Verification of the BOLAM weather prediction model - adv

Adv. Geosci., 23, 93–100, 2010
www.adv-geosci.net/23/93/2010/
doi:10.5194/adgeo-23-93-2010
© Author(s) 2010. CC Attribution 3.0 License.
Advances in
Geosciences
Verification of the BOLAM weather prediction model
over the area of Cyprus
K. Savvidou1 , K. Lagouvardos2 , S. Michaelides1 , V. Kotroni2 , and P. Constantinides1
1 Meteorological
2 National
Service, Nicosia, Cyprus
Observatory of Athens, Athens, Greece
Received: 24 March 2009 – Revised: 26 August 2010 – Accepted: 10 September 2010 – Published: 4 October 2010
Abstract. The purpose of this study is the verification of the
BOLAM weather prediction model over the area of Cyprus.
The verification period spans from 1 January 2007 till 31 December 2007 and the parameters studied are: temperature,
wind and precipitation. The model forecasts are compared
to the observations recorded at three locations on the island,
where Automatic Weather Observing Systems are operated
by the Meteorological Service of Cyprus, namely, those of
Larnaka and Paphos Airports and at Athalassa. The statistical analysis includes calculation of the mean error, the mean
absolute error and the standard deviation. Based on the construction of a contingency table, the probability of detection
of a precipitation event and the false alarm rate are calculated. Finally, an example of BOLAM forecasts for a case
study of a low pressure affecting Cyprus during winter is presented and discussed.
1
Introduction
In the framework of the INTERREG RISKMED project
(Weather Risk Reduction In The Mediterranean), the Cyprus
Meteorological Service implemented the hydrostatic model
BOLAM (Bologna Limited Area Model) as the core forecast tool, in order to provide weather risk predictions over
the area of Cyprus, including its maritime region. BOLAM
weather forecast outputs are used in order to provide warnings for high impact weather (high and low temperatures,
strong winds, heavy precipitation, etc.) through a dedicated
early warning system. In the framework of this project, oneyear verification of BOLAM forecasts is performed, in order
to quantitatively estimate forecast errors. In this manner, the
model’s forecast skill is tested as a scaled representation of
Correspondence to: K. Savvidou
([email protected])
the forecast accuracy with reference to observed conditions.
The verification is performed using ground weather stations
across Cyprus, while a specific case-study with heavy precipitation over the island is investigated in more detail.
The paper is organized as follows: Sect. 2 provides a short
description of BOLAM model, as well as a description of
the verification method and data used. Section 3 provides
verification results for temperature, wind and precipitation;
Sect. 4 presents the case-study analysis. Finally, conclusions
are drawn in Sect. 5.
2
BOLAM model, verification data and methodology
The BOLAM model used in this study is described in Buzzi
et al. (1994, 1997, 1998) and Buzzi and Foschini (2000).
It is a hydrostatic model on an Arakawa C grid (rotated
lat.-lon. coordinates) and uses σ vertical coordinates. BOLAM uses an explicit microphysical scheme with two water and three ice species (Schultz, 1995), as well as the
convective parameterization scheme proposed by Kain and
Fritsch (1993), with implementation of the modifications
suggested by Spencer and Stensrud (1998), regarding the delay of downdrafts in newly developed convection.
For the operational implementation of BOLAM at the
Cyprus Meteorological Service, two grids are used:
– The coarse grid consisting of 135 × 110 points with a
0.21◦ horizontal grid interval (∼23 km), covering the
area of the Eastern Mediterranean,
– The fine grid, consisting of 130 × 140 points with 0.07◦
horizontal grid interval (∼7 km), covering the area of
Cyprus and the adjacent seas.
In the vertical, 30 levels are used in the coarse grid and
40 levels in the fine grid, with model top at about 10 hPa.
The nesting of the inner grid starts at t + 6, based on boundary conditions provided by BOLAM outer grid at 2 h interval.
Published by Copernicus Publications on behalf of the European Geosciences Union.
