Trends in Precipitation Variability: Prague (The Czech Republic)

Variability in precipitation at scales from 1 to 10 days was investigated with the use of the time series measured at Prague-Sporilov (the Czech Republic) between 1994 and 2001. Variability was detected by the method of absolute difference in precipitation between two adjacent discrete time periods. The results indicated a general increase in precipitation variability at all investigated scales within the 8-yr observational period. The variability patterns also showed quasi-seasonal variations. The summer wetter season proved to be the most variable. The analysis was accomplished by the investigations of precipitation variability at a monthly scale based on a century-long historical time record. On a longer time perspective, precipitation variability exhibits a general increase interrupted by quasi-decadal oscillations. The range of quasi-decadal variability has become more pronounced after about 1950, the fact that hints the possibility of further intensification of the hydrologic cycle. An obtained significant correlation between the North Atlantic Oscillation (NAO) activity and precipitation variability implies that the NAO may account for a large fraction of precipitation variability. Higher NAO-index values tend to be associated with low variability. The variability investigations may have a certain implication for climate change assessments both at the local scales as well as associated with the build-up of greenhouse gases.     

Changes in daily and nightly day-to-day temperature variability during the twentieth century for two stations in Switzerland

Summary  An analysis of day-to-day variability was performed on two century-long daily minimum and maximum temperature series from Switzerland. Warmer temperatures during the 20^th century have been accompanied by a reduction in day-to-day variability, particularly for minimum temperatures and for winter. There is a significant negative correlation between day-to-day variability and the skewness of the temperature distribution, particularly in winter and for minimum temperatures. Lower variability is linked to a reduced number of cold days and nights. Higher NAO index values tend to be associated not only with warmer temperatures but also with lower day-to-day variability. This paper confirms that the temperature warming during the 20^th century has happened mainly through the loss of the coldest part of the series, not only in the 24-hour or yearly cycle, but also through the loss of the coldest episodes in each month. Received September 20, 2000 Revised January 8, 2001     

Precipitation fluctuations during the winter season from 1960 to 1995 over Emilia-Romagna, Italy

Summary ?The variability of the winter mean precipitation observed at 40 rainfall stations in Emilia-Romagna (a region in northern Italy) from 1960 to 1995 is examined. The results are compared with those obtained for the whole of Italy using records from 32 stations. Temporal variability of the time series is investigated by means of Mann-Kendall and Pettitt tests, in order to estimate the presence of trends and “change points”. Before analysis the original precipitation data set have been tested to detect the inhomogeneity points, using the Standard Normal Homogeneity Test (SNHT). Almost all stations situated in Emilia Romagna exhibit a significant decreasing trend in winter precipitation during the 1960–1995 period. The same characteristics are revealed, more significant in the northern and central part of the region, when the stations for all Italy are analysed. A significant downward shift in the winter precipitation is detected through the Pettitt test in Emilia Romagna, around 1980 at some stations, while the rest of the stations reveal the shift point occurrence around 1985. A significant downward shift in the winter precipitation is detected around 1985, when analysing the time series for all Italy. Spatial variability of winter precipitation is studied using the Empirical Orthogonal Function. The first pattern indicates that a common large-scale process could be responsible for the winter precipitation variability. The second EOF pattern shows an opposite sign of climate variability, which highlights the influence of relief on the precipitation regime. The time series associated with the first precipitation pattern (PC1) at both scales emphasises a significant decreasing trend and a downward shift point around 1985. The internal structure analysis of the North Atlantic Oscillation (NAO) index during the 1960–1995 period reveals a significant increasing trend and an upward shift around 1980. Strong correlation is also detected between PC1 (Emilia Romagna and at the scale of all Italy) and the NAO index. Thus, the changes detected in the winter precipitation around 1985 could be due to an intensification of the positive phase of the [NAO], especially after 1980. Received March 23, 2001; revised February 20, 2002; accepted March 3, 2002     

Temperature trends in the skin/surface, mid-troposphere and low stratosphere near Korea from satellite and ground measurements

