Precipitation Processing in NWSRFS

1. Precipitation Processing in NWSRFS • Data Collection • SHEF Format • MAP Computation • Putting it all together

2. Precipitation Gage Networks • Cooperative Networks (NWS) • Automated Surface Observing System (ASOS) • GOES Data Collection Platform (DCP) • Alert

3. NWS Cooperative Network • 11,000 Sites in the U.S. • Manual Observations once daily • Archiving and Publication by NCDC • Transmission to local WFO • Standard 8” gage is most common

4. NWS Cooperative Network

5. NWS Cooperative Network • Potential Problems • Manual measurement errors • Transcription errors • Observation Time problems

6. ASOS • More than 880 sites in US • Located at airports - mainly used for aviation • Precipitation, wind, dew point, visibility, cloudiness • Transmission by VHF or satellite • Tipping bucket gage

7. ASOS

8. ASOS • Potential Problems • Frozen precipitation may be missed when a heater is used • Ice may clog the device and melt later • Splash may occur during heavy events

9. Tipping Bucket

10. GOES DCP • More than 10,000 sites world-wide • DCP most often refers to automated platforms transmitting via GOES • Various manufacturers in the U.S. • Gages owned by many federal and local agencies

11. GOES DCP • Observations stored at 15-minute intervals • Pre-set transmission times - 1,2,3,4,6-hour • Random transmissions • Tipping bucket gage • Type and accuracy may vary by manufacturer

12. GOES DCP

13. GOES DCP • Potential Problems • Transmission times may not match with model run times • Decoding problems • Batteries or solar recharging may fail • Vandalism

14. ALERT • Cooperative program initiated by CNRFC in 1970s • Transmission by radio telemetry • Mostly installed in flood prone areas

15. ALERT

16. ALERT • Potential problems • Double reading from corrupt signals • Interference from other RF sources

17. Issues in Precipitation Data Collection • Effects of freezing temperatures • Hail • Snow • Sleet • Ice pellets

18. Issues in Precipitation Data Collection • Gage Location • General exposure guidelines • Protection from wind • Vegetation interception

19. Gage Location

20. Issues in Precipitation Data Collection • Gage Density • Convective vs. frontal events • Multiple cells • Orographic effects

21. Standard Hydrometeorological Exchange Format - SHEF • Documented set of rules for coding hydromet data • For real-time use • Self-descriptive format • Designed for interagency sharing of information

22. Standard Hydrometeorological Exchange Format - SHEF • Basic Formats • .A - single stations, multiple parameters • .B - multiple stations, multiple parameters, header driven • .E - single station, single parameter, evenly spaced time series

23. SHEF - .A Format .A DZOTP 20030326 CS DH1500/DUS/ HG 4.161667 .A MTOTP 20030327 CS DH0000/DUS/ HG 6.110000 .A NLCTP 20030326 CS DH1800/DUS/ PPQ 2.250000 .A CDRNL 20030327 CS DH0600/DUS/ QR 1.206000 .A VSCCL 20030327 CS DH0600/DUS/ HP 247.840000 .A PSANL 20030327 CS DH0600/DUS/ HP 228.440000 .A LBLTP 20030327 CS DH0600/DUS/ HP 85.480000 .A AMSCL 20030327 CS DH0600/DUS/ QTD 13.000000 .A LBLTP 20030327 CS DH0600/DUS/ QTD 0.600000

24. SHEF - .B Format .B CNA 011027 M DH0600/DUS/ HP/QTD/QID/QDD : ID POOL_ELEV OUTFLOW INFLOW LDCSI 250.05/78.90/0.55/ MHGSI 131.94/95.30/101.32/2.00/ JODSI 105.62/25.40/2.80/ .END .B CNA 011028 M DH0600/DUS/ HP/QTD/QID/QDD : ID POOL_ELEV OUTFLOW INFLOW LDCSI 249.96/68.60/27.57/ MHGSI 131.90/116.60/54.63/17.01/ JODSI 105.56/25.30/5.27/ .END END

25. SHEF - .E Format .E BTPCH 011027 M DH0600/DUS/ PP/DID1/0.00/0.00/0.00 .E CNDCH 011027 M DH0600/DUS/ PP/DID1/0.00/0.00/0.00 .E RVGCH 011027 M DH0600/DUS/ PP/DID1/M/3.00/M .E URPCH 011027 M DH0600/DUS/ PP/DID1/M/M/M .E CHXSI 011027 M DH0600/DUS/ PP/DID1/0.00/0.00/0.00 .E VIRT 011026 M DH1200/DUS/ PPQ/DIH06/0.05/0.15/0.40/0.40

26. Operational Forecast System (OFS) Version 5.0 User Initiation HYDROLOGIC COMMAND LANGUAGE NMC/ Hydro- Synoptic Files Synoptic T/T Preprocessor Data Utility Processed Data Utility GOES/ NWSRFS Interim File GOES/ CADAS T/T Preprocessor Database Read/Write System Processed Database Read/Write System Preprocessor Functions Forecast Functions Nat’l 6-Hr MOR File MOR T/T Pre-Processor Parametric Database Forecast Parametric Database Pre-Processor Database Processed Database Rating Curve Data Carryover Data NMC FCST Temp File FCST Temp T/T Preprocessor Parameter Storage Program Forecast Component Forecast Parameter Storage Program Cleanup, Re-order & Compress SHEF Decode and Transfer Parametric Input RJE SHEF Input Parametric Input Preprocessor Component Data Entry Component

