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Use of sea level observations in DMIs storm surge model

Use of sea level observations in DMIs storm surge model. Jacob L. Høyer, Weiwei Fu, Kristine S. Madsen & Lars Jonasson Center for Ocean and Ice, Danish Meteorological Institute. Outline. DMI and Storm surge modelling   Reanalysis experiments Blended satellite and tide gauge observations

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Use of sea level observations in DMIs storm surge model

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  1. Use of sea level observations in DMIs storm surge model Jacob L. Høyer, Weiwei Fu, Kristine S. Madsen & Lars Jonasson Center for Ocean and Ice, Danish Meteorological Institute

  2. Outline • DMI and Storm surge modelling   • Reanalysis experiments • Blended satellite and tide gauge observations • Data assimilation experiments • Conclusions

  3. Operational storm surge modelling and warning • DMI createdafter storm surge in 1872 • DMI holds the national responsibility to forecast and issuewarnings of storm surges. • 18/24 hourswarning • Hourlyupdates • Yearlyuser meetings The service is based upon: • Tide gauge observations • Models

  4. Tide gauge stations • Densenetwork of stations • DMIOperate 15 tide gauge stations • NRT storm surgemodelling and warnings • Long term sealevelchanges (10 with > 100 yearsrecord) • Extensivecollaborationwithin BOOS and NOOS

  5. 3D hydrodynamic model HBM • Spatial resolution: 6/1 nm • 4 forecasts a day, 5 days ahead • Hourly 3-D fields, • 10 minutes values extracted for 133 stations. • Model Information • Two-way nested, free surface, hydrostatic three-dimensional (3D) circulation model HIROBM-BOOS (HBM). • A staggered Arakawa C grid is applied on a horizontally spherical coordinate with a resolution of 6 nm. There are 50 vertical levels in z-coordinate. In the Danish Water (boxed), the horizontal resolution is increased to 1 nm. A detailed description of the model can be found in Berg and Poulsen (2011). • The meteorological forcing is the High Resolution Limited Area Model (HIRLAM) - a numerical short-range weather forecasting system developed by the international HIRLAM Programme (http://hirlam.org).

  6. Reanalysis simulations Motivation: Comparewindforcing from HIRLAM (NWP) and HIRHAM (reanalysis) and examineif the assimilatedwinds in HIRHAM improve the storm surgeforecasts. Method: Five events arecomparedbetween 2002 and 2005. • Same surges on the outerboundary • Same tides • Compare the modeledsealeveltotide gauge at 8 locations in the Norths Sea and the Baltic Sea Case 1: 20020121 - 20020210 Case 2: 20020215 – 20020307 Case 3: 20031201 - 20031221 Case 4: 20040314 - 20040403 Case 5: 20050101 – 20050121

  7. Reanalysis results • Minor differences in modelled sea level • Modelled sea level has too large standard deviation when forced with HIRHAM (probably due to the stronger winds). • Reason for the very similar results: • Tides and surges are same in both simulation which probably is the reason for the similar results • Observations are located close to the coast where the model coast line has a large impact Example: Sea level at HvideSandeKyst (Danish East coast, Jan 2005)

  8. Statistical blending Method • Multivariate regression where data from 17 tide gauge stations are regressed onto the satellite altimetry observations (Høyer et al., 2002, Madsen & Høyer, 2007) • Tide gauges selected based on the correlation with satellite observations • Allows real-time sea level estimation in points where satellite data are available • Sea level estimate independent upon ocean and atm. Model performance • Assumes stationarity • New version for eSurge uses coastal altimetry observations

  9. Coastal Altimetry observations • Jason-2: Pistach 20 Hz (2008-present) • Envisat 18 Hz observations from ALES (see poster for validation ) • Spike removal and along track smoothing • Data used within 3 km “Steep” “Flat”

  10. Model verification • Initial regression results from Jason-2 data • Surge part only • Tide gauge weights determined for every 20 Hz time series. Fitting error Hindcast skill

  11. Output • Hourly gridded fields • Surge + tidal components • 1 km spatial resolution • 5 test cases of historical events • NRT fields operational • Netcdf files • Available to users ~1st Feb, 2014

  12. Data assimilation experiments • Assimilation experiments are carried out for the storm surge event in January 2005. • Old version of blended tide gauge and satellite data is tested. • Results are compared with independent tide gauge data with-held from the assimilation experiment.

  13. Data assimilation test case • Hiromb-BOOS model • HIRLAM NWP forcing • Assimilation method: • Ensemble OI • 5 days event Tide Gauge Station in the North and Baltic Sea. Independent tide gauges are marked with red dots.

  14. Example, blended sea level product, Jan 2005 Example of the blended water level product on Jan 8, 2005. Only the surge part is shown above.

  15. Conclusions • Reanalysis: Not much impact using different wind forcings • Assimilation: Test case show improvements in the data assimilation test cases • New blended product ready, based upon coastal altimetry high resolution products • Blending method could be applied to other semi-enclosed seas like Adriatic

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