SEARCH · Search NASA

Results for “Additive Process Modeling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

NASA NTRS2008

Spiking Neurons for Analysis of Patterns

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Huntsberger, Terrance↗

NASA NTRS1996

Process Model for Friction Stir Welding

Friction stir welding (FSW) is a relatively new process being applied for joining of metal alloys. The process was initially developed by The Welding Institute (TWI) in Cambridge, UK. The FSW process is being investigated at NASA/MSEC as a repair/initial weld procedure for fabrication of the super-light-weight aluminum-lithium shuttle external tank. The FSW investigations at MSFC were conducted on a horizontal mill to produce butt welds of flat plate material. The weldment plates are butted together and fixed to a backing plate on the mill bed. A pin tool is placed into the tool holder of the mill spindle and rotated at approximately 400 rpm. The pin tool is then plunged into the plates such that the center of the probe lies at, one end of the line of contact, between the plates and the shoulder of the pin tool penetrates the top surface of the weldment. The weld is produced by traversing the tool along the line of contact between the plates. A lead angle allows the leading edge of the shoulder to remain above the top surface of the plate. The work presented here is the first attempt at modeling a complex phenomenon. The mechanical aspects of conducting the weld process are easily defined and the process itself is controlled by relatively few input parameters. However, in the region of the weld, plasticizing and forging of the parent material occurs. These are difficult processes to model. The model presented here addresses only variations in the radial dimension outward from the pin tool axis. Examinations of the grain structure of the weld reveal that a considerable amount of material deformation also occurs in the direction parallel to the pin tool axis of rotation, through the material thickness. In addition, measurements of the axial load on the pin tool demonstrate that the forging affect of the pin tool shoulder is an important process phenomenon. Therefore, the model needs to be expanded to account for the deformations through the material thickness and the forging affect of the shoulder. The energy balance at the boundary of the plastic region with the environment required that energy flow away from the boundary in both radial directions. One resolution to this problem may be to introduce a time dependency into the process model, allowing the energy flow to oscillate across this boundary. Finally, experimental measurements are needed to verify the concepts used here and to aid in improving the model.

Adams, Glynn↗

NASA NTRS1991

Plasma contactor research, 1990

Emissive and Langmuir probes were used to measure plasma potential profiles, plasma densities, electron energy distributions, and plasma noise levels near a hollow cathode-based plasma contactor emitting electrons. The effects of electron emission current (100 to 1500 mA) and contactor flowrate (2 to 10 sccm (Xenon)) on these data are examined. Retarding potential analyzer (RPA) measurements showing that high energy ions generally stream from a contactor along with the electrons being emitted are also presented, and a mechanism by which this occurs is postulated. This mechanism, which involves a high rate of ionization induced between electrons and atoms flowing together from the hollow cathode orifice, results in a region of high positive space charge and high positive potential. Langmuir and RPA probe data suggests that both electrons and ions expand spherically from this potential hill region. In addition to experimental observations, a simple one-dimensional model which describes the electron emission process and predicts the phenomena just mentioned is presented and is shown to agree qualitatively with these observations. Experimental results of the first stage of bilateral cooperation with the Italian Institute of Interplanetary Space Physics (IFSI CNR) are presented. Sharp, well-defined double layers were observed downstream of a contactor collecting electrons from an ambient plasma created in the IFSI Facility. The voltage drop across these double layers was observed to increase with the current drawn from the ambient plasma. This observation, which was not as clear in previous IFSI tests conducted at higher neutral pressures, is in agreement with previous experimental observations made at both Colorado State University and NASA Lewis Research Center. Greater double layer voltage drops, multiple double layers, and higher noise levels in the region near the double layers were also observed when a magnetic field was imposed and oriented perpendicular to the line joining the contactor and simulator.

