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NASA NTRS2015

Multi-Level Experimental and Analytical Evaluation of Two Composite Energy Absorbers

Two composite energy absorbers were developed and evaluated at NASA Langley Research Center through multi-level testing and simulation performed under the Transport Rotorcraft Airframe Crash Testbed (TRACT) research program. A conical-shaped energy absorber, designated the conusoid, was evaluated that consisted of four layers of hybrid carbon-Kevlar plain weave fabric oriented at [+45 deg/-45 deg/-45 deg/+45 deg] with respect to the vertical, or crush, direction. A sinusoidal-shaped energy absorber, designated the sinusoid, was developed that consisted of hybrid carbon-Kevlar plain weave fabric face sheets, two layers for each face sheet oriented at +/-45deg with respect to the vertical direction and a closed-cell ELFOAM P200 polyisocyanurate (2.0-lb/cu ft) foam core. The design goal for the energy absorbers was to achieve average floor-level accelerations of between 25- and 40-g during the full-scale crash test of a retrofitted CH-46E helicopter airframe, designated TRACT 2. Variations in both designs were assessed through dynamic crush testing of component specimens. Once the designs were finalized, subfloor beams of each configuration were fabricated and retrofitted into a barrel section of a CH-46E helicopter. A vertical drop test of the barrel section was conducted onto concrete to evaluate the performance of the energy absorbers prior to retrofit into TRACT 2. The retrofitted airframe was crash tested under combined forward and vertical velocity conditions onto soil, which is characterized as a sand/clay mixture. Finite element models were developed of all test articles and simulations were performed using LS-DYNA, a commercial nonlinear explicit transient dynamic finite element code. Test-analysis results are presented for each energy absorber as comparisons of time-history responses, as well as predicted and experimental structural deformations and progressive damage under impact loading for each evaluation level.

Jackson, Karen E.↗
NASA NTRS2014

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Planetary Boundary Layer↗
NASA NTRS2016

Evaluation of Synthetic Vision Display Concepts for Improved Awareness in Unusual Attitude Recovery Scenarios

A recent study conducted by the Commercial Aviation Safety Team (CAST) determined 40 percent of all fixed-wing fatal accidents, between 2001 and 2011, were caused by Loss-of-Control (LOC) in flight (National Transportation Safety Board, 2015). Based on their findings, CAST recommended manufacturers develop and implement virtual day-visual meteorological conditions (VMC) display systems, such as synthetic vision or equivalent systems (CAST, 2016). In a 2015 simulation study conducted at NASA Langley Research Center (LaRC), researchers gathered to test and evaluate virtual day-VMC displays under realistic flight operation scenarios capable of inducing reduced attention states in pilots. Each display concept was evaluated to determine its efficacy to improve attitude awareness. During the experiment, Evaluation Pilots (EPs) were shown the following three display concepts on the Primary Flight Display (PFD): Baseline, Synthetic Vision (SV) with color gradient, and SV with texture. The baseline configuration was a standard, conventional 'blue over brown' display. Experiment scenarios were simulated over water to evaluate Unusual Attitude (UA) recovery over 'featureless terrain' environments. Thus, the SV with color gradient configuration presented a 'blue over blue' display with a linear blue color progression, to differentiate attitude changes between sky and ocean. The SV with texture configuration presented a 'blue over blue' display with a black checkerboard texture atop a synthetic ocean. These displays were paired with a Background Attitude Indicator (BAI) concept. The BAI was presented across all four Head-Down Displays (HDDs), displaying a wide field-of-view blue-over-blue attitude indicator. The BAI aligned with the PFD and showed through the background of the navigation displays with opaque transparency. Each EP participated in a two-part experiment series with a total seventy-five trial runs: Part I included a set of twenty-five Unusual Attitude Recovery (UAR) scenarios; Part II included a set of fifty Attitude Memory Recall Tasks (AMRT). At the conclusion of each trial, EPs were asked to complete a set post-run questionnaires. Quantitative results showed that there were no significant statistical effects on UA recovery times when utilizing SV with or without the presence of a BAI. Qualitative results show the SV displays (color, texture) with BAI On are most preferred for both UA recognition and recovery when compared with the baseline display. When only comparing SV display concepts, EPs performed better when using the SV with texture, BAI On, than any other display configuration. This is an interesting find considering most EPs noted their preference towards the SV with color gradient when the BAI was on.

