Relationships between sea‐level pressure and sea‐level height in the Camargue (French Mediterranean coast) by Vincent Moron and Albin Ullmann, pages 1531–1540, Volume 25, Issue 11, 2005

• Published in: International Journal of Climatology
• Main Author: Moron, Vincent
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2006
• Subjects: Dent; La Dent; Ullmann; North Atlantic
• Online Access: http://dx.doi.org/10.1002/joc.1320; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.1320; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.1320

Abstract A statistical study of daily maximum sea‐level height at one station (Grau de la Dent) in the Camargue (Rhône delta, French Mediterranean coast) and daily sea‐level pressure (SLP) at 12 h UTC over the eastern North Atlantic is used to identify the meteorological conditions associated with sea‐level variations in the Camargue for the winters 1974–1975 to 2000–2001. Mean SLP composites during and 5 days before major surge events (defined as those with a daily maximum sea‐level height > 80 cm) suggest the dominant influence of storms, moving northwest to southeast across the North Atlantic and strengthening as they approach the Bay of Biscay. During such storms, strong onshore winds may persist for up to 4–5 days. These winds tend to strengthen from 3 days to 1 day before the surge events. The mean October–March correlation between daily maximum sea‐level height in the Camargue and SLP averaged over the Bay of Biscay (10°W–0° , 40° –50°N) is strong ( r = − 0.69). A methodology is developed for assessing the low frequency SLP variability impact on sea‐level height in the Camargue. A cross‐validated linear regression is used to hindcast the interannual and intraseasonal variability of the monthly 75th and 90th percentiles of the daily maximum sea‐level height from the monthly mean SLP over the Bay of Biscay. The linear correlation between the cross‐validated hindcast and observed time series is 0.83 (0.77) for the 75th (90th) percentile over the 1974–1975 to 2000–2001 period. The mean bias error, reflecting systematic errors in predicting the monthly percentiles, is close to zero. Copyright © 2006 Royal Meteorological Society.