Application of WRF-Chem to Forecasting PM10 Concentration over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one way nested domains using the GFS meteorological data and the TNO MACC II emissions. Forecasts, with 48h lead time, were run for a winter and summer period 2014. WRF-Chem in general captures the variability in observed PM10 concentrations, but underestimates some peak concentrations during winter-time. The peaks coincide with either stable atmospheric condition during nighttime in the lower part of the planetary boundary layer or on days with very low surface temperatures. Such episodes lead to increased combustion in residential heating, where hard coal is the main fuel in Poland. This suggests that a key to improvement in the model performance for the peak concentrations is to focus on the simulation of PBL processes and the distribution of emissions with high resolution in WRF-Chem

Application of WRF-Chem to Forecasting PM10 Concentration Over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one-way nested domains using the GFS meteorological data and the TNO MACC II emissions. The 48 hour forecasts were run for each day of the winter and summer period of 2014 and there is only a small decrease in model performance for winter with respect to forecast lead time. The model in general captures the variability in observed PM10 concentrations for most of the stations. However, for some locations and specific episodes, the model performance is poor and the results cannot yet be used by official authorities. We argue that a higher resolution sector-based emission data will be helpful for this analysis in connection with a focus on planetary boundary layer processes in WRF-Chem and their impact on the initial distribution of emissions on both time and space

Aerosol-Radiation Feedback and PM10 Air Concentrations Over Poland

We have implemented the WRF-Chem model version 3.5 over Poland to quantify the direct and indirect feedback effects of aerosols on simulated meteorology and aerosol concentrations. Observations were compared with results from three simulations at high spatial resolutions of 5 × 5 km: (1) BASE—without any aerosol feedback effects; (2) DIR—with direct aerosol-radiative effects (3) INDIR—with direct and indirect aerosol-radiative effects. We study the overall effect during January 2011 as well as selected episodes of the highest differences in PM10 concentrations between the three simulations. For the DIR simulation, the decrease in monthly mean incoming solar radiation (SWDOWN) appears for the entire study area. It changes geographically, from about −8.0 to −2.0 W m−2, respectively for the southern and northern parts of the country. The highest changes do not correspond to the highest PM10 concentration. Due to the solar radiation changes, the surface mean monthly temperature (T2) decreases for 96 % of the area of Poland, but not more than 1.0 °C. Monthly mean PBLH changes by more than ±5 m for 53 % of the domain. Locally the differences in PBLH between the DIR and BASE are higher than ± 20 m. Due to the direct effect, for 84 % of the domain, the mean monthly PM10 concentrations increase by up to 1.9 µg m−3. For the INDIR simulation the spatial distribution of changes in incoming solar radiation as well as air temperature is similar to the DIR simulation. The decrease of SWDOWN is noticed for the entire domain and for 23 % of the domain is higher than −5.0 W m−2. The absolute differences of PBLH are slightly higher for INDIR than DIR but similarly distributed spatially. For daily episodes, the differences between the simulations are higher, both for meteorology and PM10 concentrations, and the pattern of changes is usually more complex. The results indicate the potential importance of the aerosol feedback effects on modelled meteorology and PM10 concentrations

Application of WRF-Chem to Forecast PM10 Concentrations Over Poland

The meteorological and chemical transport model WRF-Chem has been implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one way nested domains and the simulations were driven by the GFS meteorological data and the TNO MACC II emissions. The Regional Acid Deposition Model (RADM2) gas phase chemistry and the Modal Aerosol Dynamics Model for Europe with Secondary Organic Aerosol Model (MADE/SORGAM) aerosol module were applied in WRF-Chem. Forecasts were run 48 hours ahead for each day during a winter period from the 1st January to 28th February 2014. We have found that the model for most stations captures the variability of observed PM10 concentrations, whereas the highest observed peaks are often underestimated. Several of the peaks coincide with either stable atmospheric condition during nighttime in the lower part of the planetary boundary layer or on days with very low surface temperatures. This suggests that a key to a good simulation of the peak concentrations is to focus on the simulation of PBL processes and the distribution of emissions with high resolution in WRF-Che

4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF

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&thinsp;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&thinsp;h, with the strongest impact starting from a 9&thinsp;h lead time. The relative humidity forecast in a vertical profile after assimilation of ZTD shows an over 20&thinsp;% decrease of mean error starting from 2.5&thinsp;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&thinsp;%. 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&thinsp;mm&thinsp;h−1.</p

High-Resolution Dynamical Downscaling of ERA-Interim Using the WRF Regional Climate Model for the Area of Poland. Part 1: Model Configuration and Statistical Evaluation for the 1981–2010 Period

In this work, we present the results of high-resolution dynamical downscaling of air temperature, relative humidity, wind speed and direction, for the area of Poland, with the Weather Research and Forecasting (WRF) model. The model is configured using three nested domains, with spatial resolution of 45 km × 45 km, 15 km × 15 km and 5 km × 5 km. The ERA-Interim database is used for boundary conditions. The results are evaluated by comparison with station measurements for the period 1981–2010. The model is capable of reproducing the main climatological features of the study area. The results are in very close agreement with the measurements, especially for the air temperature. For all four meteorological variables, the model performance captures seasonal and daily cycles. For the air temperature and winter season, the model underestimates the measurements. For summer, the model shows higher values, compared with the measurements. The opposite is the case for relative humidity. There is a strong diurnal pattern in mean error, which changes seasonally. The agreement with the measurements is worse for the seashore and mountain areas, which suggests that the 5 km × 5 km grid might still have an insufficient spatial resolution. There is no statistically significant temporal trend in the model performance. The larger year-to-year changes in the model performance, e.g. for the years 1982 and 2010 for the air temperature should therefore be linked with the natural variability of meteorological conditions

