A major linear mesoscale convective system caused severe weather over
northern France, Belgium, the Netherlands and northwestern Germany on
3 January 2014. The storm was classified as a cold-season derecho with
widespread wind gusts exceeding 25 m s-1. While such derechos
occasionally develop along cold fronts of extratropical cyclones, this
system formed in a postfrontal air mass along a baroclinic surface pressure
trough and was favoured by a strong large-scale air ascent induced by an
intense mid-level jet. The lower-tropospheric environment was characterised
by weak latent instability and strong vertical wind shear. Given the poor
operational forecast of the storm, we analyse the role of initial and lateral
boundary conditions to the storm's development by performing
convection-resolving limited-area simulations with operational analysis and
reanalysis datasets. The storm is best represented in simulations with high
temporally and spatially resolved initial and lateral boundary conditions
derived from ERA5, which provide the most realistic development of the
essential surface pressure trough. Moreover, simulations at
convection-resolving resolution enable a better representation of the
observed derecho intensity. This case study is testimony to the usefulness of
ensembles of convection-resolving simulations in overcoming the current
shortcomings of forecasting cold-season convective storms, particularly for
cases not associated with a cold front.
Introduction
Mesoscale convective systems (MCSs) often occur in central Europe,
particularly in late spring and summer. In some cases, MCSs exhibit a linear
structure, last for several hours and lead to both intense wind gusts and
precipitation over large areas and are sometimes classified as derechos
(Johns and Hirt, 1987). While such events primarily occur over western Europe
during the summer half of the year (Gatzen, 2004), they may also occur during
wintertime (Gatzen et al., 2011). The majority of such cold-season derechos
occur in association with the passage of a cold front from an extratropical
cyclone embedded in a northwesterly flow (Ludwig et al., 2015; Gatzen, 2018).
However, on 3 January 2014, a linearly organised convective system did not
form along a cold front but in a postfrontal air mass within a southwesterly
flow and crossed over the northern tip of France, the Benelux region and the
northwestern part of Germany, causing mostly non-tornadic wind damage along
an approximately 650 km long path (Fig. 1). The magnitude of the convective
gusts ranged mostly between 20 and 30 m s-1, but hurricane-force wind
gusts (>32.7 m s-1) were measured locally between 13:00
and 22:00 UTC (Fig. 1). Additionally, F1-rated wind damage was reported in
western Belgium and northwestern Germany (Fig. 1). According to these
observations, this convective event can be classified as a cold-season
derecho following the definition of Johns and Hirt (1987), which includes four
essential points: (1) a concentrated area with convective
gusts >25.7 m s-1 having a major axis length of at
least 400 km must be observed, (2) the gust reports within the area defined
in (1) must show a non-random pattern of chronological progression, (3) the
area defined in (1) must contain at least three reports of F1 wind damage
(≥32.5 m s-1) and/or convective gusts ≥33.4 m s-1,
which are separated by 64 km or more, and (4) less than 3 h should
elapse between the gust reports defined in (1). Moreover, three tornadoes
have been confirmed according to the European Severe Weather Database (ESWD;
Dotzek et al., 2009). In addition to the non-tornadic and tornadic wind
damage, local reports of thick layers of small hail or graupel are archived
in the ESWD. Furthermore, the derecho-producing mesoscale convective system
(DMCS) was not well anticipated by the national weather
services
.
The short-term synoptic reports by the German Weather Service (Deutscher
Wetterdienst, DWD) and the Royal Netherlands Meteorological Institute
(Koninklijk Nederlands Meteorologisch Instituut, KNMI), issued on the
morning of 3 January 2014, mentioned the probability of isolated strong
thundery showers with the risk of storm-force wind gusts in the afternoon and
evening. The online
report
by the European Storm Forecast Experiment (ESTOFEX) pointed out the potential
for the development of a convective line that could cause severe winds and
isolated tornadoes in the Netherlands. However, the forecast level 1 threat
area issued by ESTOFEX did not cover the main region that was affected by the
long-lived convective system. All the above-mentioned characteristics
motivate a detailed review of this event.
The radar-observed position of the leading edge of the
derecho-producing mesoscale convective system at hourly intervals between
13:00 and 22:00 UTC on 3 January 2014 is shown by the dashed black lines. The
observed maximum wind gusts (m s-1) are denoted by the small coloured
squares (see legend). The white-edged squares indicate gusts stronger than
25.7 m s-1. Tornadic and non-tornadic wind damage locations are marked
by the small blue and magenta triangles, respectively (see legend). The dark
blue dot denotes the location of the sounding shown in Fig. 6. The inset in
the bottom-right-hand corner shows the names of the countries and sea areas
within the investigation area.
Most of the studies dealing with the environmental conditions, climatology
and modelling of DMCSs originate from the United States, which showed that
the large-scale conditions associated with derecho events are highly variable
(e.g. Evans and Doswell, 2001; Coniglio et al., 2004; Cohen et al., 2007).
