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NASA NTRS1990

Analysis and improved design considerations for airborne pulse Doppler radar signal processing in the detection of hazardous windshear

High resolution windspeed profile measurements are needed to provide reliable detection of hazardous low altitude windshear with an airborne pulse Doppler radar. The system phase noise in a Doppler weather radar may degrade the spectrum moment estimation quality and the clutter cancellation capability which are important in windshear detection. Also the bias due to weather return Doppler spectrum skewness may cause large errors in pulse pair spectral parameter estimates. These effects are analyzed for the improvement of an airborne Doppler weather radar signal processing design. A method is presented for the direct measurement of windspeed gradient using low pulse repetition frequency (PRF) radar. This spatial gradient is essential in obtaining the windshear hazard index. As an alternative, the modified Prony method is suggested as a spectrum mode estimator for both the clutter and weather signal. Estimation of Doppler spectrum modes may provide the desired windshear hazard information without the need of any preliminary processing requirement such as clutter filtering. The results obtained by processing a NASA simulation model output support consideration of mode identification as one component of a windshear detection algorithm.

Lee, Jonggil↗

DOE OSTI2019

A Method for Integrating an UBEM with GIS for Spatiotemporal Visualization and Analysis

Leveraging Geographic Information Systems (GIS) for spatiotemporal visualization and analysis of simulated UBEM datasets and real-world data simultaneously can assist in identifying opportunities, as well as potential barriers, to energy efficient and climate adaptation strategies. However, current GIS-based models that support interactive exploration of adaptation strategies and future scenarios are scarce and do not easily incorporate building energy use data for visual analysis over time. This paper describes a workflow to integrate simulated building energy consumption data associated with variable energy efficiency scenarios within a GIS platform for interactive spatiotemporal visualization to support climate adaptation decision-making. The contribution of the work presented is in the ability to selectively view and analyze simulated building energy performance data layered with other real-world geospatial data through an automated feedback loop between an UBEM and ArcGIS. An interactive interface is designed in ArcGIS to enable users to explore building performance scenarios spatially and over time. Using a downtown neighborhood in Syracuse, New York, USA, as a case study, preliminary results demonstrate how the workflow provides insight into existing energy use issues and potential for implementing strategies such as energy load shifting or building retrofits. A discussion includes opportunities as well as challenges to the workflow in facilitating understanding of urban energy model outputs by multiple stakeholders in evaluating potential energy efficient strategies.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

NASA NTRS2001

Cardiac atrophy after bed rest and spaceflight

Cardiac muscle adapts well to changes in loading conditions. For example, left ventricular (LV) hypertrophy may be induced physiologically (via exercise training) or pathologically (via hypertension or valvular heart disease). If hypertension is treated, LV hypertrophy regresses, suggesting a sensitivity to LV work. However, whether physical inactivity in nonathletic populations causes adaptive changes in LV mass or even frank atrophy is not clear. We exposed previously sedentary men to 6 (n = 5) and 12 (n = 3) wk of horizontal bed rest. LV and right ventricular (RV) mass and end-diastolic volume were measured using cine magnetic resonance imaging (MRI) at 2, 6, and 12 wk of bed rest; five healthy men were also studied before and after at least 6 wk of routine daily activities as controls. In addition, four astronauts were exposed to the complete elimination of hydrostatic gradients during a spaceflight of 10 days. During bed rest, LV mass decreased by 8.0 +/- 2.2% (P = 0.005) after 6 wk with an additional atrophy of 7.6 +/- 2.3% in the subjects who remained in bed for 12 wk; there was no change in LV mass for the control subjects (153.0 +/- 12.2 vs. 153.4 +/- 12.1 g, P = 0.81). Mean wall thickness decreased (4 +/- 2.5%, P = 0.01) after 6 wk of bed rest associated with the decrease in LV mass, suggesting a physiological remodeling with respect to altered load. LV end-diastolic volume decreased by 14 +/- 1.7% (P = 0.002) after 2 wk of bed rest and changed minimally thereafter. After 6 wk of bed rest, RV free wall mass decreased by 10 +/- 2.7% (P = 0.06) and RV end-diastolic volume by 16 +/- 7.9% (P = 0.06). After spaceflight, LV mass decreased by 12 +/- 6.9% (P = 0.07). In conclusion, cardiac atrophy occurs during prolonged (6 wk) horizontal bed rest and may also occur after short-term spaceflight. We suggest that cardiac atrophy is due to a physiological adaptation to reduced myocardial load and work in real or simulated microgravity and demonstrates the plasticity of cardiac muscle under different loading conditions.

