• An order of magnitude improvement in providing digital topographic data needed by the commander for optimized deployment, mobility, planning, and logistics support.

• High resolution weather forecasts for incisive decision making and enhanced operational capability in adverse weather; reduced weather–related damage, and fuel costs.

• Realistic representation of dynamic environment and terrain in simulations to permit more effective mission planning, rehearsal, and training.

• Realistic portrayal of the effects of the Battlespace Environments to reduce operational costs and reduce casualties.

• Demonstrate an integrated dynamic IR/MMW terrestrial background scene generation capability for synthetic environments (FY98).
• Develop image perspective transformation technology for use with imagery to rapidly evaluate sub–10–meter resolution terrain data and position reality (FY98).
• Demonstrate VR–based battlefield environments that place the soldier in an environment with replicated terrain and climate, creating a highly detailed realistic setting for training and mission planning/rehearsal (FY98).
• Develop model–generated passive/active IR and background scenes of winter terrain for predicting sensor performance and design (FY02).
• Demonstrate spatially distributed, physics–based, 3D ground state and weather effects in future distributed interactive simulations (FY03).
• Develop multiscale/multiproduct geospatial data generation software capable of generating large integrated terrain databases at multiple levels of detail (FY03).
• Estimate knowledge–based performance for dual and multimode sensing systems operating in IR, MMW, and RF energy regimes over winter–impacted terrain (FY07).
• Develop battlespace fly/walkthrough and automated terrain analysis capability (FY07).
• Develop dynamic environment and terrain (DET) implementation for use with computer–generated forces (FY07).
• Demonstrate knowledge–based systems for predicting the performance of multi–mode sensing systems (IR and MMW) over winter–impacted terrain (FY08).
• Demonstrate automated feature extraction and attribution capability (FY08).

• Develop first principle models to predict the multispectral signatures of winter terrain surfaces and features for imaging sensor systems. Models will be structured to provide simulation capabilities for evaluating environmental constraints early in the development cycle of sensor systems, and to provide realistic physics–based backgrounds for training simulations.
• Determine procedures and equipment criteria enabling combat engineering operations to function effectively in winter conditions. This includes use of snow and frozen ground for expedient fortifications, facilities, roadways, and excavations, and operation of engineering equipment under winter conditions.
• Develop models of equipment and unit performance in winter conditions in sufficient detail to enable realistic simulation of these effects in interactive synthetic environments.

• Acoustic energy propagation is distinctly different in winter than in summer. The technical challenge is understanding the coupling that occurs between the complex air, snow, frozen–ground, and unfrozen–soil interfaces.
• IR, MMW, and radar interactions with winter terrain surfaces (i.e., snow, ice, frozen soil) vary dramatically with changing meteorological conditions. The challenge is to model and predict the response.
• The impacts of low temperatures, snow, ice, frozen ground, and ice accumulation on the performance of materiel and equipment must be characterized to support design modifications, the formulation of alternative techniques or procedures, and the prediction of the extent and duration of the impacts.

• Distribute background energy transfer model over a variety of complex terrain and meteorological conditions (FY98).
• Incorporate icing radiosonde data into models for predicting aircraft icing severity (FY98).
• Provide the Army Engineer Center and School with techniques, kits, and support systems to reduce low temperature degradation of engineer materiel performance (FY98).
• Provide critical data for integrated winter operation tactical decision aids (TDAs) (FY99).
• Integrate seismic–acoustic sensor performance in a synthetic environment to optimize sensor performance (FY00).
• Transition model of the spatial variability of atmospheric icing to support communications and aerial operations TDAs to the U.S. Army Aviation Center and School and the U.S. Army Intelligence Center and School (FY00).
• Integrate physics–based multiband dynamic environment models for prediction of sensor performance and optimizing sensor design (FY01).
• Demonstrate knowledge–based systems for predicting the performance of multimode sensing systems (IR and MMW) over winter–impacted terrain (FY03).