Various types of satellite (AIRS/AMSU, MODIS) and ground measurements are used to analyze temperature trends in the four vertical layers (skin/surface, mid-troposphere, and low stratosphere) around the Korean Peninsula (123–132°E, 33–44°N) during the period from September 2002 to August 2010. The ground-based observations include 72 Surface Meteorological Stations (SMSs), 6 radiosonde stations (RAOBs), 457 Automatic Weather Stations (AWSs) over the land, and 5 buoy stations over the ocean. A strong warming (0.052 K yr^?1) at the surface, and a weak warming (0.004～0.010 K yr^?1) in the mid-troposphere and low stratosphere have been found from satellite data, leading to an unstable atmospheric layer. The AIRS/AMSU warming trend over the ocean surface around the Korean Peninsula is about 2.5 times greater than that over the land surface. The ground measurements from both SMS and AWS over the land surface of South Korea also show a warming of 0.043～0.082 K yr^?1, consistent with the satellite observations. The correlation average (r = 0.80) between MODIS skin temperature and ground measurement is significant. The correlations between AMSU and RAOB are very high (0.91～0.95) in the anomaly time series, calculated from the spatial averages of monthly mean temperature values. However, the warming found in the AMSU data is stronger than that from the RAOB at the surface. The opposite feature is present above the mid-troposphere, indicating that there is a systematic difference. Warming phenomena (0.012～0.078 K yr^?1) are observed from all three data sets (SMS, AWS, MODIS), which have been corroborated by the coincident measurements at five ground stations. However, it should also be noted that the observed trends are subject to large uncertainty as the corresponding 95% confidence intervals tend to be larger than the observed signals due to large thermal variability and the relatively short periods of the satellitebased temperature records. The EOF analysis of monthly mean temperature anomalies indicates that the tropospheric temperature variability near Korea is primarily linked to the Arctic Oscillation (AO), and secondarily to ENSO (El Niño and Southern Oscillation). However, the low stratospheric temperature variability is mainly associated with Southern Oscillation and then additionally with Quasi-Biennial Oscillation (QBO). Uncertainties from the different spatial resolutions between satellite data are discussed in the trends.     

An analysis of the time scales of variability in centuries-long enso-sensitive records in the last 1000 years

We document the characteristic time scales of variability for seven climate indices whose time-dependent behavior is sensitive to some aspect of the El Niño/Southern Oscillation (ENSO). The ENSO sensitivity arises from the location of these long-term records on the periphery of the Indian and Pacific Oceans. Three of the indices are derived principally from historical sources, three others consist of tree-ring reconstructions (one of summer temperature, and the other two of winter rainfall), and one is an annual record of oxygen isotopic composition for a high-elevation glacier in Peru. Five of the seven indices sample at least portions of the Medieval Warm Period (~ A.D. 950 to 1250).Time series spectral analysis was used to identify the major time scales of variability among the different indices. We focus on two principal time scales: a high frequency band (~ 2–10 yr), which comprises most of the variability found in the modern record of ENSO activity, and a low frequency band to highlight variations on decadal to century time scales (11 <P < 150 yr). This last spectral band contains variability on time scales that are of general interest with respect to possible changes in large-scale air-sea exchanges. A technique called evolutive spectral analysis (ESA) is used to ascertain how stable each spectral peak is in time. Coherence and phase spectra are also calculated among the different indices over each full common period, and following a 91-yr window through time to examine whether the relationships change.In general, spectral power on time scales of ~ 2–6 yr is statistically significant and persists throughout most of the time intervals sampled by the different indices. Assuming that the ENSO phenomenon is the source of much of the variability at these time scales, this indicates that ENSO has been an important part of interannual climatic variations over broad areas of the circum-Pacific region throughout the last millennium. Significant coherence values were found for El Niño and reconstructed Sierra Nevada winter precipitation at ~ 2–4 yr throughout much of their common record (late 1500s to present) and between 6 and 7 yr from the mid-18th to the early 20th century.At decadal time scales each record generally tends to exhibit significant spectral power over different periods at different times. Both the Quelccaya Ice Cap ¹⁸O series and the Quinn El Niño event record exhibit significant spectral power over frequencies ~ 35 to 45 yr; however, there is low coherence between these two series at those frequencies over their common record. The Sierra Nevada winter rainfall reconstruction exhibits consistently strong variability at periods of ~ 30–60 yr.     

