High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model

Due to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields derived from the high-resolution (2.5 km) Weather Research and Forecasting (WRF) model. Forecasts are made with 24- and 48-h lead times. The purpose of this work is to present the validation of the implemented system. First, the results of the WRF model were validated using in situ observations from ∼70 synoptic stations. Second, we used the correlation method and Eastaugh\u27s percentile analysis to assess the quality of the FWI index. The data covered the 2019 fire season and were analysed for the whole forest area in Poland. Based on the presented results, it can be concluded that the FWI index (calculated based on the WRF model) has a very high predictive ability of fire risk. However, the results vary by region, distance from human habitats, and size of fire

Monitorowanie polskiej sieci stacji referencyjnych GPS

Tyt. z nagłówka.Bibliografia s. 123-124.Dostępny również w formie drukowanej.STRESZCZENIE: W związku z dynamicznym rozwojem stacji permanentnych GNSS na terenie Polski wraca problem kontroli pracy stacji oraz realizacji sytemu ETRS'89. Od kilku lat są w obiegu współrzędne stacji permanentnych GNSS, których źródło pochodzenia nie jest znane. Jedną z możliwości rozwiązania tego problemu jest koncepcja monitorowania stacji permanentnych zgodnie ze standardami EPN. Referat zawiera koncepcję takiego rozwiązania oraz wyniki obliczeń, które wykonano w 2006 r. W analizie wyników zostanie przedstawione również porównanie współrzędnych z wynikami uzyskanymi w systemie ASG-PL. SŁOWA KLUCZOWE: GPS, stacje permanentne, monitoring stacji GNSS. ABSTRACT: Dynamic development of permanent GNSS stations in Poland restores the problem of supervising the stations' performance and ETRS'89 system realization. Although the permanent GNSS stations' coordinates have been used for a few years now, their source is unknown. Permanent stations monitoring according to the EPN standards is one of the possibilities to solve the problem. The paper presents a concept of such a solution and the computation results obtained in 2006. The results analysis presents also a comparison of the coordinates with the results from the ASG-PL system. KEYWORDS: GPS, permanent station, GNSS station monitoring

Refrakcja troposferyczna w świetle meteorologicznych mezoskalowych modeli prognostycznych

Tyt. z nagłówka.Bibliografia s. 176.Dostępny również w formie drukowanej.STRESZCZENIE: W artykule przedstawiono metodę wyznaczania opóźnienia skośnego GPS w oparciu o dane analiz i prognoz niehydrostaycznego modelu atmosfery COAMPS (Coupled Ocean/Atmosphere Mesoscale Predition System), który został uruchomiony w trybie operacyjnym na klastrze komputerowym IA64 Centrum Geomatyki Stosowanej Wydziału Inżynierii Lądowej i Geodezji Wojskowej Akademii Technicznej. Opóźnienie skośne otrzymano, całkując przestrzenną funkcję refrakcji troposferycznej wzdłuż drogi propagacji fali GPS. Drogę określono, rozwiązując układ równań różniczkowych promienia, który wynika z równania eikonału. Do wyznaczenia pola refrakcji atmosferycznej wykorzystano parametry stanu atmosfery z modelu COAMPS. SŁOWA KLUCZOWE: model meteorologiczny, refrakcja troposferyczna, opóźnienie skośne. ABSTRACT: The paper presents a method of determining the GPS slant delay on the basis of diagnostic and forecasted data from the COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) non-hydrostatic model of the atmosphere which is run in operational mode on a IA64 computer cluster in the Applied Geomatics Section, Faculty of Civil Engineering and Geodesy, Military University of Technology. The slant delay value was obtained by integrating the spatial function of the tropospheric refraction along the GPS wave propagation path. The path was determined from the solution of the differential equations system of the path ray that results from the eikonal equation. The atmospheric refraction field was determined using the atmospheric parameters obtained from the COAMPS model. KEYWORDS: meteorological model, tropospheric refraction, slant delay

Spatial pattern of ASG-EUPOS sites

The article presents the spatial pattern analysis of the ASG-EUPOS permanent GNSS stations in Poland. Using different methods and tools (nearest neighbour, Riplay’s K-function, morphology of Thiessen polygons) we proved that the station distribution model changes within scales. At short distances up to 65 km, which are typical lengths in the network, stations are irregularly dispersed. Increasing this distance to 130 km and over could result in a clustered pattern

Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements—First Tests Based on Transmission System Operator Data

The Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim to explore how well those can be modeled based on the meteorological measurements provided by the Institute of Meteorology and Water Management. The hourly time series of PV generation on a country level and irradiation, wind speed, and temperature measurements from 23 meteorological stations covering one month are used as inputs to create an artificial neural network. The analysis indicates that available measurements combined with artificial neural networks can simulate PV generation on a national level with a mean percentage error of 3.2%

Spatio-temporal filtering for determination ofcommon mode error in regional GNSS networks

