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NASA NTRS1984

Electroless-plating technique for fabricating thin-wall convective heat-transfer models

A technique for fabricating uniform thin-wall metallic heat-transfer models and which simulates a Shuttle thermal protection system tile is described. Two 6- by 6- by 2.5-in. tiles were fabricated to obtain local heat transfer rates. The fabrication process is not limited to any particular geometry and results in a seamless thin-wall heat-transfer model which uses a one-wire thermocouple to obtain local cold-wall heat-transfer rates. The tile is relatively fragile because of the brittle nature of the material and the structural weakness of the flat-sided configuration; however, a method was developed and used for repairing a cracked tile.

Avery, D. E.↗

NASA NTRS2005

Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Sensors: Theoretical Concept - Part I

Modern infrared satellite sensors such as Atmospheric Infrared Sounder (AIRS), Cosmic Ray Isotope Spectrometer (CrIS), Thermal Emission Spectrometer (TES), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the Principal Component-based Radiative Transfer Model (PCRTM) predicts the Principal Component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from properties of PC scores and instrument line shape functions. The PCRTM is very accurate and flexible. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I) and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

Liu, Xu↗

NASA NTRS2002

Clues to Coral Reef Health: Integrating Radiative Transfer Modeling and Hyperspectral Data

An important contribution to coral reef research is to improve spectral distinction between various health states of coral species in areas subject to harmful anthropogenic activity and climate change. New insights into radiative transfer properties of corals under healthy and stressed conditions can advance understandings of ecological processes on reefs and allow better assessments of the impacts of large-scale bleaching and disease events, Our objective was to examine the spectral and spatial properties of hyperspectral sensors that may be used to remotely sense changes in reef community health. We compare in situ reef environment spectra (healthy coral, stressed coral, dead coral, algae, and sand) with airborne hyperspectral data to identify important spectral characteristics and indices. Additionally, spectral measurements over a range of water depths, relief, and bottom types are compared to help quantify bottom-water column influences. In situ spectra were collected in July and August 2002 at the Long Rock site in the Andros Island, Bahamas coastal zone coral reef. Our primary emphasis was on Acropora palmata (or elkhorn coral), a major reef building coral, which is prevalent in the study area, but is suffering from white band disease. A. palmata is currently being, proposed as an endangered species because its populations have severely declined in many areas of the Caribbean. In addition to the A. palmata biotope, we have collected spectra of at least seven other coral biotopes that exist within the study area, each with different coral community composition, density of corals, relief, and size of corals. Coral spectral reflectance was then input into a radiative transfer model, CORALMOD (CM1), which is based on a leaf radiative transfer model. In CM1, input coral reflectance measurements produce modeled reflectance through an inversion at each visible wavelength to provide the absorption spectrum. Initially, we imposed a scattering baseline that is the same regardless of the coral condition and that coral is optically thick and no light is transmitted through coral. Here we will focus on methodology, experimental design, and initial findings of the in situ spectral measurements and preliminary output from the radiative transfer model.

Guild, Liane↗

NASA NTRS2019

Evaluation of Brightness Temperature Sensitivity to Snowpack Physical Properties Using Coupled Snow Physics and Microwave Radiative Transfer Models

There are multiple existing microwave radiative transfer models (RTMs) to simulate the brightness temperature (Tb) of snowpacks. It is still challenging to have consistent Tb responses from RTMs due to individual physical formulations of the snowpack scattering process. This article examines three of the widely-used multi-layer RTMs: 1) the microwave emission model of layered snowpacks (MEMLS); 2) the dense media radiative transfer based on the quasi-crystalline approximation (QCA) of Mie scattering of densely packed sticky spheres (DMRTQMS); and 3) the Helsinki University of Technology (HUT) model. Interestingly, these models yield slightly different Tb responses when driven by the same physical snowpack properties. Tb variations, dependent on the choice of RTMs, are then evaluated to improve the understanding of model differences in microwave emission from a snowpack. We first perform a sensitivity study of the Tb predictions from the three RTMs as a function of snow grain sizes, densities, and depths. While Tb from all three RTMs decreases with increasing snow grain sizes, it is found that a scaling factor is required to have the same amount of Tb attenuation for small grain sizes within the Rayleigh scattering regime. For larger grain sizes, however, a scaling coefficient is not enough to match the model outputs due to the different scattering assumptions of the RTMs. For a single snow layer with increasing snow depths and densities, all three RTMs exhibit Tb attenuations arising from the increase in path lengths and optical depths. Further evaluations are conducted by feeding the three RTMs with the output of a snow physics model driven by in situ weather forcing in a coupled simulation. Outputs of this coupled model include snowpack physical properties and Tbs. By using snow stratigraphy observations, another set of Tb simulation is also conducted with RTMs driven by in situ snowpit observations. The snow physics outputs from the coupled case are compared against in situ snow stratigraphy observations.

