1	Use Case #1: Enhanced Road Weather Content Enabled by Clarus Sept. 8, 2011 Leon F. Osborne, Jr. leono@meridian-enviro.com
2	Meridian Team Meridian Environmental Technology, Inc. Iteris, Inc. University of North Dakota The Meridian Team’s Partner States Idaho Transportation Department Minnesota Department of Transportation Montana Transportation Department North Dakota Department of Transportation South Dakota Department of Transportation
3	Clarus Demonstration Use Cases
4	Clarus Road Weather Support Enhancing Road Weather Forecasting Methods Support: Control Strategies (Use Case #2) Advisory Strategies (Use Case #5)
5	Clarus Enhanced Road Weather Forecasting
6	Mesoscale Modeling Conceptual Design Challenge How to appropriately incorporate ESS observations utilizing Clarus Quality Check flags within mesoscale modeling Solution: Incorporate preprocessing methods to apply QCh flags to control data ingest into data assimilation methods used to initialize mesoscale models Clarus Enhancement: Extends the availability of observations to low density observations areas
7	Data Assimilation Results Large variations indicate both an local enhancement in temperatures and impacts of the distant-dependent objective analysis scheme Improvements are isolated but significant for select areas
8	Findings (Mesoscale Modeling) Clarus data offer additional data to initialize the (road) weather environment Greatest benefit to data assimilation for surface conditions in low density observation areas Supports various real-time applications (i.e. blowing snow analyses) Difficulties in applying the QCh flags in a cost effective and efficient manner Minor benefits to mesoscale modeling beyond initial hours Non-surface conditions drive the surface state Localized higher-resolution models (~1-km) hold more promise of utilizing greater volume of (surface) observations
9	Research Needs / Gaps (Mesoscale Modeling) Need for improved boundary layer observations Improved methods to incorporate QCh flags in an objective (automated) manner Better focus (new paradigm) of mesoscale modeling specific to the roadway environment to derive greater benefit from surface observations Benefit-Cost study needed to identify the justification for expending higher costs required to operationally support high-resolution mesoscale models
10	PPAES Conceptual Design Challenge Substantial benefits to be had from highly-detailed, rapidly-updating wintertime precipitation information, but… …all the information resources suffer from unique problems Solution: Extend surface observations with remotely sensed (e.g., weather radar and satellite) and computer model data Clarus Enhancement: Substantially extends the ‘ground truth’ surface-based observations of precipitation
11	PPAES Conceptual Design
12	PPAES Performance
13	Findings (PPAES) Has shown considerable promise and is now being used to support operational road weather products Algorithms for integrating data to the maximum benefit are complex Quality control of surface observations is a huge issue There are significant differences in sensitivity amongst surface observing sites – can dominate the analysis!
14	Research Needs / Gaps (PPAES) Improved quality control techniques for precipitation observations Not just to filter out blatantly bad observations, but also to identify sensor biases Improved RWIS maintenance programs, with more emphasis on uniform responsiveness from hardware
15	Seasonal Weight Restriction (SWR) Decision Support Tool Use Case 2 September 8, 2011 Bob Hart bobhart@meridian-enviro.com
16	SWR Design
17	SWR Design/Processing
18	EICM Concept - Profile
19	EICM Concept - Freeze
20	EICM Concept - Thaw
21	EICM Concept – SWR Issues
22	SWR Display - Pictograph
23	SWR Display - Pictograph
24	SWR Display - Pictograph
25	SWR Display - Pictograph
26	Implementation of SWR
27	SWR Display - TriState
28	SWR Display - Pictograph
29	SWR Display - Pictograph
30	Findings EICM output provides a good representation of sub-pavement profile Sub-pavement freeze/thaw processes are quite complex EICM requires detailed construction information and responds differently to different construction profiles EICM had a cold bias from ~ 12” – 25”
31	Findings Several thaw & refreeze cycles occur during the winter EICM may provide significant value in determining when restrictions should be lifted
32	DOT Perspectives The EICM output provides another resource for SWR decision The EICM forecast has reduced SWR decision anxiety The SWR guidance provides information about the restoration of subpavement structural stability Not available from other resources May be key to removal of weight restrictions The visualization of subsurface conditions helps in the SWR decision process
33	Contact Information Bob Hart - Meridian Environmental Technology, Inc. bobhart@meridian-enviro.com Leon Osborne - Meridian Environmental Technology, Inc. leono@meridian-enviro.com Mark Askelson - University of North Dakota askelson@atmos.und.edu