The Environmental Data Cube Distributing Realistic Weather Steve Lowe ESG/EDC Program Manager AER, Inc. Steve.Lowe@aer.com Maj Jim Everitt and Mark Webb (DRC) ASNE / MSEA Office

ASNE MSEA Organization Air & Space Natural Environment Modeling and Simulation Executive Agent Director of AF Weather Sponsors The MSEA M&S CO XCOM AFWA Col Zettlemoyer LtCol Rabayda Developers AFCCC Maj Everitt AER SAIC NGDC Program Office (DRCx3)

ASNE/MSEA is not in the visual simulation business Why are we here? ASNE/MSEA is not in the visual simulation business Virtual (cockpit) simulators are beginning to require/utilize environment representations behind the imagery Sensor Prediction / Lighting Models Embedded Dynamic Effects Vehicle Performance Behaviors Virtual simulators are being linked into distributed LVC simulation architectures Standalone “dial-a-weather” environment is no longer acceptable! ASNE/MSEA offers technology and support services providing realistic natural environment representations ideal for use in distributed LVC simulation architectures. FREE to DoD

Providing Realistic Context

Past: How we got Weather into an Exercise Manpower intensive process focused on graphic products Rather than DATA in the simulations. Customer Sets Weather Objectives Looks clear to me… …you won’t see targets… Run the Simulation Provide Weather Determine Effects & Make Briefing Retrieve Products = In the past, weather charts were archived hap-hazardly. When an exercise was being prepared for, the weather scenario was limited to what had been archived in it’s choice of visualization products. Also, it took lots of man hours to create the entire weather scenario that was going to be used and it had to be distributed by hand. Often the simulations didn’t even use the scenario because there was no data that could be ingested into the models. This meant that there was disagreement between what was being played in the simulation and what was being briefed. 100% Accuracy Archive Products The military was NOT really training like it fought! In isolation

ASNE/MSEA Vision for Weather Support Customer Sets Weather Objectives Simulations Environmental Data Cube Briefing Products Weather Effects Focused Data Sets System Impacts White Cell Common Distribution ASNE MSEA SME Now we can create the data that the models can ingest and match it to the available archived visualizations. The simulations match what is being briefed. The data and products still have to be distributed by hand though. Develop Scenario COP

Conditions, Place/Time, Typical Application of ESG M&S Support with ESG https://esg.afccc.af.mil Customer Request Conditions, Place/Time, Content, Format ASNE SME Customer HTTP / FTP Pickup Custom Database Typical Application of ESG Find the Event Generate Base Representation Generate Customer Representation Custom Packaging NCEP/NCAR 50-Year Reanalysis NWP Model Transforms Format Encoder

Ocean Content (Tentative) ESG Content Sample Absolute Humidity Best Lifted index Blowing Sand Blowing Snow Bulk Richardson Number Cloud Base Cloud Ceiling Density Altitude Dewpoint Temperature Evaporative Duct Height Fog Freezing Level Height Frozen Ground Geopotential Height Ground Wetness Heat Index High/Mid/Low Cloud Base High/Mid/Low Cloud Cover High/Mid/Low Cloud Top High/Mid/Low Cloud Type High/Mid/Low Icing Intensity High/Mid/Low Turbulence Intensity Illumination Inversion Height Land Cover Land Use Category Modified Refractive Index Pasquill Stabilty Index Precipitation Intensity Precipitation Rate Precipitation Type Pressure Pressure (Reduced to MSL) Pressure Altitude Relative Humidity Skin Temperature Snow Depth Soil Moisture Soil Temperature Specific Humidity Surface Duct Height Temperature Thunderstorm Probability Total Cloud Cover Total Precipitation Visibility Water Vapour Mixing Ratio Wind Chill Wind Direction Wind Gust Speed Wind Speed Wind U-Component Wind V-Component Ocean Content (Tentative) Primary Wave Direction Primary Wave Period Significant Wave Height Sea State Critical Depth Current U-Component Current V-Component Deep Sound Channel Axis Depth Depth Excess Mixed Layer Depth Salinity Shallow Sound Channel Axis Depth Sonic Layer Depth Sound Speed Surface Duct Cutoff Frequency Water Temperature

