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EGPM Algorithms: fundamentals for extratropical precipitation retrievals

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Mid- and high-latitudes experience greater seasonality ... 7th January 2004. Freezing ... Analysing high-quality mid-latitude radar data European and ... – PowerPoint PPT presentation

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Title: EGPM Algorithms: fundamentals for extratropical precipitation retrievals


1
EGPM Algorithmsfundamentals for extra-tropical
precipitation retrievals
  • Chris Kidd
  • The University of Birmingham
  • EGPM-MAG

2
The ideal world (where we would like to be)
3
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4
Into the unknown?
  • TRMM
  • Relatively safe environment steep rainfall
    gradients, with medium-heavy rainfall.

Convergence of results BUT are these politically
or scientifically correct? (EZ)
What lies outside the Tropics?
5
What can we expect?
6
Precipitation regimes
7
ECMWF model rainfall estimates
8
Seasonality
  • Mid- and high-latitudes experience greater
    seasonality than the Tropics
  • day-to-day variations can also be large
  • Implications for
  • Freezing levels (liquidfrozen ratio)
  • Surface variability (retrieval ability)
  • Snow/rain boundaries (user applications)

9
Freezing levels
Only one thing we do know is that the freezing
level is relatively stable Tom Wilheit
10
Current activities
  • Quantifying light precipitation events
    implications for retrieval accuracy
  • Analysing high-quality mid-latitude radar data
    European and Baltic radar networks (what are
    realistic mid- and high-latitude profiles?)
  • Modelling mid-latitude precipitation events
    (precipitation characteristics)
  • Identification and quantification of the
    variability of background surfaces

11
Light precipitation
Light precipitation regimes must be properly
addressed despite the contributions to the
amount being generally small
12
ECMWF (e40) vs GPI
13
ECMWF (e40) vs 3B40RT
14
Surface Variability
  • Effects and contribution of surface variability
    to precipitation retrievals.

15
Radar profile studies
  • Characteristics of mid- and high-latitude
    precipitation profiles.
  • Surface radar data from UK Chilbolton radar
    (3GHz)
  • Scheme shown here is an unsupervised
    classification scheme based upon 350,000 profiles
    during 2003
  • (TRMM produces 7 million per day!)

16
Example 1 3km maximum
17
Example 2 lt1km maximum
18
Example 3 1km maximum (light precipitation)
19
Conclusions
  • EGPM will concentrate upon
  • Light/medium precipitation retrievals
  • Heavy precipitation events for flood forecasting
    applications (esp. Mediterranean region) 15
    minute data requirement
  • Snow retrievals including precipitation over
    cold surfaces
  • through the combination of imaging and sounding
    channels, and the radar.

Ultimately, algorithms/techniques must not only
be physically correct, but also intelligently
sophisticated
20
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21
ECMWF (e40) vs 3B41RT
22
ECMWF (e40) vs 3B42RT
23
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24
Freezing level variation
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