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All-Sky Microwave Imager Data Assimilation at NASA GMAO

Efforts in all-sky satellite data assimilation at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center have been focused on the development of GSI configurations to assimilate all-sky data from microwave imagers such as the GPM Microwave Imager (GMI) and Global Change Observation Mission-Water (GCOM-W) Advanced Microwave Scanning Radiometer 2 (AMSR-2). Electromagnetic characteristics associated with their wavelengths allow microwave imager data to be relatively transparent to atmospheric gases and thin ice clouds, and highly sensitive to precipitation. Therefore, GMAOs all-sky data assimilation efforts are primarily focused on utilizing these data in precipitating regions. The all-sky framework being tested at GMAO employs the GSI in a hybrid 4D-EnVar configuration of the Goddard Earth Observing System (GEOS) data assimilation system, which will be included in the next formal update of GEOS. This article provides an overview of the development of all-sky radiance assimilation in GEOS, including some performance metrics. In addition, various projects underway at GMAO designed to enhance the all-sky implementation will be introduced.

NWP↗

The atmosphere as a research window - Signal or noise

The interpretation of measurements by instruments with FOV that are large enough to contain pronounced radiometric variations is discussed, focusing on the retrieval of cloud properties from satellite radiance measurements. Examples are presented for three retrieval approaches. The use of a physical principle to establish a relationship between the measurement and the desired parameter is shown for cirrus-cloud optical depth and precipitation from passive microwave measurements. Examples of the use of inherent variability of the atmosphere and the statistical character of this variability are the spatial covariance method and the threshold method. Also, two examples using a hybrid of these two methods are presented. It is shown that the natural variability (noise) within the instrument FOV biases the relationship between the measurement and the parameter of interest which would be predicted by simple one-dimensional radiative-transfer theory. It is suggested that the noise of the measurement also contains signal, forming the basis for hybrid methods.

Stephens, Graeme L.↗

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗

Laboratory simulation of cometary neutral gas ionization

The laboratory simulation of the interaction of the solar wind with a comet is used to study the cometary neural gas ionization. The experiment is carried out in the UCR T-1 facility with an ice ball as the comet model. Photographs and data are taken with a variety of values of the solar wind velocity, interplanetary magnetic field (IMF), and comet configurations. The results show that the cometary neutral gas ionization depends on both the velocity of the solar wind and the interplanetary magnetic field. The plasma cloud surrounding the comet is visible only when the solar wind velocity and IMF are both above certain minimum values. This velocity dependent phenomena is explained by Alfven's critical ionization velocity effect. The critical magnetic field may be explained by assuming two stream lower hybrid instability as a triggering mechanism for the ionization of the neutral gas by plasma flow. Critical upper and lower limits for the magnetic field, required by anomalous ionization, are also derived that satisfy the experimental observations.

Chang, Tsuey-Fen↗

Ice Accretion Roughness Variations on a Hybrid CRM65-Midspan Wing Model

Ice accretion roughness measurements were performed in the Icing Research Tunnel (IRT) at NASA Glenn Research Center for the Hybrid CRM65-Midspan model in a range of icing conditions. The Hybrid CRM65-Midspan model was chosen for this investigation because 1) the model exhibits high sweep relative to models previously explored in the roughness investigations, 2) the model has leading edge characteristics similar to wing shapes currently used in mid-size commercial airliners, and 3) the sweep and thickness ratios relate better to hybrid lifting body designs for N+2 and N+3 vehicles than other models available. The investigation consisted of multiple sets of tests which focused on 1) 0-angle of attack cases replicating the conditions employed by Anderson et al. (1998) using both Appendix C and SLD cloud conditions, 2) cases based on the “Max Scallop” case by Broeren et al. (2016) and a “High Temperature” case with cloud properties similar to the “Max Scallop” case. Additional tests were performed 1) based on the “Max Scallop” case with variations in freestream static temperature and 2) using test section speeds near 10,000-hold flight conditions. The point clouds were characterized using the approach of McClain and Kreeger (2013) for the ice roughness variations and using the approach of McClain (2016) for the mean ice thickness variations. The resulting roughness and mean thickness variations generally follow the temporal scaling previously identified using on airfoil models without sweep, but the collapse of the time progression profiles is not as tight as found for past measurements on models without sweep. LEWICE and modified panel-method predictions were used explore spatial roughness variations and to compare to the roughness correlations developed by McClain et al. (2021) for the “Max Scallop” cases.

