Which do you trust more: a radar echo 2km above ... - MeteoSchweiz

Federal Department of Home Affairs FDHA
Federal Office of Meteorology and Climatology MeteoSwiss
Das Radar Ensemble
auf hydrologischer Wanderschaft
Urs Germann, MeteoSwiss, Locarno-Monti
Dank an
M Zappa (WSL), I Zawadzki, M Berenguer (McGill Montréal), FOEN.
Radar+Satelllite team: M Boscacci, A Hering, I Giunta, L Panziera, M Gabella, L Clementi
J Joss

High resolution in 4 dimensions
2
12km
0km
Groundview: precipitation rate 1km x 5min
Sideviews: max reflectivity 2km x 5min
dBZ
55
mm/h
100
black symbols: lightning
Quantitative estimation of
precipitation at ground?
Systematic objective largesample
verification
(daily rainfall, all days!, May-Oct)
40
25
10
1
Bias Stdev ETS
% factor %
0.3mm
1997 -43 2.5 40
2004 -1 1.7 63
13 0.2
18 June 2006 100km
Boscacci, Intranet
Joss et al, vdf, 1998
Germann+Joss, Springer, 2004
Germann et al, QJRMS, 2006

Uncertainty [dB]
8dB
6
4
2
Uncertainty everywhere
Uncertainty of point precipitation
measurement in N-Ticino
(otl, mag, cim, com, hir, pio, roe, sbe)
2.2km 6.4km 10.7km
0dB
0 2 4 6 8 10 12
Distance from nearest rain gauge [km]
Conclusion:
For 3h rainfall sums gauge
uncertainty reaches that of
radar at separation distance
of about (N-Ticino)
2.2km for spatial
variability of 2 Sep 05,
6.4km for spatial
variability of 19-22 Aug 05,
10.7km for spatial
variability of 14 Jun 05.
Remember: Average
distance from nearest
gauge in Switzerland is
12km
3

Use radar for hydrology?
4
Yes, if
- catchment is small (say,

Think ensemble
5
Radar
ensemble
vary
sligthly
?
Ensemble of runoff
Rain map
?
?
Runoff
model
100 m 3 /s
50 m 3 /s
Time

Radar ensemble precipitation estimation
6
original field
(unperturbed)
estimate of
radar error for
each point in
space and time
(error
variances)
“deterministic”
stochastic
simulation of
error field
Singular-value decomposition
of error covariance matrix
+ auto-regressive filter
perturbation
field
with correct
space-time
variances and
covariances
estimate of how
errors are
correlated in
space and time
(error
covariances)
Produce many
members, the
spread among
which represents
the uncertainty
in radar
precipitation
estimates.
probabilistic
ensemble member
(perturbed)

3 ensemble members (example)
perturbation fields (from stochastic simulation)
7
+
original field
(unperturbed)
-8
dB 0 8
=
ensemble members (perturbed precipitation fields)
0.2
1 10 100
mm in 1h
0.2
1 10 100
mm in 1h

Radar ensemble implementation
8
Automatically running in
real-time since May 2007
(MAP D-PHASE,
with M Zappa WSL)
As far as we
know, the 1st
real-time
experiment of
this type
worldwide.
Germann et al, 2008

Questions
9
Does radar reach accuracy of raingauges for modelling runoff of Pincascia?
Does radar ensemble correctly represent true radar uncertainty?
Objective verification using 1 year of data
from operational coupling
of radar-ensemble and runoff model
for Pincascia catchment (44km 2 ).
(All days are considered. No subjective selection of events.)
FOEN rivergauge of Pincascia river in Lavertezzo

Does radar reach accuracy of raingauges for modelling runoff of Pincascia?
YES…
10
Radar
Raingauge
Bias -10%
Stdev 2.1dB
Bias -36%
Stdev 2.0dB

Does radar ensemble correctly represent true radar uncertainty?
YES…
11
Radar
Radar-Ensemble
Bias -10%
Stdev 2.1dB
Bias +3%
Stdev 2.1dB

Collaboration with Canton of Ticino
12
Radar
precipitation
estimates for
subcatchments of
Lago di Lugano
(=Ceresio).
with A Salvetti,
Ufficio dei corsi d‘acqua,
Bellinzona

Collaboration with FOEN (BAFU)
13
Radar
precipitation
estimates for
subcatchments of
Rhine.
with S Vogt,
FOEN, Bern

14
Does radar reach accuracy of raingauges for modelling runoff of Pincascia?
Does radar ensemble correctly represent true radar uncertainty?
YES…
YES…