caa a22 4500 605546762 CHVBK 20210128100942.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s10236-015-0808-z doi (NATIONALLICENCE)springer-10.1007/s10236-015-0808-z An investigation of ensemble-based assimilation of satellite altimetry and tide gauge data in storm surge prediction [Elektronische Daten] [Paula Etala, Martín Saraceno, Pablo Echevarría] Cyclogenesis and long-fetched winds along the southeastern coast of South America may lead to floods in populated areas, as the Buenos Aires Province, with important economic and social impacts. A numerical model (SMARA) has already been implemented in the region to forecast storm surges. The propagation time of the surge in such extensive and shallow area allows the detection of anomalies based on observations from several hours up to the order of a day prior to the event. Here, we investigate the impact and potential benefit of storm surge level data assimilation into the SMARA model, with the objective of improving the forecast. In the experiments, the surface wind stress from an ensemble prediction system drives a storm surge model ensemble, based on the operational 2-D depth-averaged SMARA model. A 4-D Local Ensemble Transform Kalman Filter (4D-LETKF) initializes the ensemble in a 6-h cycle, assimilating the very few tide gauge observations available along the northern coast and satellite altimeter data. The sparse coverage of the altimeters is a challenge to data assimilation; however, the 4D-LETKF evolving covariance of the ensemble perturbations provides realistic cross-track analysis increments. Improvements on the forecast ensemble mean show the potential of an effective use of the sparse satellite altimeter and tidal gauges observations in the data assimilation prototype. Furthermore, the effects of the localization scale and of the observational errors of coastal altimetry and tidal gauges in the data assimilation approach are assessed. Springer-Verlag Berlin Heidelberg, 2015 Storm surge prediction nationallicence Data assimilation nationallicence Ensemble Kalman filter nationallicence Etala Paula Servicio de Hidrografía Naval, Av. Montes de Oca 2124, C1270ABV, City of Buenos Aires, Argentina aut Saraceno Martín Centro de Inv. del Mar y la Atmosfera (CIMA)/UBA/FCEN-CONICET, UMI3351-IFAECI/CNRS-CONICET-UBA, Ciudad Universitaria, Pab.II 2 piso, (1428), City of Buenos Aires, Argentina aut Echevarría Pablo Servicio Meteorológico Nacional, 25 de mayo 658 4 piso, C1002ABN, City of Buenos Aires, Argentina aut Ocean Dynamics Springer Berlin Heidelberg 65/3(2015-03-01), 435-447 1616-7341 65:3<435 2015 65 10236 https://doi.org/10.1007/s10236-015-0808-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10236-015-0808-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Etala Paula Servicio de Hidrografía Naval, Av. Montes de Oca 2124, C1270ABV, City of Buenos Aires, Argentina aut NATIONALLICENCE 700 1- Saraceno Martín Centro de Inv. del Mar y la Atmosfera (CIMA)/UBA/FCEN-CONICET, UMI3351-IFAECI/CNRS-CONICET-UBA, Ciudad Universitaria, Pab.II 2 piso, (1428), City of Buenos Aires, Argentina aut NATIONALLICENCE 700 1- Echevarría Pablo Servicio Meteorológico Nacional, 25 de mayo 658 4 piso, C1002ABN, City of Buenos Aires, Argentina aut NATIONALLICENCE 773 0- Ocean Dynamics Springer Berlin Heidelberg 65/3(2015-03-01), 435-447 1616-7341 65:3<435 2015 65 10236