DMCSs developing in strongly forced synoptic regimes are associated with weak
latent instability (i.e. low values of convective available potential energy, CAPE) and high shear values, which is mostly the case during the cold
season (e.g. Bentley and Mote, 2000; Evans and Doswell, 2001; Gatzen et al.,
2011). In addition, cold-season derechos sometimes occur in environments of
very limited low-level moisture (i.e. 2 m above ground level (a.g.l.) dew
points below 10 ∘C), which are then referred to as low-dew point
derechos (Corfidi et al., 2006). The high-shear, low-CAPE (HSLC) environments
are very challenging for the operational forecast of severe convection
(Sherburn and Parker, 2014a, b).
Nevertheless, efforts have been made since the mid 2000s towards a better
understanding of European derechos (e.g. Gatzen, 2004; Punkka et al., 2006;
Lòpez, 2007; Gatzen et al., 2011; Hamid, 2012; Celiński-Myslaw and
Matuszko, 2014; Toll et al., 2015; Taszarek et al., 2019). Gatzen (2004),
Punkka et al. (2006), Lòpez (2007) and Hamid (2012) examined the
large-scale conditions of single derecho events during the warm season in
different parts of Europe. Celiński-Myslaw and Matuszko (2014) found that
six multi-season derechos affected southern and central Poland between 2007 and
2012. Gatzen (2018) identified and classified 40 derechos that affected
Germany during the 18-year period 1997–2014, including 12 winter cases.
However, modelling studies about European derechos are rarely found in the
literature. For instance, Toll et al. (2015) and Taszarek et al. (2019)
performed hindcast experiments of warm-season derechos in eastern Europe.
Ludwig et al. (2015) were able to successfully reproduce the derecho
intensity of deep convection associated with the cold front of winter storm
Kyrill in 2007 (Fink et al., 2009). Hence, more observational and numerical
studies about well-organised DMCSs developing in cold-season conditions are
needed, for instance to better understand the processes and potentially
enhance the predictability of these uncommon events.
The purpose of this study is to analyse the synoptic characteristics and the
predictability of this derecho event. With this aim, we examine the presence
of the ingredients necessary for the development of the severe cold-season
DMCS. In situ observations and numerical weather prediction (NWP) model data
enable a detailed examination. Given the poor performance of the operational
forecasts, high-resolution hindcast experiments are performed to investigate
the reasons for this shortcoming.
This article is structured as follows. Section 2 describes the data and
methods. The synoptic-scale situation and the environmental conditions
associated with the convective windstorm are highlighted in Sect. 3.
Section 4 discusses the predictability issues and analyses the model
experiments. The last section includes a short summary and our conclusions.
Data and numerical model
The in situ wind measurements used in this study include data from the
synoptic weather station networks operated by numerous national weather
services (Météo-France, Royal Meteorological Institute of Belgium
(RMIB), United Kingdom's Meteorological Office (UK Met Office), KNMI, DWD)
and by the private weather service MeteoGroup. The 12:00 UTC upper-air
sounding from Larkhill (WMO 03743) is considered representative of the
environmental conditions in which the DMCS developed. The RMIB radar
composite image is produced on a 500 m grid by combining pseudo Constant
Altitude Plan Position Indicators (CAPPI) at 1.5 km altitude of four
operative C-band radars located in Belgium and France. The KNMI composite
image consists of pseudo CAPPI at a height of 1.5 km on a 1 km grid, which
are based on the measurements of two Dutch C-band Doppler radars.
In addition to the in situ and radar data, the recently released ERA5 data
from the European Centre for Medium-Range Weather Forecasts (ECMWF) are used
to examine the synoptic-scale conditions. ERA5 was produced using 4DVar data
assimilation with the model cycle Cy41r2 of ECMWF's Integrated Forecast
System (IFS). The hourly reanalysis data output have a grid spacing of
approximately 31 km (Hersbach et al., 2019). Furthermore, the predictability
issue will be briefly described using the operational ECMWF's Ensemble
Prediction System (ECMWF-EPS) and the Consortium for Small-scale Modelling
Limited-area Ensemble Prediction System (COSMO-LEPS). ECMWF-EPS consists of
50 perturbed members and one control run with a grid spacing of about 32 km
(IFS release Cy40r1). COSMO-LEPS includes 16 ensemble members with a grid
spacing of approximately 7 km. The initial and lateral boundary conditions
(ILBCs) for each of these 16 members are selected based on a cluster analysis
from two consecutive ECMWF-EPS runs (Montani et al., 2011).
The COSMO model (version 5.0, subversion 9) is used in its climate version
(CLM), henceforth termed CCLM (Rockel et al., 2008), to perform
high-resolution hindcast simulations of the event. The CCLM is synchronised
regularly with the NWP version of the COSMO model operationally used at the
DWD but excluding data assimilation or latent heat nudging. The CCLM has
shown its capabilities in several convection-resolving modelling studies in
the recent past (e.g. Fosser et al., 2015; Ludwig et al., 2015; Leutwyler et
al., 2016; Mathias et al., 2017). For this study, a total of three
simulations (each including several nesting steps) have been conducted to
analyse the DMCS in more detail. A reference simulation is driven by ILBCs
derived from the ERA5 dataset. Additional hindcast experiments have been
conducted using ERA-Interim reanalysis (ERAI, IFS release Cy31r2; Dee et al.,
2011) and ECMWF operative analysis data (ECAN, IFS release Cy40r1) to
investigate the sensitivity of different ILBCs to the DMCS development.
