1. QPF & WinQPF/HAS-QPF (with apologies to Dave Ondrejik and thanks to Pete Manousos, although he may not know it) Presented during COMET Hydrometeorology Course 99-02 Your Operator Chris Bovitz, Hydrologic Forecaster West Gulf River Forecast Center, Fort Worth, Texas Safe - Reliable - Courteous

2. WinQPF/HAS-QPF n n Goal of presentation – –History of QPF project – –Origins of HAS unit/function – –Origins of WinQPF and HAS-QPF – –QPF Verification – –Probabilistic QPF – –A forecasting technique

3. Intro: Terminology n n Mean Areal Precipitation (MAP) – –Precipitation accumulation spatially and temporally averaged over a defined region, usually a drainage basin n n Future Mean Areal Precipitation (FMAP) – –(a.k.a. QPF) Forecast precipitation accumulations spatially and temporally averaged over a defined area. n n Future Mean Areal Temperature (FMAT) – –Forecast temperatures spatially & temporally averaged over an area.

4. Goal of RFC QPF Program n n To accurately produce GRIDDED FMAP/FMAT for each subbasin for use in river forecast model

5. History of QPF n n Hydrologic forecasts without QPF

6. Hydrologic Forecasts Prior to QPF n n Used only observed amounts through 12Z n n Ignored that it could still be raining, or that rain was certain n n Led to stair-stepped river forecasts during sustained rain events

7. Example of “Stair Stepping” There must be a better way

8. The Origin of QPF n n QPF initiated in the 1970s n n Event-driven – –Composed only during significant events (but what’s significant?) n n One QPF value supplied per basin – –In 6-hour increments (up to 72 hours) n n Matches time step of RFC river model – –QPF manually entered into RFC model in tabular form n n Resulted in 2 forecasts produced by RFC – –Official (without QPF) and Contingency (with QPF) n n Gave forecasters “what-if” scenarios n n But which forecast is the official forecast?

9. QPF Begins to Evolve n n RFCs wanted WSFO input – –Wanted opinion of “local experts,” i. e., WSFO meteorologists with expertise in forecasting their areas – –At this time, RFCs were still staffed mainly with hydrologists (no designated meteorologists) n n Critical Flood Support Office (CFSO) were created to coordinate QPF among WSFOs

10. Dawn of Daily QPF n n 1988: QPF supplied daily – –Even during dry weather – –CRW and PIT first offices to supply daily QPF (to OHRFC) n GUI created –Increased efficiency in entering and sending forecast to RFC –Developed by Matt Peroutka (CLE) –Used smaller QPF regions n Still was used at PIT as recently as 1998 n Gradually, other WFOs produced daily QPFs –Eventually became mandatory

11. HAS Unit & Function is Formed n n HAS - Hydrometeorological Analysis & Support n n Meteorologist or Met-trained hydrologist – –Need to be knowledgeable in Met to best coordinate with WFO meteorologists – –Need to be familiar with Hydro to brief fellow hydrologists

12. HAS Forecaster Duties n n Produce best possible precipitation data set for use in hydrologic models n n Produce daily FMAP (QPF) – –With updates if needed or requested by hydrologists or WFO n n Coordinate with RFC Senior Duty Hydrologist (SDH) – –Primarily via briefings n n Produce daily HMD (Hydrometeorological Discussion) – –Allows other WFOs and public to know about QPF used in river forecasts and the current state of the rivers in RFC’s area of responsibility n n Other duties – –Coordinate with WFOs via telephone or hydrometeorological coordination message (HCM) – –Act as liaison between RFC hydrologists and WFO meteorologists – –Produce extended QPF – –Produce FMATs for snowmelt runoff forecasts – –Work on research projects, other RFC-WFO coordination

13. A need existed to enhance QPF entry and modification n n 1992: Risk reduction project began n n Needed ability to display multiple WFOs’ QPFs side-by-side n n Needed easy editability to facilitate HAS adjustments

14. 1993 - WinQPF Developed n n Developed by Mark Fenbers (Senior HAS, OHRFC) n n QPF entry via a Windows GUI – –Configurable for each WFO n n Allows user defined preferences – –Colors, overlays, etc. n n Computes FMAP in gridded format n n Extended QPF capability n n FMAT capability n n Transmit and archive capability n n Good stepping stone for probabilistic QPF (future)

15. HAS-QPF Developed (1994-95) n n Similar look and feel to WinQPF n n Compiled for Unix operating system on Hewlett-Packard, IBM workstations n n Used by HAS at most RFCs – –Western offices use Mountain Mapper – –Will not not be incorporated into AWIPS – –But stand-alone program does work – –New software is under development

16. QPF Verification n Key to self-calibration n Compares FMAP values to MAP values from WFOs (and RFCs) n Daily MAP sent to WFOs n Scores depend on quality of MAP values –Rain gages not always maintained –Inaccurate location (lat/lon) –Majority of reports are 24hr - leads to disaggregation problems –Algorithms make assumptions n Precipitation evenly spread over drainage basin in space and time

17. QPF Verification - How to Score? n n How do we come up with a single value which incorporates timing, amount, and areal coverage of precipitation? n n Just use ye olde POD, FAR, CSI? – –What are good POD/FAR/CSI scores during synoptic events? Landfalling tropical cyclone events? Stratiform events? Convective events? n n Difficult to draw useful conclusions from raw verification scores of individual basins n n Bayesian Correlation Score (BCS) (a.k.a Bayesian Informativeness Score - BIS) –Krzysztofowicz, Mon. Wea. Rev., 1992 –From Krzysztofowicz, Mon. Wea. Rev., 1992 –Attempts to reduce a three-dimensional problem (Areal coverage, timing, amount) into a value which can be easily compared –1=perfect forecast 0=no skill –Major contributor to BIS is standard deviation of precip climatology n n Attempts to normalize variability between different locations

18. QPF Verification - Results n n On average, how do we do? – –Major events are underforecasted – –Minor events are overforecasted n n Why? – –Underestimate scattered nature of precipitation – –“Trained” to seek the highest value – –Hard to forecast extreme events – –Point values versus mean areal values – –Personal wet/dry biases

19. QPF Verification n n Verification not only helps self-calibration, but also can answer other questions – –Are we better off with or without QPF? – –Does RFC HAS improve the WFO forecast? – –Does RFC HAS improve over NCEP? – –Do we have the skill to produce 48- or 72-hour QPF?

20. Probabilistic QPF (PQPF) n n Similar to “contingency” concept, but more specific n n Gives forecasts with different probabilities of occurring – –By exceedence fractiles (what?) n n 0.75 0.30” n n 0.50 0.75” n n 0.25 1.25” – –River forecasts will be generated the same way n n Puts the “decision-making” power in the hands of the decision makers

21. WinQPF/HAS-QPF A FORECASTING TECHNIQUE A FORECASTING TECHNIQUE