3
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
-2.0
Mean Error (kt)
T+
72
T+
66
T+
60
T+
54
T+
48
T+
42
T+
36
T+
30
T+
24
T+
18
Wind Speed ME for warm months
-4.0
-5.0
Lead
time
LARNAKA
ATHALASSA
T+
72
T+
66
T+
60
T+
54
T+
48
T+
42
T+
36
T+
30
T+
24
T+
18
T+
12
1.5
0.0
1.0
0.5
1.0
-1.0
0.0
0.0
-0.5
-2.0 T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
-1.0 T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
-1.0
-3.0
-1.5
-2.0
-2.0
-4.0
-2.5
-3.0
-3.0
Lead Time
1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
-2.5
-3.0
PAPHOS
LARNAKA
PAPHOS
(a)
Lead time
( b )LARNAKA
WindATHALASSA
Speed ME for warm
monthsPAPHOS
ATHALASSA
(b)
(c)
Fig.-1.01.T+12
Wind
verification:
Error for th
T+18 T+24
T+30 T+36 T+42 T+48(a)
T+54 Mean
T+60 T+66 T+72
months,
and (c) Mean Error for the warm months.
-2.0
1.0
0.0
-3.0
-4.0
-5.0
-5.0
(a)
Mean Error (kt)
1.0
-4.0
3.1
PAPHOS
(a)
-3.0
Results
LARNAKA
Wind
Speed
Mean
Wind
Speed
ME for
coldError
months
Mean Error
(kt)
Mean
Error
(kt) (kts)
Mean
Error
T+
72
T+
66
T+
60
T+
54
T+
48
T+
42
T+
36
T+
30
T+
24
T+
18
T+
12
-1.0
ATHALASSA
Mean Error (kt)
Mean Error (kt)
Mean Error (kts)
the Airports of Larnaka (33.37◦ E, 34.52◦ N) and Paphos
(32.49◦ E, 34.72◦ N) which are coastal stations, and at Atha◦
lassa (33.4◦ E, 35.1
which
is anError
inland station with eleWindN),
Speed
Mean
vation 162 m a.m.s.l. (above mean sea level). For the temperature1.0and the wind speed, the observed values were compared
0.0 the fine grid forecast values at 11 lead times: T + 12,
against
-1.0
T + 18, T + 24, . . . , T + 72, for the entire 2007. The forecast-2.0
values are selected from the nearest to the stations land
grid-3.0
box of the model. The Mean Error (ME), the Mean Absolute
Error (MAE) and their respective standard deviations
-4.0
were calculated for the whole year, but also separately for
Lead Time
the cold and warm
months of the
year. For thePAPHOS
precipitation,
ATHALASSA
LARNAKA
the comparison was performed through the use of the daily
recorded precipitation amounts
(a) at the three stations and of
BOLAM fine grid forecasts, averaged over the 5 grid boxes
Wind Speed
ME for
warm
months
in cross arrangement
around
each
station.
The ‘probability
of detection’ (POD) and the “false alarm rate” (FAR) for four
1.0
precipitation
thresholds: 1, 5, 10 and 20 mm for 2007 were
0.0
calculated.
T+
12
Mean Error (kts)
Larnaka reveals that the maximum values areskill
again
lead
which
correspond
does
notat
decrease
with
forecast
lead time
tonoted
local
noon
and
thetimes
values
are
higher
during
the w
to local noon and the values are higher during
the warmtomonths,
aroundof
4kt.
can to
be predic
period.
attributed
the weakness
theThis
model
attributed
to the weakness
of etthe
model toof Similar
predict
diurnal
cycle
the
seaof breeze.
results
concerning
the
94
K. Savvidou
al.: Verification
the
BOLAMthe
weather
prediction
modelof
over
themagnitude
area
Cyprus of wind
Similar results concerning the magnitude of
wind forecast
were
alsoverification
found by of BO
Lagouvardos
et al.errors
(2003)
for the
The
orography
fields
are
derived
from
a
terrain
data
file
with
Speed
Mean
Error
Lagouvardos et al. (2003) for the verification of BOLAMWind
model
over
Greece.
1.5
30 arc s resolution provided by the US Geological Survey
1.0
1.0
The MAE and the Standard Deviation (STDEV
(USGS).
0.5
0.0
0.0
The
and boundary
for BOLAM
outer domain(STDEV)
Theinitial
MAE
and thedata
Standard
Deviation
ofstations
the MEand
have
aall
similar
behavior
inFigs.-0.5
all three
for
lead
times
(see
2
-1.0
are
provided
by
the
operational
global
model
GFS,
at
6-h
-1.0
allintervals.
three The
stations
and for all lead times (see Figs.-2.02a, 2b).
are found
at
andThe
the lowest
highestvalues
at Larnaka.