Flight Experiment↗

DOE OSTI2016

Fault detection and analysis in nuclear research facility using artificial intelligence methods

In this article, an online detection of transducer and actuator condition is discussed. A case study is on the reading of area radiation monitor (ARM) installed at the chimney of PUSPATI TRIGA nuclear reactor building, located at Bangi, Malaysia. There are at least five categories of abnormal ARM reading that could happen during the transducer failure, namely either the reading becomes very high, or very low/ zero, or with high fluctuation and noise. Moreover, the reading may be significantly higher or significantly lower as compared to the normal reading. An artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are good methods for modeling this plant dynamics. The failure of equipment is based on ARM reading so it is then to compare with the estimated ARM data from ANN/ ANFIS function. The failure categories in either ‘yes’ or ‘no’ state are obtained from a comparison between the actual online data and the estimated output from ANN/ ANFIS function. It is found that this system design can correctly report the condition of ARM equipment in a simulated environment and later be implemented for online monitoring. This approach can also be extended to other transducers, such as the temperature profile of reactor core and also to include other critical actuator conditions such as the valves and pumps in the reactor facility provided that the failure symptoms are clearly defined.

42 ENGINEERING↗

DOE OSTI2023

Analysis of Dynamic Behavior of the Target and the Deuterium-Tritium Ice in Magnetic-Field Assisted Implosions

The use of strong magnetic fields to augment the output energy of inertial confinement fusion experiments at the National Ignition Facility is of high interest. It offers the potential of reducing electron thermal conduction and increasing hot-spot alpha heating with little to no change in hohlraum behavior. In these magnetically assisted ignition experiments, the ultimate goal is to add a B-field in the form of a pulse ranging from 25 to 60 T to a high-performing hohlraum implosion several microseconds before impingement of the laser beams. This requires eliminating metallic components in the target and replacing them with electrically nonconducting materials. However, the strong eddy currents generated by the rapidly increasing high B-field, which were calculated to be as high as 2000 K, can heat the hohlraum. Here in this paper, we examine the transient effects of this rapid temperature change on the behavior of the target as well as the fuel layer composed typically of deuterium and tritium. Using simulations and calculations for limiting case scenarios, we find that the effect of the heating is not restrictive toward the performance of the target or the quality of the deuterium-tritium ice.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Characterization of energy response for photon-counting detectors using x-ray fluorescence

Purpose: To investigate the feasibility of characterizing a Si strip photon-counting detector using x-ray fluorescence. Methods: X-ray fluorescence was generated by using a pencil beam from a tungsten anode x-ray tube with 2 mm Al filtration. Spectra were acquired at 90° from the primary beam direction with an energy-resolved photon-counting detector based on an edge illuminated Si strip detector. The distances from the source to target and the target to detector were approximately 19 and 11 cm, respectively. Four different materials, containing silver (Ag), iodine (I), barium (Ba), and gadolinium (Gd), were placed in small plastic containers with a diameter of approximately 0.7 cm for x-ray fluorescence measurements. Linear regression analysis was performed to derive the gain and offset values for the correlation between the measured fluorescence peak center and the known fluorescence energies. The energy resolutions and charge-sharing fractions were also obtained from analytical fittings of the recorded fluorescence spectra. An analytical model, which employed four parameters that can be determined from the fluorescence calibration, was used to estimate the detector response function. Results: Strong fluorescence signals of all four target materials were recorded with the investigated geometry for the Si strip detector. The average gain and offset of all pixels for detector energy calibration were determined to be 6.95 mV/keV and −66.33 mV, respectively. The detector’s energy resolution remained at approximately 2.7 keV for low energies, and increased slightly at 45 keV. The average charge-sharing fraction was estimated to be 36% within the investigated energy range of 20–45 keV. The simulated detector output based on the proposed response function agreed well with the experimental measurement. Conclusions: The performance of a spectral imaging system using energy-resolved photon-counting detectors is very dependent on the energy calibration of the detector. The proposed x-ray fluorescence technique offers an accurate and efficient way to calibrate the energy response of a photon-counting detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2006

