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1

Characteristics of seasonal changes of the Baltic Sea extreme sea levels

Wolski Tomasz, Wiśniewski Bernard

Oceanologia

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2023

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Vol. 65 (1)

151--170

EN

This work analyses the monthly spatial distribution of extreme sea levels in the Baltic Sea as well as the relationship of these levels with the NAO and AO indicators. The research was based on hourly sea level data from the 45 tide gauge stations gathered in the years 1960 to 2020. The analysis shows that the duration of extreme sea levels tends to increase moving from along the line joining the open sea and the gulf end. This is associated with the narrowing of the gulf and the geomorphological and bathymetric configuration of the coastal zone. The duration of high and low sea levels in the Baltic Sea decreases from a maximum in January to a minimum in the months of May to August, then it increases again until the end of the year. This cycle corresponds well to the annual occurrence of storm surges, which are affected by the annual changes in atmospheric circulation. The impact of the variations of the circulation on extreme sea levels was confirmed by examining the relation between maximum, minimum and mean levels of the Baltic waters and the zone circulation indices NAO and AO for each month of the year and the seasons in the multiyear period 1960–2020. The results indicate that the strongest correlations exist between sea levels and NAO/AO in the winter months. There is a spatial differentiation of the correlation and its increase from the southwest to the northeast in Baltic Sea.

2

Annual and semi-annual variations of TEC over Nepal during the period of 2007–2017 and possible drivers

Ghimire Basu Dev, Gautam Bibek, Chapagain Narayan P., Bhatta Karan

Acta Geophysica

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2022

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Vol. 70, no 2

929--942

EN

The total electron content (TEC) variation of the ionospheric layer is mostly controlled by Geomagnetic and solar activity. The TEC of the ionosphere can be estimated using the satellite signal delay recorded at GPS sites. In this study, the TEC data from three nearby GPS stations (CHLM, BMCL, and LMJG) from Nepal are extracted for about 11 years period (2007–2017). For the computation of the TEC data, wavelet transform, global wavelet power spectrum, cross wavelet trans form, and wavelet coherence techniques are used. Utilizing such long-term GPS TEC data, Annual Oscillation (AO) and Semi-annual Oscillation (SAO) are identified in the daytime and nighttime TEC over Nepal. The SAO is found to be dominating periodicity in the daytime TEC, whereas the AO is found to dominant at night. In addition, possible connections with the indicators of geomagnetic and solar activity were studied. The geomagnetic indices AE and AU are exhibit a change in phase and are most consistent with both daytime and nighttime AO, implying that these indices could be the likely drivers of TEC’s AO and SAO periodicities. The Dst index, on the other hand, is recognized as the most prominent driver of SAO in both daytime and nighttime TEC.

3

Treatment and utilization of the concentrate from membrane separation processes of landfill leachates

Nowak Rafał, Włodarczyk-Makuła Maria

Civil and Environmental Engineering Reports

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2020

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Vol. 30, no. 2

92--104

EN

The purpose of the paper was to assess the effectiveness of selected physico-chemical processes to improve the quality of retentates/concentrates obtained during the treatment of landfill leachates using membrane separation. Among the physico-chemical methods, Advanced Oxidation Process (AOP) and electrocoagulation were analysed. Landfill leachate resulting from the infiltration of waste mass by atmospheric precipitation as well as the dissolution and leaching of waste components are most often subjected to membrane separation. Permeate is usually discharged to the receiver, while the concentrate is recirculated and sprinkled on a waste pile. However, such action is only the retention of impurities in the body of the landfill and has an impact on the chemistry of raw leachates. Due to the very high concentrations of organic and inorganic compounds identified in the retentate, it is necessary to treat it, which will effectively reduce the amount of impurities in the leachate. Economic use seems to be another solution. An example would be growing energy crops but such application requires additional research.

4

The atmospheric circulation patterns during dry periods in Lithuania

Rimkus E., Kažys J., Valiukas D., Stankunavičius G.

Oceanologia

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2014

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No. 56 (2)

223--239

EN

This paper reveals the atmospheric circulation patterns during dry periods in Lithuania.~The research covers the period from 1961 to 2010. Atmospheric circulation features were analysed using the Hess and Brezowski classification of macro-circulation forms, NAO and AO indices, a 500 hPa geopotential height field and the Tibaldi-Molteni blocking index. Different phases of the dry period (developing, persisting and attenuation) were evaluated individually. Also, the regional differences of dry period formation were investigated. In general dry periods are determined by a decrease in zonal and an increase in meridional circulation forms as well as the atmospheric blocking process over the Baltic region longitudinal belt 0-20 days prior to the start of the dry period. An especially strong shift from general circulation patterns are observed during the developing phase of a dry period. Drought persistence in the Baltic region is almost always predetermined by strong anticyclonic circulation. Most drought development stages are associated with negative NAO/AO phases.

