UCRL-JC- 125043
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ARAC-3, A New Generation EmergencyResponse Modeling System
RL. LeeJ.R. Albritton
S. ChanJ.M. Leone, Jr.J.S. NasstromG. Sugiyama
This paper was prepared for submittal to the
American Nuclear Society’s Sixth Topical Meetingon Emergency Preparedness and Response
San Francisco, CAApti 22-25,1997
DISCLAIMER
This document was prepared as an account of work sponsored by an agency ofthe United States Government. Neither the United States Government nor theUniversity of California nor any of their employees, makes any warranty, expressor implied, or assumes any legal liability or responsibility for the accuracy,completeness, or usefulness of any information, apparatus, product, or processdisclosed, or represents that its use would not infringe privately owned rights.Reference herein to any specific commercial product, process, or service by tradename, trademark, manufacturer, or otherwise, does not necessarily constitute orimply its endorsement, recommendation, or favoring by the United StatesGovernment or the University of California. The views and opinions of authorsexpressed herein do not necessarily state or reflect those of the United StatesGovernment or the University of California, and shall not be used for advertisingor product endorsement purposes.
ARAC-3, A New Generation Emergency Response Modeling System
R. L. Lee, J. IL Albrittq S. _ J. M. hone, Jr., J. S. Nasstro~ and G. SugiyamaLawrence Livermore National Laboratory
Livermorq CA 94550(510) 422-1859
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SUMMARY
A description of the new ARAC-3modeling system is presented. Among the majornew capabilities are a prognostic forecast modeland entirely new diagnostic and dispersionmodels. Various components of the system arebeing tested to determine their performance bothindividually and within an integrated setting.When completed in 1999, ARAC-3 will containall the features of the current ARAC-2 system aswell as new capabilities that will enable ARACto function as a state-of-t.hart emergencyresponse system well into the next decade.
I. INTRODUCTION
The Atmospheric Release AdvisoryCapability (ARAC) program has provided real-- world-wide, emergency response servicefor the Department of Energy (DOE) for almosttwo decades. Over the past ten years, WC hasevolved from a service that supported exclusivelynuclear-related emergencies into one capable ofproviding advisory to a wide range of accidentsand potential accidents involving hazardousmaterials]. During this period of time, theARAC models have undergone a number ofincremental changes in order to make themapplicable to an increasing variety of accidentscenarios. However, since the majority of thecodes were developed during the early 1980’s,these models have not taken advantage of thestat~of-the-art technologies that are currentlyavailable. In 1995, ARAC management,supported by DOE, embarked on a program toupgrade ARAC with the latest hardware andsoftware platforms. The new models will enableWC to respond to the variety of emergenciesthat will emerge during the next decade, andbeyond.
ARAC-3 (Fig. 1) is a new red-time,operational system that is being developed toreplace the current AIWC-2 system. Whencompleted, the new system will provide improvedworldwide emergency response service to boththe DOE and DOD agencies. Among theimportant new features of the ARAC-3 systemare (i) a prognostic forecast model to generatemeteorological fields and to supplement the windfields produced by the diagnostic models; (ii) newdiagnostic and dispersion models that are basedon continuously-varying terrain; (iii) the abilityto digest data from a variety of newmeteorological and geographic input datasources; (iv) the capability to perform acrossseveral UNIX-based distributed computationalplatforms; (v) a suite of new research andgraphical tools to support meteorologicalresearch. The ARAC-3 system will be developedwith the new software technologies such asFORTRAN 90, C*, parallelization and netCDFfde protocols. It is anticipated that an initialARAC-3 system will be in place by 1997 withfull operational capabilities by the year 1999.
IL THE PROGNOSTIC MODEL
A major upgrade of the ARAC modelingsystem has been achieved by implementing a newforecast capability based on the NavalOperational Regional Atmospheric PredictionSystem (NOIWPS)2. NORAPS is a relocatablehigh-resolution prognostic model developed bythe Naval Research Laboratory and used byNaval operations to provide twice daily weatherforecasts for speciilc regions in the world ofinterest to the Navy. It is a primitive equation(hydrostatic) model with a split-explicit timeintegration sigma coordinates with variableresolution in the vertical, and options for triplenesting in the horizontal. The physics in themodel include a 1.5 order TKE closure scheme,
large scale precipitation, dry convectiveadjustment and a modifkd Kuo cumulusparameterization scheme.
