retrospective analysis of ne atlantic weather (especially storms) extrop miami workshop:...
Post on 21-Jan-2016
220 Views
Preview:
TRANSCRIPT
Retrospective analysis of NE Atlantic weather (especially storms)
EXTROP Miami Workshop: Investigation of Tropical and Extra-tropical cyclones using passive and active microwave radar, Miami, 27.2.-1.3.2006
Frauke Feser
and Hans von Storch
Institute for Coastal Research, GKSS, Germany
Outline …
• Regional climate modelling as a downscaling problem
• Determination of added value provided by downscaling with RCMs
• Applications of 1958-2004 “reconstruction”
Climate = statistics of weather
The genesis of climateCs = f(Cl, Φs)
with Cl = larger scale climate
Cs = smaller scale climate
Φs = physiographic detail at smaller scale
von Storch, H., 1999: The global and regional climate system. In: H. von Storch and G. Flöser: Anthropogenic Climate Change, Springer Verlag, ISBN 3-540-65033-4, 3-36
“downscaling”
The concept of downscaling does NOT imply that smaller scales are irrelevant for simulating the larger scales in atmosphere and ocean models
Small scale processes, such as convection, play a key role in forming the global climate. However only the overall effect of these processes matters, not the space-time details. Therefore “parameterizations” of small scale processes are sufficient for such models.
It is this fortuitous arrangement, which allows us simulate the global and continental climate well – even without simulating any regional climate adequately.
2d grid corresponding to a T42 spectral description
global model
Well resolved
Insufficiently resolved
vari
ance
Problem:
Global models and analyses do not resolve regional detail.
Global climate models operate with grid sizes of often 200 km, and analyses with 100 km.
Thus, they resolve spatial scales of, possibly, 500-1000 km.
500- 1000 km ?
100-200 km
Large … small spatial scales
Regional climate modelling as a downscaling problem
von Storch, H., H. Langenberg and F. Feser, 2000: A spectral nudging technique for dynamical downscaling purposes. Mon. Wea. Rev. 128: 3664-3673
Dynamical downscaling mit LAM (Limited Area Model)
.operator suitable a
)(
:nintegratio Forward
modeln observatio
model dynamical
errorsn observatio and model , h wit
equation n Observatio
equation space State
1111
*1
*1
1
1
Kwith
)dK(dΨΨ
Gd
);ηF(ΨΨ
G
F
δ) G(Ψd
ε) ;ηF(ΨΨ
t*t
*t t
tt
tt*t
tt
ttt
tttt
Concept of Dynamical DownscalingRCM Physiographic detail
3-d vector of state
Known large scale state
projection of full state on large-scale scale
Large-scale (spectral) nudging
Spectral nudging vs. standard formulation
• The genesis of regional climate is better framed as a downscaling problem and not as a boundary value problem.
• Spectral nudging constrains the dynamics on the “large” scales while “small” and “medium” scales remain unconstrained.
• “Solution” in the interior of a RCM domain is not determined by the boundary values. The problem is mathematically ill posed.
Weis
se,
pers
. co
mm
.
January 1980-January 1997
Extreme value analysis of wind speed at platform K13 (southern North Sea)
simulated
observed
Model output vs radar and buoy measurements
Lid
ia G
asl
ikova,
pers
. co
mm
.
Significant wave height
Wave mean direction (coming from)
Determination of added value provided by
downscaling with RCMs
Feser, F., and H. von Storch, 2005: Spatial two-dimensional discrete filters for limited area model evaluation purposes. Mon. Wea Rev 133, 1774-1786
Feser, F., 2006: Enhanced detectability of added value in limited area model results separated into different spatial scales, Monthly Weather Review (in press)
Spatial scale separation in 1 dimensionSpatial scale separation in 1 dimension
• Design of digital filters for discriminating different spatial scales.
• Expected added value in medium scales, if large scale sufficiently well described.
N=8 Low pass + medium pass filter
Response functions of constructed 2d isotopic digital filters, constructed to approximate regions of unaffected “waves” and suppressed “waves”.
Example of a decomposition of a field into large- and medium scale contributions.
Note that the two fields do not add up to the full field.
Zonal wind component at a height of 10 m
Determination of added value
• Comparison with operational regional weather analysis prepared by DWD (1992-1999) – representing supposedly the “truth”.
• NCEP is geostatistically interpolated to LAM grid (only 2m temp and SLP).
• Comparison on different spatial scales: large and medium scales.
• Ratio of temporal standard deviations• Pattern correlation coefficients.
Ratio of 2m temperature st’ddev’s DJF 1992-1999 (medium scales only)
DWD/NCEP [%] DWD/REMO [%]
Pattern correlation coefficients [PCC, %] Positive values indicate an
added value provided by the RCM.
Significant improvements (rejection of null hypothesis of no added value; 5% risk) are marked by an asterisk *.
RCM/sn = REMO with spectral nudging
RCM/nn = REMO with lateal forcing only
PCC of DWD (“truth”) and
NCEP
PCC change when
RCM/sn is used
PCC change if RCM/nn is used
Added value …
• … in medium scales.• Medium scales are determined by both the
large scale dynamics and the regional physiographic details (Cs = f(Cl, Φs))
• More added value with large-scale constraint (spectral nudging)
• Little improvement for SLP, which is a large-scale variable.
• Significant improvement for 2m temp, which is strongly affected by regional detail.
Applications of the 1958-2004 reconstruction of regional
weather
Weisse, R., H. von Storch and F. Feser, 2005: Northeast Atlantic and North Sea storminess as simulated by a regional climate model 1958-2001 and comparison with observations. J. Climate 18, 465-479
Feser, F., R. Weisse and H. von Storch, 2001: Multidecadal atmospheric modelling for Europe yields multi-purpose data. EOS 82, 305+310
Weisse, R. and A. Plüß, 2005: Storm related sea level variations along the North Sea Coast as simulated by a high-resolution model 1958-2002, Ocean Dynamics, DOI: 10.1007/s10236-005-0037-y
General Strategy• Dynamical downscaling to obtain high-resolution (50 km grid; 1 hourly) description of weather stream.
•Use of NCEP re-analysis allows reconstruction of regional weather in past decades (1958-2004)
• Meteorological data are fed into dynamical models of weather-sensitive systems.
Integration area used in GKSS reconstruction and regional scenarios
Applications• Assessment of changing
storminess • Storm surges • Ocean wave conditions • Long-range pollution –
examples: gasoline lead and benz-a-pyren
• “Commercial” applications (e.g., assessment of oil drifts in case of coastal accidents, assessment of fatigue in ships and off-shore constructions (with FGS Flensburg), Planning of harbor, costal defense and off-shore wind constructions)
Stormcount 1958-2001
Weis
se , p
ers
. co
mm
.
C/year
t < t >
model estimate
Estimated lead depositions into the Baltic Sea, compared to analyses based on observational evidence
Conclusions
• Regional models can be used to “reconstruct” detailed weather in the past decades by downscaling global re-analyses.
• In particular information about marine wind can be used for assessing past developments and contemporary risk assessments.
On Wednesday, three more (partly critical)
presentations on related issues
• Matthias Zahn, Uni HH/GKSS: Case studies of polar lows
• Jörg Winterfeld, GKSS: Added value of wind fields from regional models
• Stig Wilkenskjeld, GKSS: Extreme wind waves from WAM
top related