27. NWSRFS Keys • 6-hour time step • Programs - • Database initialization – ppinit, fcinit • Forecast program – fcst • Utilities – ppdutil, prdutil

28. NWSRFS Keys • fcst functions - • FCEXEC – runs the forecast program • MAT – computes mean areal temperature time series from point data • RRS – creates river, reservoir, snow time series • FMAP – writes future mean areal precipitation to the PDB • MAP – computes mean areal precipitation

29. NWSRFS Keys • MAP Techniques - • Timing – STARTRUN, LSTCMPDY, LSTALLOW • Computational Control – CONVEC, ESTTULSA, PP24TIME • QC – PP24MAX, PRTPP24, PRTPP6

30. OFS MAP Preprocessor Function • Used for real-time operational forecasting • Currently computes only 6-hour MAP • Uses as inputs: • Total daily precipitation (or current portion of partial days) • Precipitation at 1-, 3-, and 6-hour stations • Runs from STARTRUN to LSTCMPDY

31. MAP Processing Steps • For each full day • Make preliminary checks • Can daily total be used? • Is daily total larger than PP24MAX

32. MAP Processing Steps • Make preliminary adjustments and estimates • Apply correction factors • Set missing data to zero if requested • Convert 1- and 3-hour stations to 6-hour • Use 6-hour values to compute daily totals if necessary

33. MAP Processing Steps • Estimate missing daily totals for daily stations • Use surrounding stations with observed values

34. MAP Processing Steps Where: P = precipitation x = station being estimated i = estimator station P = monthly characteristics w = weight n = number of estimators

35. MAP Processing Steps Weighting options: w = 1 / d2i-x CONVEC technique on = use closest station in each quadrant CONVEC technique off = use stations within a specified radius

36. MAP Processing Steps • Calculate normalized values and estimate missing values at 6-hour stations • Use daily to fill single missing 6-hour period • Compute 6-hour normalized values

37. MAP Processing Steps • Calculate normalized values and estimate missing values at 6-hour stations (cont.) • If no stations nearby with normalized values, set to uniform distribution • For stations with some 6-hour data and a daily total, compute the normalized values for observed 6-hour periods • For other periods, use surrounding stations to estimate and adjust to sum to 1.0

38. MAP Processing Steps • Compute MAP from station weights • Compute daily MAP • Distribute into 6-hour periods based on “timing weights” using 6-hour normalized values

39. MAP Output >>>>>>>> @COMP MAP 1NWSRFS FORECAST SYSTEM - PROGRAM FCST (VERSION: OB2-r23L - 04/04/03) USER=LEMPA 0 MAP FUNCTION RUN PERIOD 08/21/2003-07EST THRU 08/27/2003-07EST FOR CARRYOVER GROUP LEMPA 15 MAP AREAS THE FOLLOWING RUN OPTIONS ARE TURNED ON-- TECHNIQUE DESCRIPTION --------- ----------- PP24MAX DAILY PRECIP TOTALS EXCEEDING 20.00 INCHES NOT USED PRTPP24 PRINT DATA FOR STATIONS WITH ONLY 24 HR PRECIPITATION PRTPP6 PRINT DATA FOR STATIONS WITH 6 AND 24 HR PRECIPITATION PRTMAP PRINT COMPUTED MAP VALUES

40. MAP Output 8/22/2003- 6CST DAILY TOTALS ARE IN MM STATION NAME STATE ID DAILY NORMALIZED CODE ------------ ----- -- ----- ---------- ---- lasflores - sumpul CH LAFLORES 53. 0.0 0.0 1.0 0.0 las cruces - ostua JU CRUCES 34. .00 .00 .99 .01 mocal - mocal LE MOCAL 15. 0.0 0.0 1.0 0.0 tamarindo lempa LI TAMARIND 2. 0.0 0.0 1.0 0.0 citala - lempa SA CITALA 5. .00 .29 .71 .00 zapotillo - lempa SA ZAPOTILO 2. 0.0 0.0 1.0 0.0 5 de noviembre CA 5DENOVIE 42.E .01 .00 .99 .00 E la palma CH LAPALMA 3.E .00 .24 .76 .00 E nueva concepcion CH NUEVACON 0.E 0.0 0.0 1.0 0.0 E

41. MAP Computation Methods of station weighting • Thiessen polygon • Gridpoint weighting • Pre-determined weights

42. NWSRFS Applications

43. NWSRFS Applications • Mexico • Rain gages collected manually • Phone, radio communication to regional office • Data entered into central database via web page • SHEF posted to NWSRFS database • MAP computed from predetermined station weights

44. NWSRFS Applications • El Salvador • Rain gages collected through GOES • Reservoir data via e-mail from CEL • SHEF posted to NWSRFS database • MAP computed from predetermined station weights

45. NWSRFS Applications • South Africa • Rain gages collected by DWAF • Radar data analyzed • Basin average precipitation computed • Precipitation assigned to dummy station • SHEF posted to NWSRFS database • MAP computed from that single station receiving a weight of 1.0.

46. NWSRFS Applications • Panama • Rain gages collected by ACP • Radar data analyzed • 1-hour basin average precipitation computed • 1-hour time series written directly to database Standard 6-hour MAPs also computed as a back-up.

47. NWSRFS Applications • SERFC • 1-hour MAPX files created by MPE • 1-hour MAPX and 6-hour MAP written to database • Forecaster can choose one or the other at run time MAPX most useful during convective events.