Low-frequency oscillations in climatic and hydrological variables in southern South America’s tropical-subtropical regions

Summary The existence of low-frequency variability in climatic-hydrological-oceanic variables may be useful for long-term forecasting and climate modelling. By using long time series this paper attempts to identify large-scale quasi-cycles in the precipitation regimes of Northern Argentina, moisture advection from the Atlantic Ocean and the streamflow of the Paraná River. This work also shows the presence of coherent waves with long periodicity between the three series. As the three variables are estimated over different time intervals, the presence of waves in each variable is studied separately, to show they respond to the same process. The three variables show significant interdecadal variability at low frequency (22–26 years), which might be related to the ENSO cycle modulation and to the intensification or weakening of the South American Low Level Jet (SALLJ) and South Atlantic Convergence Zone (SACZ).     

Trends and Variability in Sea Ice and Icebergs off the Canadian East Coast

ABSTRACT

Seasonal time series of sea-ice area or extent in several regions along the east coast of Canada were compiled from several sources for the period 1901 to 2013 and compared with an index of ice extent off southwest Greenland, iceberg season length south of 48°N, air temperature, and other climate indices. Trends in winter ice area and iceberg season length are significant over the past 100 years and 30 years. Variability of winter ice area and iceberg season length is associated with a combination of the North Atlantic Oscillation (NAO) and the Atlantic Multidecadal Oscillation (AMO) indices superimposed on a negative trend. Thus, large declines in ice area and iceberg season length in the 1920s and 1990s can be attributed to a decreasing NAO index and a shift to the positive phase of the AMO at the end of these decades. Ice extent in southern areas such as the Scotian Shelf is more strongly correlated with the Western Atlantic index than with the NAO. Ice area trends (in percent per decade) are larger in magnitude and account for twice as much of the variance in ice area for summer than for winter, with summer trends significant over 30-, 60- and 100-year periods. Sea-ice variability is generally consistent with air temperature variability in the various regions; in the 1930s, during the early twentieth-century warming period, ice anomalies were higher and temperature anomalies were lower along the coast of eastern Canada than along the coast of southwestern Greenland.     

Investigation of ENSO variability using cyclostationary EOFs of observational data

Summary ?The variability of El Ni?o-Southern Oscillation (ENSO) on all time scales, ranging from months to decades, has been studied from the perspective of sea-surface temperature anomaly (SSTA), sea-level pressure anomaly (SLPA), and surface wind anomaly (SWA) fields using a statistical tool called cyclostationary empirical orthogonal function (CSEOF) analysis. The analysis indicates that a significant fraction of variability in the tropical Pacific can be explained in terms of an irregular interplay of two dominant modes: the low-frequency mode and the biennial mode. These modes, and in particular the biennial mode, are well defined coupled modes of the tropical ocean-atmospheric circulation system, as suggested by strong correlation (> 0.9) in the evolution of the different physical variables. The low-frequency mode and its PC time series are very similar to the so-called “interdecadal” mode identified by earlier investigators. The corresponding PC time series of the low-frequency mode has a broad spectral peak at 5.3 yrs. The biennial mode represents the oscillation pattern of El Ni?o and La Ni?a and has a clear biennial cycle, the amplitude of which varies on a longer time scale. There is a broad spectral peak also at 5.3 yrs in the principal component (PC) time series of this mode. Unlike in earlier studies, this biennial mode is clearly separable from the low-frequency mode, since these two modes have different physical evolution patterns. Results of the present study also indicate that the biennial component, having a clear phase-locking tendency, is not as variable as has been suggested in some previous investigations. It is shown that much of the inter-El Ni?o variability can be explained in terms of an irregular interplay between the biennial mode and the low-frequency mode. Finally, the role of the low-frequency mode in the tropical Pacific seems to be more important than has been suggested previously. Specifically, recent warming events since 1975 are shown to be associated with the low-frequency mode rather than with the biennial mode. Received August 15, 2001; revised March 6, 2002     

