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Precipitation estimation and nowcasting at IMGW-PIB (SEiNO system)

Szturc J., Jurczyk A., Ośródka K., Wyszogrodzki A., Giszterowicz M.

Meteorology Hydrology and Water Management. Research and Operational Applications

2018

Vol. 6, Iss. 1

1--12

A System for the Estimation and Nowcasting of Precipitation (SEiNO) is being developed at the Institute of Meteorology and Water Management – National Research Institute. Its aim is to provide the national meteorological and hydrological service with comprehensive operational tools for real-time high-resolution analyses and forecasts of precipitation fields. The system consists of numerical models for: (i) precipitation field analysis (estimation), (ii) precipitation nowcasting, i.e., extrapolation forecasting for short lead times, (iii) generation of probabilistic nowcasts. The precipitation estimation is performed by the conditional merging of information from telemetric rain gauges, the weather radar network, and the Meteosat satellite, employing quantitative quality information (quality index). Nowcasts are generated by three numerical models, employing various approaches to take account of different aspects of convective phenomena. Probabilistic forecasts are computed based on the investigation of deterministic forecast reliability determined in real time. Some elements of the SEiNO system are still under development and the system will be modernized continuously to reflect the progress in measurement techniques and advanced methods of meteorological data processing.

Probabilistic prognosis of cliffslide along baltic sea coast in Poland

Brzozowski T., Tejchman A.

Studia Geotechnica et Mechanica

2003

Vol. 25, nr 1-2

135-144

In recent years, an increasing activity of sliding process in many parts of Polish cliff coast has been observed. It has created a serious danger for all structures located nearby. In order to explain the mechanisms governing sliding process as well as to elaborate calculation stability methods appropriate for these mechanisms, comprehensive investigations have been undertaken. Slope stability is usually analysed by means of deterministic approach. However, such methods are insufficient for determination of stability of cliffs and dangerous zones along the cliff coastline. In the paper, a probabilistic method of cliff sliding prognosis is presented. In the method proposed, soil strength parameters are assumed to be random values. Abrasive activity of a sea is simulated by changes of cliff profile. Numerical calculations based on the method allow verification of cliff stability and evaluation of the range of failure zone in the inland part of cliff.