# Presentation: 486871

## Urban Test Beds:Productivity, Problems, and ProgressMeasurement Networks, Logistics, and ModelsWilliam J. Shaw12th GMU Conference on Transport and DispersionJuly 9, 2008

## Urban Test Bed—Definition and Analogy

- _Urban Test Bed_“A multifunctional infrastructure that provides multiyear continuous measurement and archival of environmental data, across a metropolitan area and through the atmospheric boundary layer, supporting improvements in a range of activities from scientific research to user applications.”Williamson et al., 2007, AMS Seventh Symposium on the Urban Environment.

- Analogy: ARM Cloud and Radiation Test Bed (CART; now  ACRF)

## Logistical Challenges

- Cost
- The ARM annual budget for operating the Central Facility in Oklahoma is multiple $M
- Start-up costs for instruments, including negotiating terms of their location, can be substantial
- This is a challenge to agencies supporting urban test beds, because it requires a substantial commitment over many budget cycles, especially since long-term measurements do not carry the immediacy and excitement of campaigns
- Instrument Oversight
- For instruments to provide reliable data, they must be regularly monitored and calibrated.
- For more sophisticated instruments, continuing development of processing techniques is an important component of success

## Logistical Resources

- Surface Meteorological Networks
- Many are already in place
- The coverage in urban areas is remarkably dense
- Many urban surface network data already collected and at least roughly QA’d (by MesoWest and now by NOAA’s MADIS)
- Upper-air Meteorology
- This remains largely a gap
- Profilers are useful (but not dense or everywhere)
- Current Doppler radar data may be especially helpful
- Models
- It will never be possible to measure “everything, everywhere, all of the time”
- Routine mesoscale modeling with data assimilation are and will be essential to establishing information such as inflow conditions for urban CFD investigations

## Scientific Challenges

- Focus
- It is unlikely that a single test bed can adequately address all needs for operations and research in urban fire, air quality, dispersion, severe weather, etc. Can we prioritize the needs that urban test beds will serve?
- Multiple Locations
- Because of the highly nonlinear behavior of many essential processes, multiple disparate test bed locations will be needed.
- Thinking Long-term
- Scientists’ DNA seems to carry a campaign gene
- To be truly valuable, test beds must have adequate observations and well-defined scientific uses for their long-term data

## Some Key Long-term Data Needed from Urban Test Beds

- Diurnal and spatial variability of mixing layer depth
- Turbulence structure of the mixing layer, especially under stable stratification and in the urban core.
- This is also a science question.
- Wind and stability structure of the urban boundary layer, especially inflow conditions to the urban core (models)
- Test beds should be sited to allow for better understanding of the urban boundary layer where the inflow is complicated by complex terrain
- Regular tracer releases and sampling
- Needed to evaluate behavior of meteorological and dispersion models over a range of conditions beyond the idealized.
- Needed to understand indoor–outdoor exchange

## Political Challenges

- Data Sensitivity
- Data that define indoor-outdoor exchange for specific buildings or air flow in subways, for example, can be highly sensitive.
- These data are essential for understanding some outdoor dispersion measurements.
- How will test beds make such data available to scientists in order to make fundamental progress?