Meeting Report : Mid-latitude convective storms
and their initiation
Convective storms produce some of the most damaging weather
experienced in the UK,
but predicting the precise location and timing of such small features remains a
difficult forecasting problem. The development of a new generation of numerical
weather prediction (NWP) models, with grid-spacings
of the order of one kilometer, has however led to a resurgence of interest in
this area. In particular, the Convective Storm Initiation Project (CSIP, a
consortium of several UK
universities, the Met Office and the Institut für Meteorologie und Klimaforschung, IMK) aims to understand and quantify the
mechanisms controlling the location and timing of convective storms in the UK.
This should allow improvements in the NWP of such events. Professor Alan Blyth (University
of Leeds) gave an introduction to
the CSIP project, and in particular to the CSIP field campaigns, which took
place in the summers of 2004 and 2005 in southern England.
Convective storms can only form where there is potential
instability (also known as
convective instability). The
synoptic scale regions of instability could be reasonably predicted by the
previous generation of hydrostatic NWP models, with grid-spacings
of approximately 10 km. However, as Professor
Keith Browning (University of Reading)
explained, in general there is a “lid” of Convective Inhibition (CIN) which
must be overcome for a storm to form. This process, of overcoming CIN, was
generally not resolved by the previous generation of NWP models, but normally controls
if, where, and when storms occur. A wide variety of initiation mechanisms were
observed during CSIP, including: surface heating allowing thermals to reach
their level of free convection; areas of deeper convection over higher ground
in low winds; convergence lines generated by coastlines; upper level
circulations (potential vorticity anomalies) reducing CIN (these were usually
visible in the water vapour channel of Meteosat); longitudinal cloud organization (“cloud
streets”); frontal upglide leading to mid-level
convection and secondary initiation at the edges of cold-pool outflows from
previous storms. In addition, the CSIP observations suggested that on one day
storms were initiated within surface “hot-spots”, generated by gaps in cirrus
cloud cover and on another day deep convection was initiated by gravity waves. Dr John Marsham (University
of Leeds) showed how idealised modelling could be used
to test these hypotheses. For the cirrus case, the magnitude of the surface
flux variations induced by the cloud were evaluated from surface and Meteosat observations; applying these fluxes in Large Eddy
Model (LEM) simulations showed that the “hot-spots” were sufficient to control
convective initiation, despite the clouds moving at approximately 15 m/s. For
the gravity wave case, LEM modelling showed that the
positions and timings of the observed arcs were consistent with an earlier
storm generating waves, which initiated the subsequent arcs of deep convection.
Interestingly, the Unified Model (UM) forecast the generating storm, but did
not forecast the convective initiation by the waves, perhaps due to the
time-stepping used in the model. This is being investigated at the Joint Centre
for Mesoscale Meteorology (JCMM) at the University
of Reading. Dr John Marsham also discussed the
effects of thin stable layers at mid-levels. The model results showed that the UM’s limited resolution of such features could affect the
timing of modelled precipitation by approximately one
hour, and the rain-rate by a factor of two.
The CSIP field campaigns, were
centered around the Chilbolton radar facility and Dr John Nicol
(University of Reading)
showed cases from CSIP which highlighted the unique capabilities of this
instrument. In particular: the dual-wavelengths allow the observer to
distinguish between Rayleigh scattering from
particles and Bragg scattering from turbulence; polarisation
data allows insects, liquid water and ice to be distinguished (e.g. Figure 1) and
gives information on raindrop size distributions and the radar’s Doppler
facility also allows velocities to be retrieved. The CSIP field campaigns have also provided
an opportunity to develop the Fabry technique; this
method allows mapping of the near-surface refractive index, by measuring the
backscatter from stationary “ground-clutter”.
The refractive index field depends on the air temperature and humidity,
but tends to be dominated by variations in humidity, and data from automatic
weather stations deployed during CSIP will be used to evaluate this technique. Dr Ulrich Corsmeier
(IMK) described how data from the numerous instruments deployed during the CSIP
campaign could be combined to give a clear picture of one day; in this case the
development of a sea-breeze over the south coast. Data from radiosondes,
automatic weather stations, aircraft and lidar were
combined to show the movement of the cooler wetter air inland during the day.
