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The numerical weather model starts from the initial state of the Earth's atmosphere in a given place and time. The initial state is created by blending the previous forecast runs (first-guess), together with observations from different platforms. The better the initial state, the better the forecast; hence, it is worthy to combine new observation types. The GNSS tomography technique, developed in recent years, provides a 3-D field of humidity in the troposphere. This technique shows positive results in the monitoring of severe weather events. However, to assimilate the tomographic outputs to the numerical weather model, the proper observation operator needs to be built.
This study demonstrates the TOMOREF operator dedicated to the assimilation of the GNSS tomography‐derived 3‐D fields of wet refractivity in a Weather Research and Forecasting (WRF) Data Assimilation (DA) system. The new tool has been tested based on wet refractivity fields derived during a very intense precipitation event. The results were validated using radiosonde observations, synoptic data, ERA5 reanalysis, and radar data. In the presented experiment, a positive impact of the GNSS tomography data assimilation on the forecast of relative humidity (RH) was noticed (an improvement of root‐mean‐square error up to 0.5%). Moreover, within 1 hour after assimilation, the GNSS data reduced the bias of precipitation up to 0.1 mm. Additionally, the assimilation of GNSS tomography data had more influence on the WRF model than the Zenith Total Delay (ZTD) observations, which confirms the potential of the GNSS tomography data for weather forecasting.
Natalia Hanna; Estera Trzcina; Maciej Kryza; Witold Rohm. TOMOREF operator as a tool to improve weather forecasts. 2021, 1 .
AMA StyleNatalia Hanna, Estera Trzcina, Maciej Kryza, Witold Rohm. TOMOREF operator as a tool to improve weather forecasts. . 2021; ():1.
Chicago/Turabian StyleNatalia Hanna; Estera Trzcina; Maciej Kryza; Witold Rohm. 2021. "TOMOREF operator as a tool to improve weather forecasts." , no. : 1.
Global Navigation Satellite Systems (GNSS) sense the atmosphere remotely and provide low-cost, high-quality information about its state. Nowadays, radio occultation (RO) profiles from space platforms and tropospheric delays from ground-based stations are routinely assimilated in Numerical Weather Models (NWM).
In spite of provision of valuable information for weather forecasting, both space- and ground-based data have significant limitations. The RO technique has low horizontal resolution and does not provide reliable profiles in the first 3-5km of the troposphere. Whereas, the station-specific integrated value of troposphere are sparse and pose a problem to NWM adjoint operator for correcting model fields at different heights. These deficiencies could be resolved by the GNSS tomography technique that utilizes an inverse Radon transform to derive the 3D refractivity distribution over certain troposphere space. The combination of space-based and ground-based observations in the tomographic model will enable us to increase the number of intersections of GNSS signals and improve the refractivity solution within individual model locations.
The aim of this research is to harness the full potential of Space 4.0 era, rapidly growing numbers of RO and GNSS satellite constellations as well as low-cost GNSS ground-based networks worldwide. We will not only use current infrastructure but also examine impact of future constellations on model performance. 3D model of refractivity from dense observations should be an excellent tool in weather prediction. Our previous research proves that the assimilation of the GNSS tomography outputs into the NWM improves relative humidity and the short-term weather forecasts. Therefore, the research goal of this project is to assess the benefit of integrated tomography model on the severe weather prediction and urban scale weather models.
Witold Rohm; Paweł Hordyniec; Gregor Möller; Maciej Kryza; Estera Trzcina; Mateusz Taszarek. Combination of ground-based and space-based GNSS tomography (2021-2025). 2021, 1 .
AMA StyleWitold Rohm, Paweł Hordyniec, Gregor Möller, Maciej Kryza, Estera Trzcina, Mateusz Taszarek. Combination of ground-based and space-based GNSS tomography (2021-2025). . 2021; ():1.
Chicago/Turabian StyleWitold Rohm; Paweł Hordyniec; Gregor Möller; Maciej Kryza; Estera Trzcina; Mateusz Taszarek. 2021. "Combination of ground-based and space-based GNSS tomography (2021-2025)." , no. : 1.
Emissions from the household sector are the most significant source of air pollution in Poland, one of the most polluted countries in the EU. Estimated health impacts of the reduction of these emissions under three scenarios are presented. The EMEP4PL model and base year emission inventory were used to estimate average annual PM10 and PM2.5 concentrations with spatial resolution of 4 km × 4 km. The change in emissions under each of the scenarios was based on data from a survey on household boilers and insulation. Scenario 1 included replacement of all poor-quality coal-fired boilers with gas boilers; Scenario 2 included replacement of all poor-quality coal-fired boilers with low-emission boilers but still using solid fuels; and Scenario 3 included the thermal refurbishment of houses with the worst insulation. Impacts on the following health parameters were estimated: premature deaths (PD), Chronic Bronchitis (CB), Bronchitis in Children (BiC) and Work Days Lost (WDL). The concentration–response functions recommended by the WHO HRAPIE project were used. The analysis was conducted for two regions: Lower Silesia and Lodzkie province. The largest reduction of health impact was observed for Scenario 1. For Lower Silesia, the annual PD decreased by 1122 (34.3%), CB by 1516 (26.6%), BiC by 9602 (27.7%) and WDL by 481k (34.7%). For Lodzkie province, the largest impacts were estimated as decreases in PD by 1438 (29.9%), CB by 1502 (25.3%), BiC by 9880 (26.8%) and WDL by 669k (30.4%).
