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STORMS IN NORTHERN EUROPE

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STORMS IN NORTHERN EUROPE CHANGES, PERSPECTIVES, AND IMPACTS HANS VON STORCH Institute of Coastal Research, (Helmholtz Zentrum Geesthacht), and – PowerPoint PPT presentation

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Title: STORMS IN NORTHERN EUROPE


1
STORMS IN NORTHERN EUROPE CHANGES,
PERSPECTIVES, AND IMPACTS
  • HANS VON STORCHInstitute of Coastal Research,
    (Helmholtz Zentrum Geesthacht), and
  • KlimaCampus Hamburg, Germany

TOKIO MARINE'S 2011 SUMMIT ON GLOBAL WARMING AND
CLIMATE CHANGE, APRIL 29, 2011, ATLANTA USA
2
Counting storms in weather maps steady increase
of NE Atlantic storms since the 1930s .
3
Popular argument When it is getting warmer, then
we have more water vapor in the atmosphere, and
mid-latitude storms become more intense (more
fuel).
However at mid latitudes, intense storms are
baroclinic, and thus driven by temperature
differences explaining, why we have more
storms in the cold season that in the warm
season.
Unchanging extratropical storm conditions are not
inconsistent with a rise in temperature
4
Homogeneity of local observations(Wind speed
measurement SYNOP Measuring net of German
Weather service Coastal stations at the German
Bight Observation period 1953-2005)
  • Causes of inhomogenities
  • Changes in
  • Instruments
  • Sampling frequencies
  • Measuring units
  • Environments (e.g. trees, buildings)
  • Station relocations (Dotted lines)

Lindenberg et al., 2011
5
Representativity of near surface wind speed
measurements
6
  • The major problem for applying statistical
    analysis in climate change studies is related
  • to the assumptions of a stationary sampling
    process, and
  • to the assumption of representativity.
  • The local data change their statistics because of
    changing observational practices and conditions
    (inhomogeneity) also their representativity for
    a larger area is often compromised.
  • Usage of weather analyses, incl. re-analyses and
    proxies such as damages are generally not
    suitable.

7
For assessing recent and ongoing changes of
mid-latitude storm conditions, principally two
approaches are possible
  • Use of proxies derived from air pressure
    readings.
  • Simulation by empirical or dynamical downscaling
    of large scale information.

8
  • A proxy of storminess Intraseasonal statistics
    of daily geostrophic winds (pressure gradients)
  • Air pressure readings are mostly homogenous
  • The scaled pressure gradient is called
    geostrophic wind.
  • The tropospheric wind is to first order
    approximation proportional to atmospheric
    pressure gradient
  • We use annual/seasonal percentiles (e.g., 95 or
    99iles ) of geostrophic wind derived from
    triangles of pressure readings as proxies for
    annual /seasonal storminess.

Schmidt and von Storch, 1993
9
Testing the robustness of the link seasonal
percentiles of geostrophic wind speed and of
surface wind speeds in the virtual reality of a
50 years regional simulation
Correlations between time series of geostrophic
wind speed percentiles and wind speed percentiles
Krueger and von Storch, 2011
Triangles used
10
Geostropic wind stats N Europe
99iles of annual geostrophic wind speeds for a
series of station triangles in the North Sea
regions and in the Baltic Sea region.
Alexandersson et al., 2002
11
Dynamical (process based model) downscaling
cascade for constructing variable regional marine
weather statistics
  • Dynamical downscaling to obtain high-resolution
    (10-50 km grid 1 hourly) description of weather
    stream- with spectral nudging constraint- use of
    NCEP or ERA re-analysis allows reconstruction of
    regional weather in past decades (1948-2010)-
    when global scenarios are used, regional
    scenarios with better description of space/time
    detail can be derived.
  • Meteorological data are fed into dynamical
    models of weather-sensitive systems, such as
    ocean waves, catchment hydrology, long-range
    pollution etc.

12
Extreme value analysis of wind speed at platform
K13 (southern North Sea) January 1980-January 1997
Weisse, pers. comm.
13
Stormcount 1958-2001
t T
t T
Weisse et al., J. Climate, 2005
Change of Bft 8/year
14
Skill in representing wave conditions
significant wave height
days
wave direction
days
Red buoy, yellow radar, blue wave model run
with REMO winds
Gerd Gayer, pers. comm., 2001
15
www.coastdat.de
  • The CoastDat data set
  • Long (50 years) and high-resolution
    reconstructions of recent offshore and coastal
    conditions mainly in terms of wind, storms,
    waves, surges and currents and other variables in
    N Europe
  • Scenarios (100 years) of possible consistent
    futures of coastal and offshoreconditions
  • extension ecological variables, SE Asia
  • Clients
  • Governmental various coastal agencies dealing
    with coastal defense and coastal traffic
  • Companies assessments of risks (ship and
    offshore building and operations) and
    opportunities (wind energy)
  • General public / media explanations of causes
    of change perspectives and options of change

16
Some applications of
  • Ship design
  • Navigational safety
  • Offshore wind
  • Interpretation of measurements
  • Oils spill risk and chronic oil pollution
  • Ocean energy
  • Scenarios of storm surge conditions
  • Scenarios of future wave conditions