Nicholas, Stephanie↗
NASA NTRS2016

Evaluation of Mid-Size Male Hybrid III Models for use in Spaceflight Occupant Protection Analysis

In an effort to improve occupant safety during dynamic phases of spaceflight, the National Aeronautics and Space Administration (NASA) has worked to develop occupant protection standards for future crewed spacecraft. One key aspect of these standards is the identification of injury mechanisms through anthropometric test devices (ATDs). Within this analysis, both physical and computational ATD evaluations are required to reasonably encompass the vast range of loading conditions any spaceflight crew may encounter. In this study the accuracy of publically available mid-size male HIII ATD finite element (FE) models are evaluated within applicable loading conditions against extensive sled testing performed on their physical counterparts. Methods: A series of sled tests were performed at the Wright Patterson Air force Base (WPAFB) employing variations of magnitude, duration, and impact direction to encompass the dynamic loading range for expected spaceflight. FE simulations were developed to the specifications of the test setup and driven using measured acceleration profiles. Both fast and detailed FE models of the mid-size male HIII were ran to quantify differences in their accuracy and thus assess the applicability of each within this field. Results: Preliminary results identify the dependence of model accuracy on loading direction, magnitude, and rate. Additionally the accuracy of individual response metrics are shown to vary across each model within evaluated test conditions. Causes for model inaccuracy are identified based on the observed relationships. Discussion: Computational modeling provides an essential component to ATD injury metric evaluation used to ensure the safety of future spaceflight occupants. The assessment of current ATD models lays the groundwork for how these models can be used appropriately in the future. Identification of limitations and possible paths for improvement aid in the development of these effective analysis tools.

Putnam, Jacob B.↗
NASA NTRS2015

Evaluation of Volatile Species in Green Monopropellant Project

NASA is interested in green monopropellants to replace hydrazine in reaction control systems (RCSs). Some current NASA programs require reduced vapor pressure and low toxicity monopropellant (green) and superior performance (specific impulse and density) formulations. Earlier vapor phase studies of a candidate green monopropellant at the NASA White Sands Test Facility (WSTF) showed the presence of a volatile species that warranted further investigation. The purpose of this study was to further characterize the volatile species and to evaluate it. The evaluation was with respect to whether the volatile species was an impurity or how it is formed, and to use that information to examine whether its presence as an impurity can be eliminated during formulation. The evaluation also considered whether formation of the volatile impurity could be prevented while not compromising the propellant. To reduce variables associated with evaluation of the propellant formulation as a whole, a precursor to one of the individual components in the propellant formulation was subjected to a NASA Standard 6001B Flammability, Off-gassing, and Compatibility Requirements and Test Procedures "Determination of Off-gassed Products (Test 7)". Testing took place in the NASA WSTF Molecular Desorption and Analysis Laboratory. One gram of the precursor was placed in a flask within a specimen container. After thermal conditioning for 72 +/- 1 h at 50 +/- 3 deg C (122 +/- 5 deg F), the atmosphere inside the specimen container was analyzed for off-gassed compounds by cryotrap gas chromatography-mass spectrometry (GC-MS) and fixed sample loop GC-flame ionization detection (GC-FID). The specimen container used was glass to minimize potential catalytic surfaces. The identification of compounds was difficult due to the complexity of the vapor phase concentrations and overlapping chromatographic peaks and mass spectra. However, eleven compounds were specifically identified and five compounds or classes of compounds were reported as unidentified. Quantitation of most of the compounds, including unidentified compounds, was as methane. Quantitating compounds or classes of compounds that were detected but for which specific calibration is not established as methane is in accordance with the Test 7 standard protocol. The thermal decomposition temperature of the precursor was significantly higher than the test temperature. Based on thermal decomposition temperature and on an examination of the structure and chemistry of the identified volatile species, the presence of the volatile species appears to be chemically reasonable with respect to the propellant formulation and is at this time attributed to impurities. Further examination of the overall propellant formulation process (including the individual components' synthesis processes) and process quality control (including purity of reagents and possible decomposition reactions) is indicated.

