Outline

1
Outline
Precipitation Estimation by Radar Over Complex
Terrain
David P. Jorgensen NOAA/NSSL - Norman, OK David
Kingsmill Brooks Martner NOAA/ESRL - Boulder, CO

• Project description
• QPE procedure
• Results Future Work

2
Motivation
Precipitation Estimation by Radar Over Complex
Terrain

• Evaluate role of shorter-wavelength gap-filling
  radars in improving QPE over network (WSR-88D)
  radars
• Evaluate different approaches in correcting for
  bright-band effects (i.e., VPR techniques)
• Plug QPE into distributed hydro models to
  quantitatively evaluate QPE based on predictions
  of river flow

3
HydroMet Testbed Project

• Evaluate role of gap-filing radars to improve QPE

Western U.S
4
Portable Radars
NSSL C-Band
ESRL X-Pol

• Non polarized
• 1.5 circular beamwidth
• 111 km max range

• Polarized
• 1.0 circular beamwidth
• 40 km max range

5
HMT Specific Z-R Relationship

• Distrometer located at Colfax about 12 km from
  both SMART-R and XPOL
• 12 Intensive Operational Periods (rain events)
  from 29 November 2005 to 3 March 2006
• 10,000 1-s distrometer records in the IOPs

Z100R1.76
6
Concept of Hybrid Scans

• Use high resolution digital terrain data to find
  lowest unblocked beam for each azimuth
• VCP-12 scans (same as local WSR-88Ds)
• Beam must clear terrain by 100 m

7
SMART-R Radar Beam Heights
radar
8
Idealize Vertical Profile of Reflectivity
?Z 6.8 dBZ - 0.05 x Range ?Z1 1.5 dBZ Ice
Slope 5.5 dBZ/km
9
Hybrid Reflectivity Examples
Blockage by trees
Total blockage by trees
10
Example of VPR Effect
Raw Reflectivity
VPR Corrected
11
QPE Comparison to WSR-88 D (KDAX)
1st event high freezing level
2nd event low freezing level
3
Freezing Level Height km
2
1
12
Raingages
13
Radar vrs Rain Gage Analysis
1st event high freezing level
2nd event low freezing level
Radar underestimate
Radar (slightly) overestimate
14
Conclusions

• WSR-88D radar-derived QPE compares well with the
  gap radars when in rain events (freezing level gt
  2.5 km)
• WSR-88D underestimates gap radar QPE when
  majority of the basin is snow (freezing level lt
  1.6 km)
• Compared to gages (equivalent melted precip) the
  gap radars slightly overestimate QPE for higher
  freezing level events (evaporation?)
• All radars underestimate QPE in low freezing
  level events (VPR model inadequacy?)