Wyniki wyszukiwania - BazTech

1

Seawater temperature changes in the southern Baltic Sea (1959–2019) forced by climate change

Zalewska Tamara, Wilman Bartłomiej, Łapeta Bożena, Marosz Michał, Biernacik Dawid, Wochna Agnieszka, Saniewski Michał, Grajewska Agnieszka, Iwaniak Michał

Oceanologia

|

2024

|

Vol. 66 (1)

37--55

EN

The study included the analysis of changes in sea surface and water column temperature and air temperature in the years 1959–2019 in the southern Baltic Sea based on in situ measurement (CTD probe), satellite data, and model data (ERA5). SST increased on average by 0.6°C per decade. Analyses at different depths showed that the highest temperature increase per decade at 0.60–0.65°C characterised the layers from 0 to 20 m. The smallest increase (0.11°C) was recorded at a depth of 70 m, below which the temperature change per decade increases again to 0.24°C. The results from satellite observations covering 1982–2019 were consistent with measurement data. The most intense water warming occured in the spring – summer (0.8–1°C per decade); in the winter, the change did not exceed 0.2°C. In the offshore area, in 1951–2020, air temperature increased by approx. 2°C, with an average increase of 0.37°C per decade. The average increase in seawater temperature in the coastal zone was 0.2°C per decade. The most intense warming characterised March to May (0.25–0.27°C). The average annual air temperature increase on the coast from 1951 to 2020 was 0.34°C per decade. The results represent an important contribution to research and prediction of changes in the marine environment caused by global climate change.

2

Strong Negative Indian Ocean Dipole Phenomenon in 2016 Reduce the Upwelling Intensity along the Seas of Southern Java

Undap Marthin Wahyu Bethara Wahyono, Suryoputro Agus Anugroho Dwi, Wirasatriya Anindya

Ecological Engineering & Environmental Technology

|

2023

|

Vol. 24, iss. 9

84--95

EN

The seas of Southern Java are located at the eastern equatorial Indian Ocean and therefore, they are strongly influenced by the Indian Ocean Dipole (IOD). Strong negative IOD occurred in 2016. However, none of the previous studies investigated its effect on the seas of Southern Java. This study aims to reveal the influence of the strong negative IOD in 2016 on the upwelling intensity along the seas of Southern Java as represented by surface temperature and chlorophyll-a. This research was conducted using satellite-based data and the analysis was based on climatology, and anomaly for 15 years (2007–2021). The data used includes sea surface temperature (OISST), wind (ASCAT), IOD index (DMI), chlorophyll-a (OC-CCI), and sea level anomaly (altimetry). The findings show that the strong negative IOD in 2016 had a significant impact on sea surface temperatures which made these waters warmer. The most visible impact is through the sea surface temperature anomaly map where in 2016 throughout the year it experienced a positive anomaly with a value of 2°C higher than the climatological average. The value of chlorophyll-a in these waters has also dropped drastically which, when viewed from the anomaly map, has a value of 0.2 mg/m3 lower than the climatological average, especially during the upwelling month. This means that, strong negative IOD in 2016 reduced the upwelling intensity along the seas of Southern Java. We also found the propagation of downwelling Kelvin waves from the Indian Ocean to the Southern Java waters which bring warm temperatures and cause downwelling events during the strong negative IOD in 2016 that hampers coastal upwelling along the seas of Southern Java.

3

Response of the Bay of Bengal to super cyclone Amphan examined using synergistic satellite and in-situ observations

Chacko Neethu, Jayaram Chiranjivi

Oceanologia

|

2022

|

No. 64 (1)

131--144

EN

Tropical cyclone Amphan is the first super cyclone that happened in the north Indian Ocean in the last 20 years. In this work, multi-platform datasets were used to investigate the responses of the upper ocean to cyclone Amphan. The most striking response was the cold wake left by the cyclone spanning the entire Bay of Bengal with an amplitude up to ∼4°C. Satellite salinity observations revealed that the maximum increase in surface salinity was ∼1.5 PSU on the right side of the track of Amphan. Surface circulation was also observed to be modulated with the passage of a cyclone with a rightward bias in the change in its speed and direction. The currents observed from a moored buoy showed strong inertial oscillations. Argo observations showed that changes induced by the cyclone occurred up to 150 m depth of the cyclone and ocean heat content in the upper 150 m depth decreased due to the passage of the cyclone. There was an enhancement of surface chlorophyll concentration (∼1.5 mg/m3) after the passage of the cyclone, which was centred along the track of the cyclone where the winds were the highest. Mixed layer heat and salinity budget analysis showed that the sea surface cooling and increase in salinity was primarily driven by vertical mixing processes, though horizontal advection contributed meagrely. This study also brings forward the fact that regional differences exist in the responses of the ocean to the forcing of cyclones.