Williams, John D.↗

NASA NTRS1993

Three-dimensional modeling of diesel engine intake flow, combustion and emissions-2

A three-dimensional computer code, KIVA, is being modified to include state-of-the-art submodels for diesel engine flow and combustion. Improved and/or new submodels which have already been implemented and previously reported are: wall heat transfer with unsteadiness and compressibility, laminar-turbulent characteristic time combustion with unburned HC and Zeldo'vich NO(x), and spray/wall impingement with rebounding and sliding drops. Progress on the implementation of improved spray drop drag and drop breakup models, the formulation and testing of a multistep kinetics ignition model, and preliminary soot modeling results are described. In addition, the use of a block structured version of KIVA to model the intake flow process is described. A grid generation scheme was developed for modeling realistic (complex) engine geometries, and computations were made of intake flow in the ports and combustion chamber of a two-intake-value engine. The research also involves the use of the code to assess the effects of subprocesses on diesel engine performance. The accuracy of the predictions is being tested by comparisons with engine experiments. To date, comparisons were made with measured engine cylinder pressure, temperature and heat flux data, and the model results are in good agreement with the experiments. Work is in progress that will allow validation of in-cylinder flow and soot formation predictions. An engine test facility is described that is being used to provide the needed validation data. Test results were obtained showing the effect of injection rate and split injections on engine performance and emissions.

Reitz, R. D.↗

NASA NTRS2003

Monte Carlo Methodology Serves Up a Software Success

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Source record↗

NASA NTRS2006

Effects of Vegetation and of Heat and Vapor Fluxes from Soil on Snowpack Evolution and Radiobrightness

The radiobrightness of a snowpack is strongly linked to the snow moisture content profile, to the point that the only operational inversion algorithms require dry snow. Forward dynamic models do not include the effects of freezing and thawing of the soil beneath the snowpack and the effect of vegetation within the snow or above the snow. To get a more realistic description of the evolution of the snowpack, we reported an addition to the Snow-Soil-Vegetation-Atmosphere- Transfer (SSVAT) model, wherein we coupled soil processes of the Land Surface Process (LSP) model with the snow model SNTHERM. In the near future we will be adding a radiobrightness prediction based on the modeled moisture, temperature and snow grain size profiles. The initial investigations with this SSVAT for a late winter and early spring snow pack indicate that soil processes warm the snowpack and the soil. Vapor diffusion needs to be considered whenever the ground is thawed. In the early spring, heat flow from the ground into a snow and a strong temperature gradient across the snow lead to thermal convection. The buried vegetation can be ignored for a late winter snow pack. The warmer surface snow temperature will affect radiobrightness since it is most sensitive to snow surface characteristics. Comparison to data shows that SSVAT provides a more realistic representation of the temperature and moisture profiles in the snowpack and its underlying soil than SNTHERM. The radiobrightness module will be optimized for the prediction of brightness when the snow is moist. The liquid water content of snow causes considerable absorption compared to dry snow, and so longer wavelengths are likely to be most revealing as to the state of a moist snowpack. For volumetric moisture contents below about 7% (the pendular regime), the water forms rings around the contact points between snow grains. Electrostatic modeling of these pendular rings shows that the absorption of these rings is significantly higher than a sphere of the same volume. The first implementation of the radiobrightness module will therefore be a simple radiative transfer model without scattering.

soil↗

NASA NTRS2004

Software for Checking Statecharts

HiVy is a software tool set that enables verification through model checking of designs represented as finite-state machines or statecharts. HiVy provides automated translation of (1) statecharts created by use of the MathWorks Stateflow program to (2) Promela, the input language of the Spin model checker, which can then be used to verify, or trace logical errors in, distributed software systems. HiVy can operate directly on Stateflow models, or its abstract syntax of hierarchical sequential automata (HSA) can be used independently as an intermediate format for translation to Promela. In a typical design application, HiVy parses and reformats Stateflow model file data using the programs SfParse and sf2hsa, respectively. If the parsing effort is successful, an abstract syntax tree is delivered into a file named with the extension .hsa. If the design comprises several model files, they may be merged into one .hsa file before translation into Promela. Stateflow scope is preserved, and name clashes are avoided in the merge process. The HiVy program hsa2pr translates the model from the intermediate HSA format into Promela. Additionally, HiVy provides through translation a list of all statechart model propositions that are the means for formalizing linear temporal logic (LTL) properties about the model for Spin verification.

