Is the coarse-grid Global Climate Model a useful tool for regional paleoclimate reconstruction?

This study considers the climate at the time of the Weichselian ice sheet maximum in Central Europe, especially in Poland, in respect of the NASA Educational version of Global Climate Model (EdGCM). The final results of the EdGCM simulations for the Last Glacial Maximum (LGM) are presented here and these have been analysed to determine whether or not they are useful for regional scale modelling; the problem being that, in a global climate model, both horizontal and vertical grid resolution is very low. Also, an attempt has been made to define the role of the ice megalobe which, in terms of the numerical coarse-grid model,covered the northern parts of Germany and Poland. The broad details of the climate during the Weichselian are defined and our results are compared with previous opinion. The influence of ice megalobe on regional climate is demonstrated and it is also concluded that a coarse-grid global climate model could be a helpful tool in a regional climate recognition. However, whether at a regional or local scale, it is recommended that a specially-configured version of a Regional Climate Model (RCM) based on Global Climate Model (GCM) boundary conditions be used in similar reconstructions

The impact of global warming on lake surface water temperature in Poland - the application of empirical-statistical downscaling, 1971-2100

The paper presents historical (1971-2015) and scenario-based (2006-2100) changes in surface water temperatures in 10 lakes of Poland. The analysis of historical measurement (1971-2015) showed that mean annual lake surface water temperature (LSWT) was characterised by an increasing tendency by 0.37°C∙dec-1 on average, and was higher by 0.01°C∙dec-1 than air temperature in the analogical period. The highest increase in LSWT was recorded in spring months (April, May) and in summer (July). The future changes in LSWT was based on simulations of 33 AOGCMs available in the scope of CMIP5 project for RCPs: 2.6, 4.5, 6.0, and 8.5. The developed empirical-statistical downscaling models (ESD) use the air temperature field as predictors, with consideration of autocorrelation for two preceding months. ESD models are characterised by high quality of reconstruction of water temperatures in the historical period, with correlation from 0.82 (December, February) to 0.93 (July). The future CMIP5 scenarios for the period 2006-2100 assume an increase in air temperature at the end of the 21st century from +1.8°C (RCP 2.6) to +5.1°C (RCP 8.5) in reference to the period 1971-2005. According to the downscaling models, this corresponds to an increase in water temperature in the analysed lakes ranging from +1.4°C (RCP 2.6) to +4.2°C (RCP 8.5) in the years 2081-2100, respectively, with evident variability between the adopted emission paths beginning from the period 2041-2060. At a monthly scale, water temperature will increase the slowest in February (2081-2100: RCP 2.6 = +0.5°C, RCP 8.5 = +1.8°C). The highest increase in temperature will occur from May to August (RCP 8.5 = +6°C in June). Substantial effects of transformations of the thermal regime are already observed today, e,g. in the reduction of the ice season length. According to developed scenarios, a further considerable increase in water temperature will be the primary factor determining the transformation of lake ecosystems. The obtained results provide a theoretical basis for further research conducted in the scope of many disciplines, among others hydrology, hydrobiology, ecology, water management, energy production, etc. In the case of Poland, issues related to low water resources per capita are particularly important. Contemporary studies concerning changes in water resources showed that the natural factor playing the key role in their reduction is temperature increase and therefore it should constitute for the possibly fast development of multidisciplinary concepts of mitigation policy to potential impact of climate change

Comparison of thermal classifications for selected regions of Poland

W pracy porównano dwie najczęściej stosowane w Polsce metody klasyfikacyjne w zakresie warunków termicznych, tj. klasyfikację termiczną według Lorenc, opartą na wartościach odchylenia standardowego, oraz kwantylową klasyfikację termiczną. Do celów wieloaspektowej analizy statystycznej wykorzystano uśrednione obszarowo wartości średniej temperatury powietrza z miesięcy, sezonów i lat z okresu 1951-2008. Przedstawiono dysproporcje między rezultatami klasyfikacji, które wynikają z przyjętych w nich założeń metodycznych, wpływając m.in. na stosowany zakres skali oraz na ich „czułość”, w zależności od rozdzielczości czasowej danych i długości okresu referencyjnego. Sprawdzono pod kątem statystycznym słuszność przyjętych założeń, a także określono zależności występujące między obiema klasyfikacjami