4

Regime shift in sea-ice characteristics and impact on the spring bloom in the Baltic Sea

Pärn Ove, Friedland René, Rjazin Jevgeni, Stips Adolf Konrad

Oceanologia

|

2022

|

No. 64 (2)

312--326

EN

We evaluated the temporal and spatial trends of the hydrological (temperature and sea ice) and biochemical (chlorophyll-a concentration) characteristics in springtime in the Baltic Sea. Both are strongly affected by climate change, resulting in a decrease in the duration of sea-ice melting in the previous decade. A new regime of sea ice began in 2008 and in all basins of the Baltic Sea, a rapid warming during spring could be detected. Using satellite data, the temporal and spatial variations in spring bloom were analysed during severe and warmer winters. Using a coupled hydrodynamic-biogeochemical model, we tested the response of spring bloom to the changing ice conditions. The results of the modelling indicated that the presence of ice significantly influences the predicted chlorophyll-a concentration values in the Baltic Sea. Therefore, it is necessary that any coupled model system has a realistic ice model to ensure the best simulation results for the lower trophic food web as well.

5

Tools for optimizing performance of VOYages at sea

Johannessen J. A., Perrin A., Gaultier L., Herlédan S., Pouplin C., Collard F., Maze J. P., Dussauze M., Rapp J., Fanebust R., Andersen S., Franks O., Meyer R.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2021

|

Vol. 15 No. 1

233--239

EN

The aim of the TOPVOYS project supported by the MarTERA ERA-Net Cofund program within the European Commission is to advance and implement analyses tools and decision support system for voyage optimisation. Based on marine weather analyses and forecasts combined with near real time satellite-based observations of wind, wave and surface current conditions as well as sea surface temperature fields the best shipping route are examined. The proposed approach aims to identify the optimum balance between minimisation of transit time and fuel consumption as well as reduction of emissions without placing the vessel at risk to damage and or crew injury. As such it is compliant with the International Maritime Organization guidelines [6] for ship routeing to keep the traffic smooth and avoid accidents, notably in the presence of unfavorable marine meteorological conditions. The tool performances will be demonstrated both in post-voyage analyses and real time operations for the North Atlantic Ocean crossings, voyages from Europe through the Mediterranean Sea and the Suez Channel to the Far East (e.g. China, South Korea) and voyages around Southern Africa.

6

Zima 2019-2020 roku : historyczne minimum zlodzenia Bałtyku

Marsz Andrzej A., Styszyńska Anna

Przegląd Geofizyczny

|

2021

|

Z. 3-4

227--249

PL

W sezonie zimowym 2019-2020 wystąpiło historyczne minimum rocznej maksymalnej powierzchni zlodzonej Bałtyku (MIE) w całym 301.letnim okresie obserwacji (1720-2020). MIE osiągnęła w tym sezonie lodowym wartość zaledwie 37 tys. km2, przy średniej (1720-2019) równej 213 tys. km2 i (odchyleniu standardowym) równym 112,9 tys. km2. W pracy rozpatruje się zespół procesów, które doprowadziły do osiągnięcia przez MIE ekstremalnie niskiej wartości. Analizę przeprowadzono dla okresu ostatnich 70 lat (1951-2020). Główną przyczyną wystąpienia w sezonie zimowym 2019-2020 tak niskiej MIE jest zmiana reżimu cyrkulacji środkowotroposferycznej w latach 1987-1989, polegająca na przejściu epoki cyrkulacyjnej E w epokę cyrkulacyjną W. W ostatniej epoce cyrkulacyjnej frekwencja makro-typu W według klasyfikacji Wangengejma-Girsa wzrosła znacznie powyżej wartości średnich (ryc. 3). Ponieważ zmienność frekwencji makrotypów cyrkulacji środkowotroposferycznej steruje zmiennością wartości elementów klimatycznych, w tym temperaturą powietrza, usłonecznieniem, prędkością wiatru (tab. 1), zmiana frekwencji makrotypów doprowadziła do zmiany bilansu cieplnego Bałtyku. Po roku 1988 wzrosła akumulacja ciepła słonecznego w wodach Bałtyku w okresie letnim i zmniejszyły się strumienie ciepła jawnego i ciepła parowania z powierzchni Bałtyku w okresach zimowych. W efekcie tych zmian temperatura powierzchni morza (SST) systematycznie wzrastała i SST na coraz większych powierzchniach morza nie osiągała w okresach zimowych temperatury krzepnięcia. W przebiegu SST pojawił się trend dodatni i tym samym wystąpił ujemny trend w przebiegu MIE. Spowodowało to zmianę reżimu lodowego Bałtyku, w ostatniej epoce cyrkulacyjnej silnie zmniejszyła się średnia wartość MIE i znacznie wzrosła częstość występowania łagodnych sezonów lodowych, w tym sezonów ekstremalnie łagodnych (MIE < 81.0 tys. km2). Wystąpienie w okresie ostatniej zimy (DJFM; 2019-2020) bardzo silnej cyrkulacji strefowej (ryc. 6), będącej skutkiem dominacji frekwencji makrotypu W (tab. 3) doprowadziło do wystąpienia bardzo silnych anomalii temperatury powietrza i anomalii SST (ryc. 7), uniemożliwiających, poza skrajnymi północnymi akwenami Bałtyku (Zatoka Botnicka), rozwój zlodzenia. Wystąpienie historycznego minimum MIE w sezonie lodowym 2019-2020 stanowi wynik ewolucji pola SST Bałtyku, zacho-zącej pod wpływem zmiany charakteru cyrkulacji atmosferycznej po roku 1988.