5

Występowanie dni z przejściem temperatury powietrza przez 0°C na wybranych stacjach w atlantyckim sektorze Arktyki

Łupikasza E., Niedźwiedź T., Małarzewski Ł.

Problemy Klimatologii Polarnej

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2013

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Nr 23

121--135

PL

Opracowanie dotyczy ważnego wskaźnika współczesnych zmian klimatu – dni z przejściem temperatury powietrza przez 0°C, które wyróżniono na podstawie temperatury dobowej maksymalnej i minimalnej mierzonej na 4 wybranych stacjach w obrębie atlantyckiego sektora Arktyki w okresie regularnych pomiarów instrumentalnych. Analiza częstości występowania tych dni w kolejnych miesiącach wskazuje na ich bimodalny przebieg roczny z maksimum w maju lub czerwcu, a minimum w lipcu lub sierpniu. Obliczona metodą Mann- Kendalla istotność tendencji wykazała spadek częstości występowania dni z Tmax>0°C i Tmin<0°C w miesiącach z cieplejszej części roku oraz w grudniu. Czasowe zmiany występowania tych dni zależą od lokalnej cyrkulacji atmosfery – najsilniej od napływu powietrza z południa, który w lecie przyczynia się do spadku, zaś w zimie do wzrostu ich frekwencji.

EN

This study aims at determining the occurrence of days with freeze-thaw events at selected meteorological stations (Svalbard Lufthavn, Hornsund, Hopen, Bjørnøya) representing the Atlantic sector of the Arctic, recognizing the trends in the frequency of these days and their relation to atmospheric circulation. The days with freeze-thaw events (TD0) were selected on the basis of daily minimum and maximum air-temperature during the period of regular instrumental measurements conducted at particular stations – Hopen: November 1946 – March 2013, Bjørnøya: January 1946 – March 2013, Svalbard Lufthavn: January 1957 – March 2013, Hornsund: July 1978 – March 2013. Basic descriptive statistics were used to investigate the annual course of the days with freezethaw events (Tmax>0°C and Tmin<0°C) occurrence in the period 1979-2012 which allowed the comparison of the statistics between the stations. Statistical significance of trends were checked with Mann-Kendall test whereas the trends magnitudes were calculated with the least square method and expressed as a change in the number of days per 10 years. Spearman correlation coefficients were calculated to assess the relations between the DT0 occurrence and atmospheric circulation. Three local circulation indices (S index, W index, C index) and one macroscale circulation index (AO index) were taken into consideration. Statistical significance level of 0.05 was used for both trends and correlations coefficients. The trends were calculated for three various periods: the period of regular instrumental measurements – various at particular stations, the period 1979-2012 – common for all stations analysed and 1995-2012 which is the period of dramatic warming of the Arctic (Przybylak 2007). The investigations were conducted from monthly, seasonal (winter – Dec, Jan, Feb; spring – Mar, Apr, May; summer – Jun, Jul, Aug; autumn – Sep, Oct, Nov) and annual perspective. Days with freeze–thaw events are considered as an indicator of current climate change primarily manifesting in the rapid increase of air-temperature. The average annual number of days with freeze-thaw events varied depending on station from 63 days to 96 days in the period of 1979-2012. These days occurred during the whole year with the maximum in autumn (Svalbard Lufthavn, Hornsund and Hopen) or spring (Bjørnøya) and the minimum in summer (Svalbard Lufthavn, Hornsund, Bjørnøya) or winter (Hopen). The annual course of the number of days with freeze-thaw events is bimodal with the first rate maximum in May (Svalbard Lufthavn, Hornsund, Bjørnøya) or June (Hopen) and the secondary maximum in October. The clearest changes (increase) in the frequency of DT0 occurrence were found in Hopen and Bjørnøya in the months belonging to the warmer part of a year – July, August, September. In Svalbard Lufthavn and Hornsund significant increase in the frequency of DT0 was detected in June. In December increasing trends in the DT0 occurrence were significant which also applies to January DT0 trends at both Longyearbyen and Bjørnøya stations. Dramatic increase of the air-temperature in the Arctic which began in the middle of the nineties has not influenced the frequency of days with freeze-thaw events – the trends calculated for the period of 1995-2012 were significant only in September and sporadically (single stations) in May and December. The long-term variability in the number of days with freeze-thaw events was significantly related to atmospheric circulation. The occurrence of such days was most influenced by the S circulation index, which determined the frequency of DT0 in majority of months and seasons despite summer. At the beginning of a year (February – March) the frequency of DT0 depended most on the flow of air from west (W circulation index). The cyclonity index (C index) affected the number of DT0 at Hopen and Bjørnøya stations. The impact of macroscale circulation (AO index) on the variability of DT0 was limited to Bjørnøya station in the case of monthly values and covered Hopen station in the case of seasonal values. Statistically significant correlation coefficients calculated for the warmer part of a year (from June to September) were positive and were negative for the rest months. Significant decrease of the DT0 frequency in September might be related to the strengthening of the northern flow.