Greene, Benjamin↗
NASA NTRS2017

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

wheat↗
NASA NTRS2016

Evaluation of Mid-Size Male Hybrid III Models for use in Spaceflight Occupant Protection Analysis

Introduction: In an effort to improve occupant safety during dynamic phases of spaceflight, the National Aeronautics and Space Administration (NASA) has worked to develop occupant protection standards for future crewed spacecraft. One key aspect of these standards is the identification of injury mechanisms through anthropometric test devices (ATDs). Within this analysis, both physical and computational ATD evaluations are required to reasonably encompass the vast range of loading conditions any spaceflight crew may encounter. In this study the accuracy of publically available mid-size male HIII ATD finite element (FE) models are evaluated within applicable loading conditions against extensive sled testing performed on their physical counterparts. Methods: A series of sled tests were performed at the Wright Patterson Air force Base (WPAFB) employing variations of magnitude, duration, and impact direction to encompass the dynamic loading range for expected spaceflight. FE simulations were developed to the specifications of the test setup and driven using measured acceleration profiles. Both fast and detailed FE models of the mid-size male HIII were ran to quantify differences in their accuracy and thus assess the applicability of each within this field. Results: Preliminary results identify the dependence of model accuracy on loading direction, magnitude, and rate. Additionally the accuracy of individual response metrics are shown to vary across each model within evaluated test conditions. Causes for model inaccuracy are identified based on the observed relationships. Discussion: Computational modeling provides an essential component to ATD injury metric evaluation used to ensure the safety of future spaceflight occupants. The assessment of current ATD models lays the groundwork for how these models can be used appropriately in the future. Identification of limitations and possible paths for improvement aid in the development of these effective analysis tools.

Putnam, J.↗
NASA NTRS2017

Assessment of Intralaminar Progressive Damage and Failure Analysis Using an Efficient Evaluation Framework

Reducing the timeline for development and certification for composite structures has been a long standing objective of the aerospace industry. This timeline can be further exacerbated when attempting to integrate new fiber-reinforced composite materials due to the large number of testing required at every level of design. computational progressive damage and failure analysis (PDFA) attempts to mitigate this effect; however, new PDFA methods have been slow to be adopted in industry since material model evaluation techniques have not been fully defined. This study presents an efficient evaluation framework which uses a piecewise verification and validation (V&V) approach for PDFA methods. Specifically, the framework is applied to evaluate PDFA research codes within the context of intralaminar damage. Methods are incrementally taken through various V&V exercises specifically tailored to study PDFA intralaminar damage modeling capability. Finally, methods are evaluated against a defined set of success criteria to highlight successes and limitations.

Hyder, Imran↗
NASA NTRS2018

NEPP Evaluation of Automotive Grade Tantalum Chip Capacitors

Automotive grade tantalum (Ta) chip capacitors are available at lower cost with smaller physical size and higher volumetric efficiency compared to military/space grade capacitors. Designers of high reliability aerospace and military systems would like to take advantage of these attributes while maintaining the high standards for long-term reliable operation they are accustomed to when selecting military-qualified established reliability tantalum chip capacitors (e.g., MIL-PRF-55365). The objective for this evaluation was to assess the long-term performance of off-the-shelf automotive grade Ta chip capacitors (i.e., manufacturer self-qualified per AEC Q-200). Two (2) lots of case size D manganese dioxide (MnO2) cathode Ta chip capacitors from 1 manufacturer were evaluated. The evaluation consisted of construction analysis, basic electrical parameter characterization, extended long-term (2000 hours) life testing and some accelerated stress testing. Tests and acceptance criteria were based upon manufacturer datasheets and the Automotive Electronics Council's AEC Q-200 qualification specification for passive electronic components. As-received a few capacitors were marginally above the specified tolerance for capacitance and ESR. X-ray inspection found that the anodes for some devices may not be properly aligned within the molded encapsulation leaving less than 1 mil thickness of the encapsulation. This evaluation found that the long-term life performance of automotive grade Ta chip capacitors is generally within specification limits suggesting these capacitors may be suitable for some space applications.

