# Presentation: 067418

## Atmospheric Transport and Dispersion:Research Needs and Priorities

**	****	****David P. Bacon****	****	****Director, ****Center for Atmospheric Physics**
**Science Applications International Corporation**
**1710 SAIC Dr.****McLean, VA  22102**

**David P. Bacon**
**(703)676-4594**
**david.p.bacon@saic.com**

**Notes:**
Self explanatory.

## A Multiscale Environment

**Micrometeorology is a mixture of large and small scale forcing**
**The large scale synoptic forcing determines the overall stability and wind field**
**The local geometric (mechanical) forcing modifies the wind field**
**The local land-use (thermal) forcing also modifies the wind field**
**The local modifications may trigger instability**
**Atmospheric dispersion of contaminants depends on the details**
**Advection is driven by the *****total***** wind field (large & small scale)**
**Vertical transport in the micrometeorology system is a mixture of *****implicit***** mixing dominated by the increased turbulence of the non-uniform surface properties and *****explicit *****lofting due to mechanically or thermally driven vertical wind**

**Notes:**
Micrometeorology and hence atmospheric dispersion involves a mixture of spatial and temporal scales ranging from the global to the very local.

## All Scales are Involved

**Synoptic scale (0.01 mb/km)**
**Duration of incoming weather**
**Mesoscale (hydrostatic) (0.10 mb/km)**
**Large scale forcing (or lack thereof)**
**Microscale (non-hydrostatic) (1 mb/km)**
**Terrain forcing (or lack thereof)**
**Urban scale (10 mb/km)****(also applies to extended military facilities)**
**Building & Thermal forcing**

**Notes:**
The urban scale weather involves components from all larger scales.  The synoptic or continental scale determines the size of the particular air mass that will govern the overall weather pattern and hence determines the duration for the current pattern.  The mesoscale weather determines the general frontal patterns which will govern the large scale forcing of the wind.  The microscale weather is governed by the local terrain (mountains and coastlines), which in turn forces the mesoscale flow locally (e.g., ducting of a wind through a valley or the formation of a sea-land breeze circulation).  Finally, the urban scale involves both mechanical forcing (urban canyons caused by the buildings) and thermal forcing (land use effects and temperature gradients caused by building shadowing).

All of these scales interact, and the details of the final meteorological conditions are important for dispersion calculations.

## A Hierarchy of Atmospheric Forcing

**Scenario****	****Pressure Change****	****Horizontal Scale****	****Pressure Gradient****	****(mb)****	****(km)****	****(mb / km)**
- Synoptic (meso-)	10	1000	0.01
- Mesoscale (meso-)	10	100	0.10
- Urban Scale – Mechanical  Light Wind (2 kt)	0.006	0.05	0.12
- Cloud Scale (meso-g)	2	4	0.50
- Land / Sea Boundary	1	1	1.00
- Urban Scale – Thermal2 K Urban Heat Island	24	20	1.20
- Urban Scale – MechanicalStrong Wind (10 kt)	0.16	0.05	3.20
- Terrain Elevation5 % Grade	5	1	5.00

**Notes:**
The range of forcings in the atmosphere extends over 3 orders of magnitude from the weak synoptic forcing that acts over long distance and times to the terrain forcing that operates over a short range, but is over 1000 times greater in magnitude.

## All Weather Phenomena are Involved

**All synoptic conditions must be considered**
**Strong forcing (large air-mass interaction)**
**Weak forcing (local thermally driven circulations)**
**Dispersion depends on much more**
**Weak forced situations create substantially worse hazards**
**Overcast situations depress the UV degradation of bio agents**
**Moisture hydrolyzes many chemical agents**
**OH- oxidizes many chemical agents**
**Precipitation scavenges chemical & biological agents**

**Notes:**
In addition to the dynamic forcing, dispersion depends on sky conditions that involve other microphysical processes.  These processes change the moisture and chemical constituents of the atmosphere, which in turn affects the evolution of the pollutants.

