The utility of long-term reconstructions with regional climate/earth system models Hans von Storch Institute for Coastal Research, GKSS Research Center, Germany and KlimaCampus, U of Hamburg, Germany

What is coastDat? A set of model data (hindcasts, reconstructions and scenarios for the future) Based on experiences and activities in a number of national and international projects (e.g. WASA, HIPOCAS, STOWASUS, PRUDENCE) Presently contains atmospheric and oceanographic parameter (e.g. near-surface winds, pressure, temperature and humidity; upper air meteorological data such as geopotential height, cloud cover, temperature and humidity; oceanographic data such as sea states (wave heights, periods, directions, spectra) or water levels (tides and surges) and depth averaged currents, ocean temperatures) Covers different geographical regions (presently mainly the North Sea and parts of the Northeast Atlantic; other areas such as the Baltic Sea, polar regions or SE-Asia are to be included)

Weisse, R. , H. von Storch, U. Callies, A. Chrastansky, F. Feser, I Weisse, R., H. von Storch, U. Callies, A. Chrastansky, F. Feser, I. Grabemann, H. Günther, A. Plüss, T. Stoye, J. Tellkamp, J. Winterfeldt and K. Woth, 2009: Regional meteo-marine reanalyses and climate change projections: Results for Northern Europe and potentials for coastal and offshore applications. Bull. Amer. Meteor. Soc., May 2009

Overview Construction of CoastDat Validation of CoastDat Applications – Assessment of N European Storm Climate and related issues Applications – pathway of gasoline lead pollution Applications – marine-meteo issues

Downscaling cascade

global model variance Spatial scales Insufficiently resolved Well resolved Spatial scales

regional model variance Spatial scales Added value Insufficiently resolved Well resolved Spatial scales Added value

Concept of Dynamical Downscaling RCM 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 Similarity of zonal wind at 850 hPa between simulations and NCEP re-analyses large scales medium scales standard formulation large-scale nudging

Spectral nudging vs. standard formulation

Extreme wind speeds over sea – simulated and recorded These plots are the quantile-quantile diagrams (REMO & NCEP Vs Observations) for 10-m wind speed at 2 buoys station. The first one is an Atlantic offshore buoy (ZBGSO, located at 48.7N,12.40W), already assimilated by NCEP. The second one shows results from a Mediterranean buoy (ZATOS, located at 39.96N, 24.72E, Aegean Sea), whose data have NOT been previously assimilated by NCEP.

Interannual Variability of Storm Indices Storm index Lund: red - reconstruction, blue - observations (after Bärring and von Storch 2005)

Interannual Variability Water Levels (Weisse and Plüß 2006) Annual mean winter high waters Cuxhaven red – reconstruction, black – observations

Wind and Waves at K13 Wind speed [m/s] Wind direction [degrees] Sig. wave height [m] Mean wave direction [degrees] Observations – black; Hindcast - green (Weisse and Günther. 2007)

20-yr running trends in SST at Helgoland (German Bight) (Meyer et al. 2009)

Applications a) Assessment of N European Storm Climate and related issues Pathway of gasoline lead pollution Marine-meteo issues

Changes of the wind climate Climate = statistics of weather, as given by distributions or parameters thereof, such as means, percentiles etc. Changes of wind stats difficult to determine, because of changing observation practices. Earlier: visual assessment, nowadays: instrumental. Another difficulty is that the recorded values depend on the immediate environment of the location where the observation is made. This environment is subject to gradual and abrupt changes. Almost all long record of wind observations are inhomogeneous, i.e., they do not only reflect changes of the wind statistics but also other factors, such as observation method, practice, location, analysis method …. Inhomogeneity is a key constraint, which is usually overlooked by non-experts. Improved instruments and analysis introduces into data records such inhomogeneities (and thus, false signals).

