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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 NTRS2015

Ultrafast High Accuracy PCRTM_SOLAR Model for Cloudy Atmosphere

An ultrafast high accuracy PCRTM_SOLAR model is developed based on PCA compression and principal component-based radiative transfer model (PCRTM). A fast algorithm for simulation of multi-scattering properties of cloud and/or aerosols is integrated into the fast infrared PCRTM. We completed radiance simulation and training for instruments, such as IASI, AIRS, CrIS, NASTI and SHIS, under diverse conditions. The new model is 5 orders faster than 52-stream DISORT with very high accuracy for cloudy sky radiative transfer simulation. It is suitable for hyperspectral remote data assimilation and cloudy sky retrievals.

Yang, Qiguang↗

NASA NTRS1979

Multispectral Resource Sampler (MRS): Proof of concept study on atmospheric corrections. Determinations of atmospheric optical parameters using the multispectral resource sampler atmospheric optical

An investigation was performed to determine which mathematical algorithms should be used in the calculation of atmospheric optical parameters using the Multispectral Resource Sampler (MRS) sensor. A simulation of the MRS sensor was performed using a radiative-transfer model. The simulation provides the spectral radiance at the satellite sensor in terms of various atmospheric parameters, such as optical thickness, solar zenith angle, nadir view angle, relative azimuth angle, bi-directional reflectance of the target, background albedo, and wavelength. Atmospheric correction algorithms were also developed for the determination of the total spectral optical thickness of the atmosphere for: (1) homogeneous (horizontal) hazy atmospheres with diffuse targets; (2) inhomogeneous (horizontal) hazy atmospheres with diffuse targets; and (3) homogeneous (horizontal) hazy atmospheres with non-diffuse targets.

Turner, R. E.↗

NASA NTRSDate not supplied

A New BRDF Hotspot Model and its Use in Improving Radiative Transfer Model Efficiency and Application to VLIDORT-based PCRTM Model

The term “hotspot” refers to the sharp increase of reflectance occurring when incident (solar) and reflected (viewing) directions almost coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications. The RossThick-LiSparse-Reciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is widely used in radiative transfer simulations, and the hotspot model mostly used is from Maignan- Bréon but it typically requires large values of numerical quadrature and Fourier expansion terms in order to represent the hotspot accurately. To improve its use in atmospheric radiative transfer (RT) model simulations, we have developed a modified version based on the Maignan-Bréon’s hotspot BRDF model that converge much faster numerically, making it more practical for use in RT models that require Fourier expansion of BRDF to simulate the top-of-atmosphere (TOA) hotspot signatures. On basis of the vector linearized discrete ordinate radiative transfer model (VLIDORT), we have built a line-by-line based simulation system that can simulate the TOA radiance for atmospheres with 26 gases, different aerosols, dust and clouds, and surface with different BRDF. Using simulated results under diverse atmospheric conditions, we have developed VLIDORT-PCRTM model.

Xiaozhen Xiong↗

NASA NTRS1986

Assessing impacts of off-nadir observation on remote sensing of vegetation - Use of the Suits model

The use of Suits' (1972a, b) digital radiative transfer model to simulate the effect of nonLambertian canopy reflectance on off-nadir observations of vegetation is discussed. Canopy reflectances of cord grass are calculated using the radiative transfer model, field radiometric measurements, and airborne multispectral scanner data. The effects of varying view angles on canopy reflectance are analyzed and compared. The comparison reveals that the model is effective in simulating the sense and magnitude of reflectance change due to variable angles of observations; however, the model does not reproduce the observed dependence of nadir canopy reflectance on solar zenith angle. It is concluded that the radiative transfer model is applicable for predicting the variation in canopy reflectance due to changing view zenith angles.

Bartlett, D. S.↗

NASA NTRSDate not supplied

Data Simulation Using VLIDORT and PCRTM and its Use for Radiometric Calibration of Hyperspectral UV-NIR-SWIR Sensors

Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer discrete ordinate scattering codes, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate the radiation fields for hyperspectral UV-NIR-SWIR sensors from 250nm to 2500nm with a very high speed. Since the accurate gas absorptions, molecules and aerosol/cloud particle scatterings, and the surface reflectance have been considered in these simulations, these model data can be used for satellite or airborne sensor design, characterization, or end-to-end system level uncertainty assessment. Comparison of the modelled data with measured results has been a general practice for operational satellite sensor calibrations, such as the Ozone Mapping and Profiler Suite (OMPS) onboard on SNPP and NOAA-20. This presentation will give more details of this simulation system and models. Some examples of the generation of simulations data for CLARREO PathFinder (CPF) and the Surface Biology and Geology (SBG), as well as some examples to use these data for CPF and OMPS radiometric calibration will be presented.