Automotive↗
NASA NTRS2019

Stress Corrosion Evaluation of Elgiloy Alloy for the ISS ECLSS — Universal Waste Management System

Elgiloy® alloy (UNS R30003)—a spring material per AMS 5876D (reference 1)—is one among several alloys recently evaluated for stress corrosion cracking resistance in support of the International Space Station (ISS) Environmental Control and Life Support System (ECLSS). Elgiloy was evaluated particularly for its expected use in the Universal Waste Management System (described in references 2 and 3). Data for other alloys previously evaluated were reported in references 4 and 5. Materials included in reference 4 are Inconel 625, Hastelloy® C276, commercially pure titanium, titanium with 6% aluminum and 4% vanadium (Ti6Al4V), extra-low interstitial Ti6Al4V, and Cronidur 30. The results for Nitinol 60 are in reference 5. During the water recovery process, the metallic components fabricated from these materials are exposed to acidic solutions used for waste treatment. The purpose of the current and previous stress corrosion evaluations is to determine if these materials have adequate stress corrosion resistance.

Torres, Pablo D.↗
NASA NTRS2020

Application of Remote Sensing for Ex-Ante Decision Support and Evaluating Impact

Deforestation is an environmental stressor that dramatically threatens biodiversity while having adverse, deep-rooted socioeconomic impacts. Interventions to address deforestation require considerable long-term investments; therefore, assessing their impact is crucial. The UN Convention on Biological Diversity encourages establishing Protected Areas (PAs) as a strategy to conserve biodiversity, secure ecosystem services, support local livelihoods, and reduce climate change impacts. The Global Environment Facility (GEF) has supported the conservation and management of PAs, yet site accessibility and data availability present challenges in assessing PAs using traditional evaluation methods. We present a novel application of satellite Earth observations for evaluating the effectiveness and impact of PAs as a deforestation mitigation strategy. Geospatial analysis and ecological forecasting methodologies provide an efficient way to quantify land cover change, estimate above-ground carbon stock, and evaluate ecosystem services provided by the PAs ex-ante. We demonstrate the value of a geospatial approach through evaluation of GEF-supported PAs in Kenya.

Remote sensing↗
NASA NTRS2020

An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation

To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1°×1° daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the 1°×1° grid cells. Up to ∼50 % of the difference between satellite AOD is attributed to cloud contamination. The diversity in AOD products shows clear spatial patterns and varies from 10 % (parts of the ocean) to 100 % (central Asia and Australia). More importantly, we show that the diversity may be used as an indication of AOD uncertainty, at least for the better performing products. This provides modellers with a global map of expected AOD uncertainty in satellite products, allows assessment of products away from AERONET sites, can provide guidance for future AERONET locations and offers suggestions for product improvements. We account for statistical and sampling noise in our analyses. Sampling noise, variations due to the evaluation of different subsets of the data, causes important changes in error metrics. The consequences of this noise term for product evaluation are discussed.

Aerosol↗
NASA NTRS2021

Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions

We present results from an evaluation of precipitable water vapor (W) over remote oceanic areas as derived from global reanalysis models and from satellites against observations from the Maritime Aerosol Network (MAN) for cloudless skies during the period of 2004–2017. They cover polar, mid latitude and tropical oceanic regions and represent a first effort to use MAN observations for such evaluation. The global reanalysis model products evaluated in this study are from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA I), and the Climate Forecast System Reanalysis (CFSR) model. The satellite products evaluated are from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Polarization and Directionality of the Earth's Reflectances (POLDER), the Global Ozone Monitoring Experiment (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and the Atmospheric Infra-red Sounder (AIRS). Satellite retrievals of W are based on the attenuation of solar reflected light by water vapor absorption bands, except those from AIRS that rely on brightness temperature measurements. A very good agreement is observed between the model estimates and MAN, with mean differences of ~5% and standard deviations of ~15%. These results are within the uncertainties associated with the models and the measurements, indicating the skill of the reanalysis models to estimate W over oceans under clear sky conditions. Mean differences of W between the satellite and MAN products are ~11, 6.7, 12, −7, and 3% for MODIS, POLDER, GOME-2, SCIAMACHY and AIRS respectively, while their standard deviations are 31, 29, 28, 20 and 17%. These differences reveal the need to address inconsistencies among different satellite sensors and ground-based measurements to reduce the uncertainties associated with the retrievals.

