Projections of changes in maximum air temperature and hot days in Poland

Tomczyk, Arkadiusz M.; Piniewski, Mikołaj; Eini, Mohammad Reza; Bednorz, Ewa

doi:10.1002/joc.7530

Cited by 19 publications

(6 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The only unexpected results were the decreasing the number of hot days and increasing number of frost days for near-future period under the SSP5–8.5 scenario (Tables S2 , S3 ). In general, there is good agreement between our results and previous studies that confirm that the number of hot and frosty days will, respectively, increase and decrease under RCP8.5 scenarios from the CMIP5 simulation for the far-future period 10 , 60 . However, the number of hot days in the near-future period in this research will slightly decrease and the number of frosty days increased in the same period and scenario.…”

Section: Discussionsupporting

confidence: 90%

Projection of climate change impacts on extreme temperature and precipitation in Central Poland

Ghazi,

Przybylak,

Pospieszyńska

2023

Sci Rep

View full text Add to dashboard Cite

Climate change is exacerbating the risk of the occurrence of extreme weather. This study has projected the change in mean and extreme climate conditions in Central Poland during near-future (2026–2050), mid-term (2051–2075), and far-future (2076–2100) periods under two climate-change scenarios in six General Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6). The results showed that, compared to the historical reference period (1990–2014), Central Poland will experience an increase in temperature and precipitation by the end of the twenty-first century. It is expected that the mean annual temperature and mean annual precipitation totals will increase by 1–4.8 °C and 2–7.5%, respectively. Furthermore, it is projected that the average number of hot, very hot days and extremely hot days (Tmax > 25 °C, > 30 °C, and > 35 °C), tropical nights (Tmin > 20 °C), and extremely high daily precipitation (> 10 mm, > 20 mm and > 30 mm) will also increase, while the average number of slight frost days (Tmin < 0 °C), and frost and severe frost days (Tmax < 0 °C, Tmax < − 10 °C) will decline on average by the end of the twenty-first century. Therefore, it is essential for policymakers to take some appropriate measurements and strategies in advance to strengthen resilience to extreme climate events.

show abstract

Section: Discussionsupporting

confidence: 90%

Projection of climate change impacts on extreme temperature and precipitation in Central Poland

Ghazi,

Przybylak,

Pospieszyńska

2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Research by Tomczyk et al (2022) showed an increase in maximum air temperatures in summer seasons (analyses were conducted from 1966 to 2020). The authors observed that the most intense temperature changes occurred in the last two decades (after 2000) and predicted a further increase in maximum temperature, which is consistent with our observations.…”

Section: Resultsmentioning

confidence: 99%

Variability of Air Temperature in Skierniewice, Poland, Over the Period 1923–2022

Treder,

Tryngiel-Gać,

Klamkowski

et al. 2024

Journal of Horticultural Research

View full text Add to dashboard Cite

The study aimed to determine the magnitude of changes in air temperature in Skierniewice, Poland, over the last 100 years, with particular emphasis on multi-year variability. The source material for the analyses were air temperature measurements from 1923 to 2022 obtained from the meteorological station in the Experimental Field of the Warsaw University of Life Sciences and the station in the Experimental Orchard of the National Institute of Horticultural Research. The study presents average annual, minimum, and maximum air temperatures along with an assessment of the trend of their multi-year variability. The features of changes in the average air temperature in Skierniewice presented in the study based on a 100-year series of meteorological measurements are characterized by high temporal variability with a clear upward trend. The average warming rate over 100 years was 0.17 °C per 10 years, but in the last 60 years it has already reached 0.38 °C per 10 years. In the case of the average annual air temperature since 1981, there has been a sequence of years warmer than average throughout the measurement period. The number of summer days (>25 °C) and hot days, when the maximum temperature exceeds 30 °C, is also increasing. In the analyzed period, the decade 2013–2022 was the warmest.

show abstract

“…This knowledge is particularly important in the context of management of water resources, which in the case of lakes are easily available and commonly used in different sectors of the economy. Considering unfavourable forecasts of climatic changes (Piccolroaz et al, 2021; Tomczyk et al, 2022), the near future may bring a situation involving hierarchisation of demand for water. The occurrence of broadly defined drought is already a frequent phenomenon in Poland (Jaagus et al, 2022; Karamuz & Romanowicz, 2021; Somorowska, 2022).…”

Section: Discussionmentioning

confidence: 99%

Daily water‐level forecasting for multiple polish lakes using multiple data‐driven models

Ptak

et al. 2022

Geographical Journal

View full text Add to dashboard Cite

Water level in lakes fluctuates frequently due to the impact of natural and anthropogenic forcing. Frequent fluctuations of water level will impact lake ecosystems, and it is thus of great significance to have a good knowledge of water-level dynamics in lakes. However, forecasting daily water-level fluctuation in lake systems remains a tough task due to its non-linearity and complexity. In this study, two deep data-driven models, including gated recurrent unit (GRU) and long short-term memory (LSTM), were coupled with attention mechanism for the forecasting of daily water level in lakes for the first time. Daily water-level times series in five lowland lakes in Poland were used to evaluate the models. Root mean squared error (RMSE) and mean average error (MAE) were used for the evaluation of model performance. The modelling results were compared with the traditional feed-forward neural networks (FFNN), GRU, LSTM, and zero-order forecast. The modelling results showed that sequential deep learning models do not outperform feed-forward models in all cases. In most cases, LSTM with attention mechanism (average RMSE = 0.88 cm, average MAE = 0.69 cm) outperforms GRU with attention mechanism (average RMSE = 1.00 cm, average MAE = 0.81 cm). However, attention mechanism did not help to improve the accuracy of the GRU and LSTM for most cases. Based on the average performance in different lakes, GRU performs the best among the deep learning models (average RMSE = 0.84 cm, average MAE = 0.66 cm).Zero-order forecast models perform better than deep learning models for predicting tomorrow (average RMSE = 0.71 cm, average MAE = 0.39 cm), while deep learning models perform better as the horizon of prediction increases.

show abstract

Projections of changes in maximum air temperature and hot days in Poland

Cited by 19 publications

References 46 publications

Projection of climate change impacts on extreme temperature and precipitation in Central Poland

Projection of climate change impacts on extreme temperature and precipitation in Central Poland

Variability of Air Temperature in Skierniewice, Poland, Over the Period 1923–2022

Daily water‐level forecasting for multiple polish lakes using multiple data‐driven models

Contact Info

Product

Resources

About