scholarly journals Connecting European snow cover variability with large scale atmospheric patterns

2010 ◽  
Vol 26 ◽  
pp. 93-97 ◽  
Author(s):  
E. Bartolini ◽  
P. Claps ◽  
P. D'Odorico

Abstract. Winter snowfall and its temporal variability are important factors in the development of water management strategies for snow-dominated regions. For example, mountain regions of Europe rely on snow for recreation, and on snowmelt for water supply and hydropower. It is still unclear whether in these regions the snow regime is undergoing any major significant change. Moreover, snow interannual variability depends on different climatic variables, such as precipitation and temperature, and their interplay with atmospheric and pressure conditions. This paper uses the EASE Grid weekly snow cover and Ice Extent database from the National Snow and Ice Data Center to assess the possible existence of trends in snow cover across Europe. This database provides a representation of snow cover fields in Europe for the period 1972–2006 and is used here to construct snow cover indices, both in time and space. These indices allow us to investigate the historical spatial and temporal variability of European snow cover fields, and to relate them to the modes of climate variability that are known to affect the European climate. We find that both the spatial and temporal variability of snow cover are strongly related to the Arctic Oscillation during wintertime. In the other seasons, weaker correlation appears between snow cover and the other patterns of climate variability, such as the East Atlantic, the East Atlantic West Russia, the North Atlantic Oscillation, the Polar Pattern and the Scandinavian Pattern.

2009 ◽  
Vol 22 (16) ◽  
pp. 4348-4372 ◽  
Author(s):  
Anne Marie K. Stoner ◽  
Katharine Hayhoe ◽  
Donald J. Wuebbles

Abstract The ability of coupled atmosphere–ocean general circulation models (AOGCMs) to simulate variability in regional and global atmospheric dynamics is an important aspect of model evaluation. This is particularly true for recurring large-scale patterns known to be correlated with surface climate anomalies. Here, the authors evaluate the ability of all Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) historical Twentieth-Century Climate in Coupled Models (20C3M) AOGCM simulations for which the required output fields are available to simulate three patterns of large-scale atmospheric internal variability in the North Atlantic region: the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), and the Atlantic multidecadal oscillation (AMO); and three in the North Pacific region: the El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the Pacific–North American Oscillation (PNA). These patterns are evaluated in two ways: first, in terms of their characteristic temporal variability and second, in terms of their magnitude and spatial locations. It is found that historical total-forcing simulations from many of the AOGCMs produce seasonal spatial patterns that clearly resemble the teleconnection patterns resulting from identical calculation methods applied to reanalysis and/or observed fields such as the 40-yr ECMWF Re-Analysis, NCEP–NCAR, or Kaplan sea surface temperatures (SSTs), with the exception of the lowest-frequency pattern, AMO, which is only reproduced by a few models. AOGCM simulations also show some significant biases in both spatial and temporal characteristics of the six patterns. Many models tend to either under- or overestimate the strength of the spatial patterns and exhibit rotation about the polar region or east–west displacement. Based on spectral analysis of the time series of each index, models also appear to vary in their ability to simulate the temporal variability of the teleconnection patterns, with some models producing oscillations that are too fast and others that are too slow relative to those observed. A few models produce a signal that is too periodic, most likely because of a failure to adequately simulate the natural chaotic behavior of the atmosphere. These results have implications for the selection and use of specific AOGCMs to simulate climate over the Northern Hemisphere, with some models being clearly more successful at (i.e., displaying less bias in) simulating large-scale, low-frequency patterns of temporal and spatial variability over the North Atlantic and Pacific regions relative to others.


2007 ◽  
Vol 38 (1) ◽  
pp. 45-58 ◽  
Author(s):  
M. Reza Ghanbarpour ◽  
Bahram Saghafian ◽  
Mohsen M. Saravi ◽  
Karim C. Abbaspour

Determination of snow characteristics in mountainous basins is difficult due to the complex spatial and temporal variability of snow cover. Accurate representation of snow cover variations in space and time is an important factor in snowmelt modeling, hydrological forecasts, water resources planning, and drought management. This study demonstrates how remotely sensed data can complement the measurements of ground hydro-meteorological data to simulate the spatial and temporal variations of snow cover characteristics in a mountainous basin. In this paper, we studied Karun basin, located in the south west of Iran, because of its importance in accumulating large snow reserves, and subsequently contributing snowmelt to the total runoff. Snow cover variability was simulated by extraction of maps of snow cover indices using remotely sensed data. Contribution of snowmelt to the runoff was determined using a seasonal water balance model as well as estimations based on indirect approaches by modeling variables such as critical temperature, which is an important variable in snow studies. Agreement between indirect approaches used in this paper is an encouraging result that shows the reliability of the procedure where snow data is scarce. The results of correlation analysis between topographic and meteorological variables with snow cover indices suggested that elevation is the single most important variable on large-scale snow variability.