EN

In the winter season 2019-2020, there was a historical minimum of the annual maximum ice extent (MIE) of the Baltic Sea within the entire 301-year observation period (1720-2020). In this ice season MIE reached a value of only 37,000 km2, with an average (1720-2019) of 213,000 km2 and (standard deviation) of 112,900 km2. The paper considers the set of pro-cesses that led to the MIE reaching an extremely low value. The analysis was carried out for the last 70 years (1951-2020). The main reason for the occurrence of such a low MIE in the winter season 2019-2020 is the change in the mid-tropospheric circulation regime in the years 1987-1989, consisting in the transition of the E circulation epoch into the W circulation epoch. In the last period of circula-tion epoch the frequency of the W macrotype according to the Wangengejm-Girs classifica-tion increased significantly above the mean values (Fig. 3). As the variability of the frequency of the macrotypes of the mid-tropospheric circulation controls the variability of the values of climatic elements, including air temperature, sunshine duration, wind speed (Table 1), the change in the frequency of macrotypes led to a change in the thermal balance of the Baltic Sea. After 1988 the accumulation of solar heat in the waters of the Baltic Sea in the Summer period increased, and the fluxes of sensible heat and the heat of evaporation from the surface of the Baltic Sea in Winter periods decreased. As a result of these changes the sea surface temperature (SST) was systematically increasing, and the SST on increasingly larger sea sur-faces did not reach the freezing point in Winter. There was a positive trend in the course of SST and thus a negative trend in the course of MIE. This caused a change in the ice regime of the Baltic Sea. In the last circulation epoch the mean value of MIE decreased significantly and the frequency of mild ice seasons increased significantly, including extremely mild seasons (MIE <81,000 km2). The occurrence of a very strong zonal circulation during the last winter (DJFM; 2019-2020) (Fig. 6), resulting from the dominance of the W macrotype frequency (Table 3), led to a very strong air temperature anomalies and to the SST anomalies (Fig. 7), preventing, apart from the extremely northern waters of the Baltic Sea (Gulf of Bothnia), the development of the ice cover. The occurrence of the historical MIE minimum in the 2019-2020 ice season is the result of the evolution of the Baltic SST field, which took place as a result of the change in the nature of the atmospheric circulation after 1988.

7

Flood prediction based on climatic signals using wavelet neural network

Linh Nguyen Thi Thuy, Ruigar Hossein, Golian Saeed, Bawoke Getnet Taye, Gupta Vivek, Rahman Khalil Ur, Sankaran Adarsh, Pham Quoc Bao

Acta Geophysica

|

2021

|

Vol. 69, no. 4

1413--1426

EN

Large-scale climatic circulation modulates the weather patterns around the world. Understanding the teleconnections between large-scale circulation and local hydro-climatological variables has been a major thrust area of hydro-climatology research. The large-scale circulation is often quantifed in terms of sea surface temperature (SST) and sea-level pressure (SLP). In this paper, we investigate the potential of wavelet neural network (WNN) hybrid model to predict maximum monthly discharge of the Madarsoo watershed, North of Iran considering two large-scale climatic signals like SST and SLP as inputs. Error measures like root-mean-square error (RMSE), and mean absolute error along with the correlation measures like coefcient of correlation (R), and Nash–Sutclife coefcient (CNS) were used to quantify the performance of prediction of maximum monthly discharge of three diferent hydrometry stations of the watershed. In all the cases, the WNN hybrid machine learning model was found to be giving superior performance consistently against the standalone artifcial neural network (ANN) model and multiple linear regression model to predict the food discharges of March and August months. The prediction of food for August which is more devastating is found to be slightly better than the prediction of foods of March, in the stations served with smaller drainage area. The RMSE, R and CNS of Tamer hydrometry station in August were found to be 0.68, 0.996, and 0.99 m3 /s, respectively, for the test period by using WNN model against 1.55, 0.989 and 0.95 by ANN model. Moreover, when evaluated for predicting the maximum monthly discharge in March and August between 2012 and 2013, the wavelet-based neural networks performed remarkably well than the ANN.