Furthermore
-1.5
duration of the simulations is 72 h, initialized Athalassa
Athalassa
andthethe
at Larnaka. Furthermore,
should
be noted
the forecast
skill-3.0doesit not
decrease
withthat
forecast
lead time -2.0
w
every day using
00:00highest
UTC GFS data.
-2.5
-3.0
parameters
are verifiedwith
are the forecast
temperature, lead
wind time
skillThedoes
not that
decrease
-4.0within the 72 hours of the simulation
period.
speed and precipitation. The observations are provided
Lead Time
period.
by three automatic weather observing stations located at
Lead time
Wind speed
Lead time
ATHALASSA
LARNAKA
PAPHOS
(c)
PAPHOS
The forecast skillATHALASSA
of the modelLARNAKA
for the wind
is good (see
(c) error for the year, (b) mean
Fig. 1. Wind verification: (a) mean
Fig. 1a) and especially for Athalassa, where ME is less than
error for
cold months,
and (c) mean error
for the
warm months.
1. theWind
verification:
(a)
Mean
Error for th
1kt for all the lead times (1 kt(c)
= 0.514 m/s). At Paphos and Fig.
Larnaka,
the model
underestimates the
speed Error
at all months,
Fig.
1. Wind
verification:
(a)wind
Mean
for the and
year,(c)(b)
Mean
Error
for warm
the cold
Mean
Error
for the
months.
lead times with ME exhibiting a diurnal cycle. The highmonths,
and (c) Mean Error for the warm months.
Lagouvardos et al. (2003) for the verification of BOLAM
est underestimation is found at lead times which correspond
model over Greece.
at 12:00 UTC; less than 2 kt for Paphos and around 3 kt for
The MAE and the Standard Deviation (STDEV) of the ME
Larnaka. The seasonal verification (Fig. 1b and c) of the
have a similar behavior in all three stations and for all lead
model reveals that at Athalassa the wind speed is overestitimes (see Fig. 2a and b). The lowest values are found at
mated during the cold months (with ME values lower than
Athalassa and the highest at Larnaka. Furthermore, it should
1 kt) and is underestimated during the warm months (when
be noted that the forecast skill does not decrease with forecast
the ME reaches its maximum values, around 2.5 kt) at lead
lead time within the 72 h of the simulation period.
times which correspond at 18:00 UTC. The seasonal pattern
of ME at Larnaka reveals that the maximum values are noted
3.2 Temperature
again at lead times which correspond to local noon and the
values are higher during the warm months, around 4 kt. This
The temperature is underestimated by the model in all three
can be attributed to the weakness of the model to predict the
stations and at all lead times (Fig. 3a). A 24-h cyclic behavior
diurnal cycle of the sea breeze. Similar results concerning
is noted for forecast lead times of the second and third day
the magnitude of wind forecast errors were also found by
Adv. Geosci., 23, 93–100, 2010
www.adv-geosci.net/23/93/2010/
Athalassa and Larnaka is overestimated during night a
LARNAKA
PAPHOS
ATHALASSA
ATHALASSA
(a)
LARNAKA
LARNAKA
Temperature Mean Error
PAPHOS
PAPHOS
(a)
(a)
Temperature Mean Error for Cold months
Temperature Mean Error
Wind Speed STDEV of ME
1.0
2.0
(a)
(b)
0.0
T+12
T+18
T+24
T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
2.0
1.0 and (b) Standard
-1.0
Fig.
deviation of the
0.04.02. Wind verification: (a) Mean Absolute Error,
1.0
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
0.0
0.0
-2.0
-1.0
3.0 error.
Mean
-1.0 T+12
T+48
T+54
T+60
T+66T+66
T+72T+72
T+12 T+18
T+18T+24
T+24T+30
T+30T+36
T+36T+42
T+42
T+48
T+54
T+60
Mean Error
STDEV of ME
Mean
Erron
Mean
ErrorError
Mean
1.05.0
-2.02.0
-3.01.0
3.2 0.0
Temperature
-4.0
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
Lead Time
Lead time
T+72
-3.0
-1.0
-2.0
-3.0
-4.0
-2.0
-4.0
-5.0
-3.0
-6.0
2.
Temperature Mean Error for Warm months
1.
Mean Error
ATHALASSA
Mean Error
MAE
Mean Error
STDEV
of ME
The
temperature
is underestimated
bythe
thewarm
modelmon
in
largest
underestimation
is found during
4(Fig.