Icing↗

The International Space Station, Optical Communications, and Delay Tolerant Networking: Towards A Solar System Internet Architecture

As Delay Tolerant Networking (DTN) matures as a software product its use cases have extended to infrastructural and architectural studies, bringing DTN closer to a widespread, operational technology. While it is known that a DTN can be configured, given complete information about a system of nodes, to provision a system with a complete network capability, what remains is to tackle practical considerations such as scalability, networking best practices, and how to establish service providers. In this paper, we document progress towards a scalable DTN architecture that was tested across multiple organizational and project boundaries; our approach was tested across nodes flying on the International Space Station (ISS) connected to a ground network. The network consists of four main network areas: the ISS, the White Sands Complex (WSC), the Mission Cloud Platform (MCP), and NASA’s Huntsville Operations Support Center (HOSC). The connections on the ground (WSC, MCP, and HOSC) are straightforward technically, but represent administrative and non-technical challenges that had to be overcome. The connection from the ISS to WSC was realized through a hybrid optical/RF means. In particular, NASA’s Integrated Laser Communications Relay Demonstration (LCRD) can form a relay from lowEarth-orbit (LEO) to the Earth, and was used in conjunction with the LCRD LEO User Modem and Amplifier Terminal (ILLUMA-T) on the ISS to form a link to one of three geographically diverse ground stations. A major goal was to achieve communications while keeping the ISS nodes unaware of ground station choices and scheduling. These disparate links were networked using High-rate DTN (HDTN), which enabled the desired architecture. The network architecture, tests, HDTN performance metrics, and general observations made are all discussed in detail, including a discussion on the successful utilization of the DTN security standard known as DTN Bundle Protocol Security (BPSec). We conclude with suggestions for next steps, and in particular focus on extending this architecture to the Near Space Network (NSN) and the upcoming LunaNet.

Alan Hylton↗

A Massively Parallel Hybrid Dusty-Gasdynamics and Kinetic Direct Simulation Monte Carlo Model for Planetary Applications

In order to understand the global structure, dynamics, and physical and chemical processes occurring in the upper atmospheres, exospheres, and ionospheres of the Earth, the other planets, comets and planetary satellites and their interactions with their outer particles and fields environs, it is often necessary to address the fundamentally non-equilibrium aspects of the physical environment. These are regions where complex chemistry, energetics, and electromagnetic field influences are important. Traditional approaches are based largely on hydrodynamic or magnetohydrodynamic (MHD) formulations and are very important and highly useful. However, these methods often have limitations in rarefied physical regimes where the molecular collision rates and ion gyrofrequencies are small and where interactions with ionospheres and upper neutral atmospheres are important. At the University of Michigan we have an established base of experience and expertise in numerical simulations based on particle codes which address these physical regimes. The Principal Investigator, Dr. Michael Combi, has over 20 years of experience in the development of particle-kinetic and hybrid kinetichydrodynamics models and their direct use in data analysis. He has also worked in ground-based and space-based remote observational work and on spacecraft instrument teams. His research has involved studies of cometary atmospheres and ionospheres and their interaction with the solar wind, the neutral gas clouds escaping from Jupiter s moon Io, the interaction of the atmospheres/ionospheres of Io and Europa with Jupiter s corotating magnetosphere, as well as Earth s ionosphere. This report describes our progress during the year. The contained in section 2 of this report will serve as the basis of a paper describing the method and its application to the cometary coma that will be continued under a research and analysis grant that supports various applications of theoretical comet models to understanding the inner comae of comets (grant NAGS- 13239 from the Planetary Atmospheres program).

Combi, Michael R.↗

Fuzzy set methods for object recognition in space applications

Progress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.