Łukasz Adamkiewicz; Maciej Kryza; Dominika Mucha; Małgorzata Werner; Anna Gayer; Anetta Drzeniecka-Osiadacz; Tymoteusz Sawiński. Estimating Health Impacts Due to the Reduction of Particulate Air Pollution from the Household Sector Expected under Various Scenarios. Applied Sciences 2020, 11, 272 .
AMA StyleŁukasz Adamkiewicz, Maciej Kryza, Dominika Mucha, Małgorzata Werner, Anna Gayer, Anetta Drzeniecka-Osiadacz, Tymoteusz Sawiński. Estimating Health Impacts Due to the Reduction of Particulate Air Pollution from the Household Sector Expected under Various Scenarios. Applied Sciences. 2020; 11 (1):272.
Chicago/Turabian StyleŁukasz Adamkiewicz; Maciej Kryza; Dominika Mucha; Małgorzata Werner; Anna Gayer; Anetta Drzeniecka-Osiadacz; Tymoteusz Sawiński. 2020. "Estimating Health Impacts Due to the Reduction of Particulate Air Pollution from the Household Sector Expected under Various Scenarios." Applied Sciences 11, no. 1: 272.
In recent years, allergies due to airborne pollen allergens have shown an increasing trend, along with the severity of allergic symptoms in most industrialized countries, while synergism with other common atmospheric pollutants has also been identified as affecting the overall quality of citizenly life. In this study, we propose the state-of-the-art WRF-Chem model, which is a complex Eulerian meteorological model integrated on-line with atmospheric chemistry. We used a combination of the WRF-Chem extended towards birch pollen, and the emission module based on heating degree days, which has not been tested before. The simulations were run for the moderate season in terms of birch pollen concentrations (year 2015) and high season (year 2016) over Central Europe, which were validated against 11 observational stations located in Poland. The results show that there is a big difference in the model’s performance for the two modelled years. In general, the model overestimates birch pollen concentrations for the moderate season and highly underestimates birch pollen concentrations for the year 2016. The model was able to predict birch pollen concentrations for first allergy symptoms (above 20 pollen m−3) as well as for severe symptoms (above 90 pollen m−3) with probability of detection at 0.78 and 0.68 and success ratio at 0.75 and 0.57, respectively for the year 2015. However, the model failed to reproduce these parameters for the year 2016. The results indicate the potential role of correcting the total seasonal pollen emission in improving the model’s performance, especially for specific years in terms of pollen productivity. The application of chemical transport models such as WRF-Chem for pollen modelling provides a great opportunity for simultaneous simulations of chemical air pollution and allergic pollen with one goal, which is a step forward for studying and understanding the co-exposure of these particles in the air.
Małgorzata Werner; Jakub Guzikowski; Maciej Kryza; Małgorzata Malkiewicz; Daria Bilińska; Carsten Ambelas Skjøth; Piotr Rapiejko; Kazimiera Chłopek; Katarzyna Dąbrowska-Zapart; Agnieszka Lipiec; Dariusz Jurkiewicz; Ewa Kalinowska; Barbara Majkowska-Wojciechowska; Dorota Myszkowska; Krystyna Piotrowska-Weryszko; Małgorzata Puc; Anna Rapiejko; Grzegorz Siergiejko; Elżbieta Weryszko-Chmielewska; Andrzej Wieczorkiewicz; Monika Ziemianin. Extension of WRF-Chem for birch pollen modelling—a case study for Poland. International Journal of Biometeorology 2020, 65, 513 -526.
AMA StyleMałgorzata Werner, Jakub Guzikowski, Maciej Kryza, Małgorzata Malkiewicz, Daria Bilińska, Carsten Ambelas Skjøth, Piotr Rapiejko, Kazimiera Chłopek, Katarzyna Dąbrowska-Zapart, Agnieszka Lipiec, Dariusz Jurkiewicz, Ewa Kalinowska, Barbara Majkowska-Wojciechowska, Dorota Myszkowska, Krystyna Piotrowska-Weryszko, Małgorzata Puc, Anna Rapiejko, Grzegorz Siergiejko, Elżbieta Weryszko-Chmielewska, Andrzej Wieczorkiewicz, Monika Ziemianin. Extension of WRF-Chem for birch pollen modelling—a case study for Poland. International Journal of Biometeorology. 2020; 65 (4):513-526.
Chicago/Turabian StyleMałgorzata Werner; Jakub Guzikowski; Maciej Kryza; Małgorzata Malkiewicz; Daria Bilińska; Carsten Ambelas Skjøth; Piotr Rapiejko; Kazimiera Chłopek; Katarzyna Dąbrowska-Zapart; Agnieszka Lipiec; Dariusz Jurkiewicz; Ewa Kalinowska; Barbara Majkowska-Wojciechowska; Dorota Myszkowska; Krystyna Piotrowska-Weryszko; Małgorzata Puc; Anna Rapiejko; Grzegorz Siergiejko; Elżbieta Weryszko-Chmielewska; Andrzej Wieczorkiewicz; Monika Ziemianin. 2020. "Extension of WRF-Chem for birch pollen modelling—a case study for Poland." International Journal of Biometeorology 65, no. 4: 513-526.
