The southeastern coast of South America is located in one of the most cyclogenetic areas in the Southern Hemisphere. Occasionally, those systems may lead to disastrous flooding. Strong and persistent along-shore winds on the shelf may also result in some coastal flooding of smaller magnitude. Nested depth-averaged numerical models are used for the simulation of the storm surge. This study describes the storm surge dynamics in the area and the consequences of different regimes to the storm surge prediction. The large extension and limited depth of the Argentinean Shelf permits a smooth transition of the storm surge to the Río de la Plata and a relatively long forecast horizon for its innermost zone. On the other hand, it is demonstrated that currents in the navigable channels of the Bahía Blanca estuary are the main cause for a strong tide-surge interaction. There, the relative phase between the meteorological forcing and the tide can shift the peak of the storm surge several hours.
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.
The South American Environmental Risk Management Network (SAVER-Net) is an instrumentation network, mainly composed by lidars, to provide real-time information for atmospheric hazards and risk management purposes in South America. This lidar network have been developed since 2012 and all its sampling points are expected to be fully implemented by 2017. This paper describes the network’s status and configuration, the data acquisition and processing scheme (protocols and data levels), as well as some aspects of the scientific networking in Latin American Lidar Network (LALINET). Similarly, the paper lays out future plans on the operation and integration to major international collaborative efforts.
The ability of the SMARA storm surge numerical prediction system to reproduce local effects in estuarine and coastal winds was recently improved by considering one-way coupling of the air-sea momentum exchange through the wave stress, and best forecasting practices for downscaling. The inclusion of long period atmospheric pressure forcing in tide and tide/surge calculations corrected a systematic error in the surge, produced by the South Atlantic Ocean quasi-stationary pressure patterns. The maximum forecast range for the storm surge at Buenos Aires provided by the real-time use of water level observations is approximately 12 h. The best available water level prediction is the 6-h forecast (nowcast) based on the closest water level observations. The 24-h forecast from the numerical models slightly improves this nowcast. Although the numerical forecast accuracy degrades after the first 48 h, the improvement to the full range observation-based prediction is maintained at the inner Río de la Plata area and extends to the first 3 days at the intermediate navigation channels.
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