Because of differences in operationalrequirements, the LLNL version of NORAPS hasbeen modii%d to include new features that aremost relevant to the ARAC operationalenvironment. The original NORAPS exclusivelyderives its initial and boundary data fromNOGAPS, the Navy’s global forecast model.The version of NORAPS used in ARAC hasbeen extended to ingest gridded data fromNCEP’S (National Center for EnvironmentalPrograms, formerly the National MeteorologicalCenter) global (AVN) and continental (ETA)forecasts. Also, while the Navy’s operationalapplications of NORAPS are typically at gridresolutions of 45 km or greater, ARAC is oftenrequired to respond to events that occur at muchfreer resolutions, on the order of a kilometer. Tocalculate at such resolutions, NORAPS has beenmodified to ingest topographic and kmdlwaterdata at 2 km grid resolution in order to capturethe details of the geqgraphy at much freer scales.Efforts have recently been completed to improvethe physics of NORAPS by implementing acomprehensive microphysics package forforecasting precipitation, a more generalradiation package to account for cloudinteraction and a soilhrface submodel. In-housevalidation studies are currently being conductedto test the forecast capability of this modifkdversion of NOIL4PS on typical problems that areof interest to ARAC operations.
The Navy has also developed a follow-onnonhydrostatic model, COAMPS, to performforecasts at even freer grid resolutions thanNORAPS. COAMPS is an advanced mesoscalemodel with improved data assimilation methods,better boundary layer physics, and cloud-scalemicrophysics. ARAC has an agree-t with theNavy to acquire this new model and to evaluatethe feasibility of replacing NORAPS withCOAMPS as the next upgrade of the forecastmodel.
III. GEOGRAPHIC AND METEORO-LOGICAL DATABASES
The expanded capability of the WC-3system necessitates the acquisition of inform-ation from a number of new data bases. Inadditional to the high-resolution topographicinformation used by the current ARAC-2 systemadditional data such as land/water masks,
vegetation distribution and soil typ~ albedo andsnow cover are now required for input to theprognostic model.
Meteorological data sources have alsobeen expanded. While the ARAC-2 systememploy the Air Force Global Weather Central asits sole provider of both global meteorologicalobservational and gridded dat% the new systemis capable of tapping into and utilizing theextended resources of data supplied by theNCEP. NCEP operates an intemet site contain-ing a wide variety of global and regionalobservational data that can be accessed by usersall over the world. In addition to the NCEP data,the new ARAC-3 models are designed to alsoingest the global gridded data provided by theNavy’s Fleet Numerical Meteorological andOceanographic Center (FNMOC). The capabi-lity to ingest local observational data such asfrom mesonets and supported sites will bedeveloped. It is anticipated that the new systemwill take advantage of the most relevant andtimely set of meteorological data to generate therequired wind field for the dispersion calculation.
IV. ATMOSPHERIC DATA ASSIMILAT-ION SYSTEM
The new ARAC-3 meteorological dataassimilation system3 ingests observational andgridded forecast data, interpolates this data ontoa computational grid, performs a mass-consistentadjustment of the wind field to follow the relevanttopography, and generates the meteorologicalinformation for input into the dispersion model.When completed, the front end of the system willhave improved capabilities to assimilatemeteorological data from various surface andupper air sources such as rawindsonde, multil-evel meteorological tower, SODAR, LIDAR as
well as microwaveblock representation
profder. In contrast to theof terrain used in the current
ARAC-2 models, the new models employ a morerealistic continuous terrain coordinate system. Inaddition, better spatial resolution of the domain isachieved via variable resolution griddingcapabilities in both the horizontal and verticalcoordinates.
A ftite element technique is used togenerate a divergence free wind field. There areboth mathematical and practical advantages tothis particular approach. It is well known that theftite element method generates an optimallyaccurate solution of the variational problemassociated with the mass-consistent adjustmentprocedure and results in a grid-point depiction ofthe wind vectors. For co~utationrd efficiencyand to minimize storage requirements, severalconjugate gradient (iterative) options areprovided to solve the matrix system associatedwith the discretized equations.