Do Hyuk Kang↗

NASA NTRSDate not supplied

A Principal-Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Shortwave and Longwave Satellite Sensors and Its Applications

The radiative transfer model (RTM) or forward model is an essential component in satellite remote sensing. For modern hyperspectral remote sensors, fast and accurate RTMs are needed due to a large number of spectral dimensions and high spatial resolutions. We will describe a Principal Component-based radiative transfer model (PCRTM) which can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra 250 nm to 2000 micrometers quickly and accurately. The PCRTM has been demonstrated to be extremely accurate, compared to the line-by-line RTM benchmarks, and the former is several orders more computationally efficient than the latter. We will demonstrate how the PCRTM and the associated inversion algorithms are used to infer atmospheric temperature, moisture, and trace gas profiles, as well as cloud and surface properties from hyperspectral IR sounders such as Atomspheric Infrared Souder (AIRS) and Cross-track Infrared Sounder (CrIS). High-quality climate records for a 20-year duration have been derived from these IR hyperspectral data. Finally, we will show some examples of using PCRTM to retrieve cloud properties from Earth Surface Mineral Dust Source Investigation (EMIT) and its applicability of PCRTM to future missions such as the CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) CPF and the Surface Biology and Geology (SBG).

Xu Liu↗

NASA NTRS2021

Understanding Uncertainty of Snow Radiative Transfer Modeling Within a Mixed Deciduous and Evergreen Forest

Satellite-based passive microwave observations provide the best available continuous observational estimates of global snow water storage due to their broad geographic footprint and low sensitivity to clouds and precipitation. However, these observations are subject to substantial uncertainty due to the complex radiative properties of snow and from interference in forested areas. Physical radiative transfer models can be leveraged to improve the fidelity of these observations and as a data-assimilation tool. In this article, the Dense Media Radiative Transfer model with Multiple Layers (DMRT-ML) is used to simulate snow brightness temperatures from data collected from snow pits excavated during a two-day-long field study performed a temperate forest in the Northeast United States. The simulations are evaluated against surface-based radiometer observations collected at the snow pits. The DMRT-ML is configured with varying complexity to determine the snowpack characteristics most essential toward simulating brightness temperature within a temperate forest with complicated snow stratigraphy. In general, the single-layer configurations were not sufficiently complex to accurately simulate snow brightness temperature without significant tuning. The most accurate simulation was a two-layer configuration with a prescribed ice layer separating the snow layers. This simulation had a root-mean-square error <;15 K for the 37-GHz frequency. More complicated snowpack stratigraphy configurations did not substantively improve the results over the two-layer model configuration. The DMRT-ML was also used to examine differences between redundant datasets of density and grain size. It was determined that similar snow data collection and radiative transfer model configuration techniques are critical to ensure cross-study comparability.

Theodore Letcher↗

NASA NTRS2015

OSOAA: A Vector Radiative Transfer Model of Coupled Atmosphere-Ocean System for a Rough Sea Surface Application to the Estimates of the Directional Variations of the Water Leaving Reflectance to Better Process Multi-angular Satellite Sensors Data Over the Ocean