• Demonstration of advanced technologies in digital feature extraction and attribution, data management, positioning technologies beyond the GPS, and the implementation of dynamic terrain into mission planning, rehearsal, and training systems.
• Use of knowledge–based techniques to improve terrain data exploitation for detecting and identifying geospatial changes and to predict terrain and climate effects over time in support of battlefield decision making.
• Reduction of the time required to generate realistic environments in distributed modeling and simulation.

• Identifying terrain features/targets automatically to respond within the enemy’s decision cycle.
• Developing a total force positioning and navigational capability for the Army. Accurate fire and the ability to locate and navigate will be key to success on the obscured future battlefield.
• Promulgating standard verified and validated software to achieve joint interoperability goals.
• Generating terrain and weather environments in near–real time for tactical operations and distributed modeling and simulation.
• Developing a methodology to determine the effects of geospatial data and terrain based models on battlefield decision aids and to display the results to a commander in order to minimize risk.

• Integrate multispectral imagery/hyperspectral imagery with digital terrain elevations for terrain feature extraction (FY98).
• Devise neural network image data classification system (FY98).
• Develop new methods for portraying terrain analysis product reliability (FY98).
• Incorporate techniques for processing synthetic aperture radar (SAR) and interferometric synthetic aperture radar (ISAR) feature data in existing software (FY98).
• Improve visualization capabilities with the addition of dual–band IR and image intensifier capability (FY98).
• Test link capability for point and line/vector geospatial data management (FY99).
• Develop standards for the representation and content of a link structure for geospatial data (FY99).
• Develop advanced tactical navigator (ATN) for combat support (CS)/CCS vehicle usage (FY99).
• Link 3D model and texture library to database generation capability (FY99).
• Incorporate automated feature extraction techniques from spectral, SAR, and EO sources into existing digital stereo photogrammetric software (FY00).
• Extend physics based models and visualization capability to incorporate passive and active MMW (FY00).
• Develop off vehicle ATN (FY01).
• Test the link capability for complex geospatial areal data management (FY01).
• Deliver algorithms for management, dissemination, and integration of geospatial information to industry through the Open Geographic Information System (OpenGIS) consortium (FY01).
• Test initial automated feature attribution capability based on terrain reasoning software (FY01).
• Integrate mode derived IR and MMW sensor performance overlays into 3D visualization (FY01).
• Investigate capability for automated feature attribution based on terrain reasoning (FY01).
• Demonstrate visualization and command planning tools for urban data sets (FY01).
• Improve terrain data inferencing methodologies (FY02).
• Develop a spectrally enhanced multisensor exploitation capability (FY02).

• Extract battlespace weather and atmospheric information from satellite active remote sensors. Provide data from ground to space with four times the accuracy of current passive sensors, covering 40 percent of the global surface in under 4 hours.
• Automate data retrieval from tactical weapon platforms. Increase battlespace data collections by a factor of five over current sensors.
• Provide seamless data distribution between services and tactical areas. Enable common, joint data collection and communication to allow all services to share data in real time for a consistent, accurate "nowcast" common picture of the battlespace.
• Develop ground–based remote sensors that operate "on the run" to support future force mobility. Provide data at much higher rates than today’s technology.
• Develop a prototype mobile atmospheric profiler system, which, when coupled with meteorological (met) satellites and other battlefield met data sources, eliminates the requirement for logistically burdensome artillery balloon borne sensors and hydrogen generators.
• Provide quantitative assessments of the propagation characteristics and radiative transfer effects of natural clouds and man–made battlefield aerosols that affect illumination, boundary layer energy balance, surface state, and visibility, through studies of MMW propagation and aerosol detection.
• Develop advanced laboratory measurement techniques and instrumentation as tools for aerosol microphysics diagnostics and for the detection and identification of CBW agents.
• Develop aerosol and gaseous information sufficient to quantitatively model atmospheric limitations on military systems that rely on radiation (UV, visible, IR, and MMW) for detection, imaging, and identification.
• Develop and test ground–based remote sensors for battlefield atmospheric characterization of the dynamic and thermodynamic properties of aerosol and gases, such as temperature, density, wind fields, water vapor, and CBW agents. Evaluate the ability of satellite remote sensors to support this same purpose.

