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Development of an eastern Great Lakes sub-regional WRF ensemble for lake effect snow prediction.

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Presentation on theme: "Development of an eastern Great Lakes sub-regional WRF ensemble for lake effect snow prediction."— Presentation transcript:

1 Development of an eastern Great Lakes sub-regional WRF ensemble for lake effect snow prediction

2 Outline Background Background Why should we do this? Why should we do this? What have we done What have we done What will be done What will be done

3 Background… The Eastern Great Lakes Lake Effect Snow Project (EAGLLES) A field study scheduled for ??? A field study scheduled for ??? Looking for operational forecast challenges related to lake effect snow forecasting Looking for operational forecast challenges related to lake effect snow forecasting The concept of sub-regional ensembles had been proposed (Rich) The concept of sub-regional ensembles had been proposed (Rich) Proposal – to develop a sub-regional ensemble for use operationally, and for use in the EAGGLES field study Proposal – to develop a sub-regional ensemble for use operationally, and for use in the EAGGLES field study

4 Why should we do this? Several NWS Offices around the eastern Great Lakes utilize locally run meso-scale models (workstation Eta / WRF). Several NWS Offices around the eastern Great Lakes utilize locally run meso-scale models (workstation Eta / WRF). Given that an ensemble is already available, we should explore utilizing the power of ensemble prediction techniques in lake effect snow environments (identify high confidence vs. low confidence solutions). Given that an ensemble is already available, we should explore utilizing the power of ensemble prediction techniques in lake effect snow environments (identify high confidence vs. low confidence solutions). Share what works and what does not work. Share what works and what does not work.

5 Current model configurations Office Model Core Boundary Conditions Microphysics Run Times BUF*NMMGFSFerrier 2 per day CTPNMMNAMLynn 4 per day BTV*NMMGFSFerrier- CLEARWGFSLynn ALYARWNAMLynn BGMARWNAMFerrier Note: BUF is running the KF CPS, BTV is running BMJ.

6 Model Domain

7 Web Interfaces http://198.206.43.25/wrf/index.php (examine individual model runs) http://198.206.43.25/wrf/index.php (examine individual model runs) http://198.206.43.25/wrf/index.php http://www.lightecho.net/scripts/all_version5. php?image=Wx (side by side comparisons) http://www.lightecho.net/scripts/all_version5. php?image=Wx (side by side comparisons) http://www.lightecho.net/scripts/all_version5. php?image=Wx http://www.lightecho.net/scripts/all_version5. php?image=Wx

8 4 panel display

9 On-going case study (proof of concept) CTP and BGM are collaborating on a few case study from last winter using this data. CTP and BGM are collaborating on a few case study from last winter using this data. Justin Arnot will use GRADS to display ensemble products from 2 LES events, plus a synoptic snow event. Justin Arnot will use GRADS to display ensemble products from 2 LES events, plus a synoptic snow event.

10 Example – Output from 4 members (BGM, CLE, CTP1, CTP2)

11 What’s next Finish proof of concept case studies (CTP / BGM / CLE) Add runs from BUF, BTV, ALY? Finish proof of concept case studies (CTP / BGM / CLE) Add runs from BUF, BTV, ALY? Get a limited subset of grib data from the models into AWIPS (CLE). Get a limited subset of grib data from the models into AWIPS (CLE). Continue development of ensemble graphics (means, probabilities) (CTP / BGM / CLE) Continue development of ensemble graphics (means, probabilities) (CTP / BGM / CLE) More models into the system (ALY) More models into the system (ALY) Assimilate results from COMET project with SUNY Oswego (BUF) Assimilate results from COMET project with SUNY Oswego (BUF) Forecaster evaluation and feedback (All offices). Forecaster evaluation and feedback (All offices).


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