## Scale Interaction is Critical

**From 1000 km to 1 m (10****6****) / From 3 days to 5 min (10****3****)**
**Downscale interaction is evident**
**Upscale interactions include:**
**MCCs**
**CBs**
**Orographic & Land / Sea circulations**
**Urban heat island**
**This is a stiff problem mathematically if treated exactly**
**Timestep & memory limits**
**All operational weather forecast system are scale specific**
**	*****The combination of weak forcing and multi-scale problems is especially difficult due to the “stiffness” of the exact system which leads to the current limits of our physical understanding, physical modeling, and computational ability***

**Notes:**
Scale interaction is critical to dispersion calculations.  While the downscale interaction is evident (the large scale forcing the smaller scale), the atmosphere reacts in many ways that make the upscale forcing equally important.

For example, mesoscale convective complexes (MCCs) can cause bifurcation of the jet stream.  This also occurs in microcosm when a towering cumulonimbus alters the regional circulation.  At an even more local scale, orographic or land/sea circulations arise from terrain inhomogeneity at the few kilometer level and the urban heat island has its origins in the non-uniform surface heating at a similar scale.

This mixture of downscale and upscale interactions leads to a set of equations that are mathematically stiff, which in turn leads to memory and timestep limitations.  This is one reason that all operational weather forecast systems are designed to be scale specific; unfortunately, this is not sufficient for the dispersion problem or for the problem of “down-in-the-dirt” meteorology.

## Urban Parameterization

- Drag

- TKE production

**Urban Parameterization**

- Surface energy budget modification

**Notes:**
The effects of a city on the supra-urban scales materialize primarily in the drag, turbulence production, and shadowing, and surface energy budget.

## OMEGA Simulation of URBAN 2000  (Midnight 10/25 to 1:00 am 10/26)

**With Urban Parameterization**

**OMEGA Simulation of URBAN 2000  ****(Midnight 10/25 to 1:00 am 10/26)**

**Without Urban Parameterization**

**Notes:**
This slide compares two OMEGA simulations of an URBAN 2000 release.  The first did not include an urban parameterization; the second did.  The dots indicate the plume detection network with white dots indicating detections.

## A Hard Dose of Reality

**Urban issues dominate the Offensive, Defensive, & Homeland Security scenarios**
**Urban warfare is now the norm**
**Most of the recent Marine deployments involved urban areas**
**US Forces are ill-prepared to fight in an urban setting**
**Terrorist activity is likely to focus on urban targets**
**The nature of terror is to put fear into a population**
**The population is based in the cities**
**Weapons of Mass Destruction (WMD) are now readily available world-wide**
***	******Our adversary generally has the home court advantage and while we may overcome the advantage with superior technology most of the technology is susceptible to the (local) weather.  Unless we understand the details so that we can use that technology to its fullest we mitigate to a large extent the investment in technology.***

**Notes:**
Over 80% of recent deployments of the US Marine Corps have involved an urban area.  This means that more and more of the fighting will occur in urban areas with their own unique meteorology - urban heat islands, wind ducting through urban canyons, and circulations driven by the thermal gradients caused by building shadowing.

When weapons of mass destruction are added to this list (nuclear, radiological, biological, and chemical), major uncertainties are instantly of prime operational importance.

As boundary layer meteorology becomes more important, for littoral deployment of smokes and obscurants, for drop zone winds, and for hazardous dispersion, the US Army is more and more in a position of having to guess at environments that could be understood if effort was taken.

## The Fundamental Question:Which Way Does the Wind Blow?

**NOAA Washington DC Testbed**
**80 – 90****o**** Difference between DCA & Downtown *****Building Tops *****(!)**
**Need winds *****inside***** the urban canyon**
**Thermally driven often outnumber mechanically driven situations **
**Implies a need to understand the urban micro-climate**
**Implies a need for more surface information**
**Cannot measure everywhere – so we need to know how to analyze what we do measure properly**

**Notes:**
The NOAA DC testbed experiment demonstrated that there can be a considerable difference in wind speed and direction over a city.  The difference between the wind at the building tops and at Ronald Reagan Airport (the official reporting station) were often 80-90 degrees.

