Mass balances of Scandinavian glaciers are mainly influenced by winter precipitation and summer temperature. We used simple statistical models to assess the relative importance of summer temperature and winter precipitation for annual balances of eight glaciers in Scandinavia. Winter precipitation was more important for maritime glaciers, whereas summer temperature was more important for annual balances of continental glaciers. Most importantly relative importances of summer temperature and winter precipitation were not stable in time. For instance, winter precipitation was more important than summer temperature for all glaciers in the 25-year period 1972–1996, whereas the relative importance of summer temperature was increasing towards the present. Between 1963 and 1996 the Atlantic Multidecadal Oscillation (AMO) index was consistently negative and the North Atlantic Oscillation (NAO) Index was consistently positive between 1987 and 1995, both being favourable for glacier growth. Winter precipitation was more important than summer temperature for annual balances when only considering subsets of years with high NAO-index and negative AMO-index, respectively, whereas the importance of summer temperature was increased analysing subsets of years with low NAO-index and positive AMO-index, respectively. Hence, the relative importance of precipitation and temperature for mass balances was probably influenced by the state of the AMO and the NAO, as these two indexes are associated with changes in summer temperature (AMO) and winter precipitation (NAO).
Glaciers respond to climate change because their mass balance and extent are
mainly a result of variations in winter accumulation and summer ablation.
Over time, glacier changes exhibit some of the clearest evidence of
variations in the earth's climate system. As a result, glaciers are key
indicators of global, regional and local climate change (IPCC, 2007, 2013).
Past (e.g. Nesje, 2009), present (e.g. Andreassen and Oerlemans, 2009) and
future (e.g. Giesen and Oerlemans, 2010) of Scandinavian glaciers has been studied
extensively. The accumulation on Scandinavian glaciers is mainly a result of
winter precipitation (as snow) and wind redistribution of snow, whereas
glacier ablation is more complex and depends on the total energy available
for melt. Accumulation and ablation processes of Scandinavian glaciers have
been extensively studied by means of mass balance models of varying
complexity (e.g. Andreassen et al., 2006; Andreassen and Oerlemans, 2009;
Engelhardt et al., 2013; Giesen and Oerlemans, 2010; Hock et al., 2007;
Laumann and Nesje, 2009a, b, 2014; Oerlemans, 1992, 1997; Rasmussen and
Conway, 2005; Rasmussen et al., 2007; Schuler et al., 2005). Most of these
studies have focused on estimating sensitivities of winter balances, summer
balances and annual balances to changes in temperature and precipitation.
Many studies provided projections of future mass balances based on climate
projections (e.g. Giesen and Oerlemans, 2010). Climate sensitivities are
absolute influences of temperature and precipitation changes on mass
balances. They are, however, measured in different units and are therefore
difficult to compare directly (
Further studies have explicitly assessed the relative importance of winter
balance and summer balance for annual balance by correlating the summer and
winter balances with annual balance (Nesje et al., 2000). Nesje et al. (2000)
showed that the correlation between winter balance and annual balance is
higher than the correlation between summer balance and annual balance for
maritime glaciers and vice versa for continental glaciers. Mernild et
al. (2014) replicated this analysis using data from 1970 to 2009. Andreassen
et al. (2005) used ratios of standard deviations of winter balances (sBw) to
standard deviations of annual balances (sBa, sBw
Assessing the relative importance of seasonally averaged summer temperature and winter precipitation for annual balances and possible changes in time is especially interesting in light of palaeoclimatological interpretation of glacier records. In palaeoclimatology, at best summer temperature, winter precipitation and annual balance reconstructions are available and attempts have been made to reconstruct winter precipitation based on glacier reconstructions and independent summer temperature reconstructions (e.g. Bakke et al., 2005).
There are well-known transient phases of positive annual balances (e.g. 1987–1995, e.g. Nesje et al., 2000). It is therefore interesting to assess if the relative importance of summer temperature and winter precipitation for annual balance changes through time. Until now, attempts of quantifying temporal changes of summer balance and winter balance on annual balance have been constrained to estimating running means of summer and winter balances and comparing the absolute values of these running means (e.g. Engelhardt et al., 2013). However, a direct assessment of temporal changes of the relative importance of summer temperature and winter precipitation for annual balances is still missing. Cumulative annual balances show clear patterns of consistently positive mass balances and thereafter consistently negative mass balances (e.g. Nesje et al., 2000, Fig. 3). We therefore hypothesise that the relative importance of summer temperature and winter precipitation for annual balances is not stable in time and that there is a large-scale forcing mechanism causing these changes. These forcings could either be of atmospheric or oceanic origin. It is, for instance, well known that increased amounts of winter precipitation in Scandinavia are associated with stronger zonal moisture advection that is due to pressure differences between Iceland and the Azores (e.g. Wanner et al., 2001). These pressure differences are summarized by the North Atlantic Oscillation (NAO) Index. In addition to the atmosphere, systematic changes in ocean temperatures may also influence the relative importance of summer temperature and winter precipitation for annual balances of glaciers in Scandinavia. The Atlantic Multidecadal Oscillation (AMO) is a pattern of changing sea-surface temperatures in the North Atlantic (e.g. Schlesinger and Ramankutty, 1994). Changing sea surface temperatures might result in changing temperatures over land and thereby also alter the relative importance of summer temperature and winter precipitation for annual balances.