High-Resolution Dynamical Downscaling of ERA-Interim Using the WRF Regional Climate Model for the Area of Poland. Part 2: Model Performance with Respect to Automatically Derived Circulation Types

This paper presents the application of the high-resolution WRF model data for the automatic classification of the atmospheric circulation types and the evaluation of the model results for daily rainfall and air temperatures. The WRF model evaluation is performed by comparison with measurements and gridded data (E-OBS). The study is focused on the area of Poland and covers the 1981–2010 period, for which the WRF model has been run using three nested domains with spatial resolution of 45 km × 45 km, 15 km × 15 km and 5 km × 5 km. For the model evaluation, we have used the data from the innermost domain, and data from the second domain were used for circulation typology. According to the circulation type analysis, the anticyclonic types (AAD and AAW) are the most frequent. The WRF model is able to reproduce the daily air temperatures and the error statistics are better, compared with the interpolation-based gridded dataset. The high-resolution WRF model shows a higher spatial variability of both air temperature and rainfall, compared with the E-OBS dataset. For the rainfall, the WRF model, in general, overestimates the measured values. The model performance shows a seasonal pattern and is also dependent on the atmospheric circulation type, especially for daily rainfall

THE ATLAS EXPERIMENT ON-LINE MONITORING AND FILTERING AS AN EXAMPLE OF REAL-TIME APPLICATION

The ATLAS detector, recording LHC particles’ interactions, produces events with rate of40 MHz and size of 1.6 MB. The processes with new and interesting physics phenomena arevery rare, thus an efficient on-line filtering system (trigger) is necessary. The asynchronouspart of that system relays on few thousands of computing nodes running the filtering software.Applying refined filtering criteria results in increase of processing times what may lead tolack of processing resources installed on CERN site. We propose extension to this part ofthe system based on submission of the real-time filtering tasks into the Grid

U–Pb Zircon geochronology of the Cambro-Ordovician metagranites and metavolcanic rocks of central and NW Iberia

New U–Pb zircon data from metagranites and metavolcanic rocks of the Schist-Graywacke Complex Domain and the Schistose Domain of Galicia Tras-os-Montes Zone from central and NW Iberia contribute to constrain the timing of the Cambro-Ordovician magmatism from Central Iberian and Galicia Tras-os-Montes Zones which occurred between 498 and 462 Ma. The crystallization ages of the metagranites and metavolcanic rocks from the northern Schist-Graywacke Complex Domain are as follows: (a) in west Salamanca, 489 ± 5 Ma for Vitigudino, 486 ± 6 Ma for Fermoselle and 471 ± 7 Ma for Ledesma; (b) in northern Gredos, 498 ± 4 Ma for Castellanos, 492 ± 4 Ma for San Pelayo and 488 ± 3 Ma for Bercimuelle; (c) in Guadarrama, 490 ± 5 Ma for La Estacion I, 489 ± 9 Ma for La Canada, 484 ± 6 Ma for Vegas de Matute (leucocratic), 483 ± 6 Ma for El Cardoso, 482 ± 8 Ma for La Morcuera, 481 ± 9 Ma for Buitrago de Lozoya, 478 ± 7 Ma for La Hoya, 476 ± 5 Ma for Vegas de Matute (melanocratic), 475 ± 5 Ma for Riaza, 473 ± 8 Ma for La Estacion II and 462 ± 11 Ma for La Berzosa; and (d) in Toledo, 489 ± 7 Ma for Mohares and 480 ± 8 Ma for Polan. The crystallization ages of the metagranites from the Schistose Domain of Galicia Tras-os-Montes Zone are 497 ± 6 Ma for Laxe, 486 ± 8 Ma for San Mamede, 482 ± 7 Ma for Bangueses, 481 ± 5 Ma for Noia, 480 ± 10 for Rial de Sabucedo, 476 ± 9 Ma for Vilanova, 475 ± 6 Ma for Pontevedra, 470 ± 6 Ma for Cherpa and 462 ± 8 Ma for Bande.This magmatism is characterized by an average isotopic composition of (87Sr/86Sr)485Ma ≈ 0.712, (eNd)485Ma ≈ -4.1 and (TDM) ≈ 1.62 Ga, and a high zircon inheritance, composed of Ediacaran–Early Cambrian (65 %) and, to a lesser extent, Cryogenian, Tonian, Mesoproterozoic, Orosirian and Archean pre-magmatic cores. Combining our geochronological and isotopic data with others of similar rocks from the European Variscan Belt, it may be deduced that Cambro-Ordovician magmas from this belt were mainly generated by partial melting of Ediacaran–Early Cambrian igneous rocks

Extension of WRF-Chem for birch pollen modelling – a case study for Poland.

In recent years, allergies due to airborne pollen have shown an increasing trend, along with the severity of allergic symptoms in most industrialised 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