Model and scatterometer sea surface winds for storm surge applications in the Adriatic Sea

1. Model and scatterometer sea surface winds for storm surge applications in the Adriatic Sea Francesco De Biasio*, Stefano Zecchetto, Mario Marcello Miglietta Istituto di Scienze dell'Atmosfera e del Clima (ISAC) ConsiglioNazionaledelleRicerche (CNR) CorsoStatiUniti 4, 35127 Padova, Italy * email: f.debiasio@isac.cnr.it

2. 9 - 13 September 2013 | Reading | UK Presentation outline • Motivations for the study • Some operational NWP modelsavailable in the Adriatic Sea • EO surfacewind data available in the Adriatic Sea • Do NWP models and EO wind data look similar? • A case study • Local statistics • Global statistics

3. 9 - 13 September 2013 | Reading | UK http://www.esurge-venice.eu Satellite-borne scatterometers surface winds are exploited as the reference fields to be used in the assessment of the quality of GCM and LAM wind forecasts in the Adriatic Sea NWP limits: initial conditions, parameterization schemes, … EO limits: data availability, revisitation time, distance to coast. Period: August 2008 – July 2011 1 -Motivations This study was performed in the framework of the eSurge-Venice project, a project funded by the European Space Agency (ESA). It aims to: Compare the performances of the Atmospheric Global Circulation Models (GCM) and Limited Area Models (LAM) wind fields to be used as forcing into the storm surge models in the Adriatic Sea.

4. 9 - 13 September 2013 | Reading | UK 2 - Atmospheric numerical weather prediction models available in the Adriatic Sea (surface wind) • GLOBAL MODELS: • IFS – operational at ECMWF • From 01/02/2006 to 26/01/2010:TL799 (25 km), from 26/01/2010 to present:TL1279 (16 km) • Grid spacing used (after interpolation):12,0 km • LOCAL AREA MODELS (THE FIRST TWO PROVIDED TO “MUNICIPAL STORM SURGE FORECASTING OFFICE IN VENICE”: • ALADIN – operational at DHZ (Croatian Meteorological and Hydrological Service) • initialized with ARPEGE (Meteo-France), two nested grids (only the first, larger domain is used here) • Grid spacing:8 km • COSMO-LAMI – operational at ARPA Emilia-Romagna • initialized with ECMWF, one grid • Grid spacing: 7 km • WRF – Weather Research and Forecasting Model • initialized with ECMWF, one grid • Grid spacing: 10 km

5. 9 - 13 September 2013 | Reading | UK SENSOR:SeaWinds on QuikSCAT ASCAT on MetOp TYPE: Ku-band scatterometer C-band scatterometer AVAILABILITY: August 2008-November 2009 March 2009-July 2011 GRID SPACING: 12.5km OWV 12.5km OWV SWATH: One swath 1800 km wide Two swaths 550 km wide AVERAGE HITS: ~30/mo in the Adriatic Sea ~20/mo in the Adriatic Sea 3.1 - EO surfacewindfieldsavailable in the Adriatic Sea Mean number of hits/month Actually 3 additional sensors are available in the area

6. 9 - 13 September 2013 | Reading | UK 3.2 – Main wind regimes in the Adriatic Sea Bora: a violent, cold, northeasterly winter wind on the Adriatic Sea Sirocco: a warm, moist, southeast wind blowing on the northern Mediterranean coast BOTH WINDS CAN CAUSE SEVERE STORM SURGE IN THE NORTHERN ADRIATIC SEA AND IN THE VENICE LAGOON Adriatic Sea Mediterranean Sea

7. 9 - 13 September 2013 | Reading | UK 4.0 –Wind fields in the Adriatic Sea: Bora event November 17, 2008

8. 9 - 13 September 2013 | Reading | UK 4.1 –Wind fields in the Adriatic Sea: Bora event November 17, 2008 November 17, 2008 QUIK ECMWF ALADIN LAMI WRF 18:08 18:00 18:00 18:00 18:00

9. 9 - 13 September 2013 | Reading | UK 4.2 –Wind fields in the Adriatic Sea: Bora event November 17, 2008 November 18, 2008 QUIK ECMWF ALADIN LAMI WRF 03:50 03:00 03:00 03:00 03:00

10. 9 - 13 September 2013 | Reading | UK 4.3 –Wind fields in the Adriatic Sea: Bora event November 17, 2008

11. 9 - 13 September 2013 | Reading | UK 5.1 – SCAT/MODEL local statistics: wind speed bias The forecast range +12-+36 h is used for sake of comparison wind speed bias • <WSSCAT–WSECMWF> <WSSCAT–WSALADIN> <WSSCAT–WSLAMI>

12. 9 - 13 September 2013 | Reading | UK 5.2 – SCAT/MODEL local statistics: wind direction difference mean of wind direction difference • <WDSCAT–WDECMWF> <WDSCAT–WDALADIN> <WDSCAT–WDLAMI>

13. 9 - 13 September 2013 | Reading | UK 5.3 – SCAT/MODEL local statistics: wind speed correlation wind speed correlation corrcoef(WSSCAT,WSECMWF) corrcoef(WSSCAT,WSALADIN) corrcoef(WSSCAT,WSLAMI)

14. 9 - 13 September 2013 | Reading | UK 5.4 – SCAT/MODEL local statistics: wind direction correlation wind direction correlation corrcoef(WDSCAT,WDECMWF) corrcoef(WDSCAT,WDALADIN) corrcoef(WDSCAT,WDLAMI)

15. 9 - 13 September 2013 | Reading | UK 5.5 – SCAT/MODEL local statistics: wind speed centered RMSD wind speed centered Root Mean Square Difference cRMSD(WSSCAT,WSECMWF) cRMSD(WSSCAT,WSALADIN) cRMSD(WSSCAT,WSLAMI)

16. 9 - 13 September 2013 | Reading | UK 5.6 – SCAT/MODEL local statistics: wind direction difference std standard dev. of wind direction difference std_dev(WDSCAT-WDECMWF) std_dev(WDSCAT-WDALADIN) std_dev(WDSCAT-WDLAMI)

17. 9 - 13 September 2013 | Reading | UK 6.1 – SCAT/MODEL global statistics. Wind speed and direction distributions.

18. 9 - 13 September 2013 | Reading | UK 6.2 – SCAT/MODEL global statistics. TAYLOR diag. of wind speed

19. 9 - 13 September 2013 | Reading | UK 7 – Conclusions • LAMs apparently perform similarly as ECMWF in the simulation of winds over the Adriatic sea • The performance is better in open sea and worse near the coastlines • ALADIN performs better in terms of correlation and standard deviation, LAMI has a lower bias (LAMI has a smaller domain extension which may affect the results) • The errors in speed/direction are due to misplacing of wind patterns and inaccurate time evolution

20. 9 - 13 September 2013 | Reading | UK EFFECTIVE RESOLUTION OF A LAM -> NEED OF HIGHER RESOLUTION

21. 9 - 13 September 2013 | Reading | UK INTERPRETATION OF GLOBAL STATISTICS

22. 9 - 13 September 2013 | Reading | UK • Bla bla bla… • Bla bla bla… • Bla bla bla… Thank you for your attention