which provides features related as directly as possible to the corresponding TM Tasseled Cap brightness, greennes, and wetness features is presented. The reflectance factor transformation is based on spectrometer data integrated over the prelaunch composite-detector response functions of the Landsat-4 Thematic Mapper. A description, in general terms, of the approach for adjusting the transformation matrix to other types of reflectance factor data (different instrument or band response) is given.

Crist, E. P.↗

Seasonal soybean crop reflectance

Data are presented from field measurements of 1980 including 5 acquisitions of handheld radiometer reflectance measurements, 7 complete sets of parameters for implementing the Suits mode, and other biophysical parameters to characterize the soybean canopy. LANDSAT calculations on the simulated Brazilian soybean reflectance are included along with data collected during the summer and fall on 1981 on soybean single leaf optical parameters for three irrigation treatments. Tests of the Suits vegetative canopy reflectance model for the full hemisphere of observer directions as well as the nadir direction show moderate agreement for the visible channels of the MSS and poor agreement in the near infrared channel. Temporal changes in the spectral characteristics of the single leaves were seen to occur as a function of maturity which demonstrates that the absorptance of a soybean single leaf is more a function of thetransmittancee characteristics than the seasonally consistent single leaf reflectance.

Lemaster, E. W.↗

Use of high-dimensional spectral data to evaluate organic matter, reflectance relationships in soils

Recent breakthroughs in remote sensing technology have led to the development of a spaceborne high spectral resolution imaging sensor, HIRIS, to be launched in the mid-1990s for observation of earth surface features. The effects of organic carbon content on soil reflectance over the spectral range of HIRIS, and to examine the contributions of humic and fulvic acid fractions to soil reflectance was evaluated. Organic matter from four Indiana agricultural soils was extracted, fractionated, and purified, and six individual components of each soil were isolated and prepared for spectral analysis. The four soils, ranging in organic carbon content from 0.99 percent, represented various combinations of genetic parameters such as parent material, age, drainage, and native vegetation. An experimental procedure was developed to measure reflectance of very small soil and organic component samples in the laboratory, simulating the spectral coverage and resolution of the HIRIS sensor. Reflectance in 210 narrow (10 nm) bands was measured using the CARY 17D spectrophotometer over the 400 to 2500 nm wavelength range. Reflectance data were analyzed statistically to determine the regions of the reflective spectrum which provided useful information about soil organic matter content and composition. Wavebands providing significant information about soil organic carbon content were located in all three major regions of the reflective spectrum: visible, near infrared, and middle infrared. The purified humic acid fractions of the four soils were separable in six bands in the 1600 to 2400 nm range, suggesting that longwave middle infrared reflectance may be useful as a non-destructive laboratory technique for humic acid characterization.

Henderson, T. L.↗

Compositional variability of the Martian surface

Spectral reflectance data from Viking Landers and Orbiters and from telescopic observations were analyzed with the objective of isolating compositional information about the Martian surface and assessing compositional variability. Two approaches were used to calibrate the data to reflectance to permit direct comparisons with laboratory reference spectra of well characterized materials. In Viking Lander multispectral images (six spectral bands) most of the spectral variation is caused by changes in lighting geometry within individual scenes, from scene to scene, and over time. Lighting variations are both wavelength independent and wavelength dependent. By calibrating lander image radiance values to reflectance using spectral mixture analysis, the possible range of compositions was assessed with reference to a collection of laboratory samples, also resampled to the lander spectral bands. All spectra from the lander images studied plot (in six-space) within a planar triangle having at the apexes the respective spectra of tan basaltic palagonite, gray basalt, and shale. Within this plane all lander spectra fit as mixtures of these three endmembers. Reference spectra that plot outside of the triangle are unable to account for the spectral variation observed in the images.