Keller, James M.↗

High Precision Sunphotometer using Wide Dynamic Range (WDR) Camera Tracking

The NASA Ames Sun-photometer-Satellite Group, DOE, PNNL Atmospheric Sciences and Global Change Division, and NASA Goddards AERONET (AErosol RObotic NETwork) team recently collaborated on the development of a new airborne sunphotometry instrument that provides information on gases and aerosols extending far beyond what can be derived from discrete-channel direct-beam measurements, while preserving or enhancing many of the desirable AATS features (e.g., compactness, versatility, automation, reliability). The enhanced instrument combines the sun-tracking ability of the current 14-Channel NASA Ames AATS-14 with the sky-scanning ability of the ground-based AERONET Sunsky photometers, while extending both AATS-14 and AERONET capabilities by providing full spectral information from the UV (350 nm) to the SWIR (1,700 nm). Strengths of this measurement approach include many more wavelengths (isolated from gas absorption features) that may be used to characterize aerosols and detailed (oversampled) measurements of the absorption features of specific gas constituents. The Sky Scanning Sun Tracking Airborne Radiometer (3STAR) replicates the radiometer functionality of the AATS14 instrument but incorporates modern COTS technologies for all instruments subsystems. A 19-channel radiometer bundle design is borrowed from a commercial water column radiance instrument manufactured by Biospherical Instruments of San Diego California (ref, Morrow and Hooker)) and developed using NASA funds under the Small Business Innovative Research (SBIR) program. The 3STAR design also incorporates the latest in robotic motor technology embodied in Rotary actuators from Oriental motor Corp. having better than 15 arc seconds of positioning accuracy. Control system was designed, tested and simulated using a Hybrid-Dynamical modeling methodology. The design also replaces the classic quadrant detector tracking sensor with a wide dynamic range camera that provides a high precision solar position tracking signal as well as an image of the sky in the 45 field of view around the solar axis, which can be of great assistance in flagging data for cloud effects or other factors that might impact data quality.

aerosols↗

Spectral Gap Filling Method Using the Spectral Information from CLARREO-Pathfinder Measured Earth-Reflected Solar Spectra to Support CPF-CERES Intercalibration

The high-accuracy Earth-reflected solar spectral radiances from CLARREO Pathfinder (CPF) will serve as in-orbit benchmark measurements for intercalibrating other satellite imagers. The CPF team is developing a state-of-the-art intercalibration method to calibrate the shortwave channel (300-5000 nm) of the CERES instrument against the CPF reference with an uncertainty of 0.3%. Because the CPF instrument only covers spectral range from 350 nm to 2300 nm, the team has developed a spectral extension method to fill in the gaps between the spectral domains of CPF and the CERES shortwave channel. The method solely relies on using the hyperspectral information from the CPF wavelengths to predict the radiances below 350 nm and above 2300 nm. To quantify the relationship between the CPF spectrum and the non-overlapping portions of the spectrum between CPF and CERES, the team has simulated a large ensemble of spectra that cover the spectral range for both CPF and CERES. A hyperspectral bidirectional reflectance model for land surface based on thousands of measured land surface reflectance has been developed. This land surface model as well as the Cox-Munk model for ocean surface are used in the spectral gap filling. Various water/ice clouds, aerosols, atmosphere profiles and surfaces were used to simulate Earth-reflected radiances from 200 nm to 15 um under different solar and sensor geometries. The targeted uncertainty for the CPF-extended broadband CERES radiances is less than 0.1%. The previously derived training spectra were updated to replace the Kurucz solar irradiance model with the TSIS-1 Hybrid Solar Reference Spectrum. The influence of the scalar assumption in radiative transfer model equations on the uncertainty in estimating the broadband radiances was also investigated.

Hyperspectral↗

Validating Salinity from SMAP and HYCOM Data with Saildrone Data during EUREC4A-OA/ATOMIC

The 2020 ‘Elucidating the role of clouds-circulation coupling in climate-Ocean-Atmosphere’ (EUREC4A-OA) and the ‘Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign’ (ATOMIC) campaigns focused on improving our understanding of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign utilized many data collection technologies, some of which are relatively new. In this study, we used saildrone uncrewed surface vehicles, one of the newer cutting edge technologies available for marine data collection, to validate Level 2 and Level 3 Soil Moisture Active Passive (SMAP) satellite and Hybrid Coordinate Ocean Model (HYCOM) sea surface salinity (SSS) products in the Western Tropical Atlantic. The saildrones observed fine-scale salinity variability not present in the lower-spatial resolution satellite and model products. In regions that lacked significant small-scale salinity variability, the satellite and model salinities performed well. However, SMAP Remote Sensing Systems (RSS) 70 km generally outperformed its counterparts outside of areas with submesoscale SSS variation, whereas RSS 40 km performed better within freshening events such as a fresh tongue. HYCOM failed to detect the fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product and its drawbacks for their applications in this region and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