The temperature is underestimated by the model
in
all
three
stations
and
at
all
lead
times
A 24-h again
cyclicatbehavior
is noted for forec
which3a).
correspond
0600UTC.
K.
Savvidou
et
al.:
Verification
of
the
BOLAM
weather
prediction
model
over
the
area
of
Cyprus
95
(Fig. 3a). A 24-h cyclic behavior is noted for day
forecast
times ofperiod.
the second
andfirst
third
of thelead
simulation
For the
3 lead tim
day of the simulation period. For the first 3 lead
times,
ME isskill
lessisthan
or equal
to 1K. and the
The
best the
forecast
found
at Athalassa
Wind
Speed STDEV
of ME
Wind Speed Mean Absolute Error
Temperature
Mean Error
The best forecast skill is found at Athalassa and
the worst
Paphos.
The highest
values
of theat ME
are found
at leadabsolute
times which co
2.0
5.0
5.0
1.0
values of the ME are found at lead times which
correspond
the lowest
absolute
valuesat 0600UTC
are found and
during
nighttime1.0 (1
4.0
4.0
0.0
absolute
values
are
found
during
nighttime
(1800
and
0000UTC).
verification
reveals
(see Figs.The
3b, seasonal
3c) that during
0.0
3.0 T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
3.0
-1.0
T+
verification
reveals (see Figs. 3b, 3c) that during
the
cold
months,
the
temperature
at
Athalassa
and
Larnaka
is
overestimated
during
nigh
2.0
2.0
-1.0
-2.0
1.0 and
1.0
Athalassa
and Larnaka is overestimated duringlargest
night
underestimated
duringduring
day. The
underestimation
is found
the warm
-3.0
-2.0 m
0.0
0.0
-4.0
-3.0
largest underestimation
is found during the warm
months
at Larnaka
at lead times
which
correspond
again(4-5K)
at 0600UTC.
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
Lead Time
4
which correspond againLeadattime
0600UTC.
Lead time
0.
-1.
-2.
-3.
Lead Time
ATHALASSALead time
LARNAKA
PAPHOS
Mean Error
Mean Erron
Mean Error
not decrease within the 72-h duration
of the simulation.
Lead Time
The underestimation of the temperature by the model can
ATHALASSA
LARNAKA
PAPHOS
be attributed to the weakness of the model to predict the daily
superadiabatic warming (a)
especially during summer and the
Temperature Mean Error for Cold months
radiation cooling during winter, since the model produces
Mean Error
Warm
months
forecasts
for the temperature
at for
2 m.
Also,
the largest un2.0 Temperature
derestimation which is noted at 06:00 UTC can be associated
2.01.0
with
the time lag of the model in predicting the transition
Mean Erron
Mean Error
+66 T+72
Mean Erron
Lead time
The temperature
is underestimated
by the model in all three
stations
and at all
lead times
ATHALASSA
LARNAKA
PAPHOS
ATHALASSA
LARNAKA
PAPHOS
(b)
ATHALASSA
LARNAKA
PAPHOS
(a) ofLARNAKA
ATHALASSA
PAPHOS
(Fig. 3a). A 24-h cyclic behavior is noted(b)for forecast lead
times
the second
and third
(a) period. For the first 3 lead times,
(b)forthan
Temperature
Mean
Warmor
months
day
of the simulation
the ME
less
equal to 1K.
( is
c)Error
Fig. 2. Wind verification: (a) mean absolute error, and (b) standard
Temperature
Mean
Error
for
Warm
months
deviation
the mean
Fig.the
3. Temperature
verification:
(a) Mean
Error for th
The
bestofforecast
worst at Paphos.
The highest
absolute
(b)error.skill is found at Athalassa and
2.0
1.0
months,
and (c) Mean
Error for and
the warm
months.
of the
are found
at lead
correspond
at 0600UTC
the lowest
solute values
Error,
and
(b)ME
Standard
deviation
of times
the which
2.0
0.0
1.0
T+12 T+18and
T+24 T+30
T+36 T+42 T+48 T+54
T+60 T+66
T+72
absolute
values are found during nighttime -1.0
(1800
0000UTC).
The
seasonal
-2.0
of0.0the simulation period. For the first 3 lead times, the ME
-1.0 T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
verification
reveals
Figs.