In this study, we present a radiative transfer model, so-called OSOAA, that is able to predict the radiance and degree of polarization within the coupled atmosphere-ocean system in the presence of a rough sea surface. The OSOAA model solves the radiative transfer equation using the successive orders of scattering method. Comparisons with another operational radiative transfer model showed a satisfactory agreement within 0.8%. The OSOAA model has been designed with a graphical user interface to make it user friendly for the community. The radiance and degree of polarization are provided at any level, from the top of atmosphere to the ocean bottom. An application of the OSOAA model is carried out to quantify the directional variations of the water leaving reflectance and degree of polarization for phytoplankton and mineral-like dominated waters. The difference between the water leaving reflectance at a given geometry and that obtained for the nadir direction could reach 40%, thus questioning the Lambertian assumption of the sea surface that is used by inverse satellite algorithms dedicated to multi-angular sensors. It is shown as well that the directional features of the water leaving reflectance are weakly dependent on wind speed. The quantification of the directional variations of the water leaving reflectance obtained in this study should help to correctly exploit the satellite data that will be acquired by the current or forthcoming multi-angular satellite sensors.

Ocean surface↗

NASA NTRS1985

Application of a radiative transfer model to bright icy satellites

A radiative transfer model, derived largely from the work of Hapke (1981) and Goguen (1981), is fit to Voyager imaging observations of Europa, Mimas, Enceladus, and Rhea. It is possible to place constraints on the single-scattering albedo, the porosity of the optically active upper regolith, the single-particle phase function, and, in the cases of Europa and Mimas, the mean-slope angle of macroscopic surface features. The texture of the surfaces of the Saturnian satellites appears to be similar to the earth's moon. However, Europa is found to have a distinctly more compact regolith and a more forward-scattering single-particle phase function.

Buratti, B. J.↗

NASA NTRS1991

A new polarized atmospheric radiative transfer model

A plane-parallel polarized radiative transfer model is described. The model is used to compute the radiance exiting a vertically inhomogeneous atmosphere containing randomly-oriented particles. Both solar and thermal sources of radiation are considered. A direct method of incorporating the polarized scattering information is combined with the doubling and adding method to produce a relatively simple formulation. Several numerical results are presented for verification and comparison.

Evans, K. F.↗

NASA NTRSDate not supplied

Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Remote Sensors for UV, VVIS, NIR, IR, and FIR Spectral Regions

Fast and accurate radiative transfer models are needed to efficiently process satellite hyperspectral remote sensors. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate TOA radiance or reflectance spectra in the cloudy atmosphere for far IR, IR, NIR, VIS, and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. Polarization components can also be calculated. The computation speed is 3 to 4 orders of magnitude faster than MODTRAN5, LBLRTM, and VLIDORT. The PCRTM calculated radiance spectra agree with reference RTM calculated radiance spectra very well (0.03 K in IR and 0.05% in solar). Comparisons of the PCRTM model calculations with observed AIRS, CrIS, IASI, NAST-I, and SCIAMACHY data will be presented. The solar-PCRTM has been developed for CLARREO PathFinder (CPF) and has been extensively used for CPF science algorithms. The PCRTM can also be used for many current and future NASA future missions such as EMIT, SBG, TEMPO, and PACE.

pcrtm↗

NASA NTRS2023

Developing a Radar Signal Simulator for the Community Radiative Transfer Model

Active radar instruments provide vertically resolved clouds and precipitation measurements that cannot be provided by the passive instruments. These active measurements are not conventionally assimilated into the data assimilation systems because of the lack of fast forward radiative transfer models and also difficulties in the error modelling of the measurements. This paper describes the development, evaluation, and sensitivity analysis for a forward radar model implemented in the Community Radiative Transfer Model (CRTM). The scattering properties required by the forward model are provided by the hydrometeor lookup tables that were generated using the discrete dipole approximation. The model is able to calculate both the reflectivity and the attenuated reflectivity for any given radar instrument at any given zenith angles as long as CRTM instrument specific coefficients are available. The evaluation using CloudSat measurements shows a very good agreement between the simulations and measurements as long as the input profiles of hydrometeors are consistent with the measured reflectivity profiles. Major sources contributing to the differences between the measured and simulated reflectivities are input hydrometeor profiles, scattering lookup tables, lack of melting layer in the forward model, CRTM scattering solvers, and attenuation calculations. In addition to the forward model, both Tangent Linear and Adjoint of the model are also implemented and tested within CRTM. These components may be required by some data assimilation systems for the assimilation of radar measurements.

radar↗

NASA NTRS2017

Comparison of Commonly-Used Microwave Radiative Transfer Models for Snow Remote Sensing

