RadarDerived Precipitation Part 4

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Radar-Derived PrecipitationPart 4

• I. Radar Climatology
• II. Radar Representation of Precipitation
• III. WSR-88D, PPS
• IV. PPS Adjustment, Limitations
• V. Effective Use

Hydrometeorology 99-2 Matt Kelsch Tuesday, 22
June 1999 kelsch_at_comet.ucar.edu
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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

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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 mi2
• Accumulations are estimated from reflectivities
  using an empirical Z-R relationship
• Rain gauges sample
• Continuously
• At the surface
• Over an area less than 1 ft2
• Accumulations are measurements with the error
  factors associated with the gauge type

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Stage I PPS

• 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 _at_ 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.

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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 gt13mm
  (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 gt13mm (0.5 in)
• Brandes and Wilson (1979) 75 within factor of
  2

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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
  gt0.1) had data disruptions during storms

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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.

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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.

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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.