The Payoff – Runtime Access in Milliseconds !! Hypercube Concept Example: IR Sensor modeling using Target Acquisition Weapons Software (TAWS) Sensor Properties Atmospheric Transmission 4 Target Types 4 Sensors 4 Target Orientations 8 Sensor-Target Azimuths 5 Sensor-Target Ranges 3 Sensor Altitudes 3 Background Types 24 Times per day 400 Lat/Lon locations => 220 million TAWS computations Target Thermal Properties Background Thermal Properties The Payoff – Runtime Access in Milliseconds !!

Hypercube Concept Provide pre-computed performance data for simulations that can’t afford the computational burden at run-time Use a physics solution to a slightly different problem Compute a desired metric for an n-dimensional parameterized space Pd = f (Sensor, Target, Background, Weather, Tactics) Provide a simple API to allow applications to rapidly sample that space for the closest match to the run-time situation Provides for multi-dimensional interpolation, as appropriate

ASNE/MSEA Vision for Weather Support Customer Sets Weather Objectives Simulations Environmental Data Cube Briefing Products Weather Effects Focused Data Sets System Impacts White Cell Common Distribution ASNE MSEA SME Now we can create the data that the models can ingest and match it to the available archived visualizations. The simulations match what is being briefed. The data and products still have to be distributed by hand though. Develop Scenario COP

Environmental Data Cube ASNE/MSEA FY-07 New Start Provides for production of full-suite of environment representation products required to support simulation events Customized data representations or effects Derived visual representations to support decision makers Simulated Operational METOC Product Feeds Provides for coordinated distribution of all products The right product to the right consumer at the right time Manages changes/branches in scenario Provides embeddable technology to improve use of environment representation within the simulations Pre-configured for use with EDC dynamic data distributions Focused on embedding the impact without the data volume

EDC Conceptual Architecture EDC Production Data Product-based Web Services (C2 Feeds, HITL) Hypercubes Scenario Data Graphics Text (Obs) Customer Simulation DATA file Data Cache EDC Runtime Component API (Custom) Encoder Data, Effects HLA DIS ?? EDC Pack EDC Service “Sim Net” Pack A EDC Sim X HLA/RTI DIS XMSF ??? EDC Distributor Pack B EDC Sim Y Scenario Management Simulation Package Mgr Exercise V&V EDC Sim Z Pack C An EDC Simulation Package is a complete set of Data, Hypercube, Image, Text products mapped to simulation requirements.

EDC Process for Blue Flag - 07 Blue Flag NIPR Site GRIB (AFWA/MM5) JWIS METAR (JMIBL) NITES CSV Spatial Shift Temporal Shift Derived Content Custom Formats “Pacifica” June 2007 AFCCC Data 505th Base Atmospheric Representation 50km / 1-hr Califon Feb 94 IMAGES GrADS Hypercubes AWSIM HyperTAWS

WX CHARTS and METAR’s METAR KBOI 201200Z 18006G15KT 10SM TS SCT011 02/M03 Q0856 RMK SLP145 LAT351N LON1764E ESGACMES METAR KBAM 201200Z 18005G12KT 10SM CLR 03/M09 Q0821 RMK SLP100 LAT322N LON1757E ESGACMES METAR KWMC 201200Z 18005G08KT 10SM CLR 04/M08 Q0842 RMK SLP120 LAT325N LON1748E ESGACMES

Summary Existing ASNE Capabilities for Environment Representation Environmental Scenario Generator Environmental Hypercube Auxiliary Products (Graphics, Text, etc.) Environmental Data Cube is an FY-07 New Start to formalize many existing processes Unique “weather server” in its modularity / flexible use Consistent Environmental Representation is the foundation Broad range of derived products and delivery mechanisms

Questions ? Steve.Lowe@aer.com 757.348.9997 Mark.Webb.CTR@afccc.af.mil 828.271.4210 asne@afccc.af.mil https://esg.afccc.af.mil