Pingree, Paula↗

NASA NTRS2012

Parameterization of Aerosol Sinks in Chemical Transport Models

The modelers point of view is that the aerosol problem is one of sources, evolution, and sinks. Relative to evolution and sink processes, enormous attention is given to the problem of aerosols sources, whether inventory based (e.g., fossil fuel emissions) or dynamic (e.g., dust, sea salt, biomass burning). On the other hand, aerosol losses in models are a major factor in controlling the aerosol distribution and lifetime. Here we shine some light on how aerosol sinks are treated in modern chemical transport models. We discuss the mechanisms of dry and wet loss processes and the parameterizations for those processes in a single model (GEOS-5). We survey the literature of other modeling studies. We additionally compare the budgets of aerosol losses in several of the ICAP models.

Colarco, Peter↗

NASA NTRS2020

Passive Aeroelastic Tailored Wing Modal Test Using the Fixed Base Correction Method

In modal testing and finite element model correlation, analysts desire modal results using free-free or rigid boundary conditions to ease comparisons of test versus analytical data. It is often expensive both in cost and schedule to build and test with boundary conditions that replicate the free-free or rigid boundaries. Static test fixtures for load testing are often large, heavy, and unyielding, but do not provide adequate boundaries for modal tests because they are dynamically too flexible and often contain natural frequencies within the frequency range of interest of the test article. Dynamic coupling between the test article and test fixture complicates the model updating process because significant effort is required to model the test fixture and boundary conditions in addition to the test article. If there were a way to correct the modal results for fixture coupling, then setups used for other structural testing could be adequate for modal testing. In the case described in this paper, a partial static loads testing setup was used, which allowed significant schedule and cost savings by eliminating a unique setup for a modal test. A fixed base correction technique was investigated during modal testing of a flexible wing cantilevered from part of a static test fixture. The technique was successfully used to measure the wing modes de-coupled from the dynamically active test fixture. The technique is promising for future aircraft applications, but more research is needed.

structural dynamics↗

NASA NTRS2019

Design of an Automated Ultrasonic Scanning System for In-Situ Composite Cure Monitoring and Defect Detection

The preliminary design and development of an automated ultrasonic scanning system for in-situ composite cure monitoring and defect detection in the high temperature environment of an oven was completed. This preliminary design is a stepping stone to deployment in the high temperature and high pressure environment of an autoclave, the primary cure method of aerospace grade thermoset composites. Cure monitoring with real-time defect detection during the process could determine when defects form and how they move. In addition, real-time defect detection during cure could assist validating physics-based process models for predicting defects at all stages of the cure cycle. A physics-based process model for predicting porosity and fiber waviness originating during cure is currently under development by the NASA Advanced Composites Project (ACP). For the design, an ultrasonic contact scanner is enclosed in an insulating box that is placed inside an oven during cure. Throughout the cure cycle, the box is nitrogen-cooled to approximately room temperature to maintain a standard operating environment for the scanner. The composite part is mounted on the outside of the box in a vacuum bag on the build/tool plate. The build plate is attached to the bottom surface of the box. The scanner inspects the composite panel through the build plate, tracking the movement of defects introduced during layup and searching for new defects that may form during cure. The focus of this paper is the evaluation and selection of the build plate material and thickness. The selection was based on the required operating temperature of the scanner, the cure temperature of the composite material, thermal conductivity models of the candidate build plates, and a series of ultrasonic attenuation tests. This analysis led to the determination that a 63.5 mm thick build plate of borosilicate glass would be utilized for the system. The borosilicate glass plate was selected as the build plate material due to the low ultrasonic attenuation it demonstrated, its ability to efficiently insulate the scanner while supporting an elevated temperature on the part side of the plate, and the availability of a 63.5 mm thick plate without the need for lamination.

Hudson, Tyler B.↗

NASA NTRSDate not supplied

Effects of Cr and Nb alloying additions on high temperature creep deformation of Ni-based superalloys

Micro-twinning is the major creep deformation mechanism in Ni-based superalloys at temperatures above 700 °C. Recent experiments suggest that superlattice stacking faults y ' in phase may serve as the precursors to twin formation. Segregation of alloying elements to these precursors may have a significant effect on formation and extension of micro-twins. Using atomistic modeling we investigate and explain the effects of Cr and Nb alloying additions on these processes. We consider the experimentally obtained creep curves for several Ni-based superalloys with different elemental compositions and relate the observed trends to the simulation results presented in this study. Our results help to rationalize the experimentally observed puzzling effects of elemental composition of the alloy on creep resistance.