Daniel Pérez-Ramírez↗
NASA NTRSDate not supplied

Evaluation of Near Singular Integrals for Computational Electromagnetics by Dimensionality Reduction

With the need for ever faster codes, a limiting factor that must be dealt with is the accurate yet efficient evaluation of interaction integrals between the more problematic near-field elements. Several recent works have together shown that all evaluations of source potential integrals and their derivatives for the most common bases and elements can be reduced to the evaluation of boundary line integrals; these can be evaluated by Gauss-Legendre quadrature, though integrand-smoothing transforms are often needed to accelerate their computation. In this paper, we modify the reported approach to eliminate cancellation errors in the line integral integrand, reinterpret the integral as a vertex function, and study the scalar potential integral form under the sinh transform and static subtraction acceleration methods.

D R Wilton↗
NASA NTRSDate not supplied

Evaluating Microgreens Crop Readiness for Space Production

Microgreens are small-size, nutrient-rich, and fast-grown crops, which are considered as candidates for future space exploration missions. In particular, the ISS, the Lunar Gateway, and Mars and Lunar missions could benefit from growing microgreens to supplement astronaut diets in the near future. Research at NASA’s Kennedy Space Center has focused on (1) the selection of microgreens compatible species, (2) the evaluation of microgreens food safety, (3) the use of passive wicking, on-demand watering, and hydroponics cultivation, (4) simulated microgravity growth, (5) microgreen canopy gas exchange, and (6) harvesting techniques in microgravity. This interactive presentation summarizes this research. Microgreen species will be evaluated for their yield in relationship to the quantity of inputs – water, seeds, substrate, light intensity, photoperiod, crew time – required for their growth; for their organoleptic and sensory factors in order to down select species that are highly acceptable for humans; and for their microbial loads as detected in their growth environment and the food safety metrics of their edible tissue. Passive wicking, on-demand watering, and hydroponic systems are being studied as an efficient way to deliver essential nutrients and water to microgreens, included in a microgravity environment. Growth studies in simulated microgravity (using 3-dimensional clinostats) will assess microgreens growth relative to that in 1g. Gas exchange studies on microgreens canopies in various airflows will assess their photosynthesis and transpiration. Finally, a series of parabolic flights has enabled the evaluation of different harvesting and bagging techniques in microgravity. Indeed, traditional plant harvesting methods (scissors) in microgravity could generate significant microgreen debris in the space station cabin. Two innovative techniques, coupled to a dedicated bagging method, were designed and evaluated against the control, traditional, harvesting technique. This research was supported by grants from NASA KSC’s Independent Research and Technology Development Program, NASA’s Flight Opportunity Program, NASA Postdoctoral Program Fellowships (L.P. & C.J.) supported by NASA’s Space Biology program, and support from NASA’s Human Research Program.

Space Crop Production↗
NASA NTRS2021

Evaluation and Intercomparison of Wildfire Smoke Forecasts from Multiple Modeling Systems for the 2019 Williams Flats Fire

Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center's Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper, with a day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.

AOD↗
NASA NTRS2022

Evaluation of GPROF V05 Precipitation Retrievals under Different Cloud Regimes

Precipitation retrievals from passive microwave satellite observations form the basis of many widely used precipitation products, but the performance of the retrievals depends on numerous factors such as surface type and precipitation variability. Previous evaluation efforts have identified bias dependence on precipitation regime, which may reflect the influence on retrievals of recurring factors. In this study, the concept of a regime-based evaluation of precipitation from the Goddard profiling (GPROF) algorithm is extended to cloud regimes. Specifically, GPROF V05 precipitation retrievals under four different cloud regimes are evaluated against ground radars over the United States. GPROF is generally able to accurately retrieve the precipitation associated with both organized convection and less organized storms, which collectively produce a substantial fraction of global precipitation. However, precipitation from stratocumulus systems is underestimated over land and overestimated over water. Similarly, precipitation associated with trade cumulus environments is underestimated over land, while biases over water depend on the sensor’s channel configuration. By extending the evaluation to more sensors and suppressed environments, these results complement insights previously obtained from precipitation regimes, thus demonstrating the potential of cloud regimes in categorizing the global atmosphere into discrete systems.

precipitation↗
NASA NTRS2022

Model Evaluation of Short-Lived Climate Forcers for the Arctic Monitoring and Assessment Programme: A Multi-Species, Multi-Model Study

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008-2009 and 2014-2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, 03, BC, and SO(sup 2-)(sub 4)), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for C"4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

Arctic Monitoring and Assessment Programme↗