8

Climate change impacts on sea surface temperature (SST) trend around Turkey seashores

Dabanli Ismail, Şişman Eyüp, Güçlü Yavuz Selim, Birpınar Mehmet Emin, Şen Zekai

Acta Geophysica

|

2021

|

Vol. 69, no. 1

295--305

EN

This paper focuses on sea surface temperature (SST) trends due to the importance of temperature diference in climate change impact research. These trends are not only essential for climate, but they are also important for marine ecosystem. Immigration of fsh population due to the temperature changes is expected to cause unexpected economical results. For this purpose, both classical Mann–Kendall, (MK) (Mann in Econom: J Econom Soc 13:245–259, 1945; Kendall in Rank Correlation Methods, Charless Grifn, London, 1975) and innovative trend analysis (ITA) (Şen in J Hydrol Eng 17(9):1042–1046, 2012) methodologies are applied for the SST data records. Monthly SST data are considered along the Black, Marmara, Aegean, and Mediterranean coastal areas in Turkey. SST data are categorized into fve clusters considering fsh life as “hot,” “warm-hot,” “warm,” “cold,” and “very cold.” According to ITA, SST in all coastal areas tends to increase except for winter season during “very cold” (0–10 °C) temperatures. The temperature changes in both winter and summer seasons are expected to change the marine life, fsh population, tourism habit, precipitation regime, and drought feature.

9

Marked contrast in wind-driven upwelling on the southeastern Nova Scotia coast in July of two years differing in ENSO conditions

Scrosati Ricardo A., Ellrich Julius A.

Oceanological and Hydrobiological Studies

|

2020

|

Vol. 49, No. 1

81--87

EN

Upwelling occurs on several coasts of the world, but it has mostly been studied on eastern ocean boundaries. We investigated upwelling on a western ocean boundary for which limited information exists. Using daily in-situ data on sea surface temperature (SST), we found a marked contrast in coastal cooling between July 2014 (pronounced) and July 2015 (weak) at two locations 110 km apart on the Atlantic coast of Nova Scotia, Canada. These findings are consistent with a marked interannual difference in wind-driven upwelling. On the one hand, southwesterlies (which cause upwelling on this coast) were more frequent in July 2014 than in July 2015. On the other hand, Bakun's upwelling index (which is based on wind data and geographic information) indicated that coastal upwelling was more common and intense in July 2014 than in July 2015, while the reverse was true for downwelling. Interestingly, a strong El Niño event occurred in July 2015, while no El Niño (or La Niña) conditions happened in July 2014. In a recent book evaluating upwelling systems around the world, the system that is the focus of the present study was not included. Therefore, our findings should stimulate future research on upwelling on the Atlantic Canadian coast, in that way helping to further develop the knowledge base for western ocean boundaries.

10

Indian Ocean wind speed variability and global teleconnection patterns

Sinha Mourani, Jha Somnath, Chakraborty Paromita

Oceanologia

|

2020

|

No. 62 (2)

126--138

EN

The influence of the local sea surface temperature (SST) and remote ENSO (El Niño-Southern Oscillation) indices on the wind speed (WS) data were explored for the Indian Ocean region. Relationships among the parameters were studied using spatial correlation plots and significant correlation ranges. Two months (July and January) representing opposite monsoon phases were selected for analysis for the period 1950-2016. There was a significant negative correlation between WS and SST over the Bay of Bengal (BOB) during July. Although different ENSO indices correlated differently in different areas of the Indian Ocean, the region off the coast of Sri Lanka was most significantly teleconnected. The southwest monsoon locally impacted the WS and SST relationship and the WS parameter was remotely teleconnected in both the monsoon seasons. Further empirical orthogonal function (EOF) analysis was applied on the 67 years WS data of the BOB region to extract the dominant mode representing maximum variability of the total variance. The temporal pattern of the first principal component (PC1) of WS data was linked to the North Atlantic Oscillations in January and the Atlantic Multidecadal Oscillation in July respectively. The continuous wavelet power spectra of the PC1 of WS showed significant regions in the 2-4-year band resembling the ENSO variability. Wavelet coherence applied between PC1 of WS and the ENSO indices showed greatest values for January in the 8-16-year band and for July in the 0-4-year band. A close relationship was established between the WS variability in BOB and the ENSO indices.

11

Numerical simulation of the wave-induced Stokes drift effect on sea surface temperature in the North Pacific

Liu Jingdong, Shi Jian, Zhang Wenjing

Oceanological and Hydrobiological Studies

|

2019

|

Vol. 48, No. 4

381--403

EN

The effect of the wave-induced Stokes drift is not taken into account in traditional ocean circulation models used for SST simulations. The spectral parameterization scheme is considered to be the most accurate of the wave-induced Stokes drift calculation schemes. The numerical simulation results of sea surface temperature (SST) with the Stokes drift and SST without the Stokes drift in the North Pacific in 2014 were analyzed. The Stokes drift plays a cooling role in the North Pacific, and the most affected areas are high-latitude sea areas. The following factors are responsible for cooling: the seawater divergence caused by Stokes transport, changes in the sea surface current field caused by the Coriolis-Stokes force and the effects of turbulence caused by Langmuir circulation. The simulation of the vertical temperature profile in the mixed layer is improved when the Stokes drift is accounted for. The simulated results of SST using the Stokes drift approximate parameterization schemes and the spectral parameterization scheme are compared. The results confirm that the spectral parameterization scheme can be used for accurate SST simulation, and the Phillips spectrum approximate parameterization scheme is the best among the approximate parameterization schemes.