• Develop remote sensor concepts and algorithms to provide tactical data for initializing battlefield meteorological models, assessing performance of precision strike weapons, and general real–time situational awareness on the battlefield.
• Develop measurement systems that resolve the microscale dynamic structures for the verification of atmospheric models operating at these scales. Technical barriers for basic research involve the investigation and explanation of previously unobservable atmospheric phenomena occurring at these scales, such as the convective boundary layer, gravity waves, and shear instabilities.
• Determine the characteristics of aerosols, their dynamic properties in the atmospheric medium, and their optical properties over all spectral bands of military interest, and develop the instrumentation that permits the detection and analysis of aerosols.

• Complete development of a prototype atmospheric profiler as an upgrade to the Army’s meteorological measuring set (MMS) (AN/TMQ–41) and demonstrate during 4th Infantry Division (4ID) digitized rotation at the National Training Center (NTC) (FY98).
• Automate data retrieval from MMS to the integrated meteorological system (IMETS) using variable message format (VMF) bit–oriented message (BOM) protocol (FY98).
• Automate data retrieval from Improved Remotely Monitored Battlefield Sensor System (IREMBASS) met sensor (FY99).
• Complete development of neural net software for direct retrieval of wind speed and direction from met satellite radiance data. Improve the accuracy of met satellite measured winds by 50 percent (FY99).
• Develop remote sensing analysis algorithms to provide improved initialization data for battlescale forecast models including surface energy balance interactions, boundary layer temperatures and winds, water vapor, and cloud liquid water data (FY00).
• Develop remote sensing analysis methods to estimate surface layer visibilities, and identify low stratus and fog regions and their effects on local illumination and contrast (FY02).

Figure IV-11. Measurements in the Planetary Boundary Layer, Along with Weather Parameters
Click on the image to view enlarged version

• Optimize environmental prediction models to allow operation on virtually all tactical weapon systems, from the future soldier to artillery and missile systems. Provide more accurate and timely data for platform–specific decision aids.
• Develop a standalone analysis system that will emphasize key weather elements and weather phenomena for important decision making factors, which can serve all services for the purpose of improving nowcasting, forecast guidance products, and, potentially, the analysis in the mesoscale numerical weather prediction system.
• Increase firing accuracy of indirect fire cannon and missile systems by integrating the battlescale forecast model (BFM) directly into the ballistic kernel operating on fire direction center and gun platform fire control computers and use the BFM to calculate in near–real time the meteorological effects over the entire trajectory path of a projectile, rather than just at apogee.
• Build a mesoscale numerical weather prediction system appropriate for battlescale applications, including the boundary layer. The system should be capable of assimilating a wide range of data over complex inland and coastal terrain and accounting for improved cloud and aerosol treatment in the model physics, improved surface energy balance and evapotranspiration processes, and physical process oriented forecast models.
• Develop descriptions of the dynamic flow interactions with highly complex terrain, vegetation, and structures that can run on a variety of computer systems, from battlefield workstations to supercomputers.
• Improve modeling of transport and diffusion (T&D) of gases, particulates, and pollutant plumes essential to the DoD’s CBW R&D programs. Couple T&D models to mesoscale numerical weather models to forecast aerosol dispersion and concentration.
• Link battlescale forecast models with gas/aerosol transport and diffusion models to provide four–dimensional (4D) predictions of CB agent threats on the future battlefield. Increase accuracy of spatial forecast by 50 percent and concentration forecasts by 60 percent.
• Understand and model the propagation of acoustic and short wavelength electromagnetic radiation in the atmosphere under natural and battle induced conditions.
• Develop high spatial and time resolved effects of weather and illumination variations on EO propagation and target background signature models.