Engine System Model Development for Nuclear Thermal Propulsion

In order to design, analyze, and evaluate conceptual Nuclear Thermal Propulsion (NTP) engine systems, an improved NTP design and analysis tool has been developed. The NTP tool utilizes the Rocket Engine Transient Simulation (ROCETS) system tool and many of the routines from the Enabler reactor model found in Nuclear Engine System Simulation (NESS). Improved non-nuclear component models and an external shield model were added to the tool. With the addition of a nearly complete system reliability model, the tool will provide performance, sizing, and reliability data for NERVA-Derived NTP engine systems. A new detailed reactor model is also being developed and will replace Enabler. The new model will allow more flexibility in reactor geometry and include detailed thermal hydraulics and neutronics models. A description of the reactor, component, and reliability models is provided. Another key feature of the modeling process is the use of comprehensive spreadsheets for each engine case. The spreadsheets include individual worksheets for each subsystem with data, plots, and scaled figures, making the output very useful to each engineering discipline. Sample performance and sizing results with the Enabler reactor model are provided including sensitivities. Before selecting an engine design, all figures of merit must be considered including the overall impacts on the vehicle and mission. Evaluations based on key figures of merit of these results and results with the new reactor model will be performed. The impacts of clustering and external shielding will also be addressed. Over time, the reactor model will be upgraded to design and analyze other NTP concepts with CERMET and carbide fuel cores.

Nelson, Karl W.↗

NASA NTRS2012

Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network

The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis

Yao, Weigang↗

NASA NTRS2016

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results: Cloud Coverage - Part II

This is the second part of a study on how temporal sampling frequency affects satellite retrievals in support of the Deep Space Climate Observatory (DSCOVR) mission. Continuing from Part 1, which looked at Earth's radiation budget, this paper presents the effect of sampling frequency on DSCOVR-derived cloud fraction. The output from NASA's Goddard Earth Observing System version 5 (GEOS-5) Nature Run is used as the "truth". The effect of temporal resolution on potential DSCOVR observations is assessed by subsampling the full Nature Run data. A set of metrics, including uncertainty and absolute error in the subsampled time series, correlation between the original and the subsamples, and Fourier analysis have been used for this study. Results show that, for a given sampling frequency, the uncertainties in the annual mean cloud fraction of the sunlit half of the Earth are larger over land than over ocean. Analysis of correlation coefficients between the subsamples and the original time series demonstrates that even though sampling at certain longer time intervals may not increase the uncertainty in the mean, the subsampled time series is further and further away from the "truth" as the sampling interval becomes larger and larger. Fourier analysis shows that the simulated DSCOVR cloud fraction has underlying periodical features at certain time intervals, such as 8, 12, and 24 h. If the data is subsampled at these frequencies, the uncertainties in the mean cloud fraction are higher. These results provide helpful insights for the DSCOVR temporal sampling strategy.