Counting storms in weather maps – steady increase of NE Atlantic storms since the 1930s …. inhomogeneous 45 min‘s · Ideally a review of the methods employed in your field to detect and analyze change and feedbacks, finishing off with what the state of the art is in the methods and suggestions for newer methods that might be transferable to hydrologic extremes · We are most interested in the methods you employ rather than a possible synthesis with hydrology · Summarize the challenges you are facing detecting and analyzing change and feedbacks and assigning causality to them

Stormcount 1958-2001 C/year t <  t >  Linearer Trend Stuerme in Anzahl/Jahr ermittelt fuer den Zeitraum 1958-2001.  alle Stuerme >= Bft 8 (17.2m/s)   Relativer Trend, d.h. Aenderungen relativ zum langjaehrigen Mittelwert. beachte, dass der bei schweren Stuermen oft nur 1-3 betraegt. Signifikanz wurde mit Hilfe Mann-Kendall Test getestet. Da wo die Nullhypothese "kein Trend" mit 5% Irrtumswahrsch. verworfen werden muss wurde das 95% Konfidenzintervall "D" fuer den Trend "x" geplottet (x-D <= x <= x+ D)

Changing significant wave height, 1958-2002 waves 50,75, 90, 95, 99 and 99.9%iles of significant wave heights (m) and linear trends wind

Trends of annual percentiles of surge heights, 1958-2002 Weisse & Plüß, 2005 90%iles 1958-2002

Scenarios 23 Estimated change in maximum wind speeds in winter, according to IPCC climate change scenario A2 in 2070-2100 Scenario of change of extreme rainfall in summer according to downscaled Hadley Center scenario A2. (Rockel, pers. comm)

+5-10% relative to present ~+1%/decade if linear increase assumed Annual 99%ile significant wave height Climate Change Signals [m] 2071-2100 ./. 1961-1990 (Grabemann and Weisse 2008) RCAO/HAD RCAO/ECH A2 B2 Max. Change 2071-2100 +5-10% relative to present ~+1%/decade if linear increase assumed Present Day 99%ile (IPCC, 2001)

Storm surges-scenarios for 2085 A2 -changes in 99 % - iles of wind speed (6 hourly, DJF): west wind sector selected (247.5 to 292o) HIRHAM RCAO Increase of strong wind speeds (seasonal 99%iles; westerly winds) until 2070-2100 as compared to 1960-1990. of the order of  10% thus, per decade less than 1-2%  change should not be detectable at this time. Woth, 2005, GRL 45 min‘s · Ideally a review of the methods employed in your field to detect and analyze change and feedbacks, finishing off with what the state of the art is in the methods and suggestions for newer methods that might be transferable to hydrologic extremes · We are most interested in the methods you employ rather than a possible synthesis with hydrology · Summarize the challenges you are facing detecting and analyzing change and feedbacks and assigning causality to them

Local storm surge rise - scenarios for 2030, 2085 incuding sea level rise (IPCC AR4) Only the effect of changing weather conditions is considered, not the effect of water works such as dredging the shipping channel.

Climate simulations with CLM ( ~50km) for Polar Lows 1948-2007 Driven by the NCEP reanalysis Spectral Nudging Zahn, M., and H. von Storch, 2008: A longterm climatology of North Atlantic Polar Lows. Geophys. Res. Lett., 35, L22702, doi:10.1029/2008GL035769

North Atlantic Polar Lows

East Asian typhoons 60 year simulation with 50 km grid, Experimental case and season simulations with embedded 18 km grid. Feser and von Storch, forthcoming