Besides the different data assimilation cycles, both datasets differ in their
grid spacing (ERAI: T255, Δx≈80 km; ECAN: T1279, Δx≈16 km) and their temporal resolution (hourly data for ERA5,
6-hourly data for ERAI and ECAN).
A three-step nesting approach is necessary to obtain a very fine grid spacing
(Δx≈1.1 km) in the ERA5-driven reference simulation. The
ERA5 and ECAN data are first downscaled over domain 1 (D1) with a horizontal
grid spacing of 7 km, followed by domain 2 (D2, Δx≈2.8 km)
and finally domain 3 (D3, only for ERA5, Δx≈1.1 km; see
Fig. 2a for domain configuration). For ERAI ILBCs, an additional preceding
nesting step (D0, grid spacing of 25 km) is necessary to avoid large
resolution jumps (Matte et al., 2017). The ERAI and ECAN simulations are both
downscaled to a final grid spacing of 2.8 km (D2) in order to analyse the
differences in the atmospheric conditions during the development of the DMCS
in comparison to the ERA5 reference simulation. Moreover, the increase in the
horizontal resolution from D0 to D3 is accompanied by a simultaneous increase in the vertical resolution, which is a common method implemented by national
weather services using COSMO (e.g. DWD, MeteoSwiss) to obtain a numerically
stable convection-resolving NWP. The 1.1 km simulation forced with ERA5 data
is used for a detailed comparison with radar and wind gust observations.
(a) Computational domains used for the nesting of the CCLM
simulations and (b) Gantt chart overview of the different CCLM
configurations and initialisation times.
The CCLM is able to resolve deep moist convection (convection-resolving
model; Baldauf et al., 2011; Prein et al., 2015) at grid spacing smaller than
4 km, while shallow convection is still parameterised. Thus, for the first
nesting steps (D0, D1) the convective mass flux is parameterised after
Tiedtke (1989), while for the higher-resolution runs (D2, D3) this scheme is
only applied to shallow convection (see Table 1). As an upper boundary
condition, damping against boundary fields is applied. The wind gusts are
estimated based on a diagnostic parameterisation depending on the wind speed
at 10 m a.g.l. and the friction velocity (Schulz, 2008):
vg=v10m+3.0⋅2.4⋅u*.
with the empirical factors 3.0 and 2.4 motivated by the Prandtl layer theory
(Panofsky and Dutton, 1984). The friction velocity is computed using the drag
coefficient for momentum CD and the wind speed at 10 m a.g.l.:
u*=(CD)⋅0.5⋅v10m.
An overview of the physical parameterisations that are used for all domains
is given in Table 1 and a more detailed description can be found in Doms et
al. (2011). To overcome unbalanced information for the mass and wind field in
the initialisation process and to accelerate the spin-up process, a time-filtering approach after Lynch (1997) is applied in CCLM.
CCLM simulation configurations.
DomainD0D1D2D3(ERAI)(ERAI, ECAN, ERA5)(ERAI, ECAN, ERA5)(ERA5)Horizontal0.22∘0.0625∘0.025∘0.01∘grid spacing(Δx≈25 km)(Δx≈7 km)(Δx≈2.8 km)(Δx≈1.1 km)No. of40506090vertical layersConvectiveTiedtke (1989) Only shallow convection after Tiedtke (1989) parameterisationCloudTwo-category ice scheme Three-category ice or graupel scheme microphysics(Doms et al., 2011) (Reinhardt and Seifert, 2006) RadiationRitter and Geleyn (1992), Rockel et al. (1991) Soil modelMulti-layer soil model (TERRA-ML) after Jacobsen and Heise (1982) Planetary boundaryBaldauf et al. (2011), Mellor and Yamada (1982) layer turbulence
To perform a consistent analysis and comparison of the simulated DMCS based
on the different datasets for ILBCs, all 2.8 km simulations start at
12:00 UTC (D2). Due to the different spatial resolutions of the individual
forcing data, different nesting steps and initial times had to be used (see
Gantt chart in Fig. 2b for a detailed overview of the individual nesting
strategies). The highest-resolution simulation (1.1 km) based on nesting
with ERA5 data started at 13:00 UTC (D3). ECAN- and ERAI-driven simulations
with identical starting times to ERA5 (00:00 UTC) in D1 have also been
computed but will not be further discussed due to their poorer performance.
Additional simulations have been conducted to analyse the sensitivity of
ILBCs on the resulting derecho. Regarding the initial conditions, ECAN-driven
simulations initialised at 00:00 UTC were performed with initial wind and
moisture variables replaced by the respective ERA5 fields, while the ECAN
boundary conditions remained unchanged. To consider the importance of the
update frequency of the lateral boundary conditions (LBCs), an additional
ERA5-driven simulation was performed where the LBCs are updated every 6 h
(as opposed to hourly updates in the reference simulation). For all
experiments, the model output is stored on an hourly basis for the 7 km
simulations and with a 15 min interval for the 2.8 and 1.1 km simulations.
