VON STORCH Hans Institute of Coastal Research Helmholtz Zentrum Geesthacht Germany w ith material of 李 德 磊 IOCAS Qingdao 26 September 2016 LASG IAP Beijing VON STORCH Hans ID: 630104
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Slide1
Regional re-analysis without regional data
VON STORCH HansInstitute of Coastal Research, Helmholtz Zentrum Geesthacht, Germanywith material of李德磊IOCAS, Qingdao
26
September 2016
– LASG, IAP, BeijingSlide2
VON STORCH Hans
Climate researcher (in the field since 1971)Coastal climate (storms, storm surges, waves; North and Baltic Sea, North Atlantic, Yellow Sea); statistical analysisDirector emeritus of the Institute of Coastal Research of the Helmholtz Zentrum
Geesthacht, GermanyProfessor at Universität Hamburg
Guest professor at
中国
海洋大学Slide3
Overview
Spectral nudging approach for constraining regional modelling- Improved representation of medium scale variability- Constructing a homogeneous regional re-analysis.Improved representation in coastal regions:- variability at medium scales.- sub-synoptic phenomena (e.g., polar lows)- forcing fields for impact models (ocean waves, storm surges)The regional reanalysis CoastDat
for governmental agencies, commercial companies and the public/media Slide4
Climate
and downscaling
The genesis of „regional“ climate my be conceptualized (only at
midlatitudes
?) as R = f(L,
Φ
s
) with L = larger scale climate, R = smaller scale climate,
Φ
s
= physiographic detail at smaller scale (mountains, cities, coastlines etc.).
Climate models generate numbers for all scales, beginning at the grid resolution. The smallest of these scales are heavily disturbed because of an insufficient representation of the small-scale physiography but also because of the abrupt truncation at the grid resolution.
The largest scales in global re-analysis may be in many cases considered as well an
d
homogeneously described. The smallest scales are considered less realistic and subject to
inhomogeneities
(sensitive to changes of observational local data availability).Slide5
Skillfully
represented scalesInsufficiently represented scalesGrid point resolutionMaximumresolution
Skillfully represented scales
Insufficiently
represented
scales
Grid point
resolution
Maximumresolution
Added
value
Global Analysis
Regional
Analysis
Con-straining
Downscaling using R = f(L,
Φ
s
) processes the reliably and homogeneously described large scales L. The constraining may be implemented by spectral nudging into a regional or even global dynamical model.
(
von Storch, H., H.
Langenberg
and F.
Feser
, 2000: A spectral nudging technique for dynamical downscaling purposes.
Mon.
Wea
. Rev.
128: 3664-3673)Slide6
Regional re-analysiswithout regional data.
exploiting the presence of a “downscaling” situation L > Rand the availability of long, homogeneous re-analysis of “large-scale” dynamics L.Added value is in R, i.e. in the regional detail, which results from L and the regional physiographic detail (such as coastlines, mountains)Done for - Europe (including hydrodynamic of marginal seas; COASTDAT)- China (Yellow Sea region, see 李德磊),- Central Siberia and Southern Atlantic,- nd recently
the Globe.Slide7
Improved presentation of
in coastal regionsERA-I-driven multidecadal simulation with RCM CCLM over the Bohai Sea and the Yellow Sea region (李德磊, 2015)Grid resolution: 0.06oMaterial by 李德磊 Slide8
Model setups
and datasets
Long-term simulation
COSMO-CLM (CCLM):
1979.01-2013.12,
spectral
nudging
Forcing dataset
ERA-Interim (1979 – 2013,
~
80km,
6
hourly
)
Physical
Para-
meterization
Tiedtke
convection
scheme
and
Charnock-formula
for
RL
Resolution
Spatial
: 0.0625° (~7 km),
40
vertical
layers
,
hourly
output
GridRotated coordinate system168 x 190
Land Station Data67 land surface stations, 3-hourly (HadISD)Marine StationData7 stations, including 3 offshore stations and 4 coastal stations (NCDC and KMA)Satellite DataQuikSCAT L2B in 12.5 km swath data (QSCAT, 1999.12- 2009.11)Slide9
Is there an added value?
