Urban heat island (UHI) is one of the most distinctive characteristics of urban climate. The objective of the presented study was to apply a statistical modelling of the nocturnal atmospheric UHI based on the relationship between observed air temperature from ground stations and remotely-sensed temperature of the urban surface. The goal of the approach was to limit input data for the developed modelling method in order to assure transferability of the methodology to different cities. Time series of surface temperature and NDVI were obtained from the MODIS instrument for a 10 year period (2008-2017). The air temperature was collected from the in-situ observational network of 21 stations. The study was conducted for different locations with gradual changes in urbanization in order to assess the impact of urbanization on the relationship between simultaneous air and surface UHI. The urbanization was described by commonly available land cover metrics. Results showed that the proposed approach provided satisfactory AUHI modelling results for the locations with the least degree of urbanization. The best results were obtained with a simple linear regression model with the iterative procedure to minimize the mean absolute gross error (MAGE). The lowest MAGE for modelled UHI was 1.18°C with 69% of the variance explained. The strongest linear relationship between simultaneous SUHI and AUHI was noted for those station pairs which their surroundings have the highest differences in urbanization, and the highest UHI intensities observed. The strength of the SUHI/AUHI linear relationship decreases gradually with the increasing urbanization of the stations' surroundings.

In the scope of the AQMEII Phase 1 project the GEM-AQ model was run over Europe for the year 2006. The modelling domain was defined using a global variable resolution grid with a rotated equator and uniform resolution of 0.2° × 0.2° over the European continent. Spatial distribution and temporal variability of the GEM-AQ model results were analysed for surface ozone and PM₁₀ concentrations. Model results were compared with measurements available in the ENSEMBLE database. Statistical measures were used to evaluate performance of the GEM-AQ model. The mean bias error, the mean absolute gross error and the Pearson correlation coefficient were calculated for the maximum 8 h running average ozone concentrations and daily mean PM₁₀ concentrations. The GEM-AQ model performance was characterized for station types, European climatic regions and seasons. The best performance for ozone was obtained at suburban stations, and the worst performance was obtained for rural stations where the model tends to underestimate. The best results for PM₁₀ were calculated for urban stations, while over most of Europe concentrations at rural sites were too high. Discrepancies between modelled and observed concentrations were discussed in the context of emission data uncertainty as well as the impact of large-scale dynamics and circulation of air masses. Presented analyses suggest that interpretation of modelling results is enhanced when regional climate characteristics are taken into consideration.

This study presents the potential impacts of climate change in 49 Polish cities by analyzing seven climate indicators. The analysis was carried out for the following three horizons: the current climate conditions (an average period spanning 2006 to 2015), near-future conditions (an average period spanning 2026 to 2035), and future conditions (an average period spanning 2046 to 2055). Climate indices were computed with bias-corrected EURO-CORDEX model ensembles from two Representative Concentration Pathway scenarios, RCP4.5 and RCP8.5. The systematic error was reduced using the quantile mapping method with a non-parametric approach of robust empirical quantiles (RQUANT). Data were used as references in the period of current climate conditions, and those required for bias correction consisted of historical ground-based observations provided by the Institute of Meteorology and Water Management. The analysis encompassed various key climate indices, including the annual average temperature, the count of hot days, cold days, and frost days, the cumulative annual precipitation, the frequency of days with precipitation, and instances of extreme precipitation (defined as the days with precipitation exceeding 10 mm/day). These findings reveal a noteworthy rise in the average annual temperature of approximately 1 °C and an uptick in the number of hot days by 3.7 days. Conversely, a decline in the number of cold days by approximately 19 days and frost days by 8 days was observed. Additionally, there was an augmentation in the annual precipitation sum, reaching up to 80 mm in RCP 8.5, accompanied by an increase in the number of days with precipitation (up by 3.3 days) and days with extreme precipitation (up by 2 days).