3b,skill3c)
that during
the cold months, the temperature at
-3.0
is
less than or equal
to 1 K.(see
The best
forecast
is found
-2.0
-4.0
at
and the
worst at Paphos.
The highest absolute
-3.0Athalassa and
Athalassa
Larnaka
is overestimated
during night
and underestimated during day. The
-5.0
-4.0
values
of the ME are found at lead times which correspond
-6.0
largest
underestimation is found during the warm months at Larnaka
(4-5K) at lead times
-5.0
at
06:00 UTC and the lowest absolute values are found durLead time
-6.0
which
correspond
at 0600UTC.
ing in
nighttime
(18:00 stations
andagain
00:00 UTC).
The
seasonal
the model
all three
and
at all
leadverificatimes
Lead time
ATHALASSA
LARNAKA
PAPHOS
tion reveals (see Fig. 3b and c) that during the cold months,
(c)
oted for forecast
lead
times
of
the
second
and
third
the temperatureATHALASSA
at Athalassa LARNAKA
and LarnakaPAPHOS
is overestimated
(Mean
c) Error(a)formean
verification:
for the year,
rst 3 leadduring
times,
ME
is less during
than
or equal
to un1K. Fig. 3. Temperature
Temperature
Colderror
months
nightthe
and underestimated
day.
The largest
Temperature Mean
Error
(b)
mean
error
for
the
cold
months,
and (c) mean error
forMean
the warmError for
(
c)
Fig.
3.
Temperature
verification:
(a)
derestimation
is
found
during
the
warm
months
at
Larnaka
lassa and the worst at Paphos. The highest absolute months.2.0
K)
at lead times which
correspond again
at 06:00
UTC.
Fig.(4–5
3.1.0correspond
Temperature
verification:
(a)
Mean
Error
for theand
year,
Mean
Error
coldmonths.
months,
(c)(b)
Mean
Error
forfor
thethe
warm
mes which
at
0600UTC
and
the
lowest
1.0
The
temperature
MAE
(Fig.
4a)
has
a
periodical
behav0.0
months,
and
(c)
Mean
Error
for
the
warm
months.
T+12
T+18
T+30
T+36
T+48
T+54atT+60
T+66
T+72
nighttime
(1800
and
0000UTC).
The
seasonal
ior-1.0
with
peaks
at T+24
06:00
UTC
andT+42
low
points
18:00
UTC.
0.0
time between
the nocturnal katabatic wind to the daily preThe
highest
values
are
found
at
coastal
stations.
The
STDEV
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
) that during
the
cold
months,
the
temperature
at
-1.0wind, but this must be examined in a future study.
-2.0
vailing
of ME (Fig. 4b) follows a similar behavior, but the lowest
d duringvalues
night
underestimated
day.Once
The
-3.0 forand
-2.0
the coastal
stations are foundduring
at 00:00 UTC.
3.3
Precipitation
more,
the
verification
has
shown
that
the
forecast
skill
does
-4.0
-3.0
g the warm months at Larnaka (4-5K) at lead times
1.0
0.0
0.0
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
-1.0
-1.0 T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
www.adv-geosci.net/23/93/2010/
-2.0
-2.0
-3.0
-4.0
-3.0
-5.0
Lead time
Lead time
The results of the calculations of POD and FAR for the four
ATHALASSA
LARNAKA
PAPHOS
precipitation thresholds are shown in Table 1. As it was
expected, as the precipitation threshold
(b) increases, the POD
decreases, except at Larnaka where, an increase in POD is
noted from 5mm to 10 mm. At Larnaka, the POD is higher
than the other two stations for almost all the precipitation
thresholds. The lowest FAR is found at Athalassa (13%
Adv. Geosci., 23, 93–100, 2010
ME (Fig. 4b) follows a similar behavior, but the lowest values for the coastal stations are
found at 0000UTC. Once more, the verification has shown that the forecast skill does not
96
K. Savvidou
et al.:of
Verification
of the BOLAM weather prediction model over the area of Cyprus
decrease
within the 72-h
duration
the simulation.