2007 ◽  
Vol 46 (4) ◽  
pp. 445-456 ◽  
Author(s):  
Katherine Klink

Abstract Mean monthly wind speed at 70 m above ground level is investigated for 11 sites in Minnesota for the period 1995–2003. Wind speeds at these sites show significant spatial and temporal coherence, with prolonged periods of above- and below-normal values that can persist for as long as 12 months. Monthly variation in wind speed primarily is determined by the north–south pressure gradient, which captures between 22% and 47% of the variability (depending on the site). Regression on wind speed residuals (pressure gradient effects removed) shows that an additional 6%–15% of the variation can be related to the Arctic Oscillation (AO) and Niño-3.4 sea surface temperature (SST) anomalies. Wind speeds showed little correspondence with variation in the Pacific–North American (PNA) circulation index. The effect of the strong El Niño of 1997/98 on the wind speed time series was investigated by recomputing the regression equations with this period excluded. The north–south pressure gradient remains the primary determinant of mean monthly 70-m wind speeds, but with 1997/98 removed the influence of the AO increases at nearly all stations while the importance of the Niño-3.4 SSTs generally decreases. Relationships with the PNA remain small. These results suggest that long-term patterns of low-frequency wind speed (and thus wind power) variability can be estimated using large-scale circulation features as represented by large-scale climatic datasets and by climate-change models.


2017 ◽  
Vol 8 (4) ◽  
pp. 963-976 ◽  
Author(s):  
Jaak Jaagus ◽  
Mait Sepp ◽  
Toomas Tamm ◽  
Arvo Järvet ◽  
Kiira Mõisja

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting of trends and regime shifts during 1951–2015. Trend analysis is realised using the Mann–Kendall test and regime shifts are detected with the Rodionov test (sequential t-test analysis of regime shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at all 12 stations by 0.3–0.4 K decade−1. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days decade−1. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March and also in June. A time series of specific runoff measured at 21 stations had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 L s−1 km−2 decade−1, while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May have notably decreased indicating the shift of the runoff maximum to the earlier time, i.e. from April to March. Air temperature, precipitation, snow cover duration and specific runoff of rivers are highly correlated in winter determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter of 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in annual specific runoff correspond to the alternation of wet and dry periods. A dry period started in 1964 or 1963, a wet period in 1978 and the next dry period at the beginning of the 21st century.


2014 ◽  
Vol 7 (11) ◽  
pp. 3917-3926 ◽  
Author(s):  
J. M. Intrieri ◽  
G. de Boer ◽  
M. D. Shupe ◽  
J. R. Spackman ◽  
J. Wang ◽  
...  

Abstract. In February and March of 2011, the Global Hawk unmanned aircraft system (UAS) was deployed over the Pacific Ocean and the Arctic during the Winter Storms and Pacific Atmospheric Rivers (WISPAR) field campaign. The WISPAR science missions were designed to (1) mprove our understanding of Pacific weather systems and the polar atmosphere; (2) evaluate operational use of unmanned aircraft for investigating these atmospheric events; and (3) demonstrate operational and research applications of a UAS dropsonde system at high latitudes. Dropsondes deployed from the Global Hawk successfully obtained high-resolution profiles of temperature, pressure, humidity, and wind information between the stratosphere and surface. The 35 m wingspan Global Hawk, which can soar for ~ 31 h at altitudes up to ~ 20 km, was remotely operated from NASA's Dryden Flight Research Center at Edwards Air Force Base (AFB) in California. During the 25 h polar flight on 9–10 March 2011, the Global Hawk released 35 sondes between the North Slope of Alaska and 85° N latitude, marking the first UAS Arctic dropsonde mission of its kind. The polar flight transected an unusually cold polar vortex, notable for an associated record-level Arctic ozone loss, and documented polar boundary layer variations over a sizable ocean–ice lead feature. Comparison of dropsonde observations with atmospheric reanalyses reveal that, for this day, large-scale structures such as the polar vortex and air masses are captured by the reanalyses, while smaller-scale features, including low-level jets and inversion depths, are mischaracterized. The successful Arctic dropsonde deployment demonstrates the capability of the Global Hawk to conduct operations in harsh, remote regions. The limited comparison with other measurements and reanalyses highlights the potential value of Arctic atmospheric dropsonde observations where routine in situ measurements are practically nonexistent.