Synoptic conditions governing upwelling along the Polish Baltic coast

The study analyses atmospheric feedback to the occurrence of upwelling along the Polish Baltic coast. Upwelling events were identified on the basis of daily mean sea surface temperature (SST) maps from the period 1982–2010 derived from the NOAA OI SST V2 High Resolution Dataset. Synoptic conditions favourable to the occurrence of upwelling were determined on the basis of the NCEP/NCAR reanalysis data. On average, there are approximately 23 days with upwelling each year along the Polish Baltic coast, which account for approximately 13

Točnost prognoza temperature zraka dobivenih odabranim kratko- i dugoročnim numeričkim modelima prognoze vremena iznad Poljske

The article discusses the results of air temperature forecasts from four short-term and two long-term forecasts of numerical weather prediction models. The analysis covered the results of model simulations from January 2015 to January 2016 and compared them at 14 meteorological stations in Poland. The comparison was made based on the most commonly used measures for continuous parameters i.e., ME (mean error), MAE (mean absolute error), RMSE (root mean square error), MSE (mean square error), BIAS and Pearson correlation. In the short time horizon, the best results in the context of the MAE, RMSE, MSE and correlation values were obtained by the Unified Model, although the diagnosed differences between the models are small. All models in the 0–72 h projection horizon reached a correlation of 0.95–0.97 and an MAE in the range of 1.5 °C to 2.1 °C. In the case of long-term forecasts, the HIRLAM model was slightly better than the GFS model. Clearly, in both cases, there is a marked decrease in quality after the fourth and in the following forecast lead days.U članku se razmatraju rezultati prognoze temperature zraka pomoću četiri kratkoročna i dva dugoročna numerička modela prognoze vremena. Analiza je obuhvatila rezultate simulacija modela od siječnja 2015. do siječnja 2016., koji su uspoređeni s podacima 14 meteoroloških postaja u Poljskoj. Usporedba je izrađena na temelju najčešće korištenih mjera za kontinuirane parametre, tj ME (srednja pogreška), MAE (srednja apsolutna pogreška), RMSE (korijen srednje kvadratne pogreške), MSE (srednja kvadratna pogreška), BIAS i Pearsonova korelacija. Za ovako kratak vremenski interval, u kontekstu vrijednosti MAE, RMSE, MSE i korelacije, najbolji rezultati dobiveni su ujedinjenim modelom, iako su utvrđene razlike među modelima male. Svi modeli su u prognostičkom vremenu od 0 do 72 h dostigli korelaciju od 0,95 do 0,97 i MAE u rasponu od 1,5 °C do 2,1 °C. U slučaju dugoročnih prognoza model HIRLAM bio je nešto bolji od GFS modela. Jasno je da u oba slučaja dolazi do znatnog smanjenja kvalitete nakon četvrtog i sljedećih prognostičkih dana

Initial assessment of the Weather Research and Forecasting model for forecasting bioclimatic conditions during breeze circulation – case study of the Słowiński National Park

Land-sea interaction at the Polish Baltic Coast impacts the specific local climate conditions. Thermally driven circulation, observed mainly in the summer season, causes the advection of the cool sea air over land and influences the local atmospheric environment, including bioclimatic conditions. The aim of this paper is to present the evaluation of the WRF model for forecasting sensitive bioclimatic conditions on a selected day with sea breeze in the vicinity of the Łeba Sandbar (the Słowiński National Park). The results obtained from a numerical weather prediction model were post-processed to calculate the daily variability of two biothermal indices: the Effective Temperature (ET) and the Dry Cooling Power (H). To evaluate the thermal comfort of a person wearing typical clothes, the Michajlow’s, Petrovič and Kacvińsky’s scales were adopted. A detailed analysis performed for 31st July 2010 shows in most cases a satisfactory level of agreement between the simulated data and the in-situ measurements for nested domains with horizontal grid resolution less than 2 km. However, the simulation results tend to underestimate the thermal comfort, especially in the middle part of the Łeba Sandbar due to terrain data misrepresentations, which results in the overestimation of wind speed

