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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

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2018

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Vol. 6, Iss. 1

1--12

EN

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.

2

The forecasting of tornado events: the synoptic background of two different tornado case studies

Wrona B., Avotniece Z.

Meteorology Hydrology and Water Management. Research and Operational Applications

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2015

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Vol. 3, Iss. 1

51--58

EN

The synoptic analyses of two different tornado cases, observed in Latvia and Poland in the summer of 2012, are examined in this paper. The first of them, the tornado in Latvia seemed to be a “textbook example” of tornado occurrence. Its development took place in the contact zone of the warm, tropical air, characterized by a very high CAPE (Convective Available Potential Energy), with cold and moist polar marine air mass behind the convergence line that determined very good conditions for convective updraft. Additionally, the moderate environmental wind shear favoured the sufficient condition for concentrating the atmosphere’s vorticity into well-organized strong rotating upward motions that produced the supercell structures and tornado. Thus, from the forecaster’s point of view, the occurrence of this severe convective event was not a surprise. This phenomenon was predicted correctly more than a dozen hours before the tornado occurred. The second event occurred in the north of Poland and was associated with a thunderstorm where a supercell was formed in conditions of low CAPE but favourable wind profile, both vertical and horizontal. Helical environments (characterized by large shear vectors that veered with height in the lowest three kilometres, especially the nearest one kilometre) were arguably the most important factor that determined the Polish tornado’s occurrence. In this case the analysis of the synoptic situation was not so clear and the superficial analysis, even post factum, regarding radar, satellite or detection maps might have suggested “quite a normal” summer thunderstorm. However, the detailed examination showed the reasons why tornado genesis took place. The potential conditions for the occurrence of this severe phenomenon were indicated by forecasters, although the forecasts were less exact with regard to the place of occurrence and the heaviness of the strike.

3

MeteoGIS: GIS-based system for monitoring of severe meteorological phenomena

Jurczyk A., Ośródka K., Szturc J., Giszterowicz M., Przeniczny P., Tkocz G.

Meteorology Hydrology and Water Management. Research and Operational Applications

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2015

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Vol. 3, Iss. 2

49--61

EN

The MeteoGIS system developed at the Institute of Meteorology and Water Management – National Research Institute in Poland is a GIS-based system for real-time monitoring of weather and the generation of meteorological warnings. Apart from its monitoring features, it can also provide more advanced analysis, including SQL (Structured Query Language) queries and statistical analyses. Input data are provided mainly by the INCA-PL 2 nowcasting model which employs forecasts from the high-resolution AROME numerical weather prediction model and measurement data from the Polish weather radar network POLRAD and surface meteorological stations. As well as this, data from the PERUN lighting detection system are used. Ingestion of such data allows for the mitigation of risk from potentially hazardous weather phenomena such as extreme temperatures, strong wind, thunderstorms, heavy rain and subsequent impending floods. The following meteorological parameters at ground level are visualised in the MeteoGIS: (i) precipitation (accumulation and type), (ii) temperature, (iii) wind (speed and direction), (iv) lightning (locations and type). End users of the system are workers from civil protection services who are interested in shortterm warnings against severe weather events, especially area-oriented ones (related to districts, catchments, etc.). The reliability of visualised data is a very important issue, and from the MeteoGIS user’s point of view the improvement in data quality is a continuous process.

4

Radarowa detekcja superkomórek burzowych w Polsce

Pilorz W.

Teledetekcja Środowiska

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2014

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T. 51

93--105

EN

“Supercell storms are capable of producing the most violent of hail, wind and tornado events (Moller et. al. 1994); thus they are the most important storm type to forecast and detect” (Moller 2001). Supercell storm is defined by “presence of a deep and persistent, rotating updraft called a mesocyclone” (Weisman and Klemp 1984). Mesocyclone presence leads to the specific vertical storm structure seen as a Bounded Weak Echo Region. Mesocyclone presence also leads to the changes in the horizontal shape of the storm, observed on the radar reflecivity in a low elevation as a hook echo. Large hail, associated with supercells, is a very important threat to detect. It can be easily recognized by the presence of the reflecivity more than 50 dBZ, above 8 km above ground level (Burgess and Lemon 1990). Nine cases of supercells in Poland between 2007 and 2013 were examined. Results show that all quoted features were present. Moreover, most of them appeared before the threat which they indicate. It means that threats associated with supercells can be predicted in a short time.

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Znaczenie diagnozy stanu atmosfery dla opracowania prognoz pogody typu nowcasting

Kołodziej G.

Przegląd Geofizyczny

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2012

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Z. 2

197-209

PL

Celem pracy jest analiza wybranych przykładów trudności poprawnego zdiagnozowania stanu atmosfery i dokładnego określania przyczyn determinujących powstawanie zjawisk atmosferycznych, a także wskazanie ogólnych metod poprawienia tej diagnozy. Analizowane sytuacje zostały zaczerpnięte z codziennej praktyki operacyjnej. W artykule zaakcentowano różnicę, jaka występuje między jakością prognozy pogody przygotowanej na podstawie obserwacji dokonanej przez synoptyka a prognozą pogody na podstawie danych pochodzących z obserwacji wcześniej zinterpretowanej, np. opisanej kluczem SYNOP lub METAR. Główne rozważania przedstawione w pracy są skupione wokół próby określenia, jakich danych (narzędzi) brakuje, aby można było dać trafną diagnozę stanu atmosfery, aby na jej podstawie otrzymać wiarygodną prognozę warunków pogodowych. Istotę prognozy pogody o założonych w pracy parametrach czasowo-przestrzennych (prognoza zjawisk mezoskalowych na okres do 2 godzin) można sprowadzić w ogólności do dwóch etapów postępowania. Istotą pierwszego jest pełne zdiagnozowanie stanu atmosfery, drugi przewiduje jego ewolucję i jest określony jako trafne dobranie modelu zmian. I chociaż powyższy schemat jest typowy dla procesu przygotowania prognoz pogody, to w pracy zaakcentowano na podstawie 3 przykładów (niepoprawnego rozpoznania rodzaju chmur, zróżnicowanego wpływu warunków termiczno-wilgotnościowych na powstanie mgły, fluktuacji widzialności na stacji zlokalizowanej na linii brzegowej) niedoskonałości diagnozowania warunków atmosferycznych dla tego rodzaju prognoz, zwłaszcza w kontekście podejmowania decyzji mających istotny wpływ na zdrowie i życie ludzi. Autor sugeruje wprowadzenie nowej kategorii obserwacji pogody, które zawierałyby w sobie wyczerpujący opis procesów zachodzących w atmosferze. Obserwacje te powinny obejmować dane radarowe, zdjęcia satelitarne, obserwacje przyziemne, dane z sondaży aerologicznych, a także, o ile to możliwe, informacje od pilotów. Ponadto w pracy wskazano w jaki sposób brak dobrej informacji początkowej albo dysponowanie informacją fałszywą wpływa na wynik końcowy procesu diagnoza- -prognoza.

EN

Using some case studies the paper shows importance of accurate diagnoses of weather phenomena to a very short range forecasting, so called nowcasting. False or incorrect input information about weather conditions produces missed prediction the future. Author defines the process of weather forecasting in two stages. The first one refers to a precise description of meteorological conditions. The other one is a complex process of creation of extrapolating models that would help to predict changes of the initial state. Though the models use state-of-the- art technology, the role of knowledge and experience of a forecaster in the nowcasting process is still a key issue for many weather services. Author suggests introducing the new category of weather observation that would contain comprehensive description of atmospheric processes. The observation should comprise radar data, satellite pictures, surface weather observations, profiles and, if it is possible, information from pilots.