Synoptic-scale overview and storm environment
The large-scale environmental conditions associated with the derecho are
examined based on ERA5 reanalysis data and an upper-air sounding. At
12:00 UTC on 3 January 2014, a deep low-pressure system (core pressure of
949 hPa) named “Anne” was situated over the North Atlantic close to
Scotland (Fig. 3) and high pressure (1022 hPa) was diagnosed north of the
Alps. Consequently, a strong horizontal pressure gradient existed over the
British Isles and over parts of France, Belgium and the Netherlands. The
frontal system of the surface low extended from the Norwegian Sea over
Denmark and Germany all the way south to the Iberian Peninsula (Fig. 3). The
occluded front had a warm character, meaning that the near-surface air
directly behind the front was slightly warmer and moister than the prefrontal
air (not shown). Moreover, a surface trough was diagnosed by the UK Met
Office over the English Channel (Fig. 3), which was related to the
development of the DMCS. At 15:00 UTC, the surface trough reached western
Belgium and corresponded to a weak isallobaric gradient (Fig. 4a). This
trough was associated with large-scale upward motion located at the cyclonic
exit of a mid-level jet (Fig. 4c, e). In addition, the pressure trough was
associated with weak baroclinity, because the lower-tropospheric temperature
dropped by a few kelvin after the passage of the trough (not shown). At 18:00 UTC,
3 h later, the surface trough was located over northwestern
Germany and the isallobaric gradients strengthened (Fig. 4b). The trough also
remained in phase with the large-scale forcing for ascent, as it was
vertically aligned with strong divergence at the exit of the mid-level jet
and ahead of a negatively tilted upper-level trough situated over Belgium
(Fig. 4d, f).
Surface weather chart of mean sea level pressure (hPa), fronts and
surface troughs at (a) 12:00 UTC and (b) 18:00 UTC on
3 January 2014 (source: UK Met Office). The surface trough associated with
the development of the derecho-producing mesoscale convective system is
denoted by the orange line.
ERA5 reanalysis of the synoptic-scale conditions at 15:00 and
18:00 UTC on 3 January 2014. (a–b) Mean sea level pressure (hPa;
black lines) and hourly pressure tendency (hPa h-1; shaded),
(c–d) 500 hPa wind speed (m s-1; contour lines starting at
25 m s-1) and divergence (10-5 s-1; shaded),
(e–f) 500 hPa geopotential height (gpm; black lines) and diagnosed
700 hPa upward motion (Pa s-1; shaded). The dashed black line in
(a) and (b) denotes the surface pressure trough.
The ingredients-based method by Johns and Doswell (1992) prescribes three
necessary elements for the occurrence of deep moist convection. First, a
sufficient amount of moisture in the boundary layer is required. A tongue of
enhanced low-level moisture existed between the occluded front and the
postfrontal surface trough at 12:00 UTC (cf. Figs. 3a and 5a). Near-surface
dew points of 7 to 9 ∘C (not shown) and 950 hPa specific humidity
values above 5 g kg-1 were observed over France, western Germany and
Benelux (Fig. 5a). Backward trajectories indicate that the unusual moist
air mass (for this season) was advected from the northeastern Atlantic over
the Bay of Biscay towards western Europe (not shown). At 18:00 UTC, the
moisture tongue covered eastern France and large parts of Germany with
slightly lower values of specific humidity (Fig. 5b).
The second necessary ingredient is a sufficiently steep lapse rate in the
lower to middle troposphere above the moist layer. At 12:00 UTC, lapse rates
of 6.5 to 7 K km-1 between 900 and 650 hPa covered the British Isles,
the English Channel and northwestern France (Fig. 5c). Upper-air observations
revealed a conditionally unstable air mass confined to the layer below 650
hPa with a striking capping inversion between 650 and 600 hPa (e.g. at
Larkhill; see Fig. 6), which was induced by the subsiding air from a
potential vorticity intrusion (Gatzen, 2018). The combination of steep lapse
rates and low-to-moderate boundary layer moisture resulted in low CAPE values
of 150 to 250 J kg-1, as indicated by the 12:00 UTC sounding from
Larkhill (Fig. 6). At 18:00 UTC, this area of weak latent instability reached
northwestern Germany (Fig. 5b, d).
ERA5 reanalysis of (a, b) 950 hPa specific humidity
(g kg-1), (c, d) 900–650 hPa lapse rate (K km-1),
(e, f) 0–6 km bulk shear (m s-1; shaded) and (e, f) 0–3 km bulk shear larger than 15 m s-1 (hatched areas) at
(a, c, e) 12:00 UTC and (b, d, f) 18:00 UTC on
3 January 2014. The white dot in (a), (c) and (e)
denotes the location of the sounding shown in Fig. 6. The dashed white line
indicates the position of the surface trough according to the UK Met Office
surface analysis shown in Fig. 3.
Skewed T-log p diagram of upper-air measurements from Larkhill
(England) at 12:00 UTC on 3 January 2014. The solid (dashed) black line
represents temperature (dew point) values in ∘C. The box in the upper-right corner shows the values for 50 hPa mixed-layer and most-unstable
CAPE/CIN and different bulk shear values. The insets on the right-hand side
show the vertical distribution of the horizontal wind (kn; wind barbs).