Table
1. POD
and FAR for the three stations
and fortemperature
the four preTable
The ME
and MAEcan
for the hit
The
underestimation
of the
by 2.the
model
beevents.
attributed to the
5 cipitation thresholds.
weakness of the model to predict the daily superadiabaticAthalassa
warming
especially
during
Larnaka
Paphos
summer and the radiation cooling during winter, sinceMEthe model
produces
forecasts for
1.1
1.2
0.8
Precipitation
Athalassa
Larnaka
Paphos
MAEwhich
4.3 is noted
3.9 at 0600UTC
4.1
the Thresholds
temperature
atwith
2m.peaks
Also,
largest
underestimation
can
as a periodical
behavior
atthe
0600UTC
and
POD FAR
POD FAR
POD FAR
(mm)
(%) lag
(%)
(%) model
(%) ofin predicting the transition time between the
with(%)the
time
of STDEV
the
values be
areassociated
found
at (%)
coastal
stations.
The
1
88
48 wind
91
33
katabatic
to 43the daily
prevailing
wind, but this must be examined in a
or, butnocturnal
the lowest
values
for the96
coastal
stations
are
5
67
50
80
48
81
19
future
64 that
13 the forecast
89
38 skill56does
31 not
erification
has10study.
shown
20
40
33
60
40
50
80
he simulation.
Temperature STDEV of ME
STDEV of ME
Mean Absolute Error
perature by the model
can be
Temperature
MAE attributed to the
he daily superadiabatic
warming especially during
5.0
ring winter,
4.0 since the model produces forecasts for
3.0
est underestimation
which is noted at 0600UTC can
2.0
model in predicting the transition time between the
1.0
y prevailing
wind, but this must be examined in a
0.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
(a)
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
T+12 T+18 T+24 T+30 T+36 T+42 T+48 T+54 T+60 T+66 T+72
Lead time
Lead time
ATHALASSA
LARNAKA
PAPHOS
ATHALASSA
(a)
LARNAKA
PAPHOS
(a)
(b)
Fig.3.54. Temperature verification: (a) MAE, and (b) STDEV of ME.
STDEV of ME
Temperature STDEV of ME
3.0
2.5
2.0
1.5
1.0
0.5
0.0
3.3. Precipitation
(b)
Fig. 5. (a) 500 hPa geopotential height analysis at 12:00 UTC,
T+12 T+18of
T+24
T+30calculations
T+36 T+42 T+48 T+54
T+66 T+72
The results
the
ofT+60POD
and FAR
for the four precipitation thresholds are
3 February 2007. (b) Mean sea level pressure analysis at
Lead time
shown in Table 1. As it was expected, as the 12:00
precipitation
increases, the POD
UTC, 3 Februarythreshold
2007.
ATHALASSA
LARNAKA
PAPHOS
decreases, except
at Larnaka
where,
an increase
in POD is noted from 5mm to 10mm. At
(b)
4 A case-study: a depression that affected Cyprus on
Larnaka,
the POD is (a)
higher
than the other two 3stations
for almost all the precipitation
Fig. 4. Temperature verification:(b)
MAE, and (b) STDEV of ME.
February 2007
thresholds.
Theoflowest
MAE, and
(b) STDEV
ME. FAR is found at Athalassa (13% for the 10mm threshold) and at
On 3 February 2007, a diffluent upper- level trough assoPaphos
(19% for the 5mm threshold).
for the 10 mm threshold) and at Paphos (19% for the 5 mm
6 T+72
ciated with a deep surface low (998 hPa) centered south of
threshold).
Cyprus (see Fig. 5a and b) affected the area. In 12 h, it moved
It
is
also
interesting
to
present
the
results
of
the
ME
and
to thefor
east,the
leaving
theprecipitation
area in a northwestthresholds.
flow (not shown).
Table 1. POD and FAR for the three stations and
four
MAE for the hit events (forecast and observed) which are
This well organized frontal depression resulted in high accushown in Table 2.
mulation precipitation amounts, as shown in Fig. 6 (there is
values
the ME
and MAE are similar
inAthalassa
all three
accessibility toPaphos
measurements in the north part of the isD and FARThefor
theoffour
precipitation
thresholds
are noLarnaka
stations, indicating that there is not an area-dependent bias
land). In the southeast part of the island, the daily recorded
Precipitation
d, as the ofprecipitation
threshold
increases,
the POD
the model in forecasting
precipitation
over the domain
of
precipitation reached 160 mm. At Larnaka, the recorded prePOD FAR
POD FAR
POD
FAR
Thresholds
n increase
in POD is noted from
5mm to 10mm.
