Identification of
overhanging
precipitation
Petteri Karsisto
10.9.2012
Table of contents
• Who am I?
• Introduction to problem
• Algorithm suggestions
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10.9.2012
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A few words about me…
• Student in University of Helsinki
• Major subject: meteorology
• Part-time employee at FMI
• Currently working on Master’s Thesis
• Topic: Identification of overhanging precipitation (work
title)
• Also a part of Baltrad+
• Still a plenty of studies left…
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10.9.2012
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The problem
• Overhanging precipitation: Precipitation is measured
by a radar, but the raindrops don’t reach the ground
i.e. ”precipitation” in radar bin, fair weather at ground.
• A practical definition for OP: Precipitation is found
somewhere in a vertical column, but not near the
ground level
• This allows us to forget advection of hydrometeors
• Any correction increasing the measured reflectivity
(such as VPR correction at long ranges) will make the
OP error even worse.
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Detection algorithm overview
• These are still a work in progress!
• This presentation tries to give a rough idea
• Still a lot of work needs to be done
• Some pretty pictures could be very helpful…
• Suggestions are welcome
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• Basic idea:
• Input: OP observed somewhere (e.g. in VPR, in PPI scans of
multiple elevation angles, in neighboring radar).
• A bunch of separate algoritms for variable measurement
circumstances. Output of every algorithm:
• ”What is the probability of each bin of being OP and not actual
rain?”
• Multiple probability estimates are combined to a single probability
• OP can be removed automatically depending on the application
dependent probability threshold of OP.
• Note: OP must be detected at least somewhere e.g. with VPR
profiling
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Algorithm 1: A probability function
• Study radar beams with different elevation angles
• Find out the bins between r_max and r_min
• r_max = r(h_1 < 500 m), h_1 = height of lowest beam
• r_min = r(h_2 > 5 km), h_2 = height of highest beam
• Check the bins in same ”air column”
• OP: dBZ > threshold (can be chosen) in some bin, but
not in the bin nearest the ground
• Rain: dBZ > threshold in every bin whose height < 2
km
• Create a probability function P(dBZ_max, h_OP)
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Algorithm 1: A probability function
• Seems promising
• A qualitative study, using 8 cases where OP is
detected somewhere of the range of at least one radar
in Finland
• For dBZ: (first guesses)
• If threshold = 10 dBZ -> Exponential function
• If threshold = -10 dBZ -> Gaussian function
• Coefficients are not yet calculated
• A rule of thumb: if detected dBZ > 25 dB, then it is
almost certain to be precipitation at ground.
• For height: analysis is still TBD
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Algorithm 2: Information from weather stations
• 10 minute rain intensities are measured all around
Finland -> they provide information about rain
• Basic idea: check if there’s rain echo over a station
and if there’s rain measured at the station or not
-> Find OP
• If OP is detected, then generate probability for OP
• As stations are point measurements the probability
has to be spreaded over multiple bins
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Algorithm 3: VPR profile extrapolation
• Use diagnosed VPR profiles above radars
• Try to answer these questions:
• If radar A has OP, then how often radar B also has
OP?
• If radar A has OP, then how often radar B also has OP
after a certain amount of time?
• Can we use OP observation from radars A and B to
predict the appearance of OP at radar C?
• Then use the results to create a rough probability
function for OP, as a function of time and distance
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