MUCAPE (MUCIN) is denoted by the red (blue) area between the temperature
profile and the parcel ascent curve.
Finally, the vertical wind shear is a crucial ingredient for
linearly organised MCSs (e.g. Weisman and Klemp, 1982; Rasmussen and
Blanchard, 1998). Here, the DMCS formed in an environment with 0–6 km bulk
shear values well above 25 m s-1 (Fig. 5e). The 12:00 UTC sounding
from Larkhill also revealed almost unidirectional 0–6 km bulk shear and
mean wind speed values of about 30 m s-1 (Fig. 6). Thus, the deep
layer shear and mean wind vector were nearly parallel, which favoured the
development of a fast downwind-propagating and severe MCS (Corfidi, 2003;
Cohen et al., 2007). The lower-tropospheric shear was also very strong, with
0–3 km bulk shear values larger than 15 m s-1 (Fig. 5e). According
to ERA5 reanalysis data, these shear magnitudes remained more or less
constant at 15:00 UTC over Belgium and at 18:00 UTC over northwestern Germany
(Fig. 5f). The lifting mechanism, as the last indispensable ingredient, was
provided by the surface pressure trough and the associated low-level
convergence.
In brief, the derecho on 3 January 2014 developed in a strongly forced
synoptic regime, which was associated with a baroclinic surface trough
(Sanders, 1999, 2005). The DMCS evolved within an area characterised
by (a) a sufficient amount of lower-tropospheric moisture, (b) steep
lower-tropospheric lapse rates of 6.5 to 7 K km-1, (c) weak latent
instability (CAPE <250 J kg-1) and (d) strong vertical
wind shear, with the majority of the shear and latent instability located in
the lowest 3 km of the troposphere. This HSLC environment generally allows
the formation of cold-season DMCSs producing severe winds, especially in
the presence of strong large-scale forcing for ascent (e.g. Bentley and Mote,
2000; Evans and Doswell, 2001). In comparison with two other European
cold-season derechos studied by Gatzen et al. (2011), this event was
characterised by much weaker vertical wind shear. For example, the Kyrill
derecho formed in a highly baroclinic environment with 0–6 km bulk shear
values of up to 65 m s-1 (vs. 30 m s-1 for this case).
Similarities were found among the magnitude of low-level specific humidity
and lower-tropospheric lapse rates (Gatzen, 2018).
Predictability and high-resolution modelling
Model hindcast experiments are used to complement the description of this
extreme cold-season convective event. The following subsections include a
short analysis of the operational ensemble forecasts and a detailed
examination of the differences between the ERA5-, ERAI- and ECAN-driven CCLM
simulations. Furthermore, the benefit of our highest-resolution simulation
will be highlighted in the last subsection.
Ensemble forecasts
As already mentioned in the introduction, the DMCS on 3 January 2014 was not
well forecast. The probabilistic forecast issued from the ECMWF-EPS 00:00 UTC
run revealed a probability of 40 % to 60 % for the occurrence of
maximum surface wind gusts exceeding 20 m s-1 over Belgium on
3 January 2014 and a much lower probability for western Germany (Fig. 7a).
The predicted likelihood for gusts reaching wind speeds larger than
25 m s-1 was zero for the whole investigation area, except for the
marine areas of the English Channel and the North Sea (Fig. 7c). COSMO-LEPS
provided similar probabilistic forecasts (Fig. 7b, d) and showed an even
lower probability for wind gusts exceeding 20 m s-1 over northwestern
France, Belgium and western Germany than ECMWF-EPS (cf. Fig. 7a and b).
Moreover, ECMWF underestimated the latent instability over Benelux and
northwestern Germany, since the EPS revealed a low probability of 5 % to
25 % for CAPE values larger than 50 J kg-1 at 18:00 UTC (not
shown).
Event probability forecast valid for 00:00 UTC on 4 January 2014 by
the 00:00 UTC run of (a, c) ECMWF-EPS and (b, d) COSMO-LEPS
on 3 January 2014 in terms of (a, b) maximum 10 m a.g.l. wind
gusts exceeding 20 m s-1 within 24 h and (c, d) maximum
10 m a.g.l. wind gusts exceeding 25 m s-1 within 24 h.
Dependence on initial and lateral boundary conditions
To investigate the potential predictability of the derecho event, CCLM
hindcasts were performed using the ERA5, ERAI and ECAN data as ILBCs. The
ERA5-driven CCLM simulation (CCLM-ERA5) revealed a linearly organised
convective system over parts of northern France, Belgium and the North Sea at
16:00 UTC, which was associated with a convergence zone along a surface
pressure trough (Fig. 8a, b). In the ERAI-driven CCLM simulation
(CCLM-ERAI), deep moist convection formed in a similar way, but the surface
trough was located farther north and the convective cells remained initially
mostly discrete (Fig. 8c, d). At a later time step in this
simulation (20:00 UTC), a linearly organised MCS became apparent (not shown).