6

O "arktycznych" i "atlantyckich" mechanizmach sterujących zmiennością temperatury powietrza na obszarze Europy i północo-zachodniej Azji

Marsz A. A., Styszyńska A.

Problemy Klimatologii Polarnej

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2006

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nr 16

47-89

PL

Praca omawia wpływ zmian ciśnienia atmosferycznego w Arktyce Atlantyckiej (dalej AA) na kształtowanie zmienności temperatury powietrza na obszarze Europy (na N od 40°N) i NW Azji (do 120°E). Wpływ zmian ciśnienia w AA na temperaturę powietrza zaznacza się we wszystkich, z wyjątkiem czerwca, miesiącach roku, tworząc charakterystyczny cykl z maksimum siły oddziaływania zimą. Zimowe (01-03) zmiany ciśnienia w AA objaśniają od kilkunastu do ponad 60% zmienności temperatury rocznej (z maksimum na obszarze wokół-bałtyckim; 1951-2000). W pracy analizuje się współdziałanie zmian ciśnienia w Arktyce Atlantyckiej ze zmianami ciśnienia w Wyżu Syberyjskim w kształtowaniu zmienności temperatury powietrza na obszarze Europy i NW Azji. Dyskutuje się również kwestie związków zmian ciśnienia w AA z NAO, AO oraz frekwencją makrotypów cyrkulacji środkowotroposferycznej wg klasyfikacji Wangengejma-Girsa. Wyniki analiz wykazują, że o zimowych zmianach ciśnienia w AA decyduje wcześniejszy rozkład zasobów ciepła w wodach Atlantyku Północnego.