The spatial correlation between different stationsfor individual components in the regional GNSS networksseems to be significant. The mismodelling in satelliteorbits, the Earth orientation parameters (EOP), largescaleatmospheric effects or satellite antenna phase centrecorrections can all cause the regionally correlated errors.This kind of GPS time series errors are referred to ascommon mode errors (CMEs). They are usually estimatedwith the regional spatial filtering, such as the "stacking".In this paper, we show the stacking approach for the setof ASG-EUPOS permanent stations, assuming that spatialdistribution of the CME is uniform over the whole regionof Poland (more than 600 km extent). The ASG-EUPOSis a multifunctional precise positioning system based onthe reference network designed for Poland. We used a 5-year span time series (2008-2012) of daily solutions in theITRF2008 from Bernese 5.0 processed by the Military Universityof Technology EPN Local Analysis Centre (MUTLAC). At the beginning of our analyses concerning spatialdependencies, the correlation coefficients between eachpair of the stations in the GNSS network were calculated.This analysis shows that spatio-temporal behaviour of theGPS-derived time series is not purely random, but there isthe evident uniform spatial response. In order to quantifythe influence of filtering using CME, the norms L1 and L2were determined. The values of these norms were calculatedfor the North, East and Up components twice: beforeperforming the filtration and after stacking. The observedreduction of the L1 and L2 norms was up to 30% dependingon the dimension of the network. However, the questionhow to define an optimal size of CME-analysed subnetworkremains unanswered in this research, due to thefact that our network is not extended enough

Assessment of the Impact of GNSS Processing Strategies on the Long-Term Parameters of 20 Years IWV Time Series

Advanced processing of collected global navigation satellite systems (GNSS) observations allows for the estimation of zenith tropospheric delay (ZTD), which in turn can be converted to the integrated water vapour (IWV). The proper estimation of GNSS IWV can be affected by the adopted GNSS processing strategy. To verify which of its elements cause deterioration and which improve the estimated GNSS IWV, we conducted eight reprocessings of 20 years of GPS observations (01.1996–12.2015). In each of them, we applied a different mapping function, the zenith hydrostatic delay (ZHD) a priori value, the cut-off angle, software, and the positioning method. Obtained in such a way, the ZTD time series were converted to the IWV using the meteorological parameters sourced from the ERA-Interim. Then, based on them, the long-term parameters were estimated and compared to those obtained from the IWV derived from the radio sounding (RS) observations. In this paper, we analyzed long-term parameters such as IWV mean values, linear trends, and amplitudes of annual and semiannual oscillations. A comparative analysis showed, inter alia, that in terms of the investigation of the IWV linear trend the precise point positioning (PPP) method is characterized by higher accuracy than the differential one. It was also found that using the GPT2 model and the higher elevation mask brings benefits to the GNSS IWV linear trend estimation

Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations

The technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate a special type of plasma inhomogeneities, called travelling ionospheric disturbances (TID). Such use of GNSS sensors allows us to reconstruct the main TID parameters, such as spatial dimensions, velocities, and directions of their movement. The paper gives examples of the restoration of dynamic characteristics of ionospheric irregularities for quiet and disturbed geophysical conditions. Special attention is paid to the dynamics of ionospheric disturbances stimulated by the magnetic storms of two St. Patrick’s Days (17 March 2013 and 2015). Additional opportunities for the remote sensing of the ionosphere with the use of dense regional networks of GNSS receiving sensors have been noted too

Interannual Variability of the GNSS Precipitable Water Vapor in the Global Tropics

This paper addresses the subject of inter-annual variability of the tropical precipitable water vapor (PWV) derived from 18 years of global navigation satellite system (GNSS) observations. Non-linear trends of retrieved GNSS PWV were investigated using the singular spectrum analysis (SSA) along with various climate indices. For most of the analyzed stations (~49%) the GNSS PWV anomaly was related to the El Niño Southern Oscillation (ENSO), although its influence on the PWV variability was not homogeneous. The cross-correlations coefficient values estimated between the Multivariate ENSO Index (MEI) and PWV were up to 0.78. A strong cross-correlation was also found for regional climate pattern expressed through CAR, DMI, HAW, NPGO, TNA and TSA indices. A distinct agreement was also found when instead of climate indices, the local sea surface temperature was examined (average correlation 0.60). The SSA method made it also possible to distinguish small-scale phenomena that affect PWV, such as local droughts or wetter rainy seasons. The overall nature of the investigated changes was also verified through linear trend analysis. In general, not a single station was characterized by a negative trend and its weighted mean value, calculated for all stations was equal to 0.08 ± 0.01 mm/year

The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017

Precise simulations of severe weather events are a challenge in the era of changing climate. By performing simulations correctly and accurately, these phenomena can be studied and better understood. In this paper, we have verified how different initial and boundary conditions affect the quality of simulations performed using the Weather Research and Forecasting Model (WRF). For our analysis, we chose a derecho event that occurred in Poland on 11 August 2017, the most intense and devastating event in recent years. High-resolution simulations were conducted with initialization at 00 and 12 UTC (11 August 2017) using initial and boundary conditions derived from the four global models: Global Forecast System (GFS) from the National Centers for Environmental Prediction (NCEP), Integrated Forecast System (IFS) developed by the European Center for Medium-Range Weather Forecasts (ECMWF), Global Data Assimilation System (GDAS) and ERA5. For the last, we made separate calculations using data at the pressure and model levels. The results were evaluated against surface and radar data. We found that the simulations that used data from the GDAS and GFS models at 12 UTC were the more accurate, while ERA5 gave the worst predictions. However, all models were characterized by a low probability of detection and a high number of false alarms for simulations of extreme precipitation and wind gusts