Kashawn Hall↗

Modeling the Lunar Wake Response to a CME Using a Hybrid PIC Model

In the solar wind, a low-density wake region forms downstream of the nightside lunar surface. In this study, we use a series of 3D hybrid particle-in-cell simulations to model the response of the lunar wake to a passing coronal mass ejection (CME). Average plasma parameters are derived from the Wind spacecraft located at 1 au during three distinct phases of a passing halo (Earth-directed) CME on 2015 June 22. Each set of plasma parameters, representing the shock/plasma sheath, a magnetic cloud, and plasma conditions we call the mid-CME phase, are used as the time-static upstream boundary conditions for three separate simulations. These simulation results are then compared with results that use nominal solar wind conditions. Results show a shortened plasma void compared to nominal conditions and a distinctive rarefaction cone originating from the terminator during the CME's plasma sheath phase, while a highly elongated plasma void reforms during the magnetic cloud and mid-CME phases. Developments of electric and magnetic field intensification are also observed during the plasma sheath phase along the central wake, while electrostatic turbulence dominates along the plasma void boundaries and 2–3 lunar radii RM downstream in the central wake during the magnetic cloud and mid-CME phases. The simulations demonstrate that the lunar wake responds in a dynamic way with the changes in the upstream solar wind during a CME.

Anthony P. Rasca↗

Future hybrid infrared and microwave satellite sounding system - A theoretical analysis of its capability

The expected atmospheric sounding accuracy and the vertical resolution performance of the sounding system selected by NASA to fly aboard the Earth Observing System polar platform, the Atmospheric Infrared Sounder combined with the Advanced Microwave Sounding Unit, are evaluated under various weather conditions. The performance of the combined system is compared to that of current polar orbiting systems. The complementary nature of the IR component provides high vertical resolution, and the microwave information permits sounding through nonprecipitating clouds.

Huang, H.-L.↗

Connecting Users and Applications with Po.daac Hosted GHRSST Data

The 80+ GHRSST public datasets represent a rich resource for sea surface temperature research and applications given their time series length, resolution, spatial coverage, varying measurement types and processing levels, and availability in the full spectrum of PO.DAAC tools and services ecosystem. The PO.DAAC has created a publicly accessible recipe suite for the user community to perform straightforward yet powerful computations on GHRSST data using python recipes, Jupyter notebooks, R, Matlab, and the NCO programming language. These recipes include numerical computations for regional and global SST trends, anomaly derivations, EOF analysis, climate signal reproduction, and ocean phenology. For example, one recipe reproduces a famous SST based warming figure from the Fourth National Climate Assessment (USA) while another focuses on quantifying the regional changes in ocean SST phenology. Most are python-based while some contain hybrid calls and leverage the NCO programming interface too. All are available on the PO.DAAC user forum (https://podaac.jpl.nasa.gov/forum/) and/or via the open source NASA GitHub repository (https://github.com/nasa/podaac_tools_and_services). Several are available in the Jupyter notebook framework including podaacypy (https://github.com/nasa/podaacpy), a recipe for GHRSST granule metadata discovery and application, and more recently a Jupyter notebook developed to support data analysis and visualization of a cloud-based Zarr formatted Level 4 MUR dataset in the AWS Open Data Registry. Throughout the summer of 2020, the PO.DAAC intends to add and migrate more of its numerical recipes to the Jupyter notebook framework and publish them on its open source GitHub repository.

Gentemann, Chelle↗

A diagnostic study of vertical fluxes in cumulus clouds using model output data

Midlatitude supercell, Florida sea-breeze convection, and tropical squall line simulations were performed using the Colorado State University Regional Atmospheric Modeling System which employed the non-hydrostatic, fully compressible, equations with parameterized microphysics. The time evolution of the vertical velocity variance (VVV) is especially interesting since it is a measure of the strength of convection. This variance exhibits striking similarities when analyzed for the aforementioned cases which may indicate that all convection is fundamentally similar. Vertical mass and moisture covariances appear strongly linked to VVV, so it may be the appropriate variable on which to base a hybrid cumulus parameterization scheme.