Adams, John B.↗

The Diurnal Cycle in TOGA-COARE: Regional Scale Model Simulations

The diurnal variation of precipitation processes over the tropics is a well-known phenomenon and has been studied using surface rainfall data, radar reflectivity data, and satellite-derived cloudiness and precipitation. Recently, analyzed observations from Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) in the tropical western Pacific ocean to study the relevant mechanisms producing diurnal variation of precipitation. They found that the diurnal Sea surface temperature (SST) cycle is important for afternoon showers in the undisturbed periods and diurnal radiative processes for nocturnal rainfall. Cloud resolving models (CRMS) have been used to determine the mechanisms associated with diurnal variation of precipitating processes. CRMs allow explicit cloud-radiation and air-sea interactive processes. However, CRMs can be only used for idealized simulations (i.e., no feedback between clouds and their embedded large-scale environments; cyclic lateral boundary conditions and idealized initial conditions). In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (covers the TOGA COARE LSA/IFA with a 54 km grid and can nest down to 18, 6 and possibly even 2 km) will be adopted for studying the diurnal variations of rainfall. We will examine precipitation processes over open ocean and over land. We will also perform sensitivity tests to determine how the radiative forcing and diurnal SST cycle affects the development of convection.

Tao, W.-K.↗

The Diurnal Cycle in TOGA-COARE: Regional Scale Model Simulations

The diurnal variation of precipitation processes over the tropics is a well-known phenomenon and has been studied using surface rainfall data, radar reflectivity data, and satellite-derived cloudiness and precipitation. Recently, Sui (1997) analyzed observations from TOGA COARE in the tropical western Pacific ocean to study the relevant mechanisms producing diurnal variation of precipitation. They found that the diurnal SST cycle is important for afternoon showers in the undisturbed periods and diurnal radiative processes for nocturnal rainfall. Takayabu (1996) found a quasi-2-day cycle in precipitation during TOGA COARE and they suggested that inertia-gravity waves may be associated with this 2-day cycle. Chen and Houze (1997), however, suggested that the quasi-2-day oscillation is mainly a function of the time required by the lower-tropospheric moisture field to recover from the drying caused by deep convection. In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique will be used to simulate two TOGA COARE convective espisodes, one convectively suppressed phase (mid to late January 1993) and one convectively active phase (mid to late December 1992). We will examine precipitation processes over the open ocean and over land by comparing MM5 simulated rainfall and out-going longwave radiation. By examining the OLR and precipitation, we can determine if there is a temporal lag between the maximum precipitation and the coldest upwelling longwave radiation (the time-lag between stratiform-cirrus and convective towers). The boundary layer response by (or recovery from) precipitation processes will also be shown by examining the PBL thermodynamic structure and the sensible and latent heat fluxes. A preliminary MM5 simulation showed a clear diurnal variation in rainfall over both land and open ocean for the convectively active phase. The results also indicated that a quasi-2-day cycle in precipitation was simulated only over part of the ocean.

Tao, W.-K.↗

Diurnal Variation of Precipitation During MC3E Campaign

The diurnal variation of precipitation processes in the United States (US) is well recognized but incompletely understood (Cabone et al. 2002). The diurnal cycle of precipitation has been studied using surface rainfall data, radar reflectivity data, and satellite-derived cloudiness and precipitation (Wallace 1975; Dai et al. 1999; Carbone et al. 2002; Carbone and Tuttle, 2008; Parker and Ahijevych, 2007; Matsui et al. 2010 and others). These observations indicate that the summer-time precipitation most of the North America and typically feature late-afternoon precipitation maxima. These diurnal variation of precipitation can also be generally categorized into three different types: 1) afternoon rainfall maxima due to mesoscale and local circulations over the south and east of the Mississippi and Ohio valleys, 2) nocturnal rainfall maxima from eastward-propagating mesoscale convective systems (MCSs) over the Lee side of Rocky Mountain regions and 3) afternoon rainfall maxima in the Appalachian Mountains, and then propagate eastward toward the coast. The main objective of this paper is to use a regional cloud-scale model with very high-resolution (i.e., WRF) to examine the WRF ability to simulate diurnal variation of precipitation. Specifically, the study will (1) identify the physical processes responsible to diurnal variation of precipitation, (2) examine the sensitivity of resolution (2, 6, 18, and 30 km) to model simulated diurnal variation of precipitation and (3) identify the relationships between microphysics and cumulus parameterization schemes.

Tao, Wei-Kuo↗