Xiaozhen Xiong↗

NASA NTRS1989

Cloud model-based simulations of satellite microwave data and their application to an SSM/I rain algorithm

Satellite microwave observations of convective rain systems are simulated using a three-dimensional cloud model and a microwave radiative-transfer model. The simulated data sets are then used as a basis to derive rain estimation algorithms which are tested on actual satellite data. A tropical simulation is discussed, and the algorithms are applied to SSM/I data.

Adler, Robert F.↗

NASA NTRS2019

Impact of Dust Aerosols on Simulated Infrared Radiances Within the Community Radiative Transfer Model (CRTM)

No abstract available

Naeger, Aaron↗

NASA NTRS2020

Assessing the Impact of Soil Layer Depth Specification on the Observability of Modeled Soil Moisture and Brightness Temperature

The utility of hydrologic land surface models (LSMs) can be enhanced by using information from observational platforms, but mismatches between the two are common.This study assesses the degree to which model agreement with observations (observability) is affected by two mechanisms in particular: 1) physical incongruities between the support volumes being characterized and 2) inadequateor inconsistent parameterizations of physical processes. The Noah and Noah-MP LSMs by default characterize surface soil moisture (SSM) in the top 10 cm of the soil column. This depth may be reasonable when comparing against soil moisture from in situ probes centered at 5 cm,but it is notably different from the 5 cm (or less) sensing depth of NASA’s Soil Moisture Active Passive (SMAP) satellite mission. These depth inconsistencies are examined by using thinner model layers in the Noah and Noah-MP LSMs and comparing resultant simulations to in situ and SMAP soil moisture. In addition, a forward radiative transfer model to simulate microwave brightness temperatures (Tbs) is used to facilitate direct comparisons of LSM-based and SMAP-based L-band Tb retrievals. Observability is quantified using Kolmogorov-Smirnov distance values, calculated from empirical cumulative distribution functions of SSM and Tb time series. Experiment results depend on the particular subspace being analyzed (SSM or Tb). This study concludes that therole of increasedsoil layer discretizationon LSM observability is secondary to the influence of component parameterizations, the effects of which dominate systematic differences with observations

SMAP↗

NASA NTRS2022

L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation and Soil Salinity

The Dry Chaco in South America is a semi-arid ecoregion prone to dryland salinization. In this region, we investigated coarse-scale surface soil moisture (SM), soil temperature, soil salinity and vegetation, using L-band microwave brightness temperature (TB) observations and retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite missions, Catchment Land Surface Model (CLSM) simulations, and in situ measurements within 26 sampled satellite pixels. Across these 26 sampled pixels, the satellite-based SM outperformed CLSM SM compared to field data, and forward L-band TB simulations derived from in situ SM and temperature performed better than those derived from CLSM estimates relative to SMOS TB observations. The surface salinity for the sampled pixels was on average only 4 mg/g and only locally influenced the TB simulations, when including salinity in the dielectric mixing model of the forward radiative transfer model (RTM) simulations. To explore the potential of retrieving salinity together with other RTM parameters to optimize TB simulations over the entire Dry Chaco, the RTM was inverted using 10 years of multi-angular SMOS TB data and constraints of CLSM SM and temperature. However, the latter modeled SM was not sufficiently accurate and factors such as open surface water were missing in the background constraints, so that the salinity retrievals effectively represented a bulk correction of the dielectric constant, rather than salinity per se. However, the retrieval of vegetation, scattering albedo and surface roughness resulted in realistic values.

L-Band↗

NASA NTRS1995

Microwave and infrared simulations of an intense convective system and comparison with aircraft observations

A three-dimensional cloud model, radiative transfer model-based simulation system is tested and validated against the aircraft-based radiance observations of an intense convective system in southeastern Virginia on 29 June 1986 during the Cooperative Huntsville Meteorological Experiment. NASA's ER-2, a high-altitude research aircraft with a complement of radiometers operating at 11-micrometer infrared channel and 18-, 37-, 92-, and 183-GHz microwave channels provided data for this study. The cloud model successfully simulated the cloud system with regard to aircraft- and radar-observed cloud-top heights and diameters and with regard to radar-observed reflectivity structure. For the simulation time found to correspond best with the aircraft- and radar-observed structure, brightness temperatures T(sub b) are simulated and compared with observations for all the microwave frequencies along with the 11-micrometer infrared channel. Radiance calculations at the various frequencies correspond well with the aircraft observations in the areas of deep convection. The clustering of 37-147-GHz T(sub b) observations and the isolation of the 18-GHz values over the convective cores are well simulated by the model. The radiative transfer model, in general, is able to simulate the observations reasonably well from 18 GHz through 174 GHz within all convective areas of the cloud system. When the aircraft-observed 18- and 37-GHz, and 90- and 174-GHz T(sub b) are plotted against each other, the relationships have a gradual difference in the slope due to the differences in the ice particle size in the convective and more stratiform areas of the cloud. The model is able to capture these differences observed by the aircraft. Brightness temperature-rain rate relationships compare reasonably well with the aircraft observations in terms of the slope of the relationship. The model calculations are also extended to select high-frequency channels at 220, 340, and 400 GHz to simulate the Millimeter-wave Imaging Radiometer aircraft instrument to be flown in the near future. All three of these frequencies are able to discriminate the convective and anvil portions of the system, providing useful information similar to that from the frequencies below 183 GHz but with potentially enhanced spatial resolution from a satellite platform. In thin clouds, the dominant effect of water vapor is seen at 174, 340, and 400 GHz. In thick cloudy areas, the scattering effect is dominant at 90 and 220 GHz, while the overlaying water vapor can attenuate at 174, 340, and 400 GHz. All frequencies (90-400 GHz) show strong signatures in the core.