GEOS-5↗

DOE OSTI2021

Design and analysis of a wake model for spatially heterogeneous flow

Abstract. Methods of turbine wake modeling are being developed to more accurately account for spatially variant atmospheric conditions within wind farms. Most current wake modeling utilities are designed to apply a uniform flow field to the entire domain of a wind farm. When this method is used, the accuracy of power prediction and wind farm controls can be compromised depending on the flow-field characteristics of a particular area. In an effort to improve strategies of wind farm wake modeling and power prediction, FLOw Redirection and Induction in Steady State (FLORIS) was developed to implement sophisticated methods of atmospheric characterization and power output calculation. In this paper, we describe an adapted FLORIS model that features spatial heterogeneity in flow-field characterization. This model approximates an observed flow field by interpolating from a set of atmospheric measurements that represent local weather conditions. The objective of this method is to capture heterogeneous atmospheric effects caused by site-specific terrain features, without explicitly modeling the geometry of the wind farm terrain. The implemented adaptations were validated by comparing the simulated power predictions generated from FLORIS to the actual recorded wind farm output from the supervisory control and data acquisition (SCADA) recordings and large eddy simulations (LESs). When comparing the performance of the proposed heterogeneous model to homogeneous FLORIS simulations, the results show a 14.6 % decrease for mean absolute error (MAE) in wind farm power output predictions for cases using wind farm SCADA data and a 18.9 % decrease in LES case studies. The results of these studies also indicate that the efficacy of the proposed modeling techniques may vary with differing site-specific operational conditions. This work quantifies the accuracy of wind plant power predictions under heterogeneous flow conditions and establishes best practices for atmospheric surveying for wake modeling.

17 WIND ENERGY↗

DOE OSTI2022

Software Development for Data Visualization and Analysis of PN-Diodes & MOSFET Devices

The U.S. Department of Energy has a broad mission to ensure the nation’s security by addressing ongoing environmental challenges, developing novel energy production technologies, and mitigating nuclear security concerns. These efforts benefit from developing more effective semiconductor materials and devices. The research discussed in this report aims to further the development of these new electronics by improving implementations of vertical device structures, which offer theoretically better performance compared to lateral structures. Specifically, it reviews the background and development of a new and easy-to-use program for data processing and analysis from experiments run on vertical gallium nitride power devices. Current vertical structures fall short in critical performance metrics, such as On-Resistance and Breakdown Voltage, due to poor management of the device’s electric field. Junction termination extensions, or JTEs, are a field management technique that increases a device’s resilience to expected failure modes by controlling its surface electric fields. Each JTE design requires significant experimental validation, consisting of hundreds of tested devices, each outputting an enormous set of data points. The new software includes multiple methods of filtering large sets of device testing data to identify and remove flawed devices, automate device analyses, and provide statistical breakdowns for four metrics used to define the effectiveness of the JTE and the current carrying capacity of the device. These results can then be related back to fabrication techniques and device design, and in the future, be combined with processing simulations to further improve our understanding of the JTE mechanisms.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2012

Iterative Atmospheric Correction Scheme and the Polarization Color of Alpine Snow

Characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of a few geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of these measurements is overwhelmed by that of instruments with polarization capabilities: proposed models in this case are based on the Fresnel reflectance of an isotropic distribution of facets. Because of its remarkable lack of spectral contrast, the polarized reflectance of land surfaces in the shortwave infrared spectral region, where atmospheric scattering is minimal, can be used to model the surface also at shorter wavelengths, where aerosol retrievals are attempted based on well-established scattering theories. In radiative transfer simulations, straightforward separation of the surface and atmospheric contributions is not possible without approximations because of the coupling introduced by multiple reflections. Within a general inversion framework, the problem can be eliminated by linearizing the radiative transfer calculation, and making the Jacobian (i.e., the derivative expressing the sensitivity of the reflectance with respect to model parameters) available at output. We present a general methodology based on a Gauss-Newton iterative search, which automates this procedure and eliminates de facto the need of an ad hoc atmospheric correction. In this case study we analyze the color variations in the polarized reflectance measured by the NASA Goddard Institute of Space Studies Research Scanning Polarimeter during a survey of late-season snowfields in the High Sierra. This insofar unique dataset presents challenges linked to the rugged topography associated with the alpine environment and a likely high water content due to melting. The analysis benefits from ancillary information provided by the NASA Langley High Spectral Resolution Lidar deployed on the same aircraft. The results obtained from the iterative scheme are contrasted against the surface polarized reflectance obtained ignoring multiple reflections, via the simplistic subtraction of the atmospheric scattering contribution. Finally, the retrieved reflectance is modeled after the scattering properties of a dense collection of ice crystals at the surface. Confirming that the polarized reflectance of snow is spectrally flat would allow to extend the techniques already in use for polarimetric retrievals of aerosol properties over land to the large portion of snow-covered pixels plaguing orbital and suborbital observations.