At cipitation
simulation.
between
15:00
and 18:00 UTC was 35.2 mm. In
order
to
evaluate
the
model’s
skill in predicting the depres(%)
(%)
(%)
(%)
(%)
(%)
(mm)
other two stations for almost all
the precipitation
sions that affected the area of Cyprus, a first comparison is
at Athalassa (13% for the 10mm threshold) and at performed between the actual surface charts and the 500 hPa
1
88 48 isobaric
96 surface
43 with
91 the model’s
33 forecasts.
5
67 50
Adv. for
Geosci.,
93–100,
2010
tations and
the23,
four
precipitation
thresholds.
10
64 13
20
40 33
thalassa Larnaka Paphos
80
89
60
48
38
40
81
56
50
19
www.adv-geosci.net/23/93/2010/
31
80
forecast surface low is very close to the actual one. It can be stated here that the model
was able to catch the evolution of the surface and upper air patterns, two days before the
synoptic event.
K. Savvidou et al.: Verification of the BOLAM weather prediction model over the area of Cyprus
97
Fig. 6. The area averaged precipitation for 3 February 2007.
Fig. 6.The area averaged precipitation for 3 February 2007.
5 Conclusions
The BOLAM coarse grid forecasts are shown in Fig. 7.
The T + 60 forecast of the 500 hPa geopotential height
Accumulated precipitation maps, provided by BOLAM fine grid, are shown in Fig. 8
Verification of model outputs is an important component in
(Fig. 7a) and of mean sea level pressure (Fig. 7b), valid at
(first
day of simulation). An examination
of theforecasting,
maps shows
good
results
as farthat
as the
the conweather
as it is
through
this phase
12:00 UTC, 3 February 2007, show the trough positioned
location
of
the
precipitation
is
concerned,
with
precipitation
amounts
exceeding
40mm
fidence to an operational model is built. The Cyprus Meteomore to the east, with respect to the verifying analysis (shown
3 hours
southernover
Cyprus
0900
and 1200UTC
(Fig. 8a)
laterthat
over
rological
Service
verifies the limited
areaand
models
it runs
in Fig. 5a), whilewithin
the surface
lowover
is predicted
the between
thethecentral
the island.
The
for the (see
third
day ofetsimulation
were
operationally
Orphanou
al., 2006); this
is thequite
first time
northeastern part of
island, part
with of
a central
pressure
of results
satisfactory,
concerns
the(shown
location ofthat
precipitation
the is
predicted
amount
wasofvery
the BOLAMbut
model
verified over
the area
Cyprus.
∼1002 hPa, 4 hPa shallower
than as
theitreal
conditions
In thisday
study,
year of BOLAM
model forecasts
over the
15mmofwithin
3 hours.
For the
of one
simulation,
the forecast
output was
in Fig. 5b). The T +low;
36 forecasts
the same
fields (shown
in second
area
of over
Cyprus
verified by comparing
theisland.
model output
Fig. 7c and d), depict
a small
scale cut-of
low at thewas
500predicted
hPa
totally
wrong;
precipitation
only
theare
northernmost
part of the
with the observations at three main locations over the island.
level which is not evident in the analysis chart, while the low
The verified parameters are temperature, wind speed and prepressure at the surface
is to the west with respect to its real
5 Conclusions
cipitation. The verification was performed using data for the
position, but once more about 2 hPa shallower than the actual
year 2007.
low. Finally, the T + 12 forecast (Fig. 7e and f) reproduces
Verification of model outputs is an important component in weather forecasting, as it is
well the structure at the 500 hPa level, and the forecast surVerification of the wind speed has shown that the best perthrough this phase that the confidence to an operational model is built. The Cyprus
face low is very close to the actual one. It can be stated here
formance is found at Athalassa, the inland station, with ME
Service of
verifies
the limited
area models that it runs operationally (see
that the model was Meteorological
able to catch the evolution
the surface
less than 1 kt. The seasonal verification reveals higher ME
Orphanou
et
al.,
2006);
this
is
the
first
time
that
BOLAM
and upper air patterns, two days before the synoptic event.
during thethe
warm
months, model
around is
2.5verified
kt at leadover
timesthe
which
area
of
Cyprus.
In
this
study,
one
year
of
BOLAM
model
forecasts
over
the
area
ofwind
Accumulated precipitation maps, provided by BOLAM
correspond at 18:00 UTC. Over the coastal stations, the
Cyprus
verified
comparingAnthe model
output
with the observations
three
main
fine grid, are shown
in Fig. are
8 (first
day ofby
simulation).
speed is
underestimated,
with the highestatME
around
4 kt at
island.
