1. Providing Full Spectrum Environment Representation Support to Training Exercises
Steve Lowe – AER, Inc.
EDC Development Lead

2. Motivation
In many cases, a simulation’s fidelity depends on interaction with the environment
Aircraft tactics based on clouds and visibility
Naval tactics based on acoustic performance
Troop movement rate determined by ground wetness
Environment must be realistic and consistent
Should see ground get wet if it rains
Should see ocean response to high winds
Can’t ignore the environment in m&s
*even greater fidelity requires interaction between domains
*here’s another example

3. Integrated Natural Environment
Illumination
Terrain surface and Features
Climate
Hydrologic Cycle
Sea State
Ocean Parameters
Transmittance
Surface and Subsurface Flows
Weather
Mobility
Flight Routes
Line of Sight
Weapon Effects
Course of Action
Acoustic Tracking
Visibility
Route Selection
Dynamic Terrain
Elevation
Features
Weather Models
Bathymetry
Hydrologic Modeling
Physical Parameters
Ocean Models
The Same
Processes
System Performance
Sensors
Behavior Models
Decision Makers
Natural
Synthetic
Our goal is to realistically reproduce Mother Nature’s work!
*leverage data from history and models to produce realistic representations
*data from different domains must be consistent to create realistic responses
goal of inearp is to coordinate all domain representations

4. Environmental Scenario Generator
Dynamic Terrain
Atmosphere
Terrain
coupled
coupled
Ocean
Space
Esg is a web-based application for composing scenarios and generating environmental representations
System has been in development, but reached foc this year with 14ws as administrator
can search data using fuzzy logic (i.e., hi/lo wind spd), parameter constraints (i.e., temp>100f), and/or system effects (i.e., clouds too low for hellfire)
data delivered in standard formats (grib and csv) with customer-desired parameters
*currently have global and higher-resolution regional sets for atmosphere and ocean
can process other model runs from wrf, coamps, swan
*also have space weather derived and observed indices
*terrain data resides with nga
*now looking to use it to coordinate an environmental representation that is even more realistic and consistent between the domains
Consistent Multi-Domain
Environment Representations
Interactive Search Capability
for Relevant Scenarios
Flexible Delivery Mechanisms
Data Representation
& Interchange

7. Checkpoint
Consistent Authoritative Environment Representation required for realistic simulation behaviors
ESG is primary source for such data
See for info and access
Provides multi-domain DATA in simulation ready format
Supports rapid development of relevant scenarios
What is left to do? Remaining issues …
Runtime distribution of environment data
Effects computation inside the simulations
Can be inconsistent and too expensive
Correlated products required to foster usage

8. Environmental Data Cube (EDC)
Support System
EDC Support System Provides…
Production of full spectrum of correlated support products
Efficient distribution and inject of data/effects
Primary Goal: Consistent C4I, Control Group, and Simulation Views of the Environment Representation
C4I
Sims CG
File
API
Production
Distribution
Access
Use

9. EDC Production Site
Manage Environment Representation Requirements from Consumer perspective (not producer)
Assumes consistent made-to-order authoritative representation from which to derive products
NO derivation / transformation allowed inside EDC
Building to ESG interfaces, but could use alternate sources

10. EDC Web Interface – Project View

11. EDC Web Interface – Component View

12. EDC Web Interface – Product List

13. Sample EDC Products SAUS11 KAWN 061200 RRX
METAR ZBAA Z 12007KT 10SM CLR 26/19 Q0988 RMK SLP149 LAT399N LON1163E ESGACMES=
METAR ZBHH Z 20014G20KT 10SM BKN130 19/10 Q0862 RMK SLP136 LAT408N LON1117E ESGACMES=
METAR ZBOW Z 20012KT 10SM BKN090 23/10 Q0871 RMK SLP121 LAT407N LON1100E ESGACMES=

