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Temperatura powierzchni wody na Północnym Atlantyku a temperatura powietrza na Spitsbergenie i Jan Mayen

Marsz A. A.

Problemy Klimatologii Polarnej

1999

nr 9

37--80

This paper deals with correlation between air temperature over the Greenland Sea and water temperature in the North Atlantic The Jan Mayen and Svalbard-Lufthavn stations have been chosen to illustrate air temperature characteristics for this sea area, The monthly mean air temperature indicates strongest correlations between the above mentioned stations during the polar night (see tab. 1). This fact proves that the element which is common to both stations is atmospheric circulation. Relations between the course of air temperature at these stations and the NAO index turned to be weak (see tab. 2) and their distribution varies widely. NAO has been found not to be the most important element having influence on the formation of air temperature. The analysis of relation between the variability of the sea water temperature in the Greenland Sea and the variability of air temperature at both stations was fruitful as the relations were both weak and not clear enough. The monthly mean water temperature anomalies (SST) in the North Atlantic in grids 2° x 2° over the period January 1970 and August 1997 (26 years and 8 month) were used to analyse correlations between the sea surface temperature and air temperature at both stations. The data concerning the sea surface temperature were the subject of three-stage statistical analysis resulting in 10 grids being distinguished (see fig. 1), each of which is characterised by changes in temperatures of far greater ocean surface. These grids are called 'control grids'. The following symbols are used: ANmm[DD,SS]; where AN - explanatory symbol, meaning that it clenotes anomalies in water temperature in a grid; mm - number of a month when anomalies occur; [DD, SS] - location of a central point of a grid in space, where DO - west longitude, SS .- north latitude. For example symbol AN09[30,54] means that we are dealing with an anomaly SST from September from a grid located 30°W and 54°N. The study of synchronic and asynchronic correlations between SST anomalies in given grids and air temperatures indicated the occurrence of a number of correlations significant from the statistics point of view. They were mainly asynchronic correlations with SST changes proceeded by changes in air temperature. The maximum of air temperature correlations, which are statistically significant, was noted between SST anomalies at the end of winter and beginning of spring (the final winter coding season) and the end of summer and beginning of autumn (the final season of summer warming). It represents two extreme stages from which a further evolution of the area of the water temperature takes place in warm and cold seasons. Figures 2 – 9 show exemplary distribution of correlations coefficient values. As the variability of mea n monthly temperatures in winter months plays the most important role in the dispersion of annual mea n temperature over this area and the less important one in the warmest summer months, the subjects of this study were relations between signs, values and location of SST anomalies and monthly mea n temperatures in winter months (December to March) and summer ones (July, August). A multiple regression was taken as a model and the monthly mean air temperature is a dependent variable and the values of SST anomalies are independent variables. The analysis was carried out with the help of a forward stepwise method. In order to keep the stability of equations the relations only with three independent variable were taken into considerations. Correlations of great statistical significance were found. They allow to estimate monthly mean air temperatures at Jan Mayen and Spitsbergen with the help of SST anomalies which occurred in the North Atlantic earlier. The list of correlation for winter months and their statistical characteristics are shown as equations [1] - [8] and tor summer months as equations [9] _ [12]. They explain 44% to 66% of the variability of temperature in the winter months and from 43% to 60% of the variability of temperature in the summer months. A similar analysis was carried out in order to find relations between synchronic and asynchronic annual SST anomalies in control grids and annual mean temperatures at both stations. These correlations are represented by [13] and [14] equations (synchronic correlations) and by [15] and [16] equations (asynchronic correlations) - the SST anomalies taken from a year ‘n’ the annual temperatures from a year n+1. The variability of annual mean SST anomalies in the chosen control grids explain about 50% ot variabilities of annual mean air temperature in case of synchronic correlations and 22% to 40% in case of asynchronic ones. Figures 10, 11 and 14 illustrate exemplary characteristics of such correlations quality. The analysis of spatial distribution of grids determining the variability of air temperature in the Greenland Sea shows that the temperature over the east part of that sea area (the region ot Spitsbergen) describes the thermal states in the west part of the North Atlantic, mainly the SST anomalies in the Labrador Current, in the Sargasso Sea, in the Gulf Stream and within the cyclonic circulation of the North Atlantic. The air temperature in the western part of the Greenland Sea (the region of Jan Mayen) is also influenced by the distribution of anomalies in the eastern part of the North Atlantic. The formation of the SST anomalies in the Labrador Current in its extreme end see fig. 12) and in the Gulf Stream (see fig 13) has the greatest influence on the course of temperatures occurring over the entire Greenland Sea. The analysis of equations [1] - [16] and table 3 gives more detailed information about the parts of the ocean having the strongest influence on the temperature over the Greenland Sea. The mechanism of these correlations can be explained by modification of atmospheric circulation which is influenced by the flow of warm air from the Nort Atlantic into the atmosphere. The range and spatial distribution of the warm air flowing from the ocean to the atmosphere depend generally speaking, on the heat resources in the ocean, which can clearly be observed in anomalies in surface water temperatures. The increased or decreased mea n streams of heat from a specified part of the North Atlantic when compared to many years ones regulate the value of horizontal thermal gradients in the middle troposphere of medium latitude zones. By stabilising or destabilising long waves (the range in wave number) they have their input into the occurrence of statistically significant regression of location of upper ridges axes or upper trough with all the resulting consequences for atmospheric circulation in the layer of 1000-750 hPa (lower troposphere). Finally, the character of atmospheric circulation in a given region changes (predominance of zonal circulation or one of the meridional type) and this can be foreseeable. Further the changes in atmospheric circulation determine the deviation of climate elements tram the many years' mean values in a given many years' period, year, season or month. The results of this study show that the changes in the character of atmospheric circulation over the Greenland Sea and at the same time in the thermal regime over this sea area have been influenced to a great extent by changes in SST in the region of the North Atlantic in most part of its tropical and sub-tropical zones. The above conclusion makes the thesis that only Arctic generates climatic oscillations which then move to lower latitudes disputable. The results indicate that looking for reasons for changes in climatic conditions in the region of Atlantic Arctica cannot be carried out without taking into consideration the situation in the North Atlantic, especially meridional flow of heat in the oceanic circulation.