1. 49 COMET Hydrometeorology 00-1 Matt Kelsch Tuesday, 19 October 1999 kelsch@comet.ucar.edu Radar-Derived Precipitation Part 3 I.Radar Representation of Precipitation II.WSR-88D, PPS III.PPS Adjustment, Limitations IV.Effective Use

2. 50 IV.Stage I PPS Module 4:Precipitation Adjustment Automated rain gauges are polled at a set time interval (once per hour) and used to determine if a bias exists in the radar-derived accumulation field. Gauge reports are matched with radar estimate for that area (9 nearest radar bins) The method (using the Kalman Filter) is designed to identify a single, representative radar bias If a bias is determined to exist, the entire radar- derived accumulation field is adjusted accordingly. Accurate and representative gauge reports are essential

3. 51

4. 52 Radar-Rain Gauge Comparisons Radar samples a volume of the atmosphere –At discrete intervals –Up to several thousands feet AGL –Over a surface area which may exceed 1 mi 2 Accumulations are estimated from reflectivities using an empirical Z-R relationship Rain gauges sample –Continuously –At the surface –Over an area less than 1 ft 2 Accumulations are measurements with the error factors associated with the gauge type

5. 53 Limitations Gauges provide inadequate representation of the mesoscale structure of precipitation The vertical distribution of precipitation sampled by radar may be inadequate… –~l km above the ground @ 75 km distance – may “look over the top” of stratiform precipitation – significant evaporation may occur beneath radar beam – problem is greater where terrain blocking exists Enhanced radar return occurs in melting layer/bright band. Stage I PPS

6. 54

7. 55 Forecast Systems Laboratory (FSL) Radar/Rain Gauge Comparison at FSL for Convection: With “known” bad gauge reports manually removed: –71% within a factor of 2 –77% within a factor of 2 (67% within factor of 1.25) when either radar or gauge amount is >13mm (0.5 in) With “known” bad gauge reports NOT removed: –77% within a factor of 2 –51% within a factor of 2 when either gauge or radar amount is >13mm (0.5 in) *Brandes and Wilson (1979): 75% within factor of 2

8. 56 Rain Gauges Automated gauges - Two main problems: (1)Data disruptions cause missing periods of 5-20 min during height of storm. –Underestimations by gauge (2)Noise in communication lines from lightning cause false reports. –Overestimations by gauge Summer 1988: Matt Kelsch, Denice Walker, Erik Rasmussen, Ken Heideman Wedge gauges at BOU, LVE, PTL, LGM, ERI –False reports verified at PTL, ERI 18 out of 22 significant rain days (3 sites >0.1”) had data disruptions during storms

9. 57

10. 58

11. 59

12. 60 Stage 1 PPS Limitation (cont.) Hail enhances radar reflectivity resulting in the derivation of anomalously high rainfall rates. –Accumulation may be overestimated by more than an order of magnitude –Threshold to correct anomalous rainfall rates may cause underestimation of atypical heavy rain events –Problem varies with site, season, and ambient conditions Radar bias adjustments only work for systematic errors when the bias is uniform across the radar domain. Terrain blocking.

13. 61

14. 62 Stage 1 PPS Limitation (cont.) Hail enhances radar reflectivity resulting in the derivation of anomalously high rainfall rates. –Accumulation may be overestimated by more than an order of magnitude –Threshold to correct anomalous rainfall rates may cause underestimation of atypical heavy rain events –Problem varies with site, season, and ambient conditions Radar bias adjustments only work for systematic errors when the bias is uniform across the radar domain. Terrain blocking.

15. 63

16. 64

17. 65

18. 66

19. 67 Adaptation Parameters: The adaptation parameter philosophy assists with general variations associated with site and season (coastal plain versus semi-arid prairie), but cannot easily account for atypical events within the climatology of a particular site or season.