Note: different criteria employed

Flow and deposition of substances Lead deposition in Europe Many anthropogenic substances released into the environment are transported over long distances and are deposited all over Europe and the rest of the world. Long term and spatially representative measurements unavailable. Alternative: use of circulation and precipitation from long-term weather reconstruction to model fate of substances. Flow and deposition of substances die Emissionsdatenbasen stammen von Pacyna und wurden im wesentlichen aus Schätzungen von Experten aus den einzelnen europäischen Ländern zusammengestellt. Diese Emissionen gibt es für 70, 75, 80, 85, 90, 93 Die europäischen BaP Emissionen werden deutlich durch die stationäre Verbrennung von fossilen Brennstoffen dominiert. Mit ca. 45% der Gesamtemissionen 1990 waren industrielle Produktionsprozesse wie Kokerei, Stahl und Aluminium Produktion die bedeutendste Quellkategorie, gefolgt von der nicht industriellen Verbrennung von Kohle. Emissionen aus mobilen Dieselmotoren trugen insgesamt mit knapp 6% bei. von Storch, H., M. Costa-Cabral, C. Hagner, F. Feser, J. Pacyna, E. Pacyna, and S.Kolb, 2003: Four decades of gasoline lead emissions and control policies in Europe: A retrospective assessment, The Science of the Total Environment (STOTEN) 311, 151-176

Lead deposition in Europe 1955 1965 Emissions

Lead deposition in Europe 1995 Calculated depositions of lead deposition

model estimate

Lead deposition in Europe

www.coastdat.de Applications – marine-meteo issues More than 30 national & international clients/users Industry, Administration, Authorities, Research www.coastdat.de Ralf Weisse ralf.weisse@gkss.de

- Ship design Some applications of coastDat (as of February 2009) Problem: . RoRo liners operating on fixed routes . Operation time critical Idea: . Optimization of velocity profile taking environmental conditions into account (e.g. water depth, wave height, wave angle) Example: . 200 m RoRo liner Zeebrügge-Immingham . Compared to conventional approach delayed in 7% of time; only in 0.5% more than 30 min . Reduced operation costs (200 TEUR/year due to reduced fuel consumption) Source: Flensburger Schiffbau Gesellschaft

- Ship design II Some applications of coastDat (as of February 2009) Problem: . Motion of ship depends on several environmentally based design parameters . Need to improve sea keeping behavior . Different options may exist (e.g. roll stabilization tanks, active fin stabilizers) Idea: . Different costs and different efficiencies for the different options . Use coastDat to estimate statistics of e.g. weather downtime with and without fin stabilizers . decision support for the ship operator on whether the improvement of the sea-keeping behavior is worth the investment into a roll stabilization system Source: Flensburger Schiffbau Gesellschaft

Ship design Navigational safety 2.5 m 2.0 m 1.5 m Some applications of coastDat (as of February 2009) Ship design Navigational safety 2.5 m Background: . EU safety regulations for RoRo passenger vessels Criteria: . Sig. wave height of 1.5, 2.5, 4.0 m exceeded in less than 10% of time (according to ship specifications) . Distance to next harbor 2.0 m 1.5 m (Source: BSH)

Ship design Navigational safety Offshore wind Some applications of coastDat (as of February 2009) Ship design Navigational safety Offshore wind Wind and sea state statistics . Wind power availability . Design of structures . Design of entire system (ultimate and fatigue limit states) . Planning of installation . Planning of maintenance (weather windows) (Source: BSH)

Offshore wind - Oils spill risk Some applications of coastDat (as of February 2009) Ship design Navigational safety Offshore wind - Oils spill risk Hypothetical oil accidents . Any source region . Any target region of interest . Hypothetical accidents every hour over 50 years (sampling of large variety of different possible weather conditions) Target Region Bunte Flaechen (Source Regions) = Hauptschiffahrtsroute, man macht sich Sorgen, um erhoehtes Kollissionsrisiko mit hier geplanten Offshore Windparks. Experiment, in dem ca. 14.000 Oelunfaelle (alle 7 Stunden oder so) ueber ca. 40 Jahre in den farbigen Boxen simuliert wurden. Zahlen=Zielregionen, in denen man sich ansehen kann, wie oft und wie schnell das Oel dort ankommt. Hypothetical Source Region (Source: U. Callies)