Prasad, N.↗

NASA NTRS1965

Convective and radiative heat transfer during reentry and advanced techniques for their simulation

The use of shock tubes, ballistic ranges, and combinations thereof in simulation of convective and radiative heat loads has been described. The complementary nature and the highly independent techniques used in these facilities lend great strength to the research results where they agree. The shortcomings of these facilities are such that, if possible, both should be applied to important problems. When all-out performance is required, the combination of the two can clearly provide advantages. That these advantages are becoming more widely recognized is demonstrated by the construction of new faculties at Arnold Engineering Development Center and Boeing Company, Seattle, similar to those in service at Ames Research Center since the late 1950's.

Radiative Heat Transfer↗

DOE OSTI2023

A Refined Understanding of the Ice Cloud Longwave Scattering Effects in Climate Model

Abstract Because longwave (LW) absorption by greenhouse gases and clouds is more significant than the LW scattering effect by clouds, most climate models neglect cloud LW scattering to save computational costs. Ignoring cloud LW scattering directly overestimates outgoing longwave radiation (OLR). This study included ice‐cloud LW scattering treatment in the Exascale Energy Earth System Model (E3SM) version 2 and ran fully‐coupled simulations, prescribed sea surface temperature simulations, and offline radiative transfer calculations to comprehensively assess the impact of ice‐cloud LW scattering on global climate simulation. The instantaneous effect due to ice‐cloud LW scattering reduces the OLR by ∼1 W/m 2 on the global average and 2 W/m 2 on the tropical average. Tropospheric warming and high cloud amount reduction act to partially compensate for such instantaneous OLR reduction caused by the inclusion of LW scattering. When the simulation reaches the equilibrium, the surface warms by 0.66 K on average with respect to the simulation without LW scattering, with the Arctic surface temperature differences more than twice as large as that of the global mean. The impact of including LW scattering on the simulated climate change in response to 4 × CO 2 is also assessed. While including the cloud LW scattering does not significantly modify radiative forcing and total radiative feedback under such a scenario, it results in a 10% more positive cloud feedback.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Collaborative Research: Improved Efficiency and Coupling of the Radiation Code in the ACME Earth System Model (Final Report)

The complexity of radiative transfer, its importance to the exchange of energy in the climate system, and its high computational cost establishes importance of an accurate and efficient radiative transfer parameterization for climate simulation. Previous work by the proposing team at AER led to the development of the radiation code, RRTMG, which has been widely accepted by the global modeling community as a fast and accurate advancement over the previous generation of radiation codes. It has been in use in the NCAR CESM for many years, and it has been implemented in the initial version the DOE E3SM model. However, its computational cost remains high relative to other components in part due to its complexity and to its inefficient use of modern optimization strategies, and this project helped address this limitation for the code’s application in E3SM. Under other funding, the Investigators of this project led an effort to develop a high-performance broadband radiation code, called RTE+RRTMGP, which is a completely restructured code that will take advantage of modern computational capabilities to enhance its performance while retaining the strengths and accuracy of the original code. Designed to perform over a range of computer architectures, RTE+RRTMGP makes extensive use of Fortran 2003 features to improve both its efficiency and its use of memory. RTE+RRTMGP is expected to be adopted in the next generation of RTE+RRTMGP. This project allowed for advancements to the code’s computational capabilities and adding new and enhanced features. This included revising RTE+RRTMGP to run on GPU processors, analysis of and improvements to the code’s timing, modifying the gas optics in RRTMGP to increase the code’s accuracy, extensive validation of computed fluxes, heating rates and forcings, generating a cloud optical property and vertical sampling capabilities for RTE+RRTMGP, implementing a fast and accurate longwave scattering capability, and groundwork for the inclusion of a capability to specify solar variability. Many of the accomplishment in this project necessitated significant collaboration with the E3SM development team. The result of this project was optimization of a key physical component (radiative transfer calculations) of E3SM, directly supporting E3SM’s overarching global modeling objectives. More broadly, this project provided overall advancements in the use of radiative transfer calculations in atmospheric modeling and simulation, particularly for climate.

