Bill Lawrence – DOH. “Hydrologic Model Output Statistics”  Current short term ensembles have proven unreliable, mainly because no hydrologic uncertainty.

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Presentation transcript:

Bill Lawrence – DOH

“Hydrologic Model Output Statistics”  Current short term ensembles have proven unreliable, mainly because no hydrologic uncertainty included.  Mary Mullusky suggested using previous forecasts at XEFS workshop in 12/06  Includes both meteorological and hydrologic uncertainty.  Temporary gap-filler till better hydro uncertainty process developed

 Basic premise is to compare historical forecasts with observed, then infer how a operational forecast might vary considering current observation and deterministic forecast.  Requires long archive of forecasts and observations.  Likely only usable at daily forecast points.  ABRFC provided data (forecasts and observed) for 12 points for 10 year period.  DJ Seo and Satish Regonda primary players.

HMOS Ensemble Processor Reflect meteorological & hydrological uncertainties Deterministic forecasts of precipitation, temperature Deterministic forecasts of streamflow Ensemble traces of streamflow Weather forecasts Correct bias, account for all uncertainties Deterministic Preprocessor Hydrologic Models HMOS State Updating/ Data Assimilation

Observation Single value ensemble mean forecast Oper. Forecast Ensem. mean Number of ensembles 2000, Regime moves from low to high Line numbers  Percentiles 1 – 0 th (minimum), 2 – 1 th, 3 – 5 th, th, 5 – 50 th 6 – 75 th, 7 – 95 th, 8 – 99 th, 9 – 100 th ( maximum)

 Fully functional new system in place across Southern Region.  Pros:  Much faster and capable than previous system  Allows for creation and distribution to web page of graphics.  Allows for >90% functionality (No FOP, no ESRI, etc)

 Cons:  Region/NOAA required security patches/updates are killing the effectiveness of the system. Requires tremendous resources.  Future of the system is very much up in the air with AWIPS2  Where does SR system fit in with “new” national project???

 ABRFC started using P1 in Oct 1996  Previous years/months were created using Stage 3  DMIP1 showed different biases pre/post Oct 1996  ABRFC wants consistent bias in gridded data sets  ABRFC also wants to leverage current knowledge of precipitation processing for early years; eliminate obvious bad data  Hope is to rerun bigger events (pre Oct 10\1996) using P3

 Initial team meetings showed project to be complex and time consuming  Needed new software and data restoration  In early 2000s, ABRFC deleted all but 6 hourly PC and HG data from older archive db due to space limitations, wrote to tape  Need to restore hourly data into new archive db on ax  Restore data off old tapes  Write shef encoding software  Process thru shefdecoder – “clean entry”

 James Paul has already written application to access ax and create gage files needed for RetroP3  Next step is to write software to create mosaic of old DPAs  Likely pick an event or two to test, using human qc and intelligence  If testing is successful, final step is human processing of any/all hours  Very labor intensive, but outcome worth it

 James Paul has also written a PostP3 application…needs additional testing and coding  ABRFC eventually plans to develop a gridded version of local bias for WFOS  Latest hour  Average of Last 6 hours  Average of Last 24 hours

 ABRFC has been collaborating with NSSL for several years now regarding Q2  Goal of Q2 is to create an automated QPE for the entire lower 48 every 5 minutes; main goal is to aid in the flash flood arena.  NSSL is thinking beyond the box, ie different z-r relationships for different areas depending on soundings, etc.  ABRFC is downloading xmrgs of data to compare to our QPEs

 ABRFC will start sending “bad gage” list soon for automtic inclusion into analysis.  NSSL in no way intends to compete with RFC produced QPE  ABRFC’s initial impressions are that the QPE is very good, esp for an automated process; AP removal is excellent.  Web site :

 Website is useful operationally, as one can “review” echos from “yesterday”.  Excellent archive of both qpe and radar echos.  Since this method will have real-time gages/biases input, along with varying ZRs, and will be updated every 5 minutes, it shows real promise as a precipitation source for the Flash Flood program.