Open Access Published: 02 December 2016 A 15-Year Analysis of Surface Ozone Pollution in the Context of Hot Spells Episodes over Poland Joanna Struzewska¹ & Maciej Jefimow¹ Acta Geophysica volume 64, pages 1875–1902 (2016)Cite this article 296 Accesses 5 Citations Metrics details Abstract Analysis of summertime temperature characteristics and ozone exposure indexes were carried out for eight locations in Poland for a 15-year period (1997–2011). The number of days with the maximum temperature exceeding 25°C and 30°C was calculated for each year. The analysis covered the 8-hour running average and daily maximum of near surface ozone concentrations. Also, the accumulated exposure when ozone concentrations were above 120 μg/m³ (AOT60) was calculated as a diagnostic indicator of adverse health effects for each year. Although high ozone concentrations are associated with hot temperatures, the exposure to values higher than 120 μg /m³ is correlated with the length of the hot weather period rather than with the occurrence of days with extremely high temperatures. In most cases the elevated ozone concentrations occurred during days when the maximum temperature was higher than 24°C. Episodes of very high ozone concentrations, exceeding 180 μg /m³, were not associated with heat wave periods at analysed locations. Download to read the full article text References Bloomer, B.J., J.W. Stehr, C.A. Piety, R.J. Salawitch, and R.R. Dickerson (2009), Observed relationships of ozone air pollution with temperature and emissions, Geophys. Res. Lett. 36, 9, L09803, DOI: 10.1029/2009GL037308. Camalier, L., W. Cox, and P. Dolwick (2007), The effects of meteorology on ozone in urban areas and their use in assessing ozone trends, Atmos. Environ. 41, 33, 7127–7137, DOI: 10.1016/j.atmosenv.2007.04.061. Article Google Scholar Cardellino, C.A., and W.L. Chameides (1990), Natural hydrocarbons, urbanization and urban ozone, J. Geophys. Res. 95, D9, 13971–13979, DOI: 10.1029/JD095iD09p13971. Article Google Scholar Clark, T.L., and T.T. Karl (1982), Application of prognostic meteorological variables to forecasts of daily maximum one hour ozone concentrations in the northeastern United States, J. Appl. Meteorol. 21, 11, 1662–1671, DOI: 10.1175/1520-0450(1982)0212.0.CO;2. Article Google Scholar Della-Marta, P.M., J. Luterbacher, H. von Weissenfluh, E. Xoplaki, M. Brunet, and H. Wanner (2007), Summer heat waves over western Europe 1880-2003, their relationship to large-scale forcings and predictability, Clim. Dynam. 29, 2–3, 251–275, DOI: 10.1007/s00382-007-0233-1. Article Google Scholar Fiala, J., L. Cernikovsky, F. de Leeuw, and P. Kurfuerst (2003), Air pollution by ozone in Europe in summer 2003. Overview of exceedances of EC ozone threshold values during the summer season April-August 2003 and comparisons with previous years, Copenhagen, European Environment Agency. EEA Topic Report 3/2003. Google Scholar Gawuć, L., M. Jefimow, and J. Strużewska (2013), Impact of aerosol transport from biomass burning on surface ozone episode in Central Europe on 5 of May 2006. In: I National Conference on „Role of aerosols in the climate system”, 25–27 September 2013, Warsaw, Poland. Google Scholar Graczyk, D., and Z.W. Kundzewicz (2014), Changes in thermal extremes in Poland, Acta Geophys. 62, 6, 1435–1449, DOI: 10.2478/s11600-014-0240-7. Article Google Scholar Guenther, A.B., P.R. Zimmerman, P.C. Harley, R.K. Monson, and R. Fall (1993), Isoprene and monoterpene emission rate variability–model evaluations ai]and sensitivity analyses, J. Geophys. Res. 98, D7, 12609–12617, DOI: 10.1029/93JD00527. Article Google Scholar Hodnebrog, Ø., S. Solberg, F. Stordal, T.M. Svendby, D. Simpson, M. Gauss, A. Hilboll, G.G. Pfister, S. Turquety, A. Richter, J.P. Burrows, and H.A.C. Denier van der Gon (2012), Impact of forest fires, biogenic emissions and high temperatures on the elevated Eastern Mediterranean ozone levels during the hot summer of 2007, Atmos. Chem. Phys. 12, 8727–8750, DOI: 10.5194/acp-12-8727-2012. Article Google Scholar Im, U., R. Bianconi, E. Solazzo, I. Kioutsioukis, A. Badia, A. Balzarini, R. Baró, R. Bellasio, D. Brunner, C. Chemel, G. Curci, J. Flemming, R. Forkel, L. Giordano, P. Jiménez-Guerrero, M. Hirtl, A. Hodzic, L. Honzak, O. Jorba, C. Knote, C. Kuenen, J.P. Jeroen, P.A. Makar, A. Manders-Groot, L. Neal, J.L. Pérez, G. Pirovano, G. Pouliot, R. San Jose, N. Savage, W. Schroder, R.S. Sokhi, D. Syrakov, A. Torian, P. Tuccella, J. Werhahn, R. Wolke, K. Yahya, R. Zabkar, Y. Zhang, J. Zhang, C. Hogrefe, and S. Galmarini (2015), Evaluation of operational on-line-coupled regional air quality models over Europe and North America in the context of AQMEII phase 1: Part I: Ozone, Atmos. Environ. 115, 404–420, DOI: 10.1016/j.atmosenv.2014.09.042. Article Google Scholar Im, U., K. Markakis, A. Poupkou, D. Melas, A. Unal, E. Gerasopoulos, N. Daskalakis, T. Kindap, and M. Kanakidou (2011), The impact of temperature changes on summer time ozone and its precursors in the Eastern Mediterranean, Atmos. Chem. Phys. 11, 8, 3847–3864, DOI: 10.5194/acp-11-3847-2011. Article Google Scholar Jacob, D.J., J.A. Logan, G.M. Gardner, R.M. Yevich, C.M. Spivakovsky, S.C. Wofsy, S. Sillman, and M.J. Prather (1993), Factors regulating ozone over the United States and its export to the global atmosphere, J. Geophys. Res. 98, D8, 14817–14826, DOI: 10.1029/98JD01224. Article...