Offshore wind - Oils spill risk Some applications of coastDat (as of February 2009) Ship design Navigational safety Offshore wind - Oils spill risk Hypothetical oil accidents . Any source region . Any target region of interest . Hypothetical accidents every hour over 50 years (sampling of large variety of different possible weather conditions) Probability distributions . E.g. of travel times . May be combined with different accident probabilities, oil fighting strategies & sensitivities Bsp. Region14=Helgoland: In 65% der Faelle kommt in der magenta Box freigesetztes Oels in Helgoland an, im Mittel dauert das etwa 2-3 Tage, im Extremfall 0.5 Tage (Konsequenzen fuer Bekaempfungsstrategien). (Source: U. Callies)

Offshore wind - Oils spill risk Interpretation of measurements Some applications of coastDat (as of February 2009) Ship design Navigational safety Offshore wind - Oils spill risk Interpretation of measurements Chronic Oil Pollution (Source: A. Chrastansky) . Usually from illegal oil dumping . Number of beached oil contaminated birds usually taken as indicator for trends in chronic oil pollution . Simulation with coastDat suggests that weather variability has to be accounted for in the interpretation Alena: Oberes Bild Hauptschiffahrtsrouten in der Deutschen Bucht mit Verkehrsdichte. Entsprechend wurden passive Tracer dort ueber die coastDat Periode kontinuierlich eingesetzt. Die Torten zeigen die Anlandungsstatistiken. Illegal Oil dumping wird oft anhand von Spuelsaum funden veroelter Voegel eingeschaetzt. Diese zeigen einen Rueckgang in den letzten Jahren, man koennte vermuten, dass sich die Situation verbessert hat. Simulation mit coastDat zeigt, dass man Wettereffekte bei der Interpretation solcher Daten beruecksichtigen muss.

Offshore wind - Oils spill risk Interpretation of measurements (Source: R. Weisse) Some applications of coastDat (as of February 2009) Ship design Navigational safety Offshore wind - Oils spill risk Interpretation of measurements Chronic Oil Pollution Ocean Energy Wave Energy Flux [kW/m] . Ocean Energy Potential . Different Sources . Wave Energy Flux [kW/m] . Currents Power [W/m2] cross section Ocean Eneregy: Oberes Bild. zeigt den Wellenenergiefluss im langjaehrigen Mittel in Kilowatt/Meter senkrecht zur Wellenlaufrichtung. Normalerweise wird groesstes Potential in mittleren Breiten erwartet, die Deutsche Nordseekueste hat jedoch mit ca. 10-20 kw/m nur ein relativ geringes Potential (Bsp. 200 km Kuestenlinie x 10 kW/m = 2000 MW Leistung). Unteres Bild: Stroemung. Energiefluss in W/m2 Querschnittsflaeche (Rotor). Das skaliert im wesentlichen mit Stroemungsgeschwindigkeit hoch 3. Man sieht, dass das Potential raeumlich sehr begrenzt ist (z.B. List, Hoernum, Elbe, Jade) auf Fahrwasser, Rinnen und Seegaten (Nutzungskonflikte) und eher gering ist. Oft Argument: Wasser groessere Dichte, als Luft, deshalb Potential groesser als bei Wind. Das kann man mit folgenden Ueberlegungen relativieren: Potential proportional zu Dichte x Geschwindigkeit hoch 3 Dichte Wasser >> Dichte Luft (Faktor 1000), aber Geschwindigkeit Luft >> Geschwindigkeit Wasser (Faktor 10, 3. Potenz = Faktor 1000) und Wind steht grossflaechig zur Verfuegung, hohe Stroemungen (1 m/s) nur sehr lokal. Currents Power [W/m2]

Weisse, R. , H. von Storch, U. Callies, A. Chrastansky, F. Feser, I Weisse, R., H. von Storch, U. Callies, A. Chrastansky, F. Feser, I. Grabemann, H. Günther, A. Plüss, T. Stoye, J. Tellkamp, J. Winterfeldt and K. Woth, 2009: Regional meteo-marine reanalyses and climate change projections: Results for Northern Europe and potentials for coastal and offshore applications. Bull. Amer. Meteor. Soc., May 2009