The ECMWF operative-analysis-driven simulation (CCLM-ECAN) developed discrete
and non-severe convective cells over the investigation area along unorganised
near-surface convergence zones, as no well-defined surface pressure trough
was evident in this simulation (Fig. 8e, f). In general, the CCLM-ECAN
simulation is clearly distinct from the results with ERA5 and ERAI reanalysis
boundary conditions, despite that no major differences in the simulation of
CAPE could be identified (cf. Fig. 8f with b and d). All three simulations
featured maximum CAPE values of 200 to 250 J kg-1 over the Netherlands
(not shown). Apparently, the differently simulated structure of the
convection-initiating convergence zone had a major impact on the subsequent
upscale growth of the convection. In general, both CCLM-ERA5 and CCLM-ERAI
simulated a nearly closed convergence band in contrast to CCLM-ECAN (cf.
Fig. 8a and c with e). Even exchanging the initial specific humidity and wind
fields in CCLM-ECAN with ERA5 values did not result in significant
improvements. However, considerable sensitivity was found when modifying
the update frequency of the LBCs in CCLM-ERA5: The ERA5-driven CCLM
simulation with 6-hourly LBCs did not simulate the surface pressure trough
associated with the development of the DMCS, which extends from southeastern
England to northern France at 14:00 UTC in the reference simulation with
hourly LBCs (Fig. 9a, b). The absence of this trough resulted in a weaker and
less organised convective system (not shown), similar to the results obtained
with CCLM-ECAN. To determine the cause of the missing trough, we
investigated the synoptic-scale differences between both CCLM-ERA5
simulations at the western boundary of the computational domain D1. A
striking pressure anomaly entered D1 from the west between 07:00 and
09:00 UTC, which had its origin in an additional surface pressure trough
located west of Ireland in CCLM-ERA5 with hourly LBCs (Fig. 9c, d). This
trough affected the pressure field downstream over the English Channel,
leading to the formation of the pressure trough associated with the derecho
between 12:00 and 15:00 UTC in the ERA5-driven reference simulation. We thus
propose that the realistic representation of the convection-initiating
convergence zone and the associated low-level forcing for ascent, which was
achieved with initial ERA5 data and hourly LBCs, would have been the key
factors to successfully forecasting this cold-season storm.
Results from (a, b) CCLM-ERA5, (c, d) CCLM-ERAI
and (e, f) CCLM-ECAN at 16:00 UTC. (a, c, e) 1-hourly mean
sea level pressure (MSLP) tendency (hPa h-1; shaded) and 950 hPa
convergence smaller than -5×10-5 s-1 (hatched areas) from
the 7 km simulation. (b, d, f) Column maximum reflectivity (dBZ;
shaded) and 50 hPa mixed-layer CAPE above 50 J kg-1 (hatched areas)
from the 2.8 km simulation.
Results from CCLM-ERA5 7 km simulation with (a, c) hourly
and (b) 6-hourly lateral boundary conditions (LBCs). (a, b)
1-hourly mean sea level pressure (MSLP) tendency (hPa h-1; shaded) at
14:00 UTC, (c) MSLP (hPa; shaded) at 09:00 UTC and (d) MSLP
difference (hPa; shaded) at 09:00 UTC between simulations with hourly and
6-hourly LBCs. The black outlined box in (c) highlights the surface
pressure trough, which entered the computational domain from the west.
Results from CCLM-ERA5 at (a, b) 14:00 UTC, (c)
16:00 UTC and (d) 19:00 UTC. (a) 1-hourly mean sea level
pressure (MSLP) tendency (hPa h-1; shaded) and 950 hPa convergence
smaller than -5×10-5 s-1 (hatched areas) from the 7 km
simulation. (b, d) Column maximum reflectivity (dBZ; shaded) and
50 hPa mixed-layer CAPE above 50 J kg-1 (hatched areas) from the
1.1 km simulation. The dashed yellow lines in (a) denote the
convection-initiating convergence zones.
CCLM-ERA5 1.1 km simulation and comparison with the observed event
As the CCLM-ERA5 simulations revealed a good representation of the DMCS in
terms of its spatio-temporal evolution, this subsection will include a
detailed analysis of the system using the simulation with 1.1 km grid
spacing. To show the added value of the smaller grid spacing, the 1.1 km
results are compared with the results from the 2.8 km simulation.
Between 13:00 and 14:00 UTC, several convective cells initiated over northern
France and the English Channel along two distinct low-level convergence zones
(cf. Fig. 10a and b). Both convergence zones were associated with isallobaric
gradients (dashed yellow lines in Fig. 10a) and a weak gradient of equivalent
potential temperature in 850 hPa (not shown). Since the 0–6 km mean wind
vector had a large component perpendicular to the convection-initiating
convergence zones (not shown), the convective cells over northern France
remained mostly discrete and their upscale growth was initially limited.