2019 ◽  
Vol 59 (2) ◽  
pp. 233-244
Author(s):  
V. I. Batuev ◽  
I. L. Kalyuzhny

Long-term complex observations covering the period of 1949–2018 made possible to determine the average annual characteristics of the depth of freezing of wetlands in the North and Northwest of the European territory of Russia together with main factors of its formation, and spatial and temporal variability. The main factors that determine the depth of freezing of wetlands are ambient temperature, snow cover thickness, and a degree of watering of the micro landscape (water reserves of the micro landscape). At the initial stage of freezing, the major factor is the ambient temperature, when intensity of the freezing reaches 0.5–0.8 cm/day. As snow falls, the freezing rate becomes smaller, and when the snow cover thickness reaches 25–30 cm the depth amounts to 0.2–0.3 cm/day and smaller. It was found that the spatial variability of the freezing depth decreases from large values of the coefficient of variation (0.3–0.4) at the depth of 20–30 cm to less than 0.1 when the depth exceeds 60 cm. The largest values of the depth are recorded in the North of the Kola Peninsula, where sometimes they reach from 84 to 97 cm with the average values of 48–66. In large hummocky bogs, when the seasonal freezing comes down to 63–65 cm it links with the permafrost layer. On average, swamps of these bogs freeze down to a depth of 68 cm. The average climatic depth of freezing of oligotrophic bogs of the NorthWest is 21–24 cm; in some years, freezing of them reaches 32–40 cm. It has been shown that the relative warming of the climate resulted in decreasing in the depth of freezing of wetlands in the North and North-West of the European territory of Russia. Relative to the previous climatic period, the depth of frost penetration in the northern Ilasskoye bog decreased by 32%, and in north-western Lammin-Suo bog – by 31%.


2020 ◽  
pp. 104-130
Author(s):  
Marianne Mithun

Much of linguistic typology is inherently categorical. In large-scale typological surveys, grammatical constructions, distinctions, and even variables are typically classified as present, absent, or embodying one of a set of specified options. This work is valuable for a multitude of purposes, and in many cases such categorization is sufficient. In others, we can advance our understanding further if we take a more nuanced approach, considering the extent to which a particular construction, distinction, or variable is installed in the grammar. An important tool for this approach is the examination of unscripted speech in context, complete with prosody. This point is illustrated here with Mohawk, an Iroquoian language indigenous to the North American Northeast. As will be seen, the two types of construction which might be identified as relative clauses are emergent, one less integrated into the grammar than the other. Examination of spontaneous speech indicates that the earliest stages of development are prosodic, as speakers shape their messages according to their communicative purposes at each moment.


Author(s):  
Stuart H. Gage

This chapter examines the spatial and temporal variability and patterns of climate for the period 1972–1991 in the North Central Region of North America (NCR). Since the mid-1970s, climate has become more variable in the region, compared to the more benign period 1950–1970. The regional perspective presented in this chapter characterizes the general climatology of the NCR from 1972 to 1991 and compares the climate to a severe drought that occurred in 1988. This one-year drought was one of the most substantial in the region’s recent history, and it had a significant impact on the region’s agricultural economy and ecosystems. Petersen et al. (1995) characterize the 1988 drought with respect to solar radiation, and Zangvil et al. (2001) consider this drought from the perspective of a large-scale atmosphere moisture budget. A major reason for the seriousness of the drought in 1988 was the fact that May and June were unusually dry and hot (Kunkel and Angel 1989). Drought is defined as a condition of moisture deficit sufficient to adversely affect vegetation, animals, and humans over a sizeable area (Warwick 1975). The condition of drought may be considered from a meteorological, agricultural, and hydrologic perspective. Meteorological drought is a period of abnormally dry weather sufficiently prolonged to a point where the lack of water causes a serious hydrologic imbalance in the affected area (Huschke 1959). Agricultural drought is a climatic digression involving a shortage of precipitation sufficient to adversely affect crop production or the range of production (Rosenberg 1980). Hydrologic drought is a period of below-average water content in streams, reservoirs, groundwater aquifers, lakes, and soils (Yevjevich et al. 1977). All of these drought conditions are mutually linked. The objectives of this chapter are to (1) address the issues of climatic spatial scale to quantify variability of climate in the NCR, (2) examine the characteristics of the 1988 drought as it relates to characteristics of an ecoregion, (3) illustrate a means to quantify drought through a potential plant stress index, and (4) examine the link of regional drought to ecosystem processes. This analysis will provide background and methodology for ecologists, agriculturalists, and others interested in spatial and temporal characterization of climate patterns within large geographic regions.