This paper reviews four commonly-used microwave radiative transfer models that take different electromagnetic approaches to simulate snow brightness temperature (T(sub B)): the Dense Media Radiative Transfer - Multi-Layer model (DMRT-ML), the Dense Media Radiative Transfer - Quasi-Crystalline Approximation Mie scattering of Sticky spheres (DMRT-QMS), the Helsinki University of Technology n-Layers model (HUT-nlayers) and the Microwave Emission Model of Layered Snowpacks (MEMLS). Using the same extensively measured physical snowpack properties, we compared the simulated T(sub B) at 11, 19 and 37 GHz from these four models. The analysis focuses on the impact of using different types of measured snow microstructure metrics in the simulations. In addition to density, snow microstructure is defined for each snow layer by grain optical diameter (Do) and stickiness for DMRT-ML and DMRT-QMS, mean grain geometrical maximum extent (D(sub max)) for HUT n-layers and the exponential correlation length for MEMLS. These metrics were derived from either in-situ measurements of snow specific surface area (SSA) or macrophotos of grain sizes (D(sub max)), assuming non-sticky spheres for the DMRT models. Simulated T(sub B) sensitivity analysis using the same inputs shows relatively consistent T(sub B) behavior as a function of Do and density variations for the vertical polarization (maximum deviation of 18 K and 27 K, respectively), while some divergences appear in simulated variations for the polarization ratio (PR). Comparisons with ground based radiometric measurements show that the simulations based on snow SSA measurements have to be scaled with a model-specific factor of Do in order to minimize the root mean square error (RMSE) between measured and simulated T(sub B). Results using in-situ grain size measurements (SSA or D(sub max), depending on the model) give a mean T(sub B) RMSE (19 and 37 GHz) of the order of 16-26 K, which is similar for all models when the snow microstructure metrics are scaled. However, the MEMLS model converges to better results when driven by the correlation length estimated from in-situ SSA measurements rather than D(sub max) measurements. On a practical level, this paper shows that the SSA parameter, a snow property that is easy to retrieve in-situ, appears to be the most relevant parameter for characterizing snow microstructure, despite the need for a scaling factor.

Snow↗

NASA NTRS2020

Long Term Stability Monitoring of Aqua MODIS Thermal Emissive Bands through Radiative Transfer Modeling

Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua has been in operation providing continuous global observations for science research and applications since 2002. The long-term stability of thermal emissive bands (TEBs) of Aqua MODIS was monitored through inter-comparisons with measurements by hyperspectral infrared sensors, such as AIRS on Aqua and IASI on MetOp satellite, or through long term vicarious monitoring over cold targets, such as Dome- C and deep convective clouds (DCC). In this paper, a radiative transfer modeling-based simulation model using Community Radiative Transfer Model (CRTM) is developed to perform the long-term monitoring of the stability of TEBs of Aqua MODIS. CRTM is a fast-radiative transfer model for calculations of radiances for satellite infrared radiometers and is able to output infrared radiance and brightness temperature at spectral bands of MODIS. Long term European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis data, such as temperature and humidity profiles, are used as inputs to the CRTM simulation. By confining the area of interest to be over low to middle latitude ocean, the long-term stabilities of selected Aqua MODIS TEBs are monitored through Observation–Background (O-B) brightness temperature (BT) bias between MODIS measurements and BT retrieval from CRTM simulation. The consistency and relative stability between Aqua MODIS and ECMWF reanalysis data for surface channels of MODIS are evaluated. In addition, the radiative transfer modeling with CRTM enables us to evaluate the impacts of long term variation of global CO2 distribution on the O-B BT biases for CO2 channels of Aqua MODIS through comparison of simulations with constant or long term variable CO2 as inputs. The O-B analysis with RTM show that Aqua MODIS surface channels are all radiometrically stable with yearly BT bias drift less than 0.004K/year for B20, B22, B23 and ~0.01K/year for B31 and B32. The CO2 absorption channels of Aqua MODIS, e.g. B33-B36, are stable with BT bias drift < 0.005K/year.

MODIS↗

NASA NTRS2018

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.

