“ Multi-functional Mesoscale Observing Networks in Support of Integrated Forecasting Systems” A...

“Multi-functional Mesoscale Observing Networks in Support of Integrated Forecasting Systems”

A Report on a USWRP WorkshopOrganized by:

Fred Carr, University of Oklahoma Walt Dabberdt, Vaisala Inc.Tom Schlatter, NOAA/OAR/FSL & CIRES

Presentation to: WSN05Toulouse, France

Carr / Dabberdt / Schlatter | 5 Sept 2005 | WSN05 |

Presentation Outline

Workshop goals and background

Recommendations of the Modeling & Data Assimilation Workgroup

Recommendations of the Nowcasting Workgroup

Recommendations of the Testbed Workgroup

Existing and Planned Testbeds -- Domestic and International

Recommendations of the Implementation Workgroup

Overarching Recommendations


Workshop Goals

Develop a roadmap that leads to designing, testing and implementing integrated mesoscale observing-forecasting systems that:

– yield improved mesoscale forecasts

– utilize optimal observing system configurations

– serve multiple applications

– recognize the capabilities, interests and resources

of the public, private and academic sectors

Explore appropriate business models that will support and enable these systems


Workshop Factoids

Private Sector

Public Sector

TOTAL PARTICIPANTS

Academia and NCAR

Domestic Int’l. Total

37 4 41

49 3 52

25 4 29

111 11 122

Nowcasting -- Pat Welsh, NOAA/NWS (now

U.No.Florida) Jim Wilson, NCAR

Modeling and Data Assimilation -- Steve Koch, NOAA/OAR Xiaolei Zou, Florida State University

Test Beds -- Marty Ralph, NOAA/OAR Dave Jorgensen, NOAA/OAR

Implementation -- Joe Friday, University of Oklahoma (ret.) Maria Pirone, AER, Inc.

Working Group Leaders:

Dates:8-10 Dec. 2005


Modeling & Data Assimilation Recommendations:Scope

What is the optimal mix of observations at the meso-, storm- and urban scales?

Examples of mesoscale forecast applications requiring improved observing capabilities include:

severe weather systems in both cold and warm seasons; air quality and chemical emergency response; aviation, marine and surface transportation; and hydrology and more.

Modelers should be involved in the observing network decision process by designing observing system experiments to determine:

the most important variables to measure; the minimum spacing and resolution requirements (network design); adaptive and targeted sampling strategies; and data assimilation techniques to effectively use these new measurements.


Modeling & Data Assimilation Recommendations: Remedy Deficiencies in Current Observational Networks

Most desirable additional measurements: Lower tropospheric measurements:

– Mass, winds, moisture fields (3D) ~10 km horizontal; ~200 m vertical; 1-3 hrs– PBL turbulent fluxes, PBL heights– Turbulent flow and stability ~2 km; 15 min– Aerosols, chemical tracers, emissions data

Quantitative precipitation estimate:– Better accuracy, good and consistent quality control

Upper tropospheric measurements:– State variable measurements at 100 km spacing (0.5 km vertical), 1-3 hours– improved winds from satellite and regional aircraft – vertical profiling of state variables and hydrometeors in cloudy regions– increased vertical resolution from satellite– ozone profiling; – tropopause topology

Land surface properties: – Soil moisture and temperature profiles, snow cover and depth, SST, vegetation type/state updated daily

Radiative transfer inputs: – Ozone, CO2, water vapor, clouds


Modeling & Data Assimilation: Overarching Recommendations

It may be more cost effective to sample only the boundary layer with denser coverage than to similarly enhance observations in the upper troposphere for improving mesoscale analysis and prediction.

It may be cost effective to deploy intermittent, targeted observations at high resolution. Testbeds built around prototype observing networks need to be in place to provide real-data tests of proposed strategies









The Helsinki Testbed


Advanced Operational Nowcasting – Scope

Forecast Period: 0-6 hr

Forecast High Impact Events Winter weather: heavy precipitation (precipitation type – major

challenge), high winds, icing Summer weather: high winds, heavy rain, lightning, hail Air quality; dispersion of airborne toxins

Forecast Techniques Extrapolation Statistical Numerical (process models) Expert systems

Observing Systems - “All”

Important parameters to measure:

low-level moisture; detection of sharp gradients; boundary-layer height; strength of capping inversion; energy potentially available for convection


Nowcasting Recommendations

Top priority: Establish a national mesonetwork of surface stations. NOAA should take the lead to establish this network, and set standards for

data quality. Resolution needed: 5min and 10-25km (topography-specific). Basic measurements:

winds temperature humidity pressure precipitation amount and liquid equivalent

Application-specific options: precipitation type and size distribution soil temperature and moisture radiation fluxes ceiling height visibility


Nowcasting Recommendations

Priority Radar Recommendations: NWS should proceed without delay with the (approved) addition of dual

polarization capability to the WSR-88D network. Pursue the National Research Council Study recommendation to integrate other

radars into the WSR-88D network. Support studies to investigate means for improving boundary-layer coverage in

the future through the use of closely spaced X-band radars. NWS should pursue vigorously plans for a national expansion of the NOAA

Profiler Network with emphasis on boundary-layer observations. A research field project should be conducted that tests the utility of radar

refractivity measurements to improve nowcasting.