Global Navigation Satellite System (GNSS) tomography is a technique that aims to obtain a 3D field of humidity in the troposphere. It is based on observations of GNSS signal delays between satellites and ground‐based receivers. The technique has been developed in recent years, showing positive results in the monitoring of severe weather events. The previous studies on assimilation into the numerical weather prediction models are based on available observation operators which are not adjusted to the GNSS tomography data. In this study, we demonstrate an observation operator TOMOREF dedicated to the assimilation of the GNSS tomography‐derived 3D fields of wet refractivity in a Weather Research and Forecasting (WRF) Data Assimilation system. The new tool has been tested based on wet refractivity fields derived during a heavy precipitation event. The results were validated using radiosonde observations, synoptic data, ERA5 reanalysis, and radar data. In the presented experiment, a positive impact of the GNSS tomography data assimilation on the forecast of relative humidity (RH) has been noticed (an improvement of root mean square error up to 0.5%). Moreover, the validation of the precipitation forecasts reveals the positive impact of the GNSS data assimilation within 1 hour after assimilation (the mean bias values are reduced up to 0.1 mm). Additionally, it was observed that assimilation of GNSS tomography data has a greater influence on the WRF model than the Zenith Total Delay (ZTD) observations, which proves the potential of the GNSS tomography data for weather forecasting.
Estera Trzcina; Natalia Hanna; Maciej Kryza; Witold Rohm. TOMOREF Operator for Assimilation of GNSS Tomography Wet Refractivity Fields in WRF DA System. Journal of Geophysical Research: Atmospheres 2020, 125, 1 .
AMA StyleEstera Trzcina, Natalia Hanna, Maciej Kryza, Witold Rohm. TOMOREF Operator for Assimilation of GNSS Tomography Wet Refractivity Fields in WRF DA System. Journal of Geophysical Research: Atmospheres. 2020; 125 (17):1.
Chicago/Turabian StyleEstera Trzcina; Natalia Hanna; Maciej Kryza; Witold Rohm. 2020. "TOMOREF Operator for Assimilation of GNSS Tomography Wet Refractivity Fields in WRF DA System." Journal of Geophysical Research: Atmospheres 125, no. 17: 1.
In Poland, high concentrations of particulate matter (with a diameter smaller than 2.5 or 10 μm) exceeding the WHO threshold values are often measured in winter, while ozone (O3) concentrations are high in spring. In winter high PM2.5 and PM10 concentrations are linked to high residential combustion and road transport. The main objective of this study was to assess performance of the Weather Research and Forecasting model with Chemistry (WRF-Chem) model in reproducing observations for a period of 2017–2018 covering various meteorological conditions. We compare modelled and observed exposure metrics for PM2.5, PM10 and O3 for two sets of the WRF-Chem model runs: with coarse and fine resolution emission inventory (European Monitoring and Evaluation Programme (EMEP) and Chief Inspectorate of Environmental Protection (CIEP), respectively). CIEP run reduces the negative bias of PM2.5 and PM10 and improves the model performance for number of days with exceedance of WHO (World Health Organization) threshold for PM2.5 and PM10 24-h mean concentration. High resolution emission inventory for primary aerosols helps to better distinguish polluted urban areas from non-urban ones. There are no large differences for the model performance for O3 and secondary inorganic aerosols, and high-resolution emission inventory does not improve the results in terms of 8-h rolling mean concentrations of ozone.
Maciej Kryza; Małgorzata Werner; Justyna Dudek; Anthony Dore. The Effect of Emission Inventory on Modelling of Seasonal Exposure Metrics of Particulate Matter and Ozone with the WRF-Chem Model for Poland. Sustainability 2020, 12, 5414 .
AMA StyleMaciej Kryza, Małgorzata Werner, Justyna Dudek, Anthony Dore. The Effect of Emission Inventory on Modelling of Seasonal Exposure Metrics of Particulate Matter and Ozone with the WRF-Chem Model for Poland. Sustainability. 2020; 12 (13):5414.
Chicago/Turabian StyleMaciej Kryza; Małgorzata Werner; Justyna Dudek; Anthony Dore. 2020. "The Effect of Emission Inventory on Modelling of Seasonal Exposure Metrics of Particulate Matter and Ozone with the WRF-Chem Model for Poland." Sustainability 12, no. 13: 5414.
High concentrations of atmospheric aerosols with aerodynamic diameter below 2.5 mm (PM2.5) are frequently observed in several Central European countries during the heating season (October – March). Poland belongs to a group of EU countries with the highest concentrations of PM2.5, according to the European Environmental Agency. Large exposure to atmospheric pollutants leads to significant number of premature deaths attributable to adverse air quality in Poland.
Coal combustion for residential heating is one of the main sources of PM2.5 in Poland. The quality of this fuel is often unknown, and this increases the uncertainty of national emission inventories and makes the modelling of PM2.5 concentrations challenging. Second, daily temporal emission profile (i.e. hours of the day when emission is released to the atmosphere) in residential heating sector is also rather uncertain. In this work, we developed a daily temporal emission profile using available measurements of PM2.5 and PM10 concentrations from the 2017-2018 heating season. The profile was compared with the existing profile proposed within the INERIS project. New profile has longer peak of afternoon and night time emission, if compared to INERIS, and the morning peak is significantly lower. It means that more emission is released to the atmosphere during unfavorable meteorological conditions such as calm winds and temperature inversions, which are frequently observed during the afternoon and night.