12

Recent sea surface temperature trends and future scenarios for the Red Sea

Shaltout Mohamed

Oceanologia

|

2019

|

No. 61 (4)

484--504

EN

The current paper analyses the recent trends of Red Sea surface temperature (SST) using 0.25° daily gridded Optimum Interpolation Sea Surface Temperature (OISST) data from 1982 to 2016. The results of 3 different GFDL (Geophysical Fluid Dynamics Laboratory) model simulations are used to project the sea surface temperature (hereafter called Tos) under the four representative concentration pathway scenarios through 2100. The current research indicates that the spatially annual mean (from 1982 to 2016) Red Sea surface temperature is 27.88 ± 2.14°C, with a significant warming trend of 0.029°C yr-1. The annual SST variability during the spring/autumn seasons is two times higher than during the winter/summer seasons. The Red Sea surface temperature is correlated with 13 different studied parameters, the most dominant of which are mean sea level pressure, air temperature at 2 m above sea level, cross-coast wind stress, sensible heat flux, and Indian Summer Monsoon Index. For the Red Sea, the GFDL-CM3 simulation was found to produce the most accurate current SST among the studied simulations and was then used to project future scenarios. Analysis of GFDL-CM3 results showed that Tos in the Red Sea will experience significant warming trends with an uncertainty ranging from 0.6°C century-1 to 3.2°C century-1according to the scenario used and the seasonal variation.

13

Propagation of Upwelling on Western-Coast Sumatra During Madden-Julian Oscillation Event

Haryanto Y. D., Fitrianti N., Hartoko A., Anggoro S., Zainuri M.

Journal of Ecological Engineering

|

2018

|

Vol. 19, nr 1

122--128

EN

Madden-Julian oscillation (MJO) is an atmospheric oscillation due to atmospheric phenomenon that occurs due to the uniformity of solar energy received at the surface of the earth, MJO is a natural occurrence in the seaatmosphere system. When the MJO is active, in general there will be a disturbance in the upper air which is then followed by an anomaly at sea surface pressure causing the changes in the wind on the surface. The changes in the surface wind affect the sea surface currents which then cause the occurrence of coastal upwelling downwelling. The upwelling process itself is a process whereby a sea mass is pushed upward along the continent, when the beach is to the left of the wind direction, the ecological transport leads to the mass of water away from the coast. As a result, there is a mass vacuum (divergence) in the coastal area. This mass void will be filled by the mass of water from the inner layer that moves to the surface. Indonesian territory itself is passed by MJO in phases 3, 4 and 5, while for Sumatra region is passed by MJO phase 3 and 4. This research aims to identify the propagation of coastal upwelling during MJO on the west coast of Sumatera, therefore the data of geopotential height, surface pressure sea ( MSLP), zonal and meridional components and sea surface temperature are used to analyze how the MJO effect on the coastal upwelling occurs in the research area. The analysis was conducted in June, July and August by comparing the atmospheric conditions at the time of strong MJO in phases 3 and 4 with normal viewing of anomaly geopotential height and MSLP and then seeing the anomaly surface wind changes from zonal wind (u) and meridional wind (v) and changes in SST in Sumatra region. The result shows that there is a change of GH and MSLP when MJO passes the west coast of Sumatra and then follows the change in the value of u and v and SST to identify the upwelling, while the anomaly change negative SST does not occur when MJO is active but has time lag (lag). In this analysis it was found that SST anomaly occurs when the anomaly changes in both the upper and surface water occurring after 5 days in phases 3, 4 and 5.

14

Characterization of the northern Red Sea's oceanic features with remote sensing data and outputs from a global circulation model

Eladawy A., Nadaoka K., Negm A., Abdel-Fattah S., Hanafy M., Shaltout M.

Oceanologia

|

2017

|

No. 59 (3)

213--237

EN

Sea surface temperature (SST) and surface wind (SW) are considered the most important components in air–sea interactions. This study examines the relationships between SST, SW and various oceanic variables in the northern Red Sea (NRS) during the period of 2000–2014. The current study is the first attempt to identify the SST fronts and their relationship with the dominant circulation patterns. SST fronts are mapped using the Cayula and Cornillon algorithms. The analysis is performed with available remote sensing and reanalyzed data together with 1/12° HYbrid Coordinate Ocean Model (HYCOM) outputs. Seasonal-trend decomposition procedure based on loess (STL) is applied for trend analysis, and Principal Component Analysis (PCA) is run for the atmospheric parameters. The SST, SW speed and Chlorophyll-a (Chl-a) changes show insignificant trends during the period of 2000–2014. Meridional SST fronts are more significant during the month of January, and fronts that are perpendicular to the sea's axis occur from February to May. Distinct monthly and spatial variations are present in all the examined parameters, although these variations are less pronounced for the wind direction. The SST is mainly controlled by the air temperature and sea level pressure. Significant correlations exist between the SST and the studied parameters (alongshore wind stress rather than the cross-shore wind stress, surface circulation, MLD, and Chl-a). Surface winds generally flow southeastward parallel to the Red Sea's axis explaining that alongshore wind stress is highly correlated with the studied parameters.