The
parameters
temperature,
wind
speed
andOverexamination of the locations
maps showsover
good the
results
as far as
the verified
loLarnaka
during are
the warm
months and
at 12:00
UTC.
cation of the precipitation
is concerned,
with precipitation
all, theusing
skill of
the for
model
of the wind speed is very
precipitation.
The verification
was performed
data
theforecasts
year 2007.
amounts exceeding 40 mm within 3 h over southern Cyprus
good.
between 09:00 and 12:00
UTC (Fig. 8a)
the has shown
The temperature
generally
underestimated
by the at
model
Verification
of and
the later
windover
speed
that theisbest
performance
is found
central part of the island.
The
results
for
the
third
day
of
simexcept
during
nighttime
and
during
the
cold
months
at
Athalassa, the inland station, with ME less than 1kt. The seasonal verification revealsAthaulation were quite satisfactory,
it concerns
location
of
lassa and2.5kt
Larnaka.
Thetimes
absolute
values
of ME are at
higher
higher MEasduring
the the
warm
months,
around
at lead
which
correspond
precipitation but the predicted amount was very low; 15 mm
during the warm months and during daytime. The highest
within 3 h. For the second day of simulation, the forecast
absolute values are found at 06:00 UTC at Larnaka, being
output was totally wrong; precipitation was predicted only
around 4–5 K. The highest absolute values during the cold
over the northernmost part of the island.
months are noted at 06:00 UTC at Paphos, being around 3 K.
The forecast skill of the model in predicting precipitation
is better at Larnaka for all the precipitation thresholds, as the
values of POD are higher than the values for the other two
www.adv-geosci.net/23/93/2010/
Adv. Geosci., 23, 93–100, 2010
98
K. Savvidou et al.: Verification of the BOLAM weather prediction model over the area of Cyprus
(a)
(b)
(c)
(d)
(e)
(f)
Fig. 7. (a) T + 60 500 hPa geopotential height, verifying at 12:00 UTC, 3 February 2007. (b) T + 60 mean sea level pressure, verifying
at 12:00 UTC, 3 February 2007. (c) T + 36 500 hPa geopotential height, verifying at 12:00 UTC, 3 February 2007. (d) T + 36 mean sea
level pressure, verifying at 12:00 UTC, 3 February 2007. (e) T + 12 500 hPa geopotential height, verifying at 12:00 UTC, 3 February 2007.
(f) T + 12 mean sea level pressure, verifying at 12:00 UT, 3 February 2007.
Adv. Geosci., 23, 93–100, 2010
www.adv-geosci.net/23/93/2010/
K. Savvidou et al.: Verification of the BOLAM weather prediction model over the area of Cyprus
99
(a)
(b)
(c)
(d)
Fig. 8. (a) 3-h accumulated precipitation, ending at 12:00 UTC, 3 February 2007. (b) 3-h accumulated precipitation, ending at 15:00 UTC,
3 February 2007. (c) 3-h accumulated precipitation, ending at 18:00 UTC, 3 February 2007. (d) 3-h accumulated precipitation, ending at
21:00 UTC, 3 February 2007.
stations. Meanwhile, the values of FAR for the two higher
precipitation thresholds are lower at Athalassa than at the
other two stations. Finally, the analysis of a specific case
study, showed the ability of the model to provide accurate
forecasts for events producing high-impact weather. It is in
the authors’ plans to continue the verification of the model
for a longer period and to extend the verification to the warnings provided by BOLAM.
(ISAC-CNR, Italy) and his help during the implementation of the
model at the Cyprus Meteorological Service. The authors are
also grateful to the National Centers for Environmental Prediction
(USA) for providing GFS initial and forecast field data which
allow the operational use of meteorological models at the Cyprus
Meteorological Service.
Edited by: K. Nicolaides and A. Orphanou
Reviewed by: S. Davolio and F. Tymvios
Acknowledgements. This work was carried out as part of the
RISKMED project which was co-funded by the European Union
(INTERREG IIIB) and the Government of Cyprus. The authors
acknowledge the provision of BOLAM model by Andrea Buzzi
www.adv-geosci.net/23/93/2010/
Adv. Geosci., 23, 93–100, 2010
100
K. Savvidou et al.: Verification of the BOLAM weather prediction model over the area of Cyprus
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