We have run two simulations using the EMEP4PL model with new and old (INERIS) emission profile. The simulations covered three heating seasons of 2015-2016, 2017-2018 and 2018-2019. Application of the new emission profile results in increased model – measurements correlation and reduced model bias.
Maciej Kryza; Małgorzata Werner; Justyna Dudek. Improving PM2.5 modelling results through development of the new hourly temporal emission profile – a case study of Poland. 2020, 1 .
AMA StyleMaciej Kryza, Małgorzata Werner, Justyna Dudek. Improving PM2.5 modelling results through development of the new hourly temporal emission profile – a case study of Poland. . 2020; ():1.
Chicago/Turabian StyleMaciej Kryza; Małgorzata Werner; Justyna Dudek. 2020. "Improving PM2.5 modelling results through development of the new hourly temporal emission profile – a case study of Poland." , no. : 1.
Some European countries in Eastern or Central Europe, such as Poland, have serious problems with air quality. High concentrations of particulate matter (PM) in winter are often related to high coal and wood combustion for residential heating. Meteorological conditions, i.e. low air temperature and anticyclones, provide favourable conditions for the accumulation of air pollution, rendering it harmful to people. PM concentrations during the warmer period are much lower, however there are episodes with elevated concentrations related to e.g. long-range transport of pollutants from biomass burning areas. Policy makers in Poland put a lot of effort to improve air quality as well as inform and aware people on harmful effects of air pollution. One of the relevant tools which provides information on the past, current and future state of the air pollution are chemical transport models.
In this study we aim for validation of PM10 and PM2.5 concentrations from two different chemical transport models – WRF-Chem and EMEP4PL and two different emission databases – a) a regional EMEP database, and b) a local database provided by the Chief Inspectorate of Environmental Pollution. Modelled PM10 and PM2.5 concentrations were compared with observations from Polish stations for the year 2018. The results show a clear seasonal variation of the models performance with the lowest correlation coefficients in summer. Higher seasonal variability is observed for WRF-Chem than EMEP, which is probably related to differences in calculations of boundary layer height. Application of local database improves the results for both models. For several months, the performance of WRF-Chem and EMEP is clearly different, which shows that an ensemble approach with an application of these two models could improve the modelling results. The differences in the model performance significantly influence the results of the population exposure assessment.
Małgorzata Werner; Maciej Kryza; Justyna Dudek. Two models and two emission databases – evaluation of the PM10 and PM2.5 concentrations modelled with WRF-Chem and EMEP4PL. 2020, 1 .
AMA StyleMałgorzata Werner, Maciej Kryza, Justyna Dudek. Two models and two emission databases – evaluation of the PM10 and PM2.5 concentrations modelled with WRF-Chem and EMEP4PL. . 2020; ():1.
Chicago/Turabian StyleMałgorzata Werner; Maciej Kryza; Justyna Dudek. 2020. "Two models and two emission databases – evaluation of the PM10 and PM2.5 concentrations modelled with WRF-Chem and EMEP4PL." , no. : 1.
The amount of water vapor in the atmosphere is highly variable and not easy to measure. One of the methods to provide reliable information about the amount and distribution of the humidity in the troposphere is GNSS (Global Navigation Satellite Systems) tomography. The GNSS tomography uses the observations of signal delays between satellites and ground-based receivers over the field covered by a GNSS network. This method enables deriving the 3D distribution of wet refractivity at a low cost in all weather conditions, with high temporal and spatial resolution.
The first applications of the GNSS tomography data in the Weather Research and Forecasting Data Assimilation (WRF DA) system were performed by the adaptation of the GPSREF observation operator. In this study, we present a new tool, namely the TOMOREF observation operator, which consists of three parts: forward, tangent linear, and adjoint operators. As the input data in the assimilation process, the wet refractivity fields from two tomographic models (TUW, WUELS) are used. The analysis is carried out for a 2-week long period (May 29 – June 14, 2013) in Central Europe when severe weather conditions occurred, including heavy precipitation events. The data assimilation results are verified against radiosonde observations, synoptic data, and ERA5 reanalysis. Moreover, the performance of the TOMOREF and GPSREF operators is examined. For the forecasts of relative humidity (RH) at a pressure level of 300 hPa, the implementation of the TOMOREF operator vanishes the negative impact caused by the GPSREF operator. Additionally, the improvement of the root mean square error of the forecasts of RH up to 0.5% is observed. Comparing to the assimilation of Zenith Total Delay observations, the application of the tomographic data has overall a greater influence on the WRF model. Consequently, the GNSS tomography data can be valuable in operational weather forecasting.
Natalia Hanna; Estera Trzcina; Maciej Kryza; Witold Rohm. TOMOREF operator for assimilation of GNSS tomography wet refractivity fields in WRF DA system. 2020, 1 .
AMA StyleNatalia Hanna, Estera Trzcina, Maciej Kryza, Witold Rohm. TOMOREF operator for assimilation of GNSS tomography wet refractivity fields in WRF DA system. . 2020; ():1.
