Safety, Health, Economic Impacts R. E. Carbone. I’m a researcher - basic weather and climate process studies. No training in safety, health or economics. I have lead national and international weather research programs dedicated to the improved prediction of “high impact” weather.
I’m a researcher - basic weather and climate process studies.
No training in safety, health or economics.
I have lead national and international weather research programs dedicated to the improved prediction of “high impact” weather.
“Sydney 2000” reinforces my belief that there is an underexploited opportunity.
Do we grasp the benefits that could arise from a serious multi-sector engagement?
For the sake of focus, I’ll restrict my comments to short range weather prediction.
Are we shackled by “uniformity of service” policies?
~2/3’s of our population lives on ~2% of the land
We should define “uniformity” in a way that benefits everyone.
Are we shackled by lack of clarity and coordination among governmental and private sector relationships?
I think so.
Sheer quantity of weather-sensitive activity
Wide range of sensitivities at any given time within a forecast zone
Fine scale of spatial and temporal co-mingling of various sensitivities
High public interest in relatively small weather changes
Potential economic importance of “routinely disruptive” weather
Relatively high density of weather, water and environmental monitoring
Proliferation of ad hoc nowcasting and very short range dynamical forecasts.
Omnipresent heavy-hitters…Transportation, Water, Emergency Management, Air Quality, Public Events, Recreation
And the Added Dimension of Homeland Security
Scanning Raman-shifted Eye-safe Aerosol Lidar (REAL): Pentagon, 7 May 2004REAL
Urban aerosol mapping, locating aerosol sources, monitoring dispersion of pollutants
Wavelength: 1.5 microns
High pulse energy
Range resolution: 3 m
Useful range: 500 m to several km
An urban environment observing system.
Present Environment (PE) gridded and depicted at urban use scale (500m, 1 min)
Nowcasts of PE (trends and very short range forecasts)
Dynamically-based surface layer forecasts
Short range (dynamically-based) storm/environment forecasts.
Use-directed “significant impact” estimates and forecasts
Condition-keyed “optimal pathways” products
Baseline social scientist studies on current use and value for targeted user groups
Joint user-provider projections of high-value products and services
Micro-economic model forecasts of value
Forecast Demonstration Projects designed to provide products and services
Social Scientist observations of product and service usages, decision impacts
Detailed meteorological/environmental verification
Social Scientist interviews of targeted-users to quantify usages, decision impacts
User-provider evaluation of incremental value
Education, training and outreach can be dominant factors.
A case in point
Aviation wind shear accident prevention circa 1985.
Discovery and understanding of microbursts was the key factor
Pilot training provided, based on visual clues, general meteorological conditions.
Accident rate plummeted, well before deployment of detection systems
Develop a national consensus on “uniformity of service” defined by categories of products and services best matched to rural, ex-urban and urban needs. “Comparable mitigation” of principal impacts could be a guiding criterion.
Providers and users should jointly design Urban Forecast Demonstration Projects in light of baseline socio-economic studies of current use and value. FDPs should be conducted in representative urbanized areas jointly with targeted user groups.
The incremental use and value, as measured by changes in decision-making, tangible benefits and verifiable improvements in weather information, should then be quantified by social scientists and users alike.
A “who does what” issue arises among various branches and levels of government and various private sector interests. This issue should not impede the R&D necessary to define the elements of the solution.
It would be best to constructively debate and test potential divisions of labor before operational implementations are understood.