Decadal time scale variability recorded in the Quelccaya summit ice core δ18O isotopic ratio series and its relation with the sea surface temperature

 The spectral characteristics of the δ¹⁸O isotopic ratio time series of the Quelccaya ice cap summit core are investigated with the multi taper method (MTM), the singular spectrum analysis (SSA) and the wavelet transform (WT) techniques for the 500 y long 1485–1984 period. The most significant (at the 99.8% level) cycle according to the MTM F-test has a period centered at 14.4 y while the largest variance explaining oscillation according to the SSA technique has a period centered at 12.9 y. The stability over time of these periods is investigated by performing evolutive MTM and SSA on the 500 y long δ¹⁸O series with a 100 y wide moving window. It is shown that the cycles with largest amplitude and that the oscillations with largest extracting variance have corresponding periods aggregated around 13.5 y that are very stable over the period between 1485 and 1984. The WT of the same isotopic time series reveals the existence of a main oscillation around 12 y which are also very stable in time. The relation between the isotopic data at Quelccaya and the annual sea surface temperature (SST) field anomalies is then evaluated for the overlapping 1919–1984 period. Significant global correlation and significant coherency at 12.1 y are found between the isotopic series and the annual global sea surface temperature (GSST) series. Moreover, the correlation between the low (over 8 y) frequency component of the isotopic time series and the annual SST field point out significant values in the tropical North Atlantic. This region is characterized by a main SST variability at 12.8 y. The Quelccaya δ¹⁸O isotopic ratio series may therefore be considered as a good recorder of the tropical North Atlantic SSTs. This may be explained by the following mechanism: the water vapor amount evaporated by the tropical North Atlantic is function of the SST. So is the water vapor δ¹⁸O isotopic ratio. This water vapor is advected during the rainy season by northeast winds and precipitates at the Quelccaya summit with its tropical North Atlantic isotopic signature. It is also suggested from this described stability of the decadal time scale variability observed in the Quelccaya isotopic series, that the decadal time scale GSST variability was also stable during the last five centuries. Received: 12 February 1997 / Accepted: 9 September 1997     

Climate spectra and detecting climate change

Part of the debate over possible climate changes centers on the possibility that the changes observed over the previous century are natural in origin. This raises the question of how large a change could be expected as a result of natural variability. If the climate measurement of interest is modelled as a stationary (or related) Gaussian time series, this question can be answered in terms of (a) the way in which change is estimated, and (b) the spectrum of the time series. These computations are illustrated for 128 years of global temperature data using some simple measures of change and for a variety of possible temperature spectra. The results highlight the time scales on which it is important to know the magnitude of natural variability. The uncertainties in estimates of trend are most sensitive to fluctuations in the temperature series with periods from approximately 50 to 500 years. For some of the temperature spectra, it was found that the standard error of the least squares trend estimate was 3 times the standard error derived under the naïve assumption that the temperature series was uncorrelated. The observed trend differs from zero by more than 3 times the largest of the calculated standard errors, however, and is therefore highly significant.     

Snow cover variability across central Canada (1978–2002) derived from satellite passive microwave data

Twenty-four winter seasons (1978–2002) of mean February snow water equivalent (SWE) values were analyzed in an exploration of the spatial pattern of temporal variability in snow cover across the non-mountainous interior of Canada. The SWE data were derived from space-borne passive microwave brightness temperatures processed with a land cover-sensitive suite of algorithms. Spatial patterns in the frequency and amount of variability were investigated on an annual basis through comparisons with average trends over all 24 years. Changes in temporal variability through time were also investigated by comparing three eight year time periods to general trends. Analyses were synthesized at the ecozone scale in order to link results both to potential land cover influences on algorithm performance and climatological variability in SWE. Prairie and northern ecozones were typically found to be the most variable in terms of SWE magnitude. Analyses indicate that non-treed land cover classes are generally more variable than treed classes. The results also indicate that extreme weather events appear to be occurring with increasing consistency in the Prairie and Arctic regions. Discerning climatologically significant variability in the time series, compared to algorithm-related issues can be a challenge, but in an era of eroding surface observing networks the passive microwave time series represents an important resource for monitoring and detecting trends and variability in terrestrial snow cover.     