Chicago/Turabian StyleNatalia Hanna; Estera Trzcina; Maciej Kryza; Witold Rohm. 2020. "TOMOREF operator for assimilation of GNSS tomography wet refractivity fields in WRF DA system." , no. : 1.
The influence of atmospheric circulation conditions on pollen concentrations of two taxons (Betula and Alnus) in Wroclaw, Poland, for the years 2005–2014 was analysed. Pollen concentration was analysed separately for twenty circulation types that were determined using objective classification. The results indicate the atmospheric circulation conditions favourable for both low and high pollen concentrations over Central Europe. Pollen concentrations vary significantly according to circulation types. The highest pollen concentrations for both taxons are typical for warm, sunny, and dry anticyclonic circulation types with anticyclone in the lower and upper troposphere, especially for types with advection from the SW. The lowest pollen concentrations are observed for cold, wet, and cloudy cyclonic types with advection from the northern sectors. There is also a positive and statistically significant trend in the frequency of circulation types favourable for high concentrations of Betula and Alnus.
Hanna Ojrzyńska; Daria Bilińska; Małgorzata Werner; Maciej Kryza; Małgorzata Malkiewicz. The influence of atmospheric circulation conditions on Betula and Alnus pollen concentrations in Wrocław, Poland. Aerobiologia 2020, 36, 261 -276.
AMA StyleHanna Ojrzyńska, Daria Bilińska, Małgorzata Werner, Maciej Kryza, Małgorzata Malkiewicz. The influence of atmospheric circulation conditions on Betula and Alnus pollen concentrations in Wrocław, Poland. Aerobiologia. 2020; 36 (2):261-276.
Chicago/Turabian StyleHanna Ojrzyńska; Daria Bilińska; Małgorzata Werner; Maciej Kryza; Małgorzata Malkiewicz. 2020. "The influence of atmospheric circulation conditions on Betula and Alnus pollen concentrations in Wrocław, Poland." Aerobiologia 36, no. 2: 261-276.
In this work we analyse the impact of meteorological data assimilation on the performance of the air quality forecasting system for the area of Poland (Central Europe). The forecasting system uses the WRF-Chem model, which is online integrated meteorology and air chemistry transport model. The forecasts are run each day for the next 48 h, using two nested domains of 12 km × 12 km (Europe) and 4 km × 4 km (Poland) and 35 vertical levels. In this work we analyse the period of 11–25 February 2017, during which poor air quality was observed at the beginning, followed by unusually warm days with low concentrations of pollutants. Two sets of forecasts are compared. In the first group, we use the forecasts with no data assimilation. Secondly, we use the community Gridpoint Statistical Interpolation system (GSI) to assimilate surface and radiosonde meteorological data. Both sets of forecasts are compared with hourly measurements of PM10 and PM2.5 for Poland. Assimilation of meteorological data overall improves the air quality forecasts, but not always leads to better representation of high-concentration episode.
Maciej Kryza; Małgorzata Werner; Jakub Guzikowski. Assimilation of Meteorological Data in Online Integrated Atmospheric Transport Model—Example of Air Quality Forecasts for Poland. First Complex Systems Digital Campus World E-Conference 2015 2019, 273 -278.
AMA StyleMaciej Kryza, Małgorzata Werner, Jakub Guzikowski. Assimilation of Meteorological Data in Online Integrated Atmospheric Transport Model—Example of Air Quality Forecasts for Poland. First Complex Systems Digital Campus World E-Conference 2015. 2019; ():273-278.
Chicago/Turabian StyleMaciej Kryza; Małgorzata Werner; Jakub Guzikowski. 2019. "Assimilation of Meteorological Data in Online Integrated Atmospheric Transport Model—Example of Air Quality Forecasts for Poland." First Complex Systems Digital Campus World E-Conference 2015 , no. : 273-278.
Based on the Weather Research and Forecasting model with Chemistry (WRF-Chem) model and Gridpoint Statistical Interpolation (GSI) assimilation tool, a forecasting system was used for two selected episodes (winter and summer) over Eastern Europe. During the winter episode, very high particular matter (PM2.5, diameter less than 2.5 µm) concentrations, related to low air temperatures and increased emission from residential heating, were measured at many stations in Poland. During the summer episode, elevated aerosol optical depth (AOD), likely related to the transport of pollution from biomass fires, was observed in Southern Poland. Our aim is to verify if there is a relevant positive impact of surface and satellite data assimilation (DA) on modeled PM2.5 concentrations, and to assess whether there are significant differences in the DA’s impact on concentrations between the two seasons. The results show a significant difference in the impact of surface and satellite DA on the model results between the summer and winter episode, which to a large degree is related to the availability of the satellite data. For example, the application of satellite DA raises the factor of two statistic from 0.18 to 0.78 for the summer episode, whereas this statistic remains unchanged (0.71) for the winter. The study suggests that severe winter air pollution episodes in Poland and Eastern Europe in general, often related to the dense cover of low clouds, will benefit from the assimilation of surface observations rather than satellite data, which can be very sparse in such meteorological situations. In contrast, the assimilation of satellite data can have a greater positive impact on the model results during summer than the assimilation of surface data for the same period.