Creating wind field time-series over the Southern Baltic area using a dynamical downscaling approach

The aim of the research is to explore the possibility of using the Weather Research and Forecasting Model 3.2.1 (WRF) for creating synthetic wind speed time-series in the southern part of the Baltic Sea. The hourly wind speed time series derived from a mesoscale model were forced by the NCEP/NCAR re-analysis dataset for the period of 1991?2000 using 2-way nesting domains with horizontal resolutions of 27 and 9 km. Realism of spatial and temporal structure of the dataset was validated against in-situ offshore and onshore measurements. The dataset confirms the wind speed patterns over the Baltic Sea obtained in previous studies. The validation procedure proves that the model represents the spatio-temporal structure of the wind field well with a temporal correlation of around 0.80 for those stations with an undisturbed, high quality archive dataset. It was found that the model tends to underestimate wind speeds over offshore areas and overestimate them over onshore areas, especially for the near-surface wind field. Additionally, the author briefly presents the transition of wind speed in coastal areas as they are of great interest to the renewable energy community

Numerical modeling techniques for local wind field recognition over the Słowiński National Park

Wydział Nauk Geograficznych i GeologicznychRozprawa jest obszernym i dogłębnym opracowaniem z zakresu modelowania numerycznego, dotyczącym rozpoznania lokalnych warunków anemologicznych na obszarze Słowińskiego Parku Narodowego. Głównym celem postawionym przez autora rozprawy było przedstawienie możliwości zastosowania technik modelowania numerycznego pod kątem rozpoznania lokalnego pola wiatru z uwzględnieniem elementów cyrkulacji lokalnej. Dokonano szczegółowej analizy klimatologicznej pola wiatru w różnych skalach czasowych i przestrzennych, z uwzględnieniem specyficznych elementów lokalnego pola wiatru (występowanie cyrkulacji bryzowej i jej cyrkulacyjne uwarunkowania, prawdopodobieństwo występowania ekstremalnych prędkości wiatru w porywie, wzrost prędkości wiatru w strefie brzegowej). W pracy wykorzystano numeryczny mezoskalowy model pogody WRF (Weather Research and Forecasting Model) wykorzystujący wyidealizowane warunki brzegowe w postaci reanaliz meteorologicznych NCEP/NCAR oraz mikroskalowy, matematyczno-fizyczny model pola wiatru WASP (Wind Atlas Analysis and Application Program). Znaczną część pracy poświęcono weryfikacji rezultatów symulacji mezoskalowych, co miało na celu określenie zarówno zakresu pojawiających się błędów, jak i oszacowanie marginesu niepewności symulacji w różnych skalach czasowych.This PhD thesis is an extensive and profound analysis concerning local wind field recognition over the Słowiński National Park by the use of a numerical modeling techniques. The main of this thesis was to present application of dynamical downscaling techniques for wind field recognition with focus on its specific aspects. Dynamical downscaling for the period 1991-2000 was performed by application of the Advanced Research core of the Weather Research and Forecasting (WRF) model version 3.2.1. Simulations were forced by boundary and initial conditions derived from NCEP/NCAR re-analysis data. Further downscaling was performed by the microscale „WasP” model (Wind Atlas Analysis and Application Program). Detailed climatological analysis was made concerning different spatio-temporal scales. The uniqueness of local wind field was proved by presenting climatalogical analysis of sea-breeze occurrence. Additionally the detection and probability analysis of extreme wind speeds, and a description of the increase of wind speed in the coastal zone was done