ams2009scm-03-dabberdt

Network of Networks:A Private-Sector Perspective10 August 2009AMS Summer Community MeetingNorman, OK

Walter DabberdtVaisala CSOBoulder, CO

/ date / name / ©Vaisala

Some Observations on NoN Important follow-on to “Fair Weather”

Partnerships are crucial

Frames the problem(s) well Impedance mismatch: mesoscale meteorology and synoptic

observations Offers important network design and architecture criteria (but not a network design per se) Articulates the importance and challenges w/r/t observations of the

PBL, humidity, air quality, soil moisture Makes a strong case for comprehensive metadata & QA/QC Need for and importance of ‘quasi-operational’ network testbeds Frames the importance of stakeholders and their specific needs Proposes a ‘soft’ model for a working relationship among the sectors


Fig

. 2.1

T

ime

and

spac

e sc

ale

s of

‘hig

h-im

pact

’ wea

ther

(sou

rce:

NoN

, 200

8)

Range of Scales


Table 3.1 Spatial and temporal scales of several meteorological phenomena of consequence for the power-generation industry, and the required measurement resolution

Event Space Time Measurement Resolution

Heat wave (temp) 500-1500 km 2 days-1 week 0.5°C, 10 km, 1 hr

Winda 1-2000 km 1 min-4 days 1 m s−1, 1 km, 1 min

Wind (for wind power) 100 m-1000 km; to 1 kmb 10 min-1 week 0.5 m s−1, 100 m, 10 min; (1 m s−1, 30 m, 10min)b

Snow and ice storms 50-1000 km minutes-2 days 1 mm snow water equiv.

1 cm snow, 1 km, 30 min

Lightning region minutes to hours location to 0.5 km

Precipitationc basin to regional Hours-days, 1 mm, 1 km, 1 hr. seasonal to interannual

Cloudinessc local to regional daytime hourly to monthly 0.1 sky, 10 km, 20 min

Waste heat impact 10 km, lakes and rivers 1 hour-4 days 0.5°C, 100 m, 1 h

Normal weather urban (2 km); rural (30 km) 20 min-climate

aCould be associated with a Nor’easter (4 days), icing conditions, hurricanes or tornadoes (1 min), straight-line winds, or fire weather.

bMeasurements in the vertical direction.

cCould be from short-term (management) or long-term (planning) for hydropower production.

SOURCE: Derived from Schlatter et al. (2005).

(sou

rce:

NoN

, 200

8)


Table 3.2 Key capabilities of key meteorological observations to meet public health and safety applications

Parameter Measurement Resolution IssueHorizontal Vertical Temporal

Air Quality

Surface Fair n/a Good

Aloft Poor Poor Poor

PBL Depth

NBL Poor Poor Poor

CBL Fair Fair Poor

MBL Poor Poor Poor

Winds

Surface Good n/a Good

Aloft Fair Fair Poor

Temperature


Aloft Fair Fair Poor

Relative Humidity


Aloft Fair Good Poor

Clouds Good Good Good

Precipitation Good n/a Good

Pressure


Aloft Good Good GoodNOTE: NBL, CBL, and MBL refer to the nocturnal, continental and marine boundary layers, respectively.SOURCE: Tim Dye, Sonoma Technologies, Air Quality Community’s Meteorological Data Needs.

(sou

rce:

NoN

, 200

8)


Some Issues in Creating a Public-Private-Academic Enterprise

Who provides what functions?What sectors are engaged? Public? Private? Academia?How are the parties selected? Entry criteria? Exit criteria?How do they work together?What is the business model?What is the governance?Who are the customers? IP rights and issues?


The Value Chain

Decision Support

Prediction

Analyses

Observations Data

Technology/Sensors/Systems

To be successful, the “Enterprise” must participate throughout the value chain.

But, who does what?


Some Example Applications of the Enterprise

Transportation Roads & railroads Airports Marine terminals and harbors

Energy industry Demand and supply forecasting Wind & solar power management Distribution Maintenance

Emergency management Flooding Toxic releases – accidental & deliberate

Public health and Safety Forecasts Watches and warnings Air quality alerts Heat stress and severe cold outbreaks

Construction management High winds – e.g. tall crane ops Lightning Precipitation

Entertainment and Recreation Outdoor entertainment & sporting venues

Agriculture Freezes Irrigation Commodities exchange

Insurance industry


The Value Chain

Decision Support

Prediction

Analyses

Observations Data

Technology/Sensors/Systems

To be successful, the “Enterprise” must participate throughout the value chain.

