The present article is a study of the applicability of different sources of meteorological forcing for the coastal wave and storm surge models, which provide the operational marine forecasts for the coastal early warning systems (EWS) and are used for reconstructions of historical storms. The reconstruction of historical storms is one of the approaches to the natural coastal hazard vulnerability assessment. We evaluate the importance of the input meteorological information for the mentioned types of coastal models. For two well documented historical storms, that caused significant damages along the Bulgarian coast we simulate the significant wave heights and sea level change, using SWAN wave model and a storm surge model. The wind and mean sea level pressure fields, which are used in the present study, are extracted from the ERA Interim reanalysis of the European Center for Medium range Forecasts (ECMWF) and from the output of the high resolution limited area numerical weather prediction model ALADIN. The overall conclusion is that for the successful historical storms reconstructions ERA Interim and ERA40 reanalysis are valuable source of meteorological forcing, but due to their limitations in terms of spatial and temporal resolution, it is recommended to produce a higher spatial and temporal resolution meteorological fields, using dynamical downscaling of the reanalyzed data.
Assessing influence of some meteorological parameters on airborne particulate matters in the Himalayan hill-station of Darjeeling - A preliminary assessment
Diagnostic vs dynamic representation of the inverse barometer effect in a global ocean model and its potential for probabilistic storm surge forecasting
Norwegian Meteorological Institute（挪威气象局）；University of Bergen（卑尔根大学）；European Centre for Medium-Range Weather Forecasts（欧洲中期天气预报中心）
Comments on "Assessing future risk: quantifying the effects of sea level rise on storm surge risk for the southern shores of Long Island, New York," by Christine C. Shepard, et al (Natural Hazards, Vol. 60, No. 2, 727-745)
A Machine Learning Nowcasting Method based on Real-time Reanalysis Data
College of Information Science and Engineering, Ocean University of China（中国海洋大学信息科学与工程学院）；Institute of Urban Meteorology, China Meteorological Administration（中国气象局城市气象研究所）；National Center for Atmospheric Research（国家大气研究中心）；National Meteorological Center, China Meteorological Administration（中国气象局国家气象中心）