15

Czynniki zmian klimatycznych w środkowym i górnym plejstocenie : ich zapis geologiczny w osadach Oceanu Południowego oraz rdzeniach lodowych

Kotrys B.

Przegląd Geologiczny

|

2016

|

Vol. 64, nr 1

35--42

EN

Climate changes during the Pleistocene were driven by large-scale orbital perturbations as well as by internal feedbacks on the Earth. One of the main roles in climate modelling is played by the Southern Ocean that is a great source of sea ice, carbon dioxide, dissolved silica and nutrients. Numerous sediment and ice records derived from the Southern Ocean and Antarctica document high-resolution climatic changes that allow us a better understanding of global climate evolution. Consistently with the global climatic trend, several sea surface temperature (SST) records of the Southern Ocean are marked by a distinct shift from low to high glacial/interglacial variability around Termination V (T V), called the Mid-Brunhes Event (MBE). Prior to T V, the Southern Ocean’s SST displays lower values and low variability. It points to a distinct expansion of the Southern Ocean cold water masses and positional changes of hydrographical fronts during most of the lower Middle Pleistocene, which started in the Pliocene. Beside large climatic changes, several abrupt distinct warming and cooling phases have been recognized. Some of them (MIS 22–19, MIS 11 and MIS 5) show similarities to MIS 1, which could be used for future climate predictions. In this paper we would like to present the middle and late Pleistocene climatic mechanisms in the Southern Ocean, and to show SST changes in relation to the hydrographic frontal movement, sea ice development and CO2 oscillations.

16

Zmiany zlodzenia Morza Karskiego w latach 1979-2015. Podejście systemowe

Styszyńska A., Marsz A. A.

Problemy Klimatologii Polarnej

|

2016

|

Nr 26

109--156

PL

Praca omawia zmiany powierzchni lodów na Morzu Karskim i mechanizmy tych zmian. Scharakteryzowano przebieg zmian zlodzenia, ustalając momenty skokowego zmniejszenia się letniej powierzchni lodów. Rozpatrzono wpływ cyrkulacji atmosferycznej, zmian temperatury powietrza i zmian zasobów ciepła w wodach na zmiany zlodzonej tego morza. Analizy wykazały, że wszystkie zmienne opisujące zarówno stan zlodzenia jak i stan elementów klimatycznych są ze sobą wzajemnie powiązane przez różnego rodzaju sprzężenia zwrotne. W rezultacie tworzy się rekurentny system, w którym zmiany powierzchni lodów, wpływając na przebieg innych elementów systemu (temperaturę powietrza, temperaturę wody powierzchniowej) w znacznej części same sterują swoim rozwojem. Zmiennością całego tego systemu sterują zmiany intensywności cyrkulacji termohalinowej (THC) na Atlantyku Północnym, dostarczając do niego zmienne ilości energii (ciepła). Reakcja systemu zlodzenia Morza Karskiego na zmiany natężenia THC następuje z 6.letnim opóźnieniem.