2017 ◽  
Vol 21 (4) ◽  
pp. 2163-2185 ◽  
Author(s):  
Jefferson S. Wong ◽  
Saman Razavi ◽  
Barrie R. Bonsal ◽  
Howard S. Wheater ◽  
Zilefac E. Asong

Abstract. A number of global and regional gridded climate products based on multiple data sources are available that can potentially provide reliable estimates of precipitation for climate and hydrological studies. However, research into the consistency of these products for various regions has been limited and in many cases non-existent. This study inter-compares several gridded precipitation products over 15 terrestrial ecozones in Canada for different seasons. The spatial and temporal variability of the errors (relative to station observations) was quantified over the period of 1979 to 2012 at a 0.5° and daily spatio-temporal resolution. These datasets were assessed in their ability to represent the daily variability of precipitation amounts by four performance measures: percentage of bias, root mean square error, correlation coefficient, and standard deviation ratio. Results showed that most of the datasets were relatively skilful in central Canada. However, they tended to overestimate precipitation amounts in the west and underestimate in the north and east, with the underestimation being particularly dominant in northern Canada (above 60° N). The global product by WATCH Forcing Data ERA-Interim (WFDEI) augmented by Global Precipitation Climatology Centre (GPCC) data (WFDEI [GPCC]) performed best with respect to different metrics. The Canadian Precipitation Analysis (CaPA) product performed comparably with WFDEI [GPCC]; however, it only provides data starting in 2002. All the datasets performed best in summer, followed by autumn, spring, and winter in order of decreasing quality. Findings from this study can provide guidance to potential users regarding the performance of different precipitation products for a range of geographical regions and time periods.


2016 ◽  
Author(s):  
Luca Pozzoli ◽  
Srdan Dobricic ◽  
Simone Russo ◽  
Elisabetta Vignati

Abstract. Winter warming and sea ice retreat observed in the Arctic in the last decades determine changes of large scale atmospheric circulation pattern that may impact as well the transport of black carbon (BC) to the Arctic and its deposition on the sea ice, with possible feedbacks on the regional and global climate forcing. In this study we developed and applied a new statistical algorithm, based on the Maximum Likelihood Estimate approach, to determine how the changes of three large scale weather patterns (the North Atlantic Oscillation, the Scandinavian Blocking, and the El Nino-Southern Oscillation), associated with winter increasing temperatures and sea ice retreat in the Arctic, impact the transport of BC to the Arctic and its deposition. We found that the three atmospheric patterns together determine a decreasing winter deposition trend of BC between 1980 and 2015 in the Eastern Arctic while they increase BC deposition in the Western Arctic. The increasing trend is mainly due to the more frequent occurrences of stable high pressure systems (atmospheric blocking) near Scandinavia favouring the transport in the lower troposphere of BC from Europe and North Atlantic directly into to the Arctic. The North Atlantic Oscillation has a smaller impact on BC deposition in the Arctic, but determines an increasing BC atmospheric load over the entire Arctic Ocean with increasing BC concentrations in the upper troposphere. The El Nino-Southern Oscillation does not influence significantly the transport and deposition of BC to the Arctic. The results show that changes in atmospheric circulation due to polar atmospheric warming and reduced winter sea ice significantly impacted BC transport and deposition. The anthropogenic emission reductions applied in the last decades were, therefore, crucial to counterbalance the most likely trend of increasing BC pollution in the Arctic.


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