Valery V. Borovikov↗

NASA NTRSDate not supplied

Effects of Cr and Nb Alloying Additions on High Temperature Creep Deformation of Ni-Based Superalloys

Micro-twinning is the major creep deformation mechanism in Ni-based superalloys at temperatures above 700 C°. Recent experiments suggest that superlattice stacking faults in phase may serve as the precursors to twin formation. Segregation of alloying elements to these precursors may have a significant effect on formation and extension of micro-twins. Using atomistic modeling we investigate and explain the effects of Cr and Nb alloying additions on these processes. We consider the experimentally obtained creep curves for several Ni-based superalloys with different elemental compositions and relate the observed trends to the simulation results presented in this study. Our results help to rationalize the experimentally observed puzzling effects of elemental composition of the alloy on creep resistance.

Ni-based superalloys↗

NASA NTRS2024

Pressure Deficit in Gale Crater and a Larger Northern Polar Cap After the MY34 Global Dust Storm

We describe the model-independent analysis technique of Mars Science Laboratory (MSL) pressure and Mars Climate Sounder (MCS) data in de la Torre Juárez et al. (2019, https://doi.org/10.22541/essoar.169945479.90436599/v1) that compared multiple years of surface pressures on Gale before, during, and after the Global Dust Storm of Mars Year 34. The analysis found (a) representative pressure scale heights over Gale; (b) that the storm was followed by a pressure deficit at Gale; (c) the following C storms did not eliminate the deficit; (d) changes in the duration of the polar caps condensation seasons, with an early start of the North Polar (NP) ice cap growing season the year before the Great Dust Storm (GDS) and a late signature of the end of the expansion season thereafter, changes consistent with a larger growth phase of the NP cap; (e) MCS observed a larger than usual NP cap; and (f) cold temperature anomalies over the NP and warm over the Southern Pole after the storm. We also show that the analysis of observed MSL pressure data alone filters out effects on the pressure signal that are attributable to dynamical and orographic processes in a recent model analysis that makes similar interpretations as our 2019 study. One additional Mars year of observations is included to eliminate early concerns about sensor drifts. Noting that a similar NP anomaly was observed with MCS data after the last early GDS in MY25, and not the later GDS of MY27, the results suggest a possible unique effect of early GDSs.

Manuel de la Torre Juárez↗

NASA NTRSDate not supplied

Evaluating Machine Learning Approaches to Plume Tracking

On July 15, 2022, the Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano erupted, propelling trace gasses and ash through the troposphere and up into the stratosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using imagery from NASA’s Earth Observing System, including MODIS aerosol products and OMI sulfur dioxide products, this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline, establishes a framework for systematically and rapidly studying natural disasters, including additional volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of NASA’s Earth Observation and remote sensing data, this work shows how AI and open science can accelerate research and generate actionable results, even for unprecedented events. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions, and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters in a changing world.

machine learning↗

NASA NTRS2015

Benefits of a 4th Ice Class in the Simulated Radar Reflectivities of Convective Systems Using a Bulk Microphysics Scheme

Numerous cloud microphysical schemes designed for cloud and mesoscale models are currently in use, ranging from simple bulk to multi-moment, multi-class to explicit bin schemes. This study details the benefits of adding a 4th ice class (hail) to an already improved 3-class ice bulk microphysics scheme developed for the Goddard Cumulus Ensemble model based on Rutledge and Hobbs (1983,1984). Besides the addition and modification of several hail processes from Lin et al. (1983), further modifications were made to the 3-ice processes, including allowing greater ice super saturation and mitigating spurious evaporationsublimation in the saturation adjustment scheme, allowing graupelhail to become snow via vapor growth and hail to become graupel via riming, and the inclusion of a rain evaporation correction and vapor diffusivity factor. The improved 3-ice snowgraupel size-mapping schemes were adjusted to be more stable at higher mixing rations and to increase the aggregation effect for snow. A snow density mapping was also added. The new scheme was applied to an intense continental squall line and a weaker, loosely-organized continental case using three different hail intercepts. Peak simulated reflectivities agree well with radar for both the intense and weaker case and were better than earlier 3-ice versions when using a moderate and large intercept for hail, respectively. Simulated reflectivity distributions versus height were also improved versus radar in both cases compared to earlier 3-ice versions. The bin-based rain evaporation correction affected the squall line case more but did not change the overall agreement in reflectivity distributions.