EN

The work discusses the changes in the ice extent on the Kara Sea in the years 1979-2015, i.e. in the period for which there are reliable satellite data. The analysis is based on the average monthly ice extent taken from the database AANII (RF, St. Peterburg). 95% of the variance of average annual ice extent explains the variability of the average of ice extent in ‘warm' season (July-October). Examination of features of auto-regressive course of changes in ice extent shows that the extent of the melting ice area between June and July (marked in the text RZ07-06) can reliably predict the ice extent on the Kara Sea in August, September, October and November as well as the average ice extent in a given year. Thus the changes in ice extent can be treated as a result of changes occurring within the system. Analysis of the relationship of changes in ice extent and variable RZ07-06 with the features of atmospheric circulation showed that only changes in atmospheric circulation in the Fram Strait (Dipole Fram Strait; variable DCF03-08) have a statistically significant impact on changes in ice extent on the Kara Sea and variable RZ07-06. The analysis shows no significant correlation with changes in ice extent or AO (Arctic Oscillation), or NAO (North Atlantic Oscillation). Variable RZ07-06 and variable DCF03-08 are strongly correlated and their changes follow the same pattern. Analysis of the relationship of changes in ice extent and variable RZ07-06 with changes in air temperature (the SAT) showed the presence of strong relationships. These correlations differ significantly depending on the region; they are much stronger with changes in air temperature in the north than in the south of the Kara Sea. Temperature of cold period (average temperature from November to April over the Kara Sea, marked 6ST11-04) has a significant effect on the thickness of the winter ice and in this way the thickness of ice in the next melting season becomes part of the "memory" (retention) of past temperature conditions. The thickness of the winter ice has an impact on the value of the variable RZ07-06 and on changes in ice extent during the next ‘warm’ season. As a result, 6ST11-04 explains 62% of the observed variance of the annual ice extent on the Kara Sea. SAT variability in the warm period over the Kara Sea (the average of the period July-October, marked 6ST07-10) explains 73% of the variance of annual ice extent. SAT variability of the N part of the Kara Sea (Ostrov Vize, Ostrov Golomjannyj), which explains 72-73% of the variance ice extent during this period, has particularly strong impact on changes in ice extent during warm period. These stations are located in the area where the transformed Atlantic Waters import heat to the Kara Sea. Analysis of the impact of changes in sea surface temperature (SST) variability on sea ice extent indicated that changes in SST are the strongest factor that has influence on ice extent. The variability of annual SST explains 82% of the variance of annual ice extent and 58% of the variance of the variable RZ07-06. Further analysis showed that the SAT period of warm and annual SAT on the Kara Sea are functions of the annual SST (water warmer than the air) but also ice extent. On the other hand, it turns out that the SST is in part a function of ice extent. All variables describing the ice extent and its changes as well as variables describing the nature of the elements of hydro-climatic conditions affecting the changes in ice extent (atmospheric circulation, SAT, SST) are strongly and highly significantly related (Table 9) and change in the same pattern. In this way, the existence of recursion system is detected where the changes in ice extent eventually have influence on ‘each other’ with some time shift. The occurrence of recursion in the system results in very strong autocorrelation in the course of inter-annual changes in ice extent. Despite the presence of recursion, factors most influencing change in ice extent, i.e. the variability in SST (83% of variance explanations) and variability in SAT were found by means of multiple regression analysis and analysis of variance. Their combined impact explains 89% of the variance of the annual ice extent on the Kara Sea and 85% of the variance of ice extent in the warm period. The same rhythm of changes suggests that the system is controlled by an external factor coming from outside the system. The analyses have shown that this factor is the variability in the intensity of the thermohaline circulation (referred to as THC) on the North Atlantic, characterized by a variable marked by DG3L acronym. Correlation between the THC signal and the ice extent and hydro-climatic variables are stretched over long periods of time (Table 10). The system responds to changes in the intensity of THC with a six-year delay, the source comes from the tropical North Atlantic. Variable amounts of heat (energy) supplied to the Arctic by ocean circulation change heat resources in the waters and in SST. This factor changes the ice extent and sizes of heat flux from the ocean to the atmosphere and the nature of the atmospheric circulation, as well as the value of the RZ07-06 variable, which determines the rate of ice melting during the ‘warm’ season. A six-year delay in response of the Kara Sea ice extent to the THC signal, compared to the known values of DG3L index to the year 2016, allows the approximate estimates of changes in ice extent of this sea by the year 2023. In the years 2017 to 2020 a further rapid decrease in ice extent will be observed during the ‘warm' period (July-October), in this period in the years 2020-2023 ice free conditions on the Kara Sea will prevail. Ice free navigation will continue from the last decade of June to the last decade of October in the years 2020-2023. Since the THC variability includes the longterm, 70-year component of periodicity, it allows to assume that by the year 2030 the conditions of navigation in the Kara Sea will be good, although winter ice cover will reappear.

17

Zmiany temperatury wody powierzchniowej na morzach Arktyki Rosyjskiej i ich konsekwencje dla żeglugi na Północnej Drodze Morskiej (1979-2016)

Styszyńska A., Pastusiak T.

Problemy Klimatologii Polarnej

|

2016

|

Nr 26

165--177

PL

Praca omawia zmiany średniej miesięcznej temperatury wody powierzchniowej na morzach Arktyki Rosyjskiej w latach 1979-2016. Stwierdzono, że w badanym okresie następował powolny wzrost temperatury wody. Jednakże tylko na Morzu Barentsa był on istotny statystycznie we wszystkich miesiącach roku, a w SW części Morza Karskiego oraz w zachodniej części Morza Czukockiego w okresie od czerwca do grudnia. W analizowanym 38.leciu największy wzrost temperatury wody powierzchniowej miał miejsce na Morzu Wschodniosyberyjskim (+0,57°C/10 lat w sierpniu i +0,44°C/10 lat we wrześniu) oraz w SW części Morza Karskiego w lipcu (+0,53°C/10 lat). W dalszym ciągu na wszystkich morzach, poza Morzem Barentsa, do czerwca włącznie temperatura wody ma wartości niższe od temperatury jej zamarzania przy swoistym dla danego morza zasoleniu. Najpóźniej temperaturę zamarzania osiągają wody Morza Barentsa gdzie w ostatniej dekadzie (2006-2015) na podejściu do północnego wejścia na PDM rzadko kiedy temperatura wody spadała poniżej temperatury zamarzania oraz wody Morza Czukockiego (w grudniu). Oznacza to, że statki pokonujące PDM w listopadzie będą miały szansę przepłynąć ją po „czystej” wodzie lub w cienkich, młodych lodach, które dla współczesnych statków nie stanowią większego zagrożenia.