Weissbluth, M. J.↗

Expanding SPoRT RGBs and Machine Learning Techniques to Enhance Air Quality Monitoring in Southern Asia

Air pollution poses significant environmental, public health, and societal concerns in the Hindu Kush Himalaya (HKH) region of south-central Asia, notably during the dry monsoon months (~November to May). Key contributors to poor air quality include dust from the Middle East and western India, persistent nocturnal fog/smog, and biomass burning. To address this issue, we established a robust air quality and chemistry observation and modeling product suite utilizing multi-spectral red-green-blue (RGB) composite satellite products from Korea’s GEO-KOMPSAT-2A satellite, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model for dust transport forecasts, and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model to predict aerosols and chemical species concentrations. Our team employed similar RGB recipes transitioned by the NASA Short-term Prediction Research and Transition (SPoRT) Center for the GOES-R era products over the Western Hemisphere, with significant success in depicting dust and nocturnal fog / low clouds, and to a lesser extent smoke and fire hot spots. We will extend these capabilities for the HKH region by applying an artificial intelligence (AI) model that objectively identifies dust from multi-spectral satellite data over the Southwestern United States. The AI model will be calibrated for automated dust detection over HKH from GEO-KOMPSAT-2A satellite data, with a goal of developing a similar AI model for objectively identifying smoke as well. The ultimate goal of this effort is to enhance dust and smoke predictions in the region by establishing improved emission initializations in HYSPLIT and/or WRF-Chem through the automated AI detection of dust and smoke.

Jonathan L. Case↗

Improving the Use of Surface-Sensitive Radiances in the GMAO Hybrid-4DEnVar System

The planetary boundary layer (PBL) was designated as an incubation-class targeted observable (TO) in the 2018 Decadal Survey. As no single instrument source will provide enough information to constrain the global PBL, the assimilation of a wide range of observations in data assimilation (DA) systems will play a critical role, and GMAO has put in efforts to enhance surface-sensitive radiance assimilation. Although a vast number of microwave radiance observations are used in the GEOS global DA system, very few surface-sensitive radiances are currently used over land due to large uncertainty of land surface emissivity in the CRTM as well as cloud detection issue. Dynamically varying emissivity is retrieved from observations of window channels in the GEOS system for non-scattering FOVs and applied to sounding channel assimilation. Moreover, the original radiance bias correction is found not to work well over land, and shows drifting bias when the original emissivity sensitivity bias predictor with a dynamically varying emissivity retrieval is used. Hence, the radiance bias correction has been modified, and the quality control procedure has been adapted accordingly. Cycled experiment results show improvement in the temperature forecast at lower model levels; further refinement of this system continues.

Yanqiu Zhu↗

Recent Advances in Discrete Crack Modeling Applied to Laminated Composites with Emphasis on: Floating Node Method, VCCT and Cohesive Zone Modeling

The present talk will provide an overview of the work performed during the Advanced Composites Project (ACP) on the development, and verification and validation of the Floating Node Method (FNM) as well as the Virtual Crack Closure Technique (VCCT) and cohesive zone modeling (CZM). The FNM is a finite element-based technique to represent crack networks. The complex nature of matrix crack-delamination interactions observed in unidirectional (UD) tape laminates suggests that a methodology such as the FNM method may be required to be able to accurately simulate damage progression in these laminates. Simulating crack onset and growth within the context of the FNM relies on techniques such as VCCT and CZM. The talk is organized to provide, via select examples, an overview of the breadth of the Verification & Validation (V&V) exercises performed during the ACP, and how these challenged the state-of-the art and guided further developments in discrete crack modeling, while helping to establish confidence in the progress made and map the challenges ahead. The performance of the VCCT and CZM individually, and in combination with the FNM can be assessed through verification exercises. These exercises typically consist of a comparison of simulation results to known numerical or analytical solutions. Verification is key to identify implementation issues and limitations that, otherwise, may remain undetected and cloud any subsequent validation efforts. Indeed, a subset of these numerical exercises led to further developments of the VCCT and the FNM method as will be illustrated. Before embarking on the subsequent validation of the framework, it is critical to have adequate characterization data. However, the testing campaign conducted revealed material responses that challenged the state-of-the-art and required further developments. The developments in CZM technology associated with the modeling of the responses of hybrid interfaces (fabric/UD) will be given as an example. Finally, the talk will conclude with a summary of the validation exercises performed under quasi-static and fatigue loadings, highlighting some of the key achievements, outstanding challenges and lessons learned.

finite elements↗