Małgorzata Werner; Maciej Kryza; Jakub Guzikowski. Can Data Assimilation of Surface PM2.5 and Satellite AOD Improve WRF-Chem Forecasting? A Case Study for Two Scenarios of Particulate Air Pollution Episodes in Poland. Remote Sensing 2019, 11, 2364 .
AMA StyleMałgorzata Werner, Maciej Kryza, Jakub Guzikowski. Can Data Assimilation of Surface PM2.5 and Satellite AOD Improve WRF-Chem Forecasting? A Case Study for Two Scenarios of Particulate Air Pollution Episodes in Poland. Remote Sensing. 2019; 11 (20):2364.
Chicago/Turabian StyleMałgorzata Werner; Maciej Kryza; Jakub Guzikowski. 2019. "Can Data Assimilation of Surface PM2.5 and Satellite AOD Improve WRF-Chem Forecasting? A Case Study for Two Scenarios of Particulate Air Pollution Episodes in Poland." Remote Sensing 11, no. 20: 2364.
Large-scale synoptic conditions are able to transport considerable amounts of airborne particles over entire continents by creating substantial air mass movement. This phenomenon is observed in Europe in relation to highly allergenic ragweed (Ambrosia L.) pollen that are transported from populations in Central Europe (mainly the Pannonian Plain and Balkans) to the North. The path taken by atmospheric ragweed pollen often passes through the highly industrialised mining region of Silesia in Southern Poland, considered to be one of the most polluted areas in the EU. It is hypothesized that chemical air pollutants released over Silesia could become mixed with biological material and be transported to less polluted regions further North. We analysed levels of air pollution during episodes of long-distance transport (LDT) of ragweed pollen to Poland. Results show that, concomitantly with pollen, the concentration of air pollutants with potential health-risk, i.e. SO2, and PM10, have also significantly increased (by 104% and 37%, respectively) in the receptor area (Western Poland). Chemical transport modelling (EMEP) and air mass back-trajectory analysis (HYSPLIT) showed that potential sources of PM10 include Silesia, as well as mineral dust from the Ukrainian steppe and the Sahara Desert. In addition, atmospheric concentrations of other allergenic biological particles, i.e. Alternaria Nees ex Fr. spores, also increased markedly (by 115%) during LDT episodes. We suggest that the LDT episodes of ragweed pollen over Europe are not a “one-component” phenomenon, but are often related to elevated levels of chemical air pollutants and other biotic and abiotic components (fungal spores and desert dust).
Łukasz Grewling; Paweł Bogawski; Maciej Kryza; Donat Magyar; Branko Šikoparija; Carsten Ambelas Skjøth; Orsolya Udvardy; Małgorzata Werner; Matt Smith. Concomitant occurrence of anthropogenic air pollutants, mineral dust and fungal spores during long-distance transport of ragweed pollen. Environmental Pollution 2019, 254, 112948 .
AMA StyleŁukasz Grewling, Paweł Bogawski, Maciej Kryza, Donat Magyar, Branko Šikoparija, Carsten Ambelas Skjøth, Orsolya Udvardy, Małgorzata Werner, Matt Smith. Concomitant occurrence of anthropogenic air pollutants, mineral dust and fungal spores during long-distance transport of ragweed pollen. Environmental Pollution. 2019; 254 ():112948.
Chicago/Turabian StyleŁukasz Grewling; Paweł Bogawski; Maciej Kryza; Donat Magyar; Branko Šikoparija; Carsten Ambelas Skjøth; Orsolya Udvardy; Małgorzata Werner; Matt Smith. 2019. "Concomitant occurrence of anthropogenic air pollutants, mineral dust and fungal spores during long-distance transport of ragweed pollen." Environmental Pollution 254, no. : 112948.
The aim of the study was to investigate the variability of Alnus and Corylus pollen concentrations at two stations located in the city of Wrocław, Poland—one at the city centre and the other 4 km from the city centre. Our goal was to compare measurements from these stations in relation to meteorology and land cover. We used Spearman’s correlation coefficient to investigate any dependence between meteorological factors and pollen concentration. Additionally, to check the relation between the direction of inflow of air masses and pollen concentration, we calculated the backward trajectories using the HYSPLIT model. The results have shown that despite the short distance between the stations, the characteristic of the pollen season is different for both stations (i.a. date of start and end of pollen season, duration of the season). The Spearman’s correlation coefficient between relative humidity and air temperature and pollen concentration was found to be statistically significant. The backward trajectories calculated with HYSPLIT suggested a different origin of air masses between stations for high-concentration episodes in the case of Alnus. Our study has shown that analysis of meteorological conditions and influence of air transport into pollen concentration makes it possible to ascertain the reasons for differences in pollen level at these two stations, both of which are located in the same climatological domain. The study also shows that the aerobiological condition may change significantly over a short distance, which is a major challenge, for example, for pollen emission, transport, and concentration modelling.
Daria Bilińska; Maciej Kryza; Małgorzata Werner; Małgorzata Malkiewicz. The variability of pollen concentrations at two stations in the city of Wrocław in Poland. Aerobiologia 2019, 35, 421 -439.
AMA StyleDaria Bilińska, Maciej Kryza, Małgorzata Werner, Małgorzata Malkiewicz. The variability of pollen concentrations at two stations in the city of Wrocław in Poland. Aerobiologia. 2019; 35 (3):421-439.