De Lannoy, Gabrielle↗

NASA NTRS1997

Cirrus Cloud Radiative and Microphysical Properties from Ground Observations and In Situ Measurements During FIRE 1991 and Their Application to Exhibit Problems in Cirrus Solar Radiative Transfer Modeling

Measurements from the FIRE 1991 cirrus cloud field experiment in the central United States are presented and analyzed. The first part focuses on cirrus microphysical properties. Aircraft 2D-probe in situ data at different cloud altitudes were evaluated for cirrus cases on four different days. Also presented are simultaneous data samples from balloonborne videosondes. Only these balloonsondes could detect the smaller crystals. Their data suggest (at least for midlatitude altitudes below 10 km) that ice crystals smaller than 15 microns in size are rare and that small ice crystals not detected by 2D-probe measurements are radiatively of minor importance, as overlooked 2D-probe crystals account for about 10% of the total extinction. The second part focuses on the link between cirrus cloud properties and radiation. With cloud macrophysical properties from surface remote sensing added to the microphysical data and additional radiation measurements at the surface, testbeds for radiative transfer models were created. To focus on scattering processes, model evaluations were limited to the solar radiative transfer by comparing calculated and measured transmissions of sunlight at the surface. Comparisons under cloud-free conditions already reveal a model bias of about +45 W/sq m for the hemispheric solar downward broadband flux. This discrepancy, which is (at least in part) difficult to explain, has to be accounted for in comparisons involving clouds. Comparisons under cirrus cloud conditions identify as the major obstacle in cirrus solar radiative transfer modeling the inability of one-dimensional radiative transfer models to account for horizontal inhomogeneities. The successful incorporation of multidimensional radiative transfer effects will depend not only on better models but critically on the ability to measure and to define characteristic inhomogeneity scales of cloud fields. The relative minor error related to the microphysical treatment is in part a reflection of the improved understanding on solar scattering on ice crystals over the last decade and of the available wealth on ice-crystal size and shape data for this study. In absence of this information, uncertainties from microphysical cirrus model assumptions will remain high.

Kinne, Stefan↗

NASA NTRS1998

An Improved Radiative Transfer Model for Climate Calculations

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Bergstrom, Robert W.↗

NASA NTRS2000

A Radiative Transfer Model for Climate Calculations

This paper describes a radiative transfer model developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. We use a newly developed k-distribution model for both the thermal and solar parts of the spectrum. We employ a generalized two-stream approximation for the scattering by aerosol and clouds. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. We perform several calculations focussing primarily on the question of absorption of solar radiation by gases and aerosols. We estimate the accuracy of the k-distribution to be approx. 1 W/sq m for the gaseous absorption in the solar spectrum. We estimate the accuracy of the two-stream method to be 3-12 W/sq m for the downward solar flux and 1-5 W/sq m for the upward solar flux at the top of atmosphere depending on the optical depth of the aerosol layer. We also show that the effect of ignoring aerosol absorption on the downward solar flux at the surface is 50 W/sq m for the TARFOX aerosol for an optical depth of 0.5 and 150 W/sq m for a highly absorbing mineral aerosol. Thus, we conclude that the uncertainty introduced by the aerosol solar radiative properties (and merely assuming some "representative" model) can be considerably larger than the error introduced by the use of a two-stream method.

Bergstrom, Robert W.↗

NASA NTRS1995

An analytic radiative transfer model for a coupled atmosphere and leaf canopy

A new analytical radiative transfer model of a leaf canopy is developed that approximates multiple-scattering radiance by a four-stream formulation. The canopy model is coupled to a homogeneous atmospheric model as well as a non-Lambertian lower boundary soil surface. The same four-stream formulation is also used for the calculation of multiple scattering in the atmosphere. Comparisons of radiance derived from the four-stream model with those calculated by an iterative numerical solution of the radiative transfer equation show that the analytic model has a very high accuracy, even with a turbid atmosphere and a very dense canopy in which multiple scattering dominates. Because the coupling of canopy and atmospheric models fully accommodates anisotropic surface reflectance and atmospheric scattering and its effect on directional radiance, the model is especially useful for application to directional radiance and measurements obtained by remote sensing. Retrieval of biophysical parameters using this model is under investigation.

Liang, Shunlin↗