Other Priority Recommendations: Continue support for collaborative research projects aimed at using total lightning

data to improve severe weather warnings and nowcasts. Provide real-time near-surface water vapor fields to demonstrate how high-

resolution water vapor fields can improve nowcasting.

Establish testbeds for very short period forecasting (0-6 hr, nowcasting) of high impact weather.









The Helsinki Testbed


Mesoscale Weather Forecasting -- Testbeds

Testbed Definition: “A working relationship in quasi-operational framework among forecasters, researchers, private-sector, and government agencies aimed at solving operational and practical regional problems with a strong connection to end-users.”


Testbed Recommendations

Testbeds are crucial in transitioning observing and modeling research into operations; a successful testbed must satisfy the following criteria:

Address the detection, monitoring, and prediction of regional phenomena of particular interest.

Engage experts in the phenomena of interest. Involve stakeholders in planning, operation, and evaluation of the

testbeds. Define expected outcomes, including transition to operations,

strategies for achieving them, and measures of success. Provide special observing networks (and people,

communications, and databases) needed for pilot studies and research

Provide resources for the generation and delivery of experimental products based upon these observations.

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Mesoscale Observing Programs Are Proliferating: How can we build on them?

x

•Mesowest •ARM CART• Oklahoma Mesonet• Texas Mesonet • AIRMAP

• Hi-res temperature forecasts for energy sector

North American Monsoon Experiment

• Land-falling storms (PACJET)• Air Quality• Fire Weather• Energy, Water, & Air Quality Issues

Coastal Storms

Coastal Storms


Helsinki Testbed 2005-2006

Mesoscale weather research Forecast and dispersion models: development and verification Observing systems and strategies: test and design Information systems and technology integration End-user product development and demonstration Data distribution for public and research community

Observing Facilities (preliminary)

1 dual-pol Doppler radar

4 C-band Doppler radars

101 surface wx stations*

191 road weather stations

42 two-level AWS masts

3 shipboard weather stations

11 backscatter lidars

1 UHF wind profiler

3 RAOB sounding stations

34 precipitation sites (part of 101)*

satellite obs. (GS and PO)

COSMIC RI soundings

EUCOS operational network


Beijing Observational Network Development Plan (2006-08)

150

km

Source: CMA, July 2003


Implementation of Integrated Mesoscale Observing-Forecasting Systems

Focus: Explore the potential for forming a consortium of public-private-academic partners to implement a national mesoscale observing network based on the needs of the user communities, including:

Modeling communityGeneral publicCommercial markets

Drivers: What are the major drivers of partnerships for mesoscale observing networks?


Implementation Recommendations:

A partnership arrangement was proposed for creation of consortia to develop, maintain and support regional mesoscale networks or even a composite national network.

The proposed network(s) would consist of a mix of privately owned measurement systems, publicly owned systems and newly acquired systems supplied by the consortia.

Each consortium collects and quality-controls the data, and supports the real-time dissemination of data and information products (e.g. analyses and forecasts).

Consortium members share rights, costs and revenues according to a “participation formula” (tbd)

Typical member roles: The public sector members access the data for the public good; i.e. public safety. The private-sector consortium members (and possibly academic partners) use the

data to create and sell various value-added products. Academia and non-profit research centers have access to the data for educational

and research purposes.


Four Overarching Recommendations

Adopt the testbed concept as a priority mechanism for transitioning mesoscale observing and modeling advances from research to operations

Form a multi-sector “tiger team” to develop a functional design for a working testbed, and recommend one or more testbeds for the most pressing unmet requirements.

Develop alliances among public agencies who have complementary mesoscale needs (e.g. NOAA/NWS; Dept. of Homeland Security; EPA; DoD) to leverage resources and minimize costs.

Develop partnerships among the public, academic and private sectors that will facilitate the establishment and ongoing support of mesoscale testbeds and, subsequently, operational mesoscale observing-forecasting enterprises


Mesoscale Workshop

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For complete article, see:

Dabberdt et al., BAMS, 86(7), July 2005, 961-982

http://ams.allenpress.com/pdfserv/10.1175%2FBAMS-86-7-961

[email protected]

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