EN

The research on relations between climatic elements of Europe and the Arctic has indicated that there are significant correlations between changes in atmospheric pressure in the Atlantic part of the Arctic and air temperature in northern Europe and NW Asia. The strongest correlations are observed between changes in pressure over relatively small area of the Atlantic part of the Arctic (72.5 - 80.0°N, 10.0 - 25.0°E), in addition, the point over which changes in pressure explain most of changes in air temperature is located 75.0°N, 015.0°E. Pressure at this point is further referred as P[75,15] with an index denoting a month (e.g. P[75,15]03 denotes mean pressure in March and P[75,15]01-03 defines mean pressure at this point from the period January till March). Over the Atlantic part of the Arctic within the pressure area there is no marked climatic centre which could be regarded as the centre of atmospheric activity. The research made use of monthly series of SLP values (reanalysis: set NOAA.NCEP-NCAR. CDAS-1.MONTHLY.Intrinsic.MSL.pressure) and the values of monthly air temperature from 211 stations (Fig. 1). The observational period common for both elements covers 50 years, i.e. the period from January 1951 to December 2000. The character of correlations between P[75,15] and air temperature in the following months, from June to May, and their spatial distribution have been presented by isocorrelates maps (Fig. 2). Changes in the strength of correlations between P[75,15] and the temperature over Europe and NW Asia form a clear annual cycle interrupted in June. In June the correlations between P[75,15] and air temperature became very weak and not significant over the most of the area and not continuous in space. During the months after June these correlations got stronger and stronger reaching their maximum during cold season (from November to April). This maximum is located in the region adjacent to the Baltic Sea, where annual and winter (01-03) changes in P[75,15] explain from more than 60% to 50% of annual temperature variances (Fig. 3) The strongest correlation between P[75,15] and air temperature in Siberia is located N of Baikal, where winter (01-03) changes in P[75,15] explain 43-45% of annual temperature variances. At the end of the cold season a visible delay of the decrease in the strength of correlation is observed in the region of Siberia in relation to the European region (in Europe after March, in Siberia after April). Variability in winter and annual values of pressure at 75°N, 015°E also indicates relatively strong correlations with the changeability in temperature of the warmest month in the year in the west and central region of Europe. The annual variability in P[75,15] explains from 40% to 30% changeability of maximum temperature in the region extending from the Atlantic coast of France to central Germany. This belt extends farther east towards the Baltic Sea. The latter correlation has not been explained in this work. The analysis of correlations of changes in pressure at 75°N, 15°E with NAO indicates to the occurrence of statistically significant correlations during months of cold season in the year (October - March, May and June; Tab. 2). Similar analysis of correlations of changes in P[75,15] with AO index (Arctic Oscillation) shows strong and highly statistically significant correlations in all months of the year with maximum falling in January and February. Annual changes in P[75,15], i.e. in pressure at one point explain 73% annual changeability in AO index (r = 0.86) and the winter changeability in (December - March) P[75,15] explains 78% of winter changeability in AO index (r = 0.88) which is the first vector EOF of pressure field (1000 hPa) covering the area from 20°N to the North Pole (90°N), that is the most area of the Northern Hemisphere. This analysis shows that the changes in pressure at the point 75°N, 15°E result in intensification of cyclogenesis over west and central part of the North Atlantic and the consequent long waves (waves of W type following Wangengejm-Girs classification) cause that anticyclones formed over the Atlantic will direct towards Fram Strait through the region of Iceland. The above process has nothing or almost nothing to do with the form of changeability in polar strato-spheric eddy, as assumed by Tomphson and Wallace (1998, 2000, Thompson, Wallace, Hegerl 2000) to be essential for the Arctic Oscillation functioning. Occurrence of correlations between P[75,15] and air temperature over vast areas from 10°W to 130°E suggests that also changes in pressure in the Siberian High are engaged in this process. Theanalysis shows that in a yearly process, changes in pressure in the Atlantic part of the Arctic and in the Siberian High occur in opposite phases (see Tab.1). Barometric gradient between the Atlantic part of the Arctic and the Siberian High becomes extremely strong during the cold season of the year contributing to "pumping" air from eastern Europe to the far end of the Siberia. During the summer season the gradient becomes very weak as the about-turn takes place. The cooperation of changes in pressure in the Atlantic part of the Arctic and pressure in region located farther Baikal -- Mongolia results in very strong oscillation which partly can be identified with Euro-Asian Oscillation (Monahan et al. 2000). During winter season interannual changes in pressure in the Siberian High are relatively small and explain 10.4% variances of barometric gradient between P[75,15] and point 45°N, 110°E (the region of the centre of the Siberian High), whereas the interannual changes in P[75,15] explain 77.5% of variances in this gradient. This means that in the cold season of the year the intensity of air transfer from the west towards Asian land depends on variability in pressure in the Atlantic part of the Arctic. Because in the months of the cold season of the year NAO is the strongest and significantly correlated with changes in P[75,15] therefore, a two-element, with the same phase "conveyor belt" is formed, which during positive phases of NAO transfers the air from over the Atlantic to Europe (NAO) and then towards and into the Siberia (Euro-Asian Oscillation). P[75,15] during cold season months of the year (01-03) indicates statistically significant negative trend (-0.153 hPa/year; p < 0.006) which enables to state that the observed, over the years 1951-2000, increase in air temperature in the Siberia can be, in great extent, attributed to the activity of the above described circulation mechanism. The analysis of reasons for interannual changes in P[75,15] has indicated that there are strong and significant correlations between variability in P[75,15] and the earlier variability in the thermal conditions of the Atlantic Ocean. A very important role in this relation plays thermal condition of three sea areas, i.e. waters of the subtropical region of central part of the North Atlantic (characterized by SST anomalies in grid 34°N, 40°W from August and September), waters of the middle latitudes zone of the central part of the North Atlantic (characterized by SST anomalies from August and September in grid 54°N, 30°W) and waters of the North Atlantic Current from the approach to the Farero-Shetland Passage (characterized by SST anomalies from January and April in grid 60°N, 10°W). Thermal state of these three sea water areas (see formulas [1] and [2]) explains 58% changeability in P[75,15] which will be observed in the following winter (DJFM). The cause of the described correlation is attributed to the fact that the earlier thermal state of the above mentioned sea areas controls the occurrence of long waves, of W and E Wangengejm-Girs type during the following winter. Further, these waves influence the occurrence of low cyclones over the Atlantic part of the Arctic during winter resulting in adequate changes in mean monthly pressure. As a result, it can be stated that the interannual variability in air temperature over vast areas of Europe and over NW Asia is influenced by the processes observed over the North Atlantic and the Atlantic part of the Arctic. The research covers years 1971-2003 (ano-malies in SST taken from 1970-2002) due to the fact that the data have been not only accessible and reliable but also homogeneous with respect to climatological data of SST (CACSST data set (Reynolds and Roberts 1987, Reynolds 1988) and SST OI v.1. (Reynolds et al. 2002).