V. LAGRANGIAN OPERATIONAL DIS-PERSION INTEGRATOR (LODI)
LODI is the new transport and diffusionmodel for the A.IWC-3 system4. The dispersionmodel not only contains all of the capabilities ofthe current ARAC-2 (ADPIC) model but alsoincorporates a number of new improvements.Among LODI’S new features are a continuousterrain representation, graded horizontal grids,and variable resolution in the vertical to capturefme details of the concentration patterns withinthe surface or spdic elevated layers. Furtherimprovements in the model include the use of aRunge-Kutta integration scheme for computingtransport and a stochastic approach based on theRandom Displacement Method (RDM) forcalculating dispersion. A particular advantage ofthe RDM approach is that it is grid-independentand is not subjected to the grid resolutiondifilculties that are inherent in typical gradientdiffusion formulations.
LODI will contain an extensive library ofsource descriptions for potential applications to avariety of emergency scenarios. Typical choicesinclude Gaussian, spherical and cylindrical line-
shaped moving or stationary sources. Additionalphysical submodels are being implemented totreat dry deposition of pollutants, plume risq aswell as more complex processes such asrainout/washout and explosive cloud rise. Plansare currently being developed to make use of theturbulence information generated from theprognostic model as input to the RDM. Thisapproach allows the turbulence generated fromthe forecasts to directly influence the dispersionpattern.
Figure 2 depicts a typical dispersionscenario generated from the ARAC-3 models.The figure shows a particle plot at one hour aftera release at a Florida coastal location with thesurface wind field pattern also displayed. Theoffshore wind generated from the diagnostic windfield model using local observational data carriesthe pollutants out over the shoreline towards theocean..
VL ARAC-3 MODEL INTEGRATION ANDOPERATIONAL STRATEGIES
Integration of a prognostic model into anoperational emergency response system poses aformidable challenge with respect to generatingadvisory products in a real-time mode. It is clearthat forecast models typically require asi~lcant amount of computational time relativeto diagnostic models. Our strategy for deployingprognostic models in a real-time mode is togenerate 48 hr limited area forecasts at 15 kmresolutions or less, once daily, for two regionsencompassing most of the sites supported byARAC ( e.g. domains centered over the East andWest Coasts of the U. S.) The meteorologicalfields will be updated once every 24 hrs based onthe most current global analysis and will be usedas gridded data for the diagnostic models. Whenan emergency response is required from an areaoutside of the forecasted domains, initialresponse will most likely be supplied by thediagnostic models using the most appropriate andup-to-date observational or gridded data, or both,if available. The NORAPS domain will berelocated to the region of interest and theprognostic model will begin computations, atfreer resolutions, using the most recent global
analysis arrdor forecasts as initial and boundaryconditions. ARAC-3’s goal is to generate anirritird prognostic emergency response usingsupplemental wind data from an in-house 24 brforecast within 4 hrs of the start of an event andsubsequent prcdocts from updated forecasts in 2to 3 brs. In order to achieve the specdup requiredof the prognostic mode~ we are actively seekingways of redncirrg the computational time viaimplementation of multiprocessing techniques inconjunction with coding rrmditications to improveUrecomputationrd eftlciency of the model.
ACKNOWLEDGEMENTS
This work was performed under the auspices ofthe Deparhmrrt of Energy by the LawrenceLivermore National Laboratory nnder ContractNo. W-7405-Eng-48.
REFERENCES
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T. J. .%dfkln, J. S. Ellis, C. S. Foster, K.T. Foster, R. L. Baakctt, J. S. NasstrnmW. W. ScballG III. “Abnospheric ReleaseAdvisory Capability: Real-time Mcdclingof Airborne Hazardous Matcrisls,” Bull.Amer. Meteor. SW., 74,2343 (1993).
J. R. Albritton, R. L. Lee, R. Hcdur, C.-S.Liu “Modeling the Wind-FiekJs ofAccidental Releases by MesoscaleModeling,” Froc. 6* Topical Meeting onEmerg. Resporq San Francisco, CAApril 22-25, 1997, ANS.
G. ?m@SOM and S. Chsn, “Metm-rologicsl Data Assimilation for Real-TimeEmergency Response,” Proc. 6* TopicalMeeting on Emerg. Response, SanFrancisco, CA., April 22-25, 1997, ANS.
J. bone Jr. And J. Nasstrom “A FirstLook at the New ARAC DispersionModel,” Proc. 6* Topical Meeting onEmerg. Respons% San Francisco, CAiAPti 22-25, 1997, ANS.
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FigOre 1: Schematic diagram of the ARAC-3 modeling
F@rre 2: ARAC-3 Results from a typical point sourcerelease along the Florida coast.
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ation Departm
ent • Lawrence Liverm
ore National Laboratory
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