1 / 15

Q2 Workshop

Q2 Workshop. Multi-sensor QPE: Current Operational Capabilities, Issues and Perspectives from ABRFC view. William E. Lawrence Development and Operations Hydrologist Arkansas-Red Basin River Forecast Center Tulsa, OK. June 28, 2005. ABRFC QPE History.

sydnee-bennett
Télécharger la présentation

Q2 Workshop

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Q2 Workshop Multi-sensor QPE: Current Operational Capabilities, Issues and Perspectives from ABRFC view William E. Lawrence Development and Operations Hydrologist Arkansas-Red Basin River Forecast Center Tulsa, OK June 28, 2005

  2. ABRFC QPE History May 1992 – HAS software delivered to ABRFC March 1993 – Formal HAS operations begin August 1993 – StageIII software operational, ABRFC switches to using MAPX vs old MAP June 1994 – Start of ABRFC online archive of QPEs, largest in NWS June 1996 – ABRFC investigates COE precipitation software, and starts porting code for our use July 1996 – ABRFC finishes P1 & performs testing November 1996 – ABRFC switches to using P1 almost exclusively

  3. Why P1? The P1 code, using a simple scientific algorithm, allowed ABRFC forecasters an easier faster method to come up with reliable QPE’s Outperformed StageIII both in speed, ease of use, and quality of product Did not have severe underestimation of rainfall in cooler season months Had added functionality such as easy ways to “make” snow, remove AP, save changes, etc. Code and results were forwarded to OHD

  4. LMRFC StageIII Study ~ -33% error • (Stellman, 2000)

  5. ABRFC Process1 Study ~ + 2% error

  6. Satellite Data – Do we use it? ABRFC receives satellite data every hour Experience has shown its better than nothing, but often misplaced and amounts are unreliable ABRFC forecaster may use when all else fails, but this occurs only very rarely P3 has ability to draw in polygon area to swap to satellite data anywhere in basin Overall, we much prefer radar/gage mix of data

  7. Satellite Data – Do we use it?

  8. Satellite Data – Do we use it?

  9. Gage Data – How do we use it? Approximately 1200 automated gages in ABRFC area At any given time, approximately 400 in “bad gage list” Only ASOS gages are heated, and even they have trouble with frozen precipitation Oklahoma mesonet data is extremely valuable, well-run mesonet GOES data also valuable, but maintenance sometimes lacks Schoolnet, Alert systems least desirable as little maintenance is performed after initial setup. Overall, gage data is EXTREMELY important to ABRFC in coming up with acceptable QPEs

  10. Gage Data – How do we use it? ABRFC feels that human interaction is necessary for sufficient QC of gage data. What appears good at first look may turn out to be poor data, ie under-reporting, reporting at wrong hour, etc. Bad data isn’t always obvious until you start adding up many hours Gages constantly being moved into and out of “bad gage list” Most important HAS function at ABRFC is QCing hourly QPEs

  11. Current Issues Continue to have serious deficiencies/difficulties in producing accurate QPEs in winter events Continue to have serious deficiencies with radar estimates in mountainous areas; luckily we have few areas like this Radar estimates of QPE at ranges greater than 75 miles continue to be problematic during cool season List of problems almost exactly the same as described in ABRFC memo to OHD in 1993

  12. Current Perspective ABRFC feels that well known issues should be addressed before we dive into probabilistic QPEs. “If we can’t even produce a good deterministic QPE year round, then why are we attempting to develop a probabilistic QPE?”

  13. Why not MPE? MPE is great improvement over StageIII Output is roughly equivalent to P3 Older versions were not user friendly in frozen precipitation events, nor did they remember changes made Still problems with performance of MPE vs P3 Radar artifacts are still part of MPE ABRFC continues to work with OHD so that we may adapt using a national software

  14. MPE Artifact

  15. MPE Artifact

More Related