But, who does what?

http://www.hydrometeoindustry.org/catalogue/ProductSheets/Vaisala/RoadWeather/Vaisala_road weather_ice-and-snow-warning_large.jpg

http://www.hydrometeoindustry.org/catalogue/ProductSheets/Vaisala/RoadWeather/Vaisala_road weather_ROSA_large.jpg

http://www.hydrometeoindustry.org/catalogue/ProductSheets/Vaisala/RoadWeather/Vaisala_road weather_IceNet-data-display_large.jpg

http://www.tfhrc.gov/its/pubs/04109/alttext.htm


Component Functions of the Enterprise

Civil Works

Decision

Support

Archival ModelingOperations &Command &

ControlAnalysis

Infra Installation & Maintenance

QA & QC Commun-ications

Decision-Making & Actions

Sales &MarketingR&D Governance

Other?

Other?

AWS

Soil moisture

Sensor &Other

Suppliers

Other

Radar

Profil-ers


Some Rules of the Road

The value of testbeds Learn during the demo phase Test network designs Establish relationships: B2B; B2G; G2B; G2G; B2G2A; etc.

Keep it simplePlay to the strengths of the different sectorsMake sure the goals are clearly defined and pursuedAddress the needs of all levels of the value chain


Primary strengths of the sectors

Public interest Policy justification Infrastructure Stable environment

(incl. research) Standards (data,

metadata, interface)

Innovation Value-added products Entrepreneurship Agility Risk taking Efficiencies Operational

capabilities Market expertise

Science People (technical

resource base) Research risk-

taking Research centers Neutral ground

PublicPrivateAcademic

Source: USWRP Mesoscale Workshop, Boulder, CO (2003)


Strawman #1

Business as in the pastGovernment leads and pays Industry is a contractual supplier of government-dictated

products and servicesAcademia does the R&D


Strawman #2

An emerging (though still limited) approach Industry leads and takes financial risks and rewards Government is a core customer among many customers Academia does directed R&D for industry and government


Other Strawmen

Industry, academia and government form a new joint venture? Isn’t this happening today with the banks and auto industry (govt. + industry) but also CPB, Amtrak, USPS?

Or, government creates a GOCO (Government-Owned, Contractor Operated facility that is owned by the Government and operated under contract by a non-governmental, private firm)

All parties do their own thing, collaborating where there is mutual benefit?


The NoN Recommendation


The CASA Approach

Vision: to enable vastly improved detection and prediction of adverse weather, and mitigate the associated societal and economic impacts

Goals: Implement, in an operational context, CASA-developed remote sensing and DCAS (together with other) technologies that will enable marked improvements in decision-making for a variety of applications

Strategy: Throughout the remaining lifetime of the CASA ERC, develop,

improve and test sensing, modeling, and decision-support tools Deploy and test one or more advanced, quasi-operational

networks to demonstrate the benefits and viability of the concept, which provide the justification for

Ultimately: Implement a nationwide capability


CASA's Concept of a distributed adaptive network


CASA, Sector Attributes & Partnering


Industrial Advisory Board (IAB):

Public Sector Members:NOAA-NWSDOEEC

Private Sector Members:Vaisala Inc.Raytheon Co.EWR Weather RadarWeatherNews InternationalITT Electronic Systems-GilfillanOneNetDeTect Inc.IBMNatl. Res. Institute for Earth Science and Disaster Prevention (NIED) News 9Oklahoma State Board of Regents for Education

University Partners:U. Mass.U. OklahomaCSUUPR-Mayaguez

CASA’s R2O Transition Plan

private sector; public sector

service

Non-IAB Members IAB Members

Non-IAB Members

IAB Members & university partners

Su

pp

lie

rs

Create and operate a quasi-operational multi-functional network

the enterprise

IAB + Univs.


Industrial Advisory Board (IAB):

Public Sector Members:NOAA-NWSDOEEC

Private Sector Members:Vaisala Inc.Raytheon Co.EWR Weather RadarWeatherNews InternationalITT Electronic Systems-GilfillanOneNetDeTect Inc.IBMNatl. Res. Institute for Earth Science and Disaster Prevention (NIED) News 9Oklahoma State Board of Regents for Education

CASA’s R2O Transition Plan

private sector; public sector

service

Non-IAB Members IAB Members

Non-IAB Members

IAB Members & university partners

Su

pp

lie

rs

‘testbed’ = a quasi-operational multi-functional network

the enterprise


The End

mailto: [email protected]

ams2009scm-03-dabberdt

Technology

vaisala table

network of networks

importance of stakeholders

public health

km2 days

architecture criteria

entry criteria

challenges wrt observations