bulk microphysics schemes↗

NASA NTRSDate not supplied

Software Development for SonicSonde Instrumentation Suite

The SonicSonde is an innovative weather instrumentation suite for boundary layer sampling. Software development included creating a graphical user interface (GUI) to receive, process, archive, and display data in real-time. Targeted at the Windows operating system but with multi-platform extensibility in mind, the GUI was developed using Qt 5.14 in C++. A key design consideration was to allow for tailored displays and analysis while also permitting additional sensors to be added to the platform. As such, the application relies heavily on flexible interfaces and multithreading processing for capturing, modelling, and plotting data. The object-oriented nature of Qt made it ideal for this purpose. The application supports input through live serial streams and static .csv or .dat files, custom meteorological graphs, and user-dictated panel views and output intervals. Additionally, the GUI displays real-time information about the state of the instrument. The versatility of the SonicSonde will allow meteorologists and researchers to perform or better support a variety of aeronautic and atmospheric missions.

meterology↗

NASA NTRS1990

Heat sink effects in VPPA welding

The development of a model for prediction of heat sink effects associated with the Variable Polarity Plasma Arc (VPPA) Welding Process is discussed. The long term goal of this modeling is to provide means for assessing potential heat sink effects and, eventually, to provide indications as to changes in the welding process that could be used to compensate for these effects and maintain the desired weld quality. In addition to the development of a theoretical model, a brief experimental investigation was conducted to demonstrate heat sink effects and to provide an indication of the accuracy of the model.

Steranka, Paul O., Jr.↗

NASA NTRS1999

Real-Time Assimilation of Goes-Derived Products into A Mesoscale Model and It's Impact on Short-Term (06-36hr) Forecasts from 17 October 1998 through the Present

As the parameterizations of surface energy budgets in regional models have become more complete physically, models have the potential to be much more realistic in simulations of coupling between surface radiation, hydrology, and surface energy transfer. Realizing the importance of properly specifying the surface energy budget, many institutions are using land-surface models to represent the lower boundary forcing associated with biophysical processes and soil hydrology. However, the added degrees of freedom due to inclusion of such land-surface schemes require the specification of additional parameters within the model system such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical distribution of soil moisture. Spatial heterogeneity of these parameters makes correct specification problematic since measurements are not routinely available. A technique has been developed for assimilating GOES-IR skin temperature tendencies, solar insolation, and surface albedo into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. The technique has been successfully employed in a number of mesoscale models in case-study mode. We have taken the next step and developed a study to determine if assimilating these types of data into mesoscale models in real-time can improve short-term (648h) forecasts of temperature, relative humidity, and QPF on a daily basis over relatively large regions. Therefore, an operational modeling/assimilation system has been developed at the GHCC during the past summer that allows us to produce simulations out to 48 hours in a timely manor. The PSU/NCAR MM5 is used in a nested configuration with a 25 km grid covering the southeastern third of the US. The model has been on-line since 1 July 1998 and forecast products are posted on our web site. The satellite algorithms that generate data to be assimilated came on-line 17 October 1998. Quantitative assessment of the forecast quality is performed via traditional verification statistics. In addition, invaluable qualitative information is obtained through close collaboration with several NWSFO's who are using the MM5 products in real-time on a daily basis. The assimilation technique has been applied in an off-line mode since 17 October. Results based on bulk statistical verification of surface meteorology over the entire Southeastern US show that assimilating the GOES-derived land surface tendencies and solar radiation results in a significant reduction of the shelter air temperature and RH bias on a daily basis. In fact, the assimilation technique has produced improved temperature and RH forecasts for 97% of the 100 simulations performed to date. Work is currently underway to determine the sensitivity of the assimilation procedure to the availability of satellite data, length of assimilation period, model initialization, and synoptic-scale meteorological conditions. In addition, results from a detailed energy budget analysis using the Early Eta, our operational MM5, and the assimilation runs will help us to better understand the satellite assimilation the land-surface energy budge. Research during the spring-summer of 1999 will focus on the impact of the assimilation technique during the warm season where it is hypothesized that it can have a positive impact on QPF during conditions of weak synoptic-scale forcing.

Lapenta, William M.↗