9
Added value (positive BSS) in coastal areas for wind speed > 3 m/s
BSS:
[-
1, 1
]
BSS =1, Perfect model
BSS > 0,
added value (improvement)
BSS < 0,
no
added value
is
error variance between the regional model data
and QSCAT;
is
error
variance between the reference
data ERA-I and QSCAT.
Modified Brier Skill Score: BSS (
Winterfeldt
et al. 2011)
Areas with added value are larger for strong wind speed (right) than for wind speed > 3 m/s (left)
BSS (CCLM, ref: ERA-I,
obs:QSCAT
> 3 m/s)
BSS (CCLM, ref: ERA-I,
obs:QSCAT
> 10.8 m/s)
IEO
S
EOSlide10
Comparison of CCLM/ERA-I and in-situ data:
offshore station (IEO)No improvement of CCLM wind speed (left) relative to ERA-I wind speed (right) at offshore station IEOCCLMERA-I
qq
-plotSlide11
11
Comparison of CCLM/ERA-I and in-situ data : coastal station (SEO)CCLM wind speed (left) is in better agreement with observations than ERA-I wind speed (right) at coastal station SEOCCLMERA-I
qq-plotSlide12
Climatological mean of annual extreme surface wind speed (99%-
iles) 12Similar distribution pattern, more spatial variability and detail in CCLM wind field
CCLM: lower values over mountainous areas and larger values over some water areas
CCLM: better in agreement with observations
(m/s)Slide13
NCEP-driven multidecadal simulation with RCM CLM over North Pacific
(陈飞 et al., 2012, 2013, 2014)Grid resolution: about 0.4oEmploying spectral nudging (wind above 850 hPa, for scales > 800 km)Simulation of sub-synoptic phenomenaPolar lows in the Northern North PacificGenerating additional regional dynamical detailSlide14
North Pacific Polar Low
on
7 March 1977
NOAA-5 infrared satellite image at 09:58UTC 7th March 1977
North Pacific Polar Lows
(
陈
飞
et al.,
2012, 2013 and 2014)Slide15
Annual
frequency of past polar lows in the North Pacific
陈
飞
et al., 2013
Number of detected Polar Lows in the North
Pacific per
Polar Low season
(PLS; October
to April
). The trend
from 62 PLSs, from 1948/1949
to 2009/2010
,
amounts to 0.17 cases/year
.Slide16
Improved representation of
forcing fields for impact models NCEP-driven multidecadal simulation with RCM REMO in EuropeGrid resolution: 0.5 oEmploying spectral nudging (wind above 850 hPa, for scales > 800 km)1948-2010 simulationWind and air pressure used to drive hydrodynamical models for describing currents and sea level Wind used to drive models of the statistics of surface waves (ocean waves) in coastal seas (North Sea).Slide17
Red: buoy,
yellow: radar,
blue: wave model run with REMO winds
wave direction
significant wave height
[days]
[days]
Gerd Gayer, pers.
comm
., 2001Slide18
Annual mean winter high waters Cuxhaven
red – reconstruction
, black – observations
Interannual variability of mean water levels
(Weisse and Plüß 2006)Slide19
The
CoastDat-effort at the Institute for Coastal Research@HZG
Long-term, high-resolution
reconstructions
(60 years) of
present
and recent developments of weather related phenomena in coastal regions as well as scenarios of future developments (100 years)
Northeast Atlantic and northern Europe.
Assessment of changes in storms, ocean waves, storm surges, currents and regional transport of anthropogenic substances.
Applications
many authorities with responsibilities for different aspects of the German coasts
economic applications by engineering companies (off-shore wind potentials and risks) and shipbuilding company
Public information
www.coastdat.de
Integration area used in HZG reconstruction and regional scenariosSlide20
Wave Energy Flux [kW/m]
Currents Power [W/m
2
]
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
Weisse, pers.
c
omm
.Slide21
Conclusion …
Dynamical downscaling (R = f(L,Φs)) works … - Large scales are hardly affected but smaller scales are more realistically described in heterogeneous regions (coasts, mountains)Downscaling allows the generation of homogeneous data sets i.e., a regional re-analysis
with uniform quality (across time). Added value in describing medium scale phenomena – such as wind
storms
Added value in generating regional impact variables,
such as
wind for storm surges and ocean waves.Several such regional re-analysis
has been done, among them for the region of the Bo Hai and the Huang Hai on a 7-km grid by 李德
磊.