• The computational speed and memory/storage required to resolve the mesoscale phenomena and to represent and predict mesoscale physical processes is extraordinary. The T&D of gases and particulates require treatments more sophisticated than traditional Gaussian plume models to represent the turbulent, chaotic nature of atmospheric motions. Technical barriers for basic research involve the development of probability density function (PDF) solutions in order to predict the concentration fluctuations, a critical issue for soldier system exposure, and the development of improved nonlinear solutions for the Navier–Stokes equations that describe the physical process of T&D.
• The flow of the atmosphere around and through vegetative canopies and through urban "canopies" plays a critical role in the use of countermeasure aerosols and for chemical and biological defense. Models of such flow must be available for operation on tactical systems.

• Quantify the accuracy achievable by moving the BFM from the AN/TMQ–41 MMS to indirect fire control computers and using the BFM to correct for met effects over the entire trajectory path of a projectile (FY98).
• Develop improved capabilities to visualize forecast meteorological data and derived weather parameters in 3D on the tactical IMETS (FY98).
• Develop interfaces to allow tactical battlescale forecast data and derived propagation and illumination parameters to be provided through the Master Environmental Library to support high level architecture (HLA) simulations (FY99).
• Incorporate remote sensing and analysis of surface energy balance and surface state data to improve initialization of the battlescale forecast model (FY00).
• Extend accurate high resolution weather forecast capability for the battlefield to 48 hours (FY03).
• Deliver a nonhydrostatic moisture microphysics BFM for clouds and precipitation forecasts to the IMETS. Improve adverse weather forecasts by 40 percent while running on Army tactical computers (FY05).

• Develop integrated weather/atmospheric data, broad spectrum propagation models and advanced visualization methods, to provide 3D visualized decision aids showing graphical depictions of atmospheric impacts on mission plans and weapon use for current and future battlefields.
• Automate mission planning tools based on detailed knowledge of environmental impacts, to optimize the commander’s planning and decision making ability. Improve the required mission output, as defined by the commander, by 30 percent over current methods.
• Integrate atmospheric and background models with target prediction models to ensure that atmospheric effects are included in the assessment of weapon system performance, survivability, and vulnerability.
• Develop more quantitative methods to augment current rule–based, binary decisions based on weather–dependent critical values for subsystem, system, platform and military operations performance.
• Develop environmental decision aids for operational and tactical levels of war planning and training that give the effects and impacts of weather and battle–induced atmospheres on U.S., allied, and threat unit functions, systems, subsystems, sensors, and personnel.
• Develop real–time weather and environmental effects models (obscurants, illumination levels, EO, and acoustic propagation) to provide common, unified weather effects, features, and representations leading to improved battlescale forecasting for simulation, training, doctrine, and C³ systems that are compatible for all services.

• Battlespace prediction models and parameterization methods for boundary layer physical processes will depend crucially on in–theater data assimilation methods that fully exploit all sources of weather observations from remote and in situ platforms. Development of robust and flexible procedures will be needed to adapt to the available data options in real time.
• As the observation data from various sensors and platforms increase and the fusion and prediction are highly synergized, quality control is essential to ensure an accurate description of the state of the atmosphere.
• The extension of weather impact decision aids from current rule–based, critical value threshold comparisons to more complex interactions between weather, terrain and performance characteristics will require greater use of AI, fuzzy logic, and expert system techniques that will increase computational loads.

• Provide an integrated weather effects decision aid with a dynamic rule editor capability, allowing users from various functional areas to tailor weather impact threshold values to meet their particular mission requirements (FY98).
• Demonstrate integrated EO/acoustic/gas/biological agent propagation with tactical weather data and 3D visualization tools for mission planning at a division–level advanced warfighter experiment (AWE). Improve multicomponent mission planning by 40 percent over current binary decision aid technology, improve information assimilation by 60 percent over 2D map decision aid displays (FY98).
• Demonstrate decision aids that display 3D acoustic propagation over terrain (FY98).
• Demonstrate use of fuzzy logic and other AI methods to produce dynamic rules and weather–influenced system performance values to augment weather impact decision aids (FY99).
• Incorporate remotely sensed weather data and derived parameters to augment decision aid overlays (FY00).
• Demonstrate satellite remote sensing of battlespace environments and tactical use of such information in operational decision aids to the Communications–Electronics Command (CECOM) (FY01).