Areal rainfall statistics based on radar observations Edouard Goudenhoofdt and Laurent Delobbe Royal Meteorological Institute of Belgium (RMIB) June 3, 2013, European Conference on Severe Storms
Areal rainfall statisticsbased on radar observations
Edouard Goudenhoofdt and Laurent DelobbeRoyal Meteorological Institute of Belgium (RMIB)
June 3, 2013, European Conference on Severe Storms
RMIB operates a C-band radar since 2001
I Single-polarisation
I Doppler filtering (clutter)
I Located 600 m asl,range of 240 km
I 5-elevation every 5 min(during 2 min)
I Resolution : 1° in azimuth,250 m in range
Quantitative precipitation estimates��
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��I PCAPPI 800 m above
radar level
I Z = 200R1.6
I Hail:Z > 53 dBZ → 53 dBZ(75 mm/h)
I Cartesian grid 500 mresolution.
I Accumulation by linearinterpolation.
To be validated : clutter mitigation and profilecorrection.
Quantitative precipitation estimates��
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��I PCAPPI 800 m above
radar level
I Z = 200R1.6
I Hail:Z > 53 dBZ → 53 dBZ(75 mm/h)
I Cartesian grid 500 mresolution.
I Accumulation by linearinterpolation.
To be validated : clutter mitigation and profilecorrection.
Merging and verification with denseraingauge networks.
50 km
100 km
Radar and rain gauge networks
SPW (69)RMI(84)Radar
I hourly automaticraingauge network (blue)
I 1E 6 scale difference !I mean field bias : simple
and robustI max range 120 kmI min value 0.1 mmI min 10 valid pairs
A 8-year verification reveals relatively goodaccuracy.
Merging and verification with denseraingauge networks.
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I hourly automaticraingauge network (blue)
I 1E 6 scale difference !I mean field bias : simple
and robustI max range 120 kmI min value 0.1 mmI min 10 valid pairs
A 8-year verification reveals relatively goodaccuracy.
Mean hourly rainfall depth 2005-2012
150 100 50 0 50 100 150
150
100
50
0
50
100
150
0.06
0.07
0.08
0.09
0.10
0.11
0.12
0.13
0.14
['A
CR
R']
['bewid - 2012-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_stmeanP8Y)']
I unconditional mean(dry periods are included)
I minimum 0.07 mm(600 mm/year) in theplains
I maximum 0.14 mm(1200 mm/year) in thehills
I clear correlation withtopography (cluttereffect?)
Those results are consistent with raingaugeclimatology.
Mean hourly rainfall depth 2005-2012
180 km
0 200 400 600 800
Elevation [m]
I unconditional mean(dry periods are included)
I minimum 0.07 mm(600 mm/year) in theplains
I maximum 0.14 mm(1200 mm/year) in thehills
I clear correlation withtopography (cluttereffect?)
Those results are consistent with raingaugeclimatology.
Mean hourly rainfall depth 2005-2012
150 100 50 0 50 100 150
150
100
50
0
50
100
150
0.06
0.07
0.08
0.09
0.10
0.11
0.12
0.13
0.14
['A
CR
R']
['bewid - 2012-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_stmeanP8Y)']
I unconditional mean(dry periods are included)
I minimum 0.07 mm(600 mm/year) in theplains
I maximum 0.14 mm(1200 mm/year) in thehills
I clear correlation withtopography (cluttereffect?)
Those results are consistent with raingaugeclimatology.
Max hourly rainfall depth 2005-2012
200 100 0 100 200
200
100
0
100
200
10
15
20
25
30
35
40
45
50
55
60
['A
CR
R']
['bewid - 2013-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_stmaxP8Y)']
I High small scalevariations.
I No significant large scaletrend.
I Slightly more max inSouth-East.
Highest values are due to stationary cells and/orhail.
Max hourly rainfall depth 2005-2012
200 100 0 100 200
200
100
0
100
200
10
15
20
25
30
35
40
45
50
55
60
['A
CR
R']
['bewid - 2013-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_stmaxP8Y)']
I High small scalevariations.
I No significant large scaletrend.
I Slightly more max inSouth-East.