58 GEOSCIENCES↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

The potential of solar-induced chlorophyll fluorescence (SIF) to monitor photosynthesis and plant stress has attracted considerable interest in SIF remote sensing (RS). However, canopy SIF and RS observations are impacted by topography, vegetation three dimension (3D) structure, leaf orientation, non foliar elements (e.g., tree woody skeleton), ... Physically based downscaling of canopy SIF RS data to leaf-level (i.e., to leaf photosynthesis) requires 3D radiative transfer (RT) models simulating canopy SIF and its observation. These models are necessary to better exploit the potential of SIF, by linking leaf SIF and SIF in RS observations as a function of canopy 3D architecture and experimental configurations (sun and viewing directions, etc.). The Discrete Anisotropic Radiative Transfer (DART) model is a comprehensive 3D radiative transfer (RT) model for urban and natural landscapes. This paper presents its SIF modeling for vegetation simulated with facets, its validation with the SCOPE/mSCOPE 1D models, and its recent extension to SIF modelling for landscapes simulated with 3D turbid medium.

radiative transfer↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

Radiative transfer↗

NASA NTRS1996

Atmospheric Pre-Corrected Differential Absorption Techniques to Retrieve Columnar Water Vapor: Application to AVIRIS 91/95 Data

Water vapor is one of the main forces for weather development as well as for mesoscale air transport processes. The monitoring of water vapor is therefore an important aim in remote sensing of the atmosphere. Current operational systems for water vapor detection use primarily the emission in the thermal infrared (AVHRR, GOES, ATSR, Meteosat) or in the microwave radiation bands (DMSP). The disadvantage of current satellite systems is either a coarse spatial (horizontal) resolution ranging from one to tens of kilometers or a limited insight into the lower atmosphere. Imaging spectrometry on the other hand measures total column water vapor contents at a high spatial horizontal resolution and has therefore the potential of filling these gaps. The sensors of the AVIRIS instrument are capable of acquiring hyperspectral data in 224 bands located in the visible and near infrared at 10 nm resolution. This data includes the information on constituents of the earth's surface as well as of the atmosphere. The optical measurement of water vapor can be performed using sensor channels located in bands or lines of the absorption spectrum. The AVIRIS sensor has been used to retrieve water vapor and with less accuracy carbon dioxide, oxygen and ozone. To retrieve the water vapor amount, the so called differential absorption technique has been applied. The goal of this technique is to eliminate background factors by taking a ratio between channels within the absorption band and others besides the band. Various ratioing methods on the basis of different channels and calculation techniques were developed. The influence of a trace gas of interest on the radiance at the sensor level is usually simulated by using radiative transfer codes. In this study, the spectral transmittance and radiance are calculated by MODTRAN3 simulations with the new DISORT option. The objective of this work is to test the best performing differential absorption techniques for imaging spectrometry of tropospheric water vapor.

Schlaepfer, Daniel↗

DOE OSTI2022

A detailed experimental and modeling comparison of molecular radiative heat loss in a spark-ignition engine

Radiative heat transfer has been chiefly considered negligible in internal combustion engines, except for Diesel engines where soot radiation was recognized as a significant radiative transfer source. Only more recently, detailed simulations have shown that molecular radiation can be substantial as well. In extension to this, molecular radiative heat transfer can reach detectable levels of about 5–10% of the total heat transfer in spark-ignited engines. The broadband radiative nature of the significant emitting molecules, carbon dioxide and water, makes it necessary to address whether radiative trapping plays a substantial role in either total heat loss or energy redistribution within the cylinder. An experimental setup that allows measurements of the infrared emissions at a 2-crank-angle-degree resolution was developed to determine the importance of radiative trapping by carbon dioxide and water. Measurements were conducted in the well-characterized and documented TCC-III engine at the University of Michigan. The engine operated on a stoichiometric propane/air mixture at a speed of 1,300 RPM. Large Eddy Simulations with added line-by-line photon Monte-Carlo simulations of the molecular radiation were an integral part of this study to plan and devise the measurements. Post-processing of the simulation data included an accurate representation of the experimental volume from where infrared signals are collected. Additionally, the experimental data were used for validation of the photon Monte-Carlo simulations. Joint analysis of experimental and simulated spectra allowed quantifying the significance of radiative trapping. Results show the significant role of radiative trapping when predicting radiative heat transfer in the TCC-III engine.

42 ENGINEERING↗