Factors that affect the amplitude of El Nino in global coupled climate models

Historically, El Nino-like events simulated in global coupled climate models have had reduced amplitude compared to observations. Here, El Nino-like phenomena are compared in ten sensitivity experiments using two recent global coupled models. These models have various combinations of horizontal and vertical ocean resolution, ocean physics, and atmospheric model resolution. It is demonstrated that the lower the value of the ocean background vertical diffusivity, the greater the amplitude of El Nino variability which is related primarily to a sharper equatorial thermocline. Among models with low background vertical diffusivity, stronger equatorial zonal wind stress is associated with relatively higher amplitude El Nino variability along with more realistic east–west sea surface temperature (SST) gradient along the equator. The SST seasonal cycle in the eastern tropical Pacific has too much of a semiannual component with a double intertropical convergence zone (ITCZ) in all experiments, and thus does not affect, nor is it affected by, the amplitude of El Nino variability. Systematic errors affecting the spatial variability of El Nino in the experiments are characterized by the eastern equatorial Pacific cold tongue regime extending too far westward into the warm pool. The time scales of interannual variability (as represented by time series of Nino3 SSTs) show significant power in the 3–4 year ENSO band and 2–2.5 year tropospheric biennial oscillation (TBO) band in the model experiments. The TBO periods in the models agree well with the observations, while the ENSO periods are near the short end of the range of 3–6 years observed during the period 1950–94. The close association between interannual variability of equatorial eastern Pacific SSTs and large-scale SST patterns is represented by significant correlations between Nino3 time series and the PC time series of the first EOFs of near-global SSTs in the models and observations. Received: 17 April 2000 / Accepted: 17 August 2000     

Summer temperatures in the Canadian Rockies during the last millennium: a revised record

We present a significant update to a millennial summer temperature reconstruction (1073–1983) that was originally published in 1997. Utilising new tree-ring data (predominantly Picea engelmannii), the reconstruction is not only better replicated, but has been extended (950–1994) and is now more regionally representative. Calibration and verification statistics were improved, with the new model explaining 53% of May–August maximum temperature variation compared to the original (39% of April–August mean temperatures). The maximum latewood density data, which are weighted more strongly in the regression model than ringwidth, were processed using regional curve standardisation to capture potential centennial to millennial scale variability. The reconstruction shows warm intervals, comparable to twentieth century values, for the first half of the eleventh century, the late 1300s and early 1400s. The bulk of the record, however, is below the 1901–1980 normals, with prolonged cool periods from 1200 to 1350 and from 1450 to the late 19th century. The most extreme cool period is observed to be in the 1690s. These reconstructed cool periods compare well with known regional records of glacier advances between 1150 and the 1300s, possibly in the early 1500s, early 1700s and 1800s. Evidence is also presented of the influence of solar activity and volcanic events on summer temperature in the Canadian Rockies over the last 1,000 years. Although this reconstruction is regional in scope, it compares well at multi-decadal to centennial scales with Northern Hemisphere temperature proxies and at millennial scales with reconstructions that were also processed to capture longer timescale variability. This coherence suggests that this series is globally important for the assessment of natural temperature variability over the last 1,000 years.Authors are listed alphabetically     

Spatiotemporal analysis of particulate matter, sulfur dioxide and carbon monoxide concentrations over the city of Rio de Janeiro, Brazil