While the convective cells moved towards the northeast, they were subjected
to weak latent instability (CAPE <250 J kg-1; see
Fig. 10b). At 16:00 UTC, the convective cells organised and merged to a
linearly organised MCS extending from the North Sea over the Benelux region
to northern France (Fig. 10c), as both convergence zones phase locked along
the surface pressure trough (Fig. 8a). Still, the MCS benefited from low-end
CAPE (<150 J kg-1) downstream of the system (Fig. 10c). At
19:00 UTC, the simulated DMCS reached western Germany, exhibiting its peak
organisation (Fig. 10d). As the linear storm system moved farther east into
an environment with a drier and colder boundary layer, it began to weaken
(decreasing reflectivity) and gradually lost its organisation after 20:30 UTC
due to the lack of latent instability (not shown). Compared to the evolution
of the observed DMCS, the CCLM-ERA5 run featured a broken-line mode of the
DMCS, especially during the early stage of the system's life cycle (cf.
Fig. 11a with c and e). However, the bowed or hooked segments observed in the
real case (see Fig. 11a, b) were also present in the highest-resolution
simulation, for example at 16:00 UTC over central Belgium (50.25∘ N
4.5∘ E, Fig. 10c) or at 19:00 UTC over northwestern Germany
(52∘ N 8.5∘ E, Fig. 10d). In contrast, the simulated
2.8 km radar reflectivity reveals a more scattered and less organised
convective line (Fig. 11c, d), pointing towards the need and added value of
high-resolution simulations.
Comparison of the observed and modelled reflectivity at
approximately 1.5 km altitude at (a, c, e) 15:00 UTC and at
(b, d, f) 17:00 UTC. (a) RMIB radar reflectivity composite
(dBZ), (b) KNMI radar reflectivity composite (dBZ), (c, d)
reflectivity from the CCLM-ERA5 2.8 km simulation and (e, f)
reflectivity from the CCLM-ERA5 1.1 km simulation.
The maximum wind gust pattern obtained from CCLM-ERA5 shows some striking
differences among the 2.8 and 1.1 km simulations. The former shows multiple
stripes of gusts ranging between 20 and 30 m s-1 over the onshore
areas, with a single local wind maximum of about 35 m s-1 over the
northeastern Netherlands (Fig. 12a). By contrast, the highest-resolution
simulation covers a larger area with convective gusts exceeding
20 m s-1, which matches well with the observations (cf. Figs. 1 and
12b). In addition, the 1.1 km simulation highlights the potential for
hurricane-force gusts much better, exhibiting local maxima of up to
45 m s-1 over the mountainous regions of eastern Belgium but also
over the lowlands of northern Germany (Fig. 12b). This shortcoming of the
2.8 km simulation is probably linked to a less accurate representation of
the convective-scale processes due to its lower horizontal and vertical
resolution (see Table 1). More precisely, the downdraughts of the individual
convective cells are slightly stronger in the 1.1 km simulation, leading to
stronger pressure gradients along their gust fronts compared to the 2.8 km
simulation (cf. Fig. 12c and d). As the computation of the horizontal wind is
affected by the pressure gradient force, the friction velocity will increase
due to higher horizontal wind speeds, which will result in stronger gusts
following Eqs. (1) and (2).
CCLM-ERA5 2.8 and 1.1 km simulations of (a, b)
10 m a.g.l. maximum wind gusts (m s-1) and (c, d) maximum mean
sea level pressure (MSLP) gradient (Pa km-1) between 14:00 and
22:00 UTC.
Overall, we demonstrated that simulations with a grid spacing of about 1 km
are necessary to realistically approach the severity of deep moist convection
within the HSLC environment on 3 January 2014. However, Ludwig et al. (2015)
were able to viably reproduce the observed gust intensity of the European
derecho on 18 January 2007 using a coarser grid spacing of 2.8 km (see
Figs. 8d–f and 12 in Ludwig et al., 2015). The main difference between both
simulations is the linear upscale growth of the simulated convection. The
DMCS modelled by Ludwig et al. (2015) featured a nearly closed narrow
convective line along Kyrill's cold front, which is in contrast to the less
organised DMCS of the CCLM-ERA5 simulation in the present study. This
disparity is most likely attributable to the nature of the
convection-initiating zone (cold front vs. baroclinic trough). Furthermore,
the synoptic background flow was stronger during the Kyrill derecho. Thus, we
speculate that the magnitude of the simulated wind gusts might be sensitive
to the convective upscale growth along the convection-initiating zone when
using convection-resolving CCLM configurations with coarser grid spacing.
Summary and conclusions
In this study we have analysed the synoptic characteristics and the
predictability of a major linear mesoscale convective system which developed
in a postfrontal air mass and caused severe weather in northern France,
Belgium, the Netherlands and northwestern Germany on 3 January 2014. The
system produced hurricane-force winds and was classified as a moderate
low-dew point derecho as it satisfies the criteria of Johns and Hirt (1987),
Coniglio and Stensrud (2004) and Corfidi et al. (2006). Cold-season derechos
that are not associated with a cold front are uncommon in Germany (Gatzen,
2018).