Highest values are due to stationary cells and/orhail.
Probability of hourly rainfall (1 mm).
150 100 50 0 50 100 150
150
100
50
0
50
100
150
1.2
1.6
2.0
2.4
2.8
3.2
3.6
4.0
%
['bewid - 2013-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_spe1P8Y)']
I ranges from 2 % to4 %
I positive effect oftopography
Highly correlated with mean hourly rainfall
Probability of hourly rainfall (1 mm).
150 100 50 0 50 100 150
150
100
50
0
50
100
150
1.2
1.6
2.0
2.4
2.8
3.2
3.6
4.0
%
['bewid - 2013-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_spe1P8Y)']
I ranges from 2 % to4 %
I positive effect oftopography
Highly correlated with mean hourly rainfall
Probability of rainfall exceeding 10 mm.
200 100 0 100 200
200
100
0
100
200
0.016
0.024
0.032
0.040
0.048
0.056
0.064
0.072
%
['bewid - 2013-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_spe10P8Y)']
I ranges from 0.02 %to 0.06 %
I less effect oftopography
I higher probabilitySouth-East of radar
Partially correlated with max hourly rainfall
Probability of rainfall exceeding 10 mm.
200 100 0 100 200
200
100
0
100
200
0.016
0.024
0.032
0.040
0.048
0.056
0.064
0.072
%
['bewid - 2013-01-01 00:00:00 - STAT(scan1_cap_aclPT1H_mfb_spe10P8Y)']
I ranges from 0.02 %to 0.06 %
I less effect oftopography
I higher probabilitySouth-East of radar
Partially correlated with max hourly rainfall
Exceedance probability of four differentriver catchment.
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I catchment ofdifferent size
I smooth andlogarithmicbehavior
I smallest catchment: max 20 mm
I largest catchment :max 8 mm
Computation of return periods is limited (8 years).
Exceedance probability of four differentriver catchment.
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I catchment ofdifferent size
I smooth andlogarithmicbehavior
I smallest catchment: max 20 mm
I largest catchment :max 8 mm
Computation of return periods is limited (8 years).
Exceedance probability of four differentriver catchment.
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I catchment ofdifferent size
I smooth andlogarithmicbehavior
I smallest catchment: max 20 mm
I largest catchment :max 8 mm
Computation of return periods is limited (8 years).
Exceedance probability of adjacentequal-area squares.
0.1 0.2 0.5 1 2 5 10 20 50Mean rainfall depth [mm]
10-8
10-7
10-6
10-5
10-4
10-3
10-2
10-1
100
Pro
babili
ty
Area = 25 km2
I simpleapproximation of acatchment
I distance less than100 km for bestaccuracy
I space and timestationarity
I independencebetween windows?
Possibility to compute longer return periods?(theoretically 8 years x number of windows)
Exceedance probability of adjacentequal-area squares.
0.1 0.2 0.5 1 2 5 10 20 50Mean rainfall depth [mm]
10-8
10-7
10-6
10-5
10-4
10-3
10-2
10-1
100
Pro
babili
ty
Area = 100 km2
I simpleapproximation of acatchment
I distance less than100 km for bestaccuracy
I space and timestationarity
I independencebetween windows?
Possibility to compute longer return periods?(theoretically 8 years x number of windows)
Exceedance probability of adjacentequal-area squares.
0.1 0.2 0.5 1 2 5 10 20 50Mean rainfall depth [mm]
10-7
10-6
10-5
10-4
10-3
10-2
10-1
100
Pro
babili
ty
Area = 400 km2
I simpleapproximation of acatchment
I distance less than100 km for bestaccuracy
I space and timestationarity
I independencebetween windows?
Possibility to compute longer return periods?(theoretically 8 years x number of windows)
Conclusions
I Weather radar provide good areal rainfall estimates.
I Areal rainfall exceedance probability can be computed.
I Important application to river catchment.
I Longer return periods could be computed using a largerdomain.
Outlook
I Best single radar QPE reanalysis (almost ready)
I Radar composite to mitigate attenuation and beambroadening
I Effect of rainfall depth duration
I Proof using a proper theoretical framework