In particular, IMK’s Doppler lidar
gave very clear cross-sections through the head of the sea-breeze (Figures 2
and 3). Overall, the observations showed the sea-breeze suppressing convection
near the coast, but enhancing convection, where uplift occurred at the
sea-breeze head. Although turbulence and convection was detected along the
several hundred km long convergence line generated by the sea-breeze,
significant deep convection leading to subsequent showers was only observed in
that area where sea-breeze and synoptic scale instability in the lower
troposphere coincided. This leads to the conclusion that a sea-breeze alone
does not cause severe weather if there is no other driving force enhancing the
destabilization processes.
Peter Clark (Met Office) showed results
from the new non-hydrostatic UM, which is now run operationally with a grid-spacing
of 4 km, and was run for CSIP with a grid-spacing of 1 km. At these
resolutions, the model can often resolve the mesoscale
triggers, which allow precipitating storms to form. As a result, the model tends
to perform well, where storms are initiated by well resolved convergence lines.
For example, the 2004 Boscastle storm formed at the
intersection of two thermally driven convergence lines and is predicted by the
new UM, but not by the old mesoscale model. However,
the model does not resolve individual cumulus cells, and so requires a
spontaneous upscale organisation, with resolved
storms forming from unresolved convection, and in general the model results are
sensitive to the sub-grid turbulence scheme used. The new UM also frequently
represents secondary initiation by cold pool outflows remarkably well, although
the results can be very sensitive to cloud microphysics, particularly snow and
ice fallspeeeds. Again, such cases of secondary
initiation do not tend to be well represented by the old 12 km mesoscale model. The poorest UM forecast during CSIP was probably
for the 24th June 2005,
when mid-level storms led to floods at the Glastonbury
festival; for such mid-level convection it appears that current data
assimilation techniques do not tend to significantly improve the model’s
representation of the initiation process.
Established data assimilation schemes have been designed for
coarser resolution hydrostatic models and Dr
Mark Dixon (Met Office) highlighted the three main problems with applying
these techniques at high-resolutions (i) the failure
of the established balance constraints (ii) positional adjustment and (iii) the
multiple scales involved. Latent heat nudging techniques, which are currently
used to assimilate cloud and precipitation observations, are also based on
assumptions that break down at high-resolutions, but despite this, such schemes
have enjoyed some success. Developing 4DVariational assimilation (4DVar) for
high-resolutions should provide a more complex and computationally expensive,
but hopefully more accurate method of assimilation. It is however not yet clear
how to solve these three main challenges of high-resolution data assimilation
in the context of 4DVar.
(i)
Balance constraints: The balance constraints on
the model error covariance matrix can be switched off and the model trajectory
should establish balance between the variables, but it may be possible to
improve on this.
(ii)
Positional errors: a forecast can give an
incorrect position for a feature, such as a storm, but otherwise represent it well.
A flow dependent model error covariance matrix is one solution, but this is
difficult; an ensemble of runs is another approach, although this would be very
computationally expensive.
(iii)
The Multiscale
problem: A high-resolution model can give errors in the small scale features,
due to errors in the large scale fields inherited from the coarser models used
to provide boundary conditions. For example, errors in upper level PV anomalies
can lead to positional errors in forecast convection. In this situation
observations from outside the domain of the high-resolution model must be
assimilated into the model. This can be done by applying corrections applied to
a coarser scale model to the high-resolution model, but the background states of
those models are different, so it may be better to use these corrections as a
weak constraint on the high-resolution model. An alternative solution is to use
a variable grid, rather than the nested grids currently used in the UM, but
this makes ensembles very expensive.
These approaches will all need several years of development
to exploit their potential, but the Met Office aims to have an operational
assimilation system for high-resolution models by 2010. This is comparable with
other leading NWP centres worldwide.
In conclusion, CSIP has provided an exceptional dataset for
investigating the initiation of convective storms in the UK.
Together with modelling studies, these data can be
used to evaluate and quantify the processes that control the convective
initiation. Although this analysis is in its early stages, it has already shown
the variety of initiation processes in the UK
and some of the strengths and weaknesses of our forecasts. In particular, the
new non-hydrostatic UM has proved to be much more successful at forecasting
storms initiated by some mechanisms than others, and CSIP has already
highlighted some aspects of the UM that could be improved. As the new
generation of NWP models becomes established, further research should significantly
improve both our forecasts of convective storms and our understanding of their limitations.
John Marsham
Correspondence to: Dr
J. H. Marsham, Institute for Atmospheric science, Environment,
School of Earth and Environment, University of Leeds,
LS2 9JT, UK. Email: jmarsham@env.leeds.ac.uk