Wave Energy Flux kW/m
Currents Power W/m2
17
Range of changes in seasonal maximum wind (10 m)
in Northern Germany in a series of dynamically
downscaled scenarios (HadCM, MPI A2, B2)
18
Polar lows
  • Mesoscale (lt 1000 km) sized maritime storms
  • intense/ strong winds , severe weather
  • occur polewards of the Polar Fronts in both
    hemispheres during winter
  • typically induced by disturbances in the air
    flow
  • typically driven by convective processes
  • Here only Northern North Atlantic

Spitz-bergen
Scandinavia
19
Past annual frequencies of polar lows
PLS Polar Low Season (July-June)
Zahn and von Storch, 2008
20
Downscaling scenarios
Downscaling scenarios and simulations C20
(1960-1989) A2, B1, A1B1 (2070-2099) run with
ECHAM5/MPIOM1 downscaled with CLM, employing
spectral nudging.
21
Projected changes in polar low frequency and
vertical atmospheric stability
Differences of the area and time-averaged
ice-free SST and T500hPa over the maritime
northern North Atlantic as proxy for frequency of
favorable polar low conditions (CMIP3/IPCC AR4)
Zahn and von Storch, 2010
22
Past and future occurrence of North Atlantic
Polar Lows
  • Past changes according to dynamical downscaling
    of NCEP/NCAR re-analysis 1949-2005
  • Strong inter annual variability
  • Frequency remains on a similar level no
    systematic trend
  • Polar lows become less frequent in the Northern
    North Atlantic in the coming 100 years according
    to
  • regional modeling (dynamical downscaling) -
    control and scenario simulations with one GCM,
    and by
  • analysis of vertical stability in a large set
    of (CMIP3) global climate simulations all
    simulations show an increase in projected
    stability.
  • The genesis regions shift northward.

23
Conclusion Usage of proxies
  1. Monitoring extra-tropical storminess may be based
    on air pressure proxies.
  2. This allows assessments for 100 and more years.
  3. Decades long upward and downwards trends have
    been detected in recent years in the Northern
    European and other regions.
  4. These trends are not sustained and have show
    recent reversals in all considered regions.
  5. Recent trends are not beyond the range of natural
    variations, as given by the historical past, but
    are more of intermittent character. Regional
    temperatures rose significantly at the same time.

24
Conclusion Usage of dynamical downscaling
  1. Dynamical downscaling for describing synoptic and
    mesoscale variability is doable.
  2. Analysis of 60 year simulations point to strong
    year-to-year variability, to less
    decade-to-decade variability and no noteworthy
    trend in the region of the North
    Atlantic/European Sector both in terms of
    baroclinic storms and polar lows.
  3. Similar study done for North Atlantic Polar Lows
    , E Asian typhoons and medicanes. (work in
    progress)

25
Mediterranean hurricanes are strong mesoscale
cyclones with some resemblance with tropical
cyclones and polar lows (warm core, cloud-free
eye, winds up to hurricane speed) that develop
occasionally over the Mediterranean Sea.
Medicanes
15 Jan 1995
Dynamically downscaled
Leone Cavicchia, pers. comm
26
  • Take-Home Message
  • Baroclinic storms and polar lows represent key
    climatic risks in Northern Europe.
  • In the past, no noteworthy systematic changes
    have been detected, when homogeneous,
    sufficiently long times series of evidence has
    been considered.
  • For the futures, scenarios describe the
    possibility for a weak intensification of strong
    wind cases (baroclinic storms) in winter, and a
    reduction and northward shift of polar low
    activity.
  • Scenarios are consistent with ongoing change.
  • The methodology, based on dynamical downscaling
    and the usage of proxies for storminess are well
    developed. They may be employed for analyzing
    conditions in other parts of the world.

27
Reserve
28
How do size and surface conditions influence the
description of storm activity?
29
Single-station based proxies
(median 0.198, 0.05-quantile -0.09)
correlations between annual 99th percentiles of
ground level wind speed and annual number of
pressure observations below 980 hPa
30
Local pressure stats since 1800
Stockholm Lund
Time series of pressure-based storminess indices
derived from pressure readings in Lund and
Stockholm. From top to bottom Annual number of
pressure observations below 980 hPa (Np980),
annual number of absolute pressure differences
exceeding 16 hPa/12 h (NDp/Dt), Intra-annual
95-percentile and 99-percentile of the pressure
differences (P95 and P99) in units of hPa. From
Bärring and von Storch, 2005 see also BACC 2008.
31
Special application assessing the lull wind
conditions, leading to insufficient energy
harvest by wind mills in Germany, winters
2008-2009
Weisse, pers. Comm.
32
Downscaling vs. obs
C0,72
NCEP-based downscaling (black) and observations
(red) of MetNo (Noer, pers comm)
Monthly comparison of NCEP-downscaling (in black)
with analysed observed data (in red
Blechschmidt, 2008)
33
Density of polar low genesis
Genesis in NCEP downscaling RCM simulation
Bracegirdle, T. J. and S. L. Gray, 2008
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