Chicago/Turabian StyleDaria Bilińska; Maciej Kryza; Małgorzata Werner; Małgorzata Malkiewicz. 2019. "The variability of pollen concentrations at two stations in the city of Wrocław in Poland." Aerobiologia 35, no. 3: 421-439.
The GNSS data assimilation is currently widely discussed in the literature with respect to the various applications for meteorology and numerical weather models. Data assimilation combines atmospheric measurements with knowledge of atmospheric behavior as codified in computer models. With this approach, the “best” estimate of current conditions consistent with both information sources is produced. Some approaches also allow assimilating the non-prognostic variables, including remote sensing data from radar or GNSS (global navigation satellite system). These techniques are named variational data assimilation schemes and are based on a minimization of the cost function, which contains the differences between the model state (background) and the observations. The variational assimilation is the first choice for data assimilation in the weather forecast centers, however, current research is consequently looking into use of an iterative, filtering approach such as an extended Kalman filter (EKF). This paper shows the results of assimilation of the GNSS data into numerical weather prediction (NWP) model WRF (Weather Research and Forecasting). The WRF model offers two different variational approaches: 3DVAR and 4DVAR, both available through the WRF data assimilation (WRFDA) package. The WRFDA assimilation procedure was modified to correct for bias and observation errors. We assimilated the zenith total delay (ZTD), precipitable water (PW), radiosonde (RS) and surface synoptic observations (SYNOP) using a 4DVAR assimilation scheme. Three experiments have been performed: (1) assimilation of PW and ZTD for May and June 2013, (2) assimilation of PW alone; PW, with RS and SYNOP; ZTD alone; and finally ZTD, with RS and SYNOP for 5–23 May 2013, and (3) assimilation of PW or ZTD during severe weather events in June 2013. Once the initial conditions were established, the forecast was run for 24 h. The major conclusion of this study is that for all analyzed cases, there are two parameters significantly changed once GNSS data are assimilated in the WRF model using GPSPW operator and these are moisture fields and rain. The GNSS observations improves forecast in the first 24 h, with the strongest impact starting from a 9 h lead time. The relative humidity forecast in a vertical profile after assimilation of ZTD shows an over 20 % decrease of mean error starting from 2.5 km upward. Assimilation of PW alone does not bring such a spectacular improvement. However, combination of PW, SYNOP and radiosonde improves distribution of humidity in the vertical profile by maximum of 12 %. In the three analyzed severe weather cases PW always improved the rain forecast and ZTD always reduced the humidity field bias. Binary rain analysis shows that GNSS parameters have significant impact on the rain forecast in the class above 1 mm h−1.
Witold Rohm; Jakub Guzikowski; Karina Wilgan; Maciej Kryza. 4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF. Atmospheric Measurement Techniques 2019, 12, 345 -361.
AMA StyleWitold Rohm, Jakub Guzikowski, Karina Wilgan, Maciej Kryza. 4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF. Atmospheric Measurement Techniques. 2019; 12 (1):345-361.
Chicago/Turabian StyleWitold Rohm; Jakub Guzikowski; Karina Wilgan; Maciej Kryza. 2019. "4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF." Atmospheric Measurement Techniques 12, no. 1: 345-361.
In this study, we applied the EMEP/MSC-W model at a high spatial resolution of 4 km × 4 km over Poland (EMEP4PL), and ran the model for the whole of the years 2015 and 2030. For the second simulation we used GAINS PRIMES emission projection and kept the meteorology from 2015. Although the model results are satisfactory and comparable to the results in other European countries, the number of days with exceedances of the limit value is highly underestimated in comparison to observations for 2015. It shows that the model is limited in its simulation of very high particulate matter concentrations in the winter season. Therefore, we applied a bias correction for the year 2030 based on the observations and model results for the year 2015. Bias corrected simulation shows that at 60 stations (out of 104), the PM10 daily limit value will be exceeded at least 35 times in 2030.
Małgorzata Werner; Maciej Kryza; Kinga Wałaszek. Emission projections and limit values of air pollution concentration - a case study using the EMEP4PL model. International Journal of Environment and Pollution 2019, 65, 164 .
AMA StyleMałgorzata Werner, Maciej Kryza, Kinga Wałaszek. Emission projections and limit values of air pollution concentration - a case study using the EMEP4PL model. International Journal of Environment and Pollution. 2019; 65 (1/2/3):164.
Chicago/Turabian StyleMałgorzata Werner; Maciej Kryza; Kinga Wałaszek. 2019. "Emission projections and limit values of air pollution concentration - a case study using the EMEP4PL model." International Journal of Environment and Pollution 65, no. 1/2/3: 164.
Mariusz Szymanowski; Anetta Drzeniecka-Osiadacz; Tymoteusz Sawiński; Maciej Kryza. Historical and contemporary studies of Wrocław’s climate – measurements and models. Acta Geographica Lodziensia 2019, 108, 109 -126.
AMA StyleMariusz Szymanowski, Anetta Drzeniecka-Osiadacz, Tymoteusz Sawiński, Maciej Kryza. Historical and contemporary studies of Wrocław’s climate – measurements and models. Acta Geographica Lodziensia. 2019; 108 ():109-126.
Chicago/Turabian StyleMariusz Szymanowski; Anetta Drzeniecka-Osiadacz; Tymoteusz Sawiński; Maciej Kryza. 2019. "Historical and contemporary studies of Wrocław’s climate – measurements and models." Acta Geographica Lodziensia 108, no. : 109-126.
