1. COASTDAT: Regional downscaling re-analysis - concept and utility VON STORCH Hans Institute of Coastal Research, Helmholtz Zentrum Geesthacht, Germany 22 September 2016 - SOA First Institute of Oceanography, 青岛 (Qingdao)

2. VON STORCH Hans 1.Climate researcher (in the field since 1971) 2.Coastal climate (storms, storm surges, waves; North and Baltic Sea, North Atlantic, Yellow Sea); statistical analysis 3.Director emeritus of the Institute of Coastal Research of the Helmholtz Zentrum Geesthacht, Germany 4.Professor at Universität Hamburg 5.Guest professor at the Ocean University of China, Qingdao Chinese web page: http://www.hvonstorch.de/klima/ china/Hans von Storch.china.htm

3. Overview 1.Spectral nudging approach for constraining regional modelling - Improved representation of medium scale variability - Constructing a homogeneous regional re-analysis. 2.Improved representation in coastal regions: - variability at medium scales. - sub-synoptic phenomena (polar lows) - forcing fields for impact models (ocean waves, storm surges) 3.The regional reanalysis CoastDat.

4. 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, 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 considered as well and homogeneously described. The smallest scales are considered less realistic and subject to inhomogeneities (sensitive to changes of observational local data availability). Downscaling is a postprocessing of the reliably and homogeneously described large scales L using R = f(L, Φ s ) with a constrained regional (or even global) dynamical model. The constraining may be implemented by spectral nudging.

5. Skillfully represented scales Insufficiently represented scales Grid point resolution Maximum resolution Skillfully represented scales Insufficiently represented scales Grid point resolution Maximum resolution Added value Global Analysis Regional Analysis Con- straining

6. Pattern correlation coefficients for meridional wind at 500 hPa between the driving global reanalysis and the RCM-output with standard forcing via the lateral boundaries and the RCM-output with spectral nudging global regional Constraining of large scales

7. Regional re-analysis without regional data. exploiting the presence of a “downscaling” situation L > R and 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) for China (Yellow Sea region, see 李德磊 ), for Central Siberia and Southern Atlantic, and recently for the Globe.

8. Improved presentation of in coastal regions ERA-I-driven multidecadal simulation with RCM CCLM over East Asia ( 李德磊, 2015) Grid resolution: 0.06 o See presentation by 李德磊

9. NCEP-driven multidecadal simulation with RCM CLM over North Pacific ( 陈飞 et al., 2012, 2013, 2014) Grid resolution: about 0.4 o Employing spectral nudging (wind above 850 hPa, for scales > 800 km) Simulation of sub-synoptic phenomena Polar lows in the Northern North Pacific Generating additional regional dynamical detail

10. 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)

11. 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.

12. Improved representation of forcing fields for impact models NCEP-driven multidecadal simulation with RCM REMO in Europe Grid resolution: 0.5 o Employing spectral nudging (wind above 850 hPa, for scales > 800 km) 1948-2010 simulation Wind and air pressure used to drive models of sea level and circulation of marginal seas (not shown) for describing currents and sea level Wind used to drive models of the statistics of surface waves (ocean waves) in coastal seas (North Sea).

13. simuliert Extreme wind events simulated compared to local observations Weisse, pers. comm.

14. Red: buoy, yellow: radar, blue: wave model run with REMO winds wave direction significant wave height [days] Gerd Gayer, pers. comm., 2001

15. Annual mean winter high waters Cuxhaven red – reconstruction, black – observations Interannual variability of mean water levels (Weisse and Plüß 2006)

16. 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.  Extension to other regions and to ecological parameters. 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 scenarios

17. Yantai, 18 June 2007Page 17 wind waves Changing significant wave height, 1958-2002 Weisse, pers. comm.

18. 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. comm.

19. Storm Christian/Allan in 2013 Track of the Christian/Allan storm according to an analysis by German National Meteorological Service (red, dashed) and to the reconstruction in CoastDat. Number of heavy storms (with minimum pressure less than 970 hPa) crossing the Jutland area during winter (ONDJFM) seasons according to the CoastDat data set. Left: Storms with maximum wind speeds smaller than Christian/Allan (26.7 m/s); Right: storms with larger maximum wind speeds. von Storch et al., 2014

20. Conclusion … Dynamical downscaling works … - Large scales are hardly affected but smaller scales respond to regional physiographic detail. Medium scales are determined by both the large scale dynamics and the regional physiographic details (R = f(L,Φ s )) Downscaling allows the generation of homogeneous data sets (i.e., data sets of uniform quality across many decades of years), i.e. a regional re-analysis with uniform quality (across time). Added value in medium scales (in particular coastal regions). 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. Such a regional re-analysis has been done for the region of the Bo Hai and the Huang Hai on a 7-km grid by 李德磊.