Wind storm research at HZG Coordination of storm themes
Matthias Zahn
Institute of Coastal Research
Helmholtz-Zentrum Geesthacht
Matthias.Zahn@hzg.de
February 10, 2014
SICSS visit 10 February, Helmholtz-Zentrum Geesthacht
Focus of research: maritime storms over
the world oceans, extra tropical storms
Focus of research: maritime storms over
the world oceans, typhoons
Focus of research: maritime storms over
the world oceans, polar lows
Focus of research: maritime storms over
the world oceans, medicanes
Current members of HZG with emphasis
on storm themes:
◮
◮
◮
◮
◮
◮
Dr.Frauke Feser, leader
Dr.Matthias Zahn, detection and tracking
Martina Schubert-Frisius, model simulations
Svenja Bierstedt, long-term changes along
the Baltic coastline
Delei Li, Bohai and Yellow Sea
Benjamin Schaaf, extra tropical storms and
their coastal impacts in the North Sea
Tools of research: numerical models
dynamical downscaling
different types of models of the atmosphere/ocean,
used in so called model chains
Why models?
◮
◮
◮
◮
homogeneity
spatially extended information
long in time
future scenarios
Example of recent research: polar lows
◮
◮
◮
◮
◮
◮
diameter < 1000km
strong winds > 13.9 ms
heavy precipitation
poleward Polar Fronts in
winter
spiral cloud and cloud free
core (Arctic Hurricane)
rapid development
c
Dundee
Satellite Receiving Station
Used here: Regional Climate Model
Model grid
◮
◮
◮
60 years of NCEP/NCAR reanalysis data
downscaled using COSMO-CLM-2.4.6.
spectral nudging applied
Example of a reproduced PL case
15 Oct 1993, 6:00, The Swan
Example of a reproduced PL case
15 Oct 1993, 6:00, The Swan
How to detect storms? Spatial filter!
(a) full field
(b) low pass
(c) band pass
(d) high pass
Example of band-pass filtered MSLP
200-600km retained, PLs emerge as distinct minima
Dec 1993 case
2
1
&
A
6
5 ;;
A
+*#$*+%. #0 //
5 ;;
6 &
Jan 1998 case
&
&
A
#3*#*+3. ( //
5 )-
5 )-
6 &
Detection and tracking scheme
1. record all locations at which filt. MSLP
minimum ≤ −1hPa
2. combine detected positions to individual tracks, distance to
next (3h) pos ≤ 200km
3. checking further constraints along tracks:
◮
◮
◮
◮
◮
filt. minimum ( ≤ −2hPa once along track)
wind speed (≥ 13.9 ms once along track)
air-sea temperature difference (SST − T500hPa ≥ 43K )
no northward direction of track
limits to allowable adjacent grid boxes
OR: minimum in band-pass filtered MSLP ≤ 6hPa once
Tracks of three (of >3300) polar lows
Reproduced and detected after more than 40 years simulation time
Annual numbers of PLs (1949-2005)
Number of PLs per Polar Low Season (PLS), one PLS from July until June next year
Comparison with observed cases
bias, but qualitative
similarity to observation
data
black: our data (Zahn and v.Storch, 2008)
adjusted to observation data
red: MetNo (pers. comm.)
Wilhelmsen (1985)
Blechschmidt (2008)
Future projections
90˚
280˚
80˚
70
˚
0˚
29
60
˚
0˚
30
˚
50
0˚
350˚
˚
340
0˚
33
0˚
˚
40
30˚
20˚
Model grid
10˚
32
◮
0˚
◮
driven by ECHAM5/MPI-OM
C20: control with GHG 1960-1990
B1,A1B,A2: GHG for 2070-2100 (AR4)
31
◮
Projected cumulative frequency of PLs in
IPCC-scenarios and annual cycle
significant decrease in the
number of PLs per winter
14
Blechschmidt
Wilhelmsen
REA
C20
B1
A1B
A2
average number of polar lows per month
12
10
8
6
4
2
0
Jan
Mar
May
Jul
month
Sep
Number of PLs per month
Nov
Polar Lows and projected vertical stability
◮
◮
proxy for frequency of
favourable PL conditions
decreases
large inter model bias, but same
direction of change
Frequency changes of Polar Lows
No change in recent past, but high
interannual variability
Significant decrease of annual number
in response to global warming
Decrease linked to more stable mean
conditions
Further examples: medicanes
NCEP
°
10 W
50° N
°
5 W
°
0
°
5 E
°
10 E
°
15 E
°
20 E
°
25 E
°
30 E
°
35 E
°
40 E
6
5
°
45 N
4
40° N
3
°
35 N
2
°
30 N
1
°
0
25 N
1950
locations of genesis
1960
1970
1980
1990
2000
2010
number per season
Cavicchia (2013), NCEP downscaled to 10km
resolution with CLM
40 E
Further examples: typhoons
Further examples: extra-tropical
storminess
NEW APPROACH: global downscaling,
tracking storms worldwide
↓
a wealth of different nudging
configurations are checked:
◮ wave-length
◮ vertical profile
◮ strength of nudging
◮ variables considered
tracking procedure adjusted to
new type of data
examining different nudging configurations
October 2004, TOKAGE, N1
120˚
130˚
140˚
150˚
160˚
30˚
170˚
distance to Best Track
BEST Track Storm
EH6_N1_av_005dv L: 32
EH6_N1_av_01dtv L: 37
EH6_N1_av_01dv L: 38
EH6_N1_av_05dv L: 40
EH6_N1_dvw_005dv L: 36
EH6_N1_dvw_01dtv L: 37
EH6_N1_dvw_01dv L: 38
EH6_N1_dvw_05dtv L: 34
EH6_N1_dvw_05dv L: 40
EH6_N1_dvw_09dtv L: 33
EH6_N1_dvw_09dv L: 0
EH6_N1_dvw_echam6_dtv L: 37
EH6_N1_dvw_echam6_dv L: 51
EH6_N1_echam6 L: 34
EH6_N1_echam6_dtv L: 32
EH6_N1_echam6_dv L: 36
EH6_N1_ev_005dv L: 38
EH6_N1_ev_01dtv L: 36
EH6_N1_ev_01dv L: 44
EH6_N1_ev_05dtv L: 38
EH6_N1_ev_05dv L: 0
EH6_N1_ev_09dtv L: 32
EH6_N1_ev_09dv L: 39
EH6_N1_av_001dv L: 11
[km]
400
200
600
Wind speed
50
40
30
[m/s]
110˚
40˚
20˚
20
10
1025
MSLP
975
10˚
950
13
14
15
16
17
time
18
19
20
925
[hPa]
1000
examining different nudging configurations
October 2004, TOKAGE, n1
110˚
40˚
120˚
130˚
140˚
150˚
160˚
170˚
distance to Best Track
BEST Track Storm
EH6_n1_av_005dv L: 38
EH6_n1_dvw_005dv L: 38
EH6_n1_dvw_echam6_dv L: 31
EH6_n1_ev_005dv L: 27
[km]
400
200
30˚
600
Wind speed
40
30
[m/s]
50
20˚
20
10
1025
MSLP
975
10˚
950
13
14
15
16
17
time
18
19
20
925
[hPa]
1000
SUMMARY
We investigate changes of different types of
maritime storms
We apply sophisticated modelling methods
Results are for the recent past and an
anticipated warmed future
Thank you very much for your attention
http://coast.hzg.de/staff/zahn/