Time series of pollutants and weather variables measured at four sites in the city of Rio de Janeiro, Brazil, between 2002 and 2004, were used to characterize temporal and spatial relationships of air pollution. Concentrations of particulate matter (PM₁₀), sulfur dioxide (SO₂) and carbon monoxide (CO) were compared to national and international standards. The annual median concentration of PM₁₀ was higher than the standard set by the World Health Organization (WHO) on all sites and the 24?h means exceeded the standards on several occasions on two sites. SO₂ and CO did not exceed the limits, but the daily maximum of CO in one of the stations was 27% higher on weekends compared to weekdays, due to increased activity in a nearby Convention Center. Air temperature and vapor pressure deficit have both presented the highest correlations with pollutant??s concentrations. The concentrations of SO₂ and CO were not correlated between sites, suggesting that local sources are more important to those pollutants compared to PM₁₀. The time series of pollutants and air temperature were decomposed in time and frequency by wavelet analysis. The results revealed that the common variability of air temperature and PM₁₀ is dominated by temporal scales of 1?C8?days, time scales that are associated with the passage of weather events, such as cold fronts.     

Linking Arctic sea‐ice and atmospheric circulation anomalies on interannual and decadal timescales

Abstract

The relationship between Arctic sea‐ice concentration anomalies, particularly those associated with the “Great Salinity Anomaly” of 1968–1982, and atmospheric circulation anomalies north of 45°N is investigated. Empirical orthogonal function (EOF) analyses are performed on winter Arctic ice concentration from 1954 to 1990, sea level pressure and 500‐hPa heights from 1947 to 1994, and 850‐hPa temperatures from 1963 to 1994. Variability on both interannual and decadal timescales is apparent in the time series of the leading winter EOFs of all variables. The first EOF of winter sea‐ice concentration was found to characterize the patterns of ice variability associated with the Great Salinity Anomaly in the northern North Atlantic from 1968–82. Spatial maps of temporal correlation coefficients between the time series of the first EOF of winter sea‐ice concentration and the winter atmospheric anomaly fields are calculated at lags of 0 and ±7 year. Maximum correlations were found to exist when the time‐series of this ice EOF 1 leads the atmospheric anomaly fields by one year. A particularly interesting result is the connection between the presence of ice anomalies in the Greenland and Barents Seas and subsequent pressure anomalies of the same sign over the Irminger Basin and the Canadian Arctic. The main emphasis of the paper is to identify connections between Arctic sea‐ice and atmospheric circulation anomalies at interannual time‐scales.     

Short-period temperature variability at Winnipeg, Canada, 1872–1993: Characteristics and trends

Summary Temperature variability in Winnipeg, Canada, was assessed by determining average and extreme temperature ranges over 1, 2, 5, 10, and 15-day intervals, on a monthly basis, for the period of 1872–1993. Trends in the monthly averages for each of the intervals were also examined.The results show that Winnipeg experiences a very large amount of short-term temperature variability, especially over 2, 5, 10 and 15 days. The monthly average diurnal ranges vary from about 9 to 14 °C, while the 15-day average ranges are about two to three times as large. In general, average temperature ranges over the two shortest intervals (1 and 2 days) are slightly greater in the warm-season months than in the cold-season months, but the averages for the three longest intervals are inversely related to mean monthly temperature, as are the largest ranges observed in each of the months.Average temperature variability in the months of November through March was found to have decreased quite significantly, and rapidly, during the first two decades of this century. This decrease was likely associated with a decrease in the meridionality of the atmospheric circulation. It also occurred during a time when the average maximum and minimum temperatures in Winnipeg were rising, lending support to the conjecture that a warmer global climate will result in less 1–15 day temperature variability. The rapidity of the change also supports the hypothesis that climate changes tend to be non-linear.With 5 Figures     

Future trend of extreme value distributions of wintertime surface air temperatures over Korea and the associated physical changes

