Radar QPE Working Group

1. Radar QPE Working Group Moderator:Dan Berkowitz, Applications Branch Radar Operations Center

2. Radar QPE Working Group Objectives • Determine priorities for (Level II) base data improvement • Determine priorities for (Level III) products • Recommend improvements to National Mosaic Multisensor QPE (NMQ) for “Next Generation QPE” (Q2) • Create a working group to develop required OSI Process documents with respect to radar improvements

3. Uncertainties in Radar Precip. Estimation (abbreviated list) • Complete or partial beam blockage • Beam propagation path – height of sample • Mixed precipitation types (hail, rain, and/or snow) • Beam not filled with precipitation • Evaporation near the ground • Detection of non-meteorological targets(ground, birds, bugs, etc.) • Displacement of radar sample relative to a ground location (rain gauge) due to wind shear • It is expected that some of these problems will be rectified by dual polarization radar.

4. 1. Priorities for Base Data Improvement • Calibration problems – • We recommend WSR-88D Hotline be proactive at monitoring systems using the Reflectivity Comparison tool. Even though this support may be limited to 7 a.m. to 7 p.m. Central Time on weekdays (when meteorologists are on duty), this should be done routinely. • Clutter management problems • This is an ongoing training issue.

5. 1. Priorities for Base Data Improvement (cont’d) • Scan strategies or volume coverage patterns New VCPs with lower elevation angles are needed for: • Mountain-top radar locations • Detection of snowfall at numerous locations • Ground clutter mitigation at RDA • Research is needed to determine value of GMAP applied to fuzzy logic-identified AP clutter (NCAR-proposed Clutter Filter Decision Support). • Research is needed to determine quality of dual polarization clutter mitigation to see if NCAR software adds any value.

6. 2. Priorities for RPG-created Products • Probabilistic QPE products • PQPE could be provided for educated users but only after deterministic methods are improved. PQPE should not replace deterministic QPE products. • Snowfall (digital snowfall accumulation) • A digital snowfall product is needed by RFCs. • Automated R(Zh) selection (a.k.a. Z-R or Z/R relationship) and/or MXPRA selection • This is a good idea but needs research to determine when each relationship should be used. Environmental data can come from soundings, the RUC model, and from an operator.

7. 2. Priorities for RPG-created Products (cont’d) • Guidance for PPS Adaptable Parameters (CLUTTHRESH, RAINZ, RAINA, exclusion zones (for wind farms, highways, industrial plumes), and when it is good/bad to apply Gauge/Radar Mean Field Bias) • There is an ongoing need for training on these parameters. No software changes are needed.

8. 3. Suggested NMQ Improvements(with respect to radar products) • Automated R(Zh) selection (a.k.a. Z-R or Z/R relationship) • This is a good idea but needs research to determine when each relationship should be used. Environmental data can come from soundings, the RUC model, and from an operator. • Bias application • We like the ability to apply sectorized, local bias. As with MPE-generated bias, users should know the source(s) of the bias calculation (i.e., the number and location of gauge-radar pairs).

9. 4. Operations and Services Improvement (OSI) Process Volunteers are needed to help prepare • Statement of Need (SON) • Concept of Operations (ConOps) • Business Case Analysis • So far, we have gotten no-one (except myself). Are you interested? Please let me know.