The important wind, however, is DOWN IN THE URBAN CANYONS.  The wind at the building tops is often insufficient to determine this condition.

## Required:  An Integrated Program

**Basic Observing Program**
**Atmospheric processes in an urban environment**
**Remote sensing of surface thermal properties**
**Fundamental Algorithm / Process Modeling**
**Surface properties derived from remote sensing**
**Parameterized air-surface interaction**
**Numerical modeling / Computational Science**
**Advanced algorithms for data assimilation & prognostic forecasting**
**Methods for real-time data mining & dissemination**
**Real-time Information Transfer**
**Push / Pull binary, graphic, & text data**

**Notes:**
What is required is a balanced research effort that is focused on substance not show, on understanding not empiricism.

## Technology Challenges - I

**Remote Sensing **
**Surface properties**
**Albedo, heat capacity, thermal conductivity, porosity**
**Vegetation, anthropogenic activity**
**Atmospheric condition**
**Temperature, moisture, wind profiles**
**Precipitation, aerosols, trace gases**
**	*****Point weather forecasting depends on the details.  A general understanding of the surface and atmosphere is insufficient.***

**Notes:**
A major technological challenge is the ability to determine the surface physical properties and the atmospheric state from remote sensing.

## Technology Challenges - II

**Transition from observations to information**
**PSALM**
**Property / Sensor / Analysis / Local verification / Model interface**
**Physical modeling**
**Detailed surface fluxes in complex and urban terrain**
**Cloud processes**
**Radiative feedback of aerosols**
**Multiscale interactions**
**	*****A model is the instantiation of our knowledge of a system.  If we cannot formulate a model, then we must ask whether we truly understand the problem.***

**Notes:**
In trying to determine the surface physical properties and the atmospheric state from remote sensing it is necessary to identify a Property to be measured, the Sensor that can measure this property, implement an Analysis system to convert the measurement into physical units, develop a local verification of the system, and to implement an interface to utilize this information in models.  The development of the measurement alone is useless.

A critical factor is understanding what physical processes dominate so that the measurements can focus on the driving elements, rather on secondary issues.

## Technology Challenges III

**High performance computing**
**Numerical methods on massively parallel platforms**
**Operational implementations of HPC**
**	*****The U.S. government is falling behind other countries in large-scale weather prediction and climate modeling because it overemphasizes the need to achieve megaspeeds across multiple processors. . .  The government’s high-performance computing programs focus too much on achieving trillions of floating-point operations per second, thereby marginalizing Earth science computing. ***
**Ricky Rood (Data Assimilation Office, NASA/GSFC)**
***	******I personally don’t think it’s a matter of transporting existing codes, my suspicion is we’re going to need new ways of solving the equations.***
**David Evans (NOAA / OAR)**
**Integration of sensors & data mining**
**Space-based reconnaissance**
**UAV & Internetted sensor platforms**
**Mining information from a sea of data****	**

**Notes:**
There are a number of technology challenges to improving our ability to forecast the weather at finer scales and with greater accuracy than currently.  The first challenge is high performance computing.  NWP is one problem that demonstrates massive vectorization because the physics of the atmosphere is the same for all volumes, but which, due to communication between volumes by advective, acoustic, or radiative effects, experiences difficulty in parallelization.

## Technology Challenges - IV

**Data Transfer**
***It is not what you know – it is what you think of in time!******	******Salada Tea***
**Need to convert bits into information into knowledge**
**Need tools to provide binary, graphic, and text output**
**Response Support**
**Need automated decision support tools to collapse the decision tree and shorten the response time**

**Notes:**
Finally, it is essential that we develop methodologies to place information into the hands of decision makers as rapidly as possible and to assist them in automating the decision tree and collapsing the response time.