First, we have investigated the environmental conditions in which this DMCS
developed, revealing that the system formed in a strongly forced synoptic
regime marked by a strong southwesterly upper-level flow. In particular, the
DMCS benefited from large-scale forcing for ascent since it was positioned at
the left exit of a strong mid-level jet, which is typical for European
cold-season derechos (Gatzen, 2018). The formation of the DMCS was also
associated with a baroclinic surface pressure trough in the postfrontal air
mass. Moreover, the DMCS evolved in an environment that featured the three
necessary ingredients for the occurrence of deep moist convection (Johns and
Doswell, 1992). Steep lower- to mid-tropospheric lapse rates and enhanced
amounts of boundary layer moisture have been identified. The resulting weak
latent instability was mostly concentrated within the lowest 3 km of the
troposphere, in which the strongest vertical wind shear was also present.
However, the tropospheric speed shear was much weaker in contrast to
cold-season derechos developing along a cold front (Gatzen et al., 2011).
This lower-tropospheric HSLC regime, in combination with low-level
convergence along the surface trough, may have been crucial for the linear
organisation of the DMCS and for the development of bowing line segments,
which were observed in radar imagery (Fig. 11a, b).
The analysis of NWP model data revealed the poor performance of the
operational forecasts. Thus, high-resolution numerical experiments (with up
to 1.1 km grid spacing) were performed to investigate the reasons for this
shortcoming. Our results provide evidence that the derecho event on
3 January 2014 was predictable given the correct ILBCs. The ERA5-driven CCLM
simulation with hourly updated LBCs produced a linearly organised MCS, with
timing, track and intensity that coincided well with the development of the
observed DMCS. However, our additional simulations with ERAI and ECAN data as
ILBCs revealed that the development of the storm was sensitive to the
structure of the convection-initiating zone, which depended on the simulated
pressure field. In particular, the simulation with ECAN ILBCs failed to
reproduce an organised convective system over the affected region, pointing
to a possible shortcoming of the observational analysis in such strongly
convective situations (cf. also Mathias et al., 2017). Additional sensitivity
experiments revealed the importance of temporal high-resolution LBCs for the
development of the DMCS. An ERA5-driven simulation with 6-hourly LBCs
performed worse with regard to the intensity and the degree of organisation
of the convection. The reason for this was most likely the absence of the key
precursor, a surface pressure trough which entered the computational domain
between 07:00 and 09:00 UTC when considering hourly LBCs.
Moreover, we showed that very high horizontal and vertical resolutions were
necessary to reproduce the derecho intensity of the simulated convection.
This is partially in contrast to the case modelled by Ludwig et al. (2015),
which could represent the strong convection embedded in the cold front from
storm Kyrill with a coarser grid spacing of 2.8 km. However, a higher model
resolution might not always be necessary for a good representation of DMCSs
due to the strong case to case variability (Gatzen, 2018), but it might be
needed for systems in some cases. Overall, the 3 January 2014 derecho event
revealed the difficulty of forecasting cold-season convective windstorms when
they are not associated with a well-defined synoptic-scale cold front, where
upward motion is generally given per se. Therefore, convection-resolving
ensemble prediction systems might be considered to improve the predictability
of such low-probability, high-impact events in the future. Such systems are
already employed by the DWD and MeteoSwiss. Future work will focus on a
detailed analysis and high-resolution modelling of other DMCSs affecting
western Europe based on the database established by Gatzen (2018) and on
tests for the sensitivity to the ingredients, particularly in terms of the
physical mechanisms leading to the large-scale ascent needed to initiate the
event.
Data availability
The
ERA-Interim reanalysis data are available publicly from the ECMWF (2011).
ERA5 data are available publicly from the Copernicus Climate Change Service (2017). COSMO-LEPS, ECMWF-EPS and ECMWF operative analysis data are available
for ECMWF members upon request via the Meteorological Archival and Retrieval
System (MARS, https://apps.ecmwf.int/mars-catalogue/, last access:
13 May 2019). COSMO-CLM simulations were performed at DKRZ and are available
upon request. All code is available from the authors.
Author contributions
LM, PL and JGP conceived and designed the research. LM performed the synoptic
analysis, while PL performed the COSMO-CLM simulations. LM and PL prepared
the figures and wrote the initial draft of the paper. All authors contributed
with discussions and revisions.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
We thank the ECMWF for the provision of ERA5, ERA-Interim and ECMWF analysis
data. We thank the RMIB and KNMI for providing radar data. COSMO may be used
for operational and for research applications by the members of the COSMO
consortium. Moreover, within a license agreement, the COSMO model may be used
for operational and research applications by other national
(hydro-)meteorological services, universities, and research institutes. We
thank the German Climate Computer Center (DKRZ, Hamburg) for computing and
storage resources within the context of DKRZ project ANDIVA (no. 105). We
thank Christoph Gatzen for the useful and extensive discussions. We are
grateful to the European Severe Storm Laboratory (ESSL) for the reports taken
from the European Severe Weather Database (ESWD; http://www.eswd.eu/,
last access: 13 May 2019) shown in Fig. 1. Joaquim G. Pinto was partially
funded by the AXA Research Fund and Patrick Ludwig was partially funded by
REKLIM. We acknowledge
support by Deutsche Forschungsgemeinschaft (DFG) and Open Access Publishing
Fund of Karlsruhe Institute of Technology. Finally, we thank two anonymous
reviewers for their constructive comments that helped to improve the
manuscript.
Review statement
This paper was edited by Ricardo Trigo and reviewed by two
anonymous referees.
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