Daily winter temperatures in Korea have been analyzed via CSEOF analysis. Then, each PC time series was detrended and was fitted to an AR (autoregressive) model. Based on the identified AR model, an artificial time series of arbitrary length can be generated by using an arbitrary white-noise time series. In this way, one hundred new sets of PC time series were generated over the period of 1973–2058. Then, the trend for each PC time series was added back to the artificial PC time series extending the trend until 2058. Ultimately, artificial daily winter temperatures in Korea have been constructed by using the artificial PC time series and the original loading vectors derived from the observational data. The 100 new data sets have been investigated in order to understand the winter temperature variability 50 years into the future. Regression analysis in CSEOF space shows that temperature increase in Korea is associated with increased 850-hPa air temperature over most of the Asian domain (97°-153°E × 22°-73°N) and increased 850-hPa geopotential height in the southern part of the domain. As a result, southerly and southeasterly wind anomalies develop carrying positive temperature anomalies northward and northwestward. Both the 200-hPa air temperature and geopotential height changes indicate that there will be fairly significant northward shift of the jet stream in future. The standard deviation of the 200-hPa potential vorticity increases implying that shortwave trough and henceforth baroclinic instability will increase in future. Finally, GEV (Generalized Extreme Value) distribution and GPD (Generalized Pareto distribution) distribution have been compared between the observational records and the future records of the same length. The extreme value distributions based on the synthetic datasets show that warm extreme events will be more extreme in future and cold extreme events, on the other hand, will be less extreme. This study provides an estimate of future temperatures based on the observational data and serves as an independent baseline solution for comparisons with numerical model solutions.     

Global Warming and the Greenland Ice Sheet

The Greenland coastal temperatures have followed the early 20th century global warming trend. Since 1940, however, the Greenland coastal stations data have undergone predominantly a cooling trend. At the summit of the Greenland ice sheet the summer average temperature has decreased at the rate of 2.2 °C per decade since the beginning of the measurements in 1987. This suggests that the Greenland ice sheet and coastal regions are not following the current global warming trend. A considerable and rapid warming over all of coastal Greenland occurred in the 1920s when the average annual surface air temperature rose between 2 and 4 °C in less than ten years (at some stations the increase in winter temperature was as high as 6 °C). This rapid warming, at a time when the change in anthropogenic production of greenhouse gases was well below the current level, suggests a high natural variability in the regional climate. High anticorrelations (r = ?0.84 to?0.93) between the NAO (North Atlantic Oscillation) index and Greenland temperature time series suggest a physical connection between these processes. Therefore, the future changes in the NAO and Northern Annular Mode may be of critical consequence to the future temperature forcing of the Greenland ice sheet melt rates.     

THE IMPACT OF CLIMATE CHANGE ON THE SNOW COVER PATTERN IN ESTONIA

The paper deals with problems of temporal and spatial variability of snow cover duration, of correlation between snow cover and winter mean air temperature patterns and of the impact of climate change on the snow cover pattern in Estonia. Snow cover fields are presented in form of IDRISI raster images. Snow cover duration measured at ca 100 stations and observation points have been interpolated into raster cells. On the base of time series of raster images, a map of mean territorial distribution of snow cover duration is calculated. Estonia is characterized by a great spatial variability of snow cover mostly caused by the influence of the Baltic Sea. General regularities of snow cover pattern are determined. A 104-year time series of spatial mean values of snow cover duration is composed and analyzed. A decreasing trend and periodical fluctuations have detected. Standardized principal component analysis is used for the time series of IDRISI raster images. It enables to study the influence of different factors on the formation of snow cover fields and territorial extent of coherent fluctuations. Correlation between snow cover duration and winter mean air temperature fields is analyzed. A spatial regression model is created for estimation of the influence of climate change on snow cover pattern in Estonia. Using incremental climate change scenarios (2 °C, 4 °C and 6 °C of warming in winter) mean decrease of snow cover duration in different regions in Estonia is calculated. According to results of model calculation, the highest decrease of snow cover duration will be take place on islands and in the coastal region of West Estonia. A permanent snow cover may not form at all. In the areas with maximum snow cover duration in North-East and South-East Estonia, that decrease should be much lower.