Polarized BRDF↗

DOE OSTI2020

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Solidification dynamics in metal additive manufacturing: analysis of model assumptions

Solidification characteristics in the meltpool drive the process-microstructure relationship which helps dictate the material properties of as-built parts in additive manufacturing; therefore, being able to accurately and quickly simulate the size, shape, and solidification characteristics in the melt pool is of great interest to the field. In this study, we investigate various important physical phenomena (dynamic material properties, fluid-flow, radiation and vaporization) which can either be included or neglected in a continuum finite volume model (FVM) and their effect on the solidification conditions. Additionally, since the simplest form of such a model (conduction only) has an analytic solution which is much faster, its viability is also considered. Since the inclusion of some of these physical phenomena will inherently change the net energy input as well as the amount of energy needed to achieve melting of a control volume, each set of included phenomena had an effective absorption efficiency which was calibrated to closely match the dimensions of the melt pool to that of the ground truth data. The ground truth data for this study was defined to be the output of the FVM which included all the physical phenomena (OF). This study then goes on to compare the effects on solidification conditions each of these calibrated models has. It was found that most of the change in solidification conditions comes from the inclusion of latent heat. A posterior correlation factor (PCF) is then introduced to enable an analytic model to predict similar solidification conditions to OF model.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Reference Manual for the System Advisor Model's Wind Power Performance Model

This manual describes the National Renewable Energy Laboratory's System Advisor Model (SAM) wind power performance model. The model calculates the hourly electrical output of a single wind turbine or of a wind farm. The wind power performance model requires information about the wind resource, wind turbine specifications, wind farm layout (if applicable), and costs. In SAM, the performance model can be coupled to one of the financial models to calculate economic metrics for residential, commercial, or utility-scale wind projects. This manual describes the algorithms used by the wind power performance model, which is available in the SAM user interface and as part of the SAM Simulation Core (SSC) library, and is intended to supplement the user documentation that comes with the software.

17 WIND ENERGY↗

NASA NTRS2009

Graphical User Interface for Simulink Integrated Performance Analysis Model

The J-2X Engine (built by Pratt & Whitney Rocketdyne,) in the Upper Stage of the Ares I Crew Launch Vehicle, will only start within a certain range of temperature and pressure for Liquid Hydrogen and Liquid Oxygen propellants. The purpose of the Simulink Integrated Performance Analysis Model is to verify that in all reasonable conditions the temperature and pressure of the propellants are within the required J-2X engine start boxes. In order to run the simulation, test variables must be entered at all reasonable values of parameters such as heat leak and mass flow rate. To make this testing process as efficient as possible in order to save the maximum amount of time and money, and to show that the J-2X engine will start when it is required to do so, a graphical user interface (GUI) was created to allow the input of values to be used as parameters in the Simulink Model, without opening or altering the contents of the model. The GUI must allow for test data to come from Microsoft Excel files, allow those values to be edited before testing, place those values into the Simulink Model, and get the output from the Simulink Model. The GUI was built using MATLAB, and will run the Simulink simulation when the Simulate option is activated. After running the simulation, the GUI will construct a new Microsoft Excel file, as well as a MATLAB matrix file, using the output values for each test of the simulation so that they may graphed and compared to other values.

Durham, R. Caitlyn↗

NASA NTRS2012

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Roberts, Yolanda↗

NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