14. Sample Products for JTF Horn of Africa
Rule-Based System Impacts
Present Weather Briefing

15. Pre-Generated Effects
Example: IR Sensor modeling using Target Acquisition Weapons Software (TAWS)
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
The Payoff – Runtime Access in Milliseconds !!
Pd = F(Lat, Lon, Time, Sensor, Target, Tactical)

16. EDC Distributor
C4I
Sims CG
Provide the right products to the right player at the right time
Provide mechanism to manage scenario branches
Inject of “special” conditions on demand
Dynamic updates during exercise (to include live forecasts)
Forward Deployable to Event Network domain

17. EDC Exercise Support Site
Sims CG

18. EDC Runtime Component Manage reach-back capability to distributor
File
API
Manage reach-back capability to distributor
Manage local data store (cache) of EDC products
Provide simple local API for simulation developers
Simulation Protocol Neutral
Provide API/data access behind the sim, not via sim protocol

19. EDC Conceptual Architecture
Terrain Generation Services
AFWA
Atmosphere Servers
Event
Planners
NAVO
Ocean Servers
NOAA/NGDC
Scenario
Conditions, Place/Time,
Products
Space Servers
Internet
EDCSS Production
Manager
Effects
Graphics
Imagery
Messages
“Real-World”
C4I
HLA Simulation Network is used as first instantiation of environmental sim server (listed on diagram as the “EDCSS HLA”), with follow-on efforts to establish TENA and DIS networks if/when/where required.
Local HTTP Network
Sim Feeds
EDC
Runtime
EDC
Runtime
EDC
Runtime
Sim X
Sim Y
Sim Z
EDCSS
Distributor
EDCSS HLA
Event
Analyst
HLA feed
* HLA Simulation Network

20. EDCSS Support Terminal Fury
Environmental Scenario Generator (ESG)
Environmental COE
Atmosphere & Ocean Data
Naval Maritime Forecast Center (NMFC) Pearl Harbor
Joint Warfighting Center Suffolk
Asheville, NC
Simulated Graphics and Satellite Imagery
Sfc Atmos GRIB
Ocean GRIB
PACFLT
Joint METOC
CAPT Atangan
PACOM
Joint METOC
CAPT Schulz
CSV Wx
IR Effects
CSV Wx
OASES
AFMSTT
(AWSIM)
JCATS
Sim
JSAF
Ground Model
C7F/CTF-74
Orders
Outcomes
Air Force
Sensor Models
Navy
Sensor Models

21. Summary
Realistic M&S requires high-fidelity, consistent, and relevant multi-domain environment representations
Data, Effects, and Products
The ESG provides the base representation
National data and modeling assets provide the content
The EDC Support System provides and distributes the full suite of correlated products

22. ESG / EDC Programs
Tri-MSEA (Air&Space, Ocean, Terrain) initiative to ensure consistent and coupled environment representations available to DoD M&S
Focus is on ensuring support to large programs that will benefit the most
JFCOM Training Exercises and Experimentation Events
Navy FST, AF DMO, Army FCS simulation programs
Capabilities available to any DoD program
Existing capabilities are the result of OSD / Service investment via the M&S CO (

23. CONTACT INFO
DoD ASNE MSEA Senior Lead
Dr. Fred Lewis
U.S. Air Force
Director of Weather
DoD Ocean MSEA Senior Lead
RDML David Titley
U.S. Navy
Commander, Naval Meteorology and Oceanography Command
DoD Terrain MSEA Senior Lead
Ms. Mary Irvin
National Geospatial-Intelligence Agency
NGA Modeling and Simulation Executive Agent
DoD ASNE MSEA
Col Mark Zettlemoyer, A3O-W
DoD Ocean MSEA
Mr Steve Payne, GS15, CNMOC
DoD Terrain MSEA
Mr Paul Foley, GS15, NGA
MSEA Coordinator
Lt Col Allen Rabayda

24. Thanks ! Steve.Lowe@aer.com M&S Group Manager
Atmospheric & Environmental Research, Inc.
1510 Breezeport Way, Suite 600
Suffolk, VA 23435
for more info.