Results of air quality modelling are strongly influenced by the emission inventory used. This is related to spatial and temporal allocation of emission. In Poland, the share of residential combustion (RC) in total emission of particulate matter is large, and the temporal profile of emission from this sector is influenced by meteorological conditions. Here we show the performance of the WRF-Chem model forecasts, running for the area of Poland with two different approaches to temporal distribution of emission from RC. First, emissions are distributed temporally using the monthly, daily and hourly emission factors provided by GENEMIS project (base run). Second, the model uses the heating degree-day (HDD) approach RC. We show that both approaches result in similar model performance for PM10 and PM2.5. The HDD approach leads to better forecasts for the warm days, whereas the base run forecasts often show too high concentrations of atmospheric pollutants for such periods.
Maciej Kryza; Małgorzata Werner; Anthony J. Dore. Application of degree-day factors for residential emission estimate and air quality forecasting. International Journal of Environment and Pollution 2019, 65, 325 .
AMA StyleMaciej Kryza, Małgorzata Werner, Anthony J. Dore. Application of degree-day factors for residential emission estimate and air quality forecasting. International Journal of Environment and Pollution. 2019; 65 (4):325.
Chicago/Turabian StyleMaciej Kryza; Małgorzata Werner; Anthony J. Dore. 2019. "Application of degree-day factors for residential emission estimate and air quality forecasting." International Journal of Environment and Pollution 65, no. 4: 325.
The forecasting system based on the WRF-Chem model and the GSI assimilation tool was applied for the first time over Europe. We aimed to evaluate the differences in impact of 3D-Var assimilation of PM2.5 ground base concentrations to different aerosol chemical schemes (GOCART and MADE/SORGAM) on modelled PM2.5 and PM10 concentrations and to assess the impact of data assimilation during the winter and summer period. For both seasons and both chemical mechanisms, the simulations with data assimilation give better results than the simulations without data assimilation. The improvement of the statistics between the simulations is higher for PM2.5 than for PM10 and the differences are bigger and last longer during the summer than during the winter season. Influence of data assimilation to different chemical schemes (GOCART and MADE) varies between the seasons, however we suggest further tests for different regions and seasons as the results might vary for different regions.
Małgorzata Werner; Maciej Kryza; Mariusz Pagowski; Jakub Guzikowski. Assimilation of PM2.5 ground base observations to two chemical schemes in WRF-Chem – The results for the winter and summer period. Atmospheric Environment 2018, 200, 178 -189.
AMA StyleMałgorzata Werner, Maciej Kryza, Mariusz Pagowski, Jakub Guzikowski. Assimilation of PM2.5 ground base observations to two chemical schemes in WRF-Chem – The results for the winter and summer period. Atmospheric Environment. 2018; 200 ():178-189.
Chicago/Turabian StyleMałgorzata Werner; Maciej Kryza; Mariusz Pagowski; Jakub Guzikowski. 2018. "Assimilation of PM2.5 ground base observations to two chemical schemes in WRF-Chem – The results for the winter and summer period." Atmospheric Environment 200, no. : 178-189.
The Global Navigation Satellite System (GNSS) is commonly recognized by its all-weather capability. However, observations depend on atmospheric conditions which requires the induced tropospheric delay to be estimated as an unknown parameter. In the following study, we investigate the impact of intense weather events on GNSS estimates. GNSS slant total delays (STD) in Precise Point Positioning technique (PPP) strategy were calculated for stations in southwest Poland in a 56 days period covering several heavy precipitation cases. The corresponding delays retrieved from Weather Research and Forecasting (WRF) model by a ray-tracing technique considered only gaseous parts of the atmosphere. The discrepancies are correlated with rain rates and cloud type products from remote sensing platforms. Positive correlation is found as well as GNSS estimates tend to be systematically larger than modeled delays. Mean differences mapped to the zenith direction are showed to vary between 10 mm and 30 mm. The magnitude of discrepancies follows the intensity of phenomena, especially for severe weather events. Results suggest that effects induced by commonly neglected liquid and solid water terms in the troposphere modeling should be considered in precise GNSS applications for the atmosphere monitoring. The state-of-art functional model applied in GNSS processing strategies shows certain deficits. Estimated tropospheric delays with gradients and post-fit residuals could be replaced by a loosely constrained solution without loss of quality.
Paweł Hordyniec; Jan Kapłon; Witold Rohm; Maciej Kryza. Residuals of Tropospheric Delays from GNSS Data and Ray-Tracing as a Potential Indicator of Rain and Clouds. Remote Sensing 2018, 10, 1917 .
AMA StylePaweł Hordyniec, Jan Kapłon, Witold Rohm, Maciej Kryza. Residuals of Tropospheric Delays from GNSS Data and Ray-Tracing as a Potential Indicator of Rain and Clouds. Remote Sensing. 2018; 10 (12):1917.
Chicago/Turabian StylePaweł Hordyniec; Jan Kapłon; Witold Rohm; Maciej Kryza. 2018. "Residuals of Tropospheric Delays from GNSS Data and Ray-Tracing as a Potential Indicator of Rain and Clouds." Remote Sensing 10, no. 12: 1917.