EN

The paper discusses changes of the mean monthly sea surface temperature on the Russian Arctic seas in the years 1979-2016. It was found that during the period under investigation there was a slow increase in water temperature. However, only in the Barents Sea it was statistically significant in all months of the year, and in the SW part of the Kara and western Chukchi seas from June to December. In the analyzed 38 years the highest rise in surface water temperature was recorded in the East Siberian Sea (+0.57°C/decade in August and +0.44°C/decade in September) and in the SW Kara Sea in July (+0.53°C/decade). Still on all these seas, except for the Barents Sea, until June inclusive, the water temperature was lower than its freezing temperature for a particular salinity specific for the sea. At the latest, freezing temperatures reached the waters of the Barents Sea, where in the last decade (2006-2015) at the approach to the north entrance of the Northern Sea Route (NSR) rarely water temperature has fallen below the freezing point. At the same time, the Chukchi Sea waters reached freezing temperatures in December. This means that vessels sailing through the NSR in November will have the chance to pass it through "ice free" water or in thin, young ice, which for modern ships is not a major threat.

18

Comparison of direct and inverse methods of satellite observations downscaling for the coastal zone area

Chybicki A., Łubniewski Z.

Hydroacoustics

|

2016

|

Vol. 19

55--64

EN

The Earth observation satellite imaging systems have known limitations, especially regarding their spatial and temporal resolution. Therefore, approaches which aim to combine data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution are of high interest. This allows for joint utilization of the advantages of both these types of sensors. As there are several ways to achieve this goal, in this paper two approaches, direct and inverse, of downscaling the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR) were evaluated. The applied downscaling methods utilize biophysical properties of the surface sensed using short wave infrared and thermal band. The presented algorithm evaluation was performed on the basis of a specific test case: the coastal zone area of the Gulf of Gdańsk, Poland. In this context, the objective presented in the study was to compare two methods of downscaling for a specific test case in order to evaluate how the proposed approaches cope with the specific conditions of the coastal zone area.

19

Anomalous Variation in GPS TEC, Land and Ocean Parameters Prior to 3 Earthquakes

Yadav K., Karia S. P., Pathak K. N.

Acta Geophysica

|

2016

|

Vol. 64, no. 1

43--60

EN

The present study reports the analysis of GPS TEC prior to 3 earthquakes (M > 6.0). The earthquakes are: (1) Loyalty Island (22°36′S, 170°54′E) on 19 January 2009 (M = 6.6), (2) Samoa Island (15°29′S, 172°5′W) on 30 August 2009 (M = 6.6), and (3) Tohoku (38°19′N, 142°22′E) on 11 March 2011 (M = 9.0). In an effort to search for a precursory signature we analysed the land and ocean parameters prior to the earthquakes, namely SLHF (Land) and SST (Ocean). The GPS TEC data indicate an anomalous behaviour from 1-13 days prior to earthquakes. The main purpose of this study was to explore and demonstrate the possibility of any changes in TEC, SST, and SLHF before, during and after the earthquakes which occurred near or beneath an ocean. This study may lead to better understanding of response of land, ocean, and ionosphere parameters prior to seismic activities.

20

Spatial and temporal variability of sea surface temperature in the Baltic Sea based on 32-years (1982–2013) of satellite data

Stramska M., Białogrodzka J.

Oceanologia

|

2015

|

No. 57 (3)

223--235

EN

Satellite measurements provide synoptic view of sea surface temperature (SST) and can be used to trace global and regional climate trends. In this study we have examined the multiyear trends and variability of the Baltic Sea SST using 32-years (1982–2013) of satellite data. Our results indicate that there is a statistically significant trend of increasing SST in the entire Baltic Sea, with values ranging from 0.03 to 0.06°C year−1, depending on the location. SSTs averaged over the entire Baltic Sea increase at the rate of 0.05°C year−1. Higher values of SST trend are generally present in the summer months, while trend is not statistically significant in the winter months. The seasonal cycle of SST in the Baltic Sea is characterized by well-defined winter and summer seasons. The average amplitude (16–18°C) of this cycle is significantly larger than in the North Sea waters located at the same latitudes as the Baltic Sea. The analyzed data set also highlights considerable interannual SST variability, which is coherent in different regions of the Baltic Sea and significantly correlated with interannual variability of the air temperature. SST variability in the Baltic Sea in winter can be linked to the North Atlantic Oscillation index.