In this study, we focus on assessing the relative importance of winter precipitation and summer temperature for annual mass balances, temporal changes of these influences and on possible influences of large-scale atmospheric and oceanic patterns on these temporal changes. The aims of this study are therefore threefold: (i) model the annual mass balances of eight Scandinavian glaciers with long annual mass balance series using a suite of statistical models using seasonally averaged climate data as input variables. These models enable us to compare the relative importance of winter precipitation and summer temperature for annual mass balances of glaciers; (ii) assessing temporal changes of relative importances of winter precipitation and summer temperature. (iii) Compare these temporal changes to large-scale oceanic and atmospheric modes, such as the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO).
Map of glaciers and summer temperature and winter precipitation.
Glaciers: Ålfotbreen (ALF), Rembesdalsskåka (REM), Nigardsbreen
(NIG), Storbreen (STO), Hellstugubreen (HEL), Gråsubreen (GR), Engabreen
(ENG) and Storglaciären (STORGL). Meteorological stations Bergen,
Glomfjord and Bodø are indicated. Inset maps show 1961–1990 normal summer
(MJJAS) temperature and winter (ONDJFMA) precipitation (data available at
We modelled the mass balances of eight glaciers in Scandinavia:
Ålfotbreen (ALF), Rembesdalskåka (REM), Nigardsbreen (NIG), Storbreen
(STO), Hellstugubreen (HEL), Gråsubreen (GR) in southern Norway and
Engabreen (ENG) and Storglaciären (STORGL) in northern Norway and
northern Sweden, respectively (Fig. 1). Storglaciären has the longest
annual mass balance time series, beginning in 1946 and Engabreen has the
shortest time series, initiated in 1970. For all glaciers, data until 2010
were considered. Glacier mass balance data are available at
Cumulative mass balance changes are shown in Fig. 3. The three maritime glaciers Ålfotbreen (ALF), Rembesdalsskåka (REM), and Nigardsbreen (NIG) in southern Norway and the maritime glacier Engabreen (ENG) in northern Norway show positive cumulative annual balances between the initiation of the measurements and 2010 (Fig. 3). Mass balances are especially positive during the first half of the 1990s. The continental glaciers Storbreen (STO), Hellstugubreen (HEL), and Gråsubreen (GR) in southern Norway and the continental glacier Storglaciären (STORGL) in northern Sweden experienced negative cumulative mass balances between the start of the measurements and 2010. For these glaciers the mass balance loss was reduced in the first half of the 1990s.
We used meteorological data from the meteorological station Bergen-Florida to model mass balances in southern Norway. We decided to exclusively use precipitation data from Bergen-Florida for all glaciers in southern Norway since Bergen-Florida records the large synoptic weather systems and is not affected by local topographic effects that are affecting meteorological stations in the deep and narrow valleys closer to the glaciers studied (e.g. Nesje, 2005). For glaciers in northern Scandinavia, we used meteorological data from the coastal station Glomfjord available from the beginning of the mass balance series. The temperature measurements are continuous, but the precipitation series ends in 2003. We extended the precipitation series with data from the nearby Bodø meteorological station. The precipitation data from Bodø were scaled to the data from Glomfjord in the period of overlap (1953–2003) of the two data series.
To directly quantify the relative importances of summer temperature and
winter precipitation on annual balances, we used a suite of three
statistical models with increasing complexity and number of parameters that
needed to be estimated:
Linear models using a climate index as independent variable, Linear models using summer temperature and winter precipitation as
independent variables, Additive models using summer temperature and winter precipitation as
independent variables.
If the variance explained by two models was not significantly different, we favoured the simpler model, as it was more parsimonious.
As glaciers are mainly sensitive to summer temperatures and winter
precipitation, models were run using one summer temperature and one winter
precipitation as independent variables. We tested the influences of two
summer temperatures, namely temperatures from May–September (
The simplest way of modelling the influence of (winter) precipitation and
(summer) temperature on glacier mass balances is to generate a climate index,
where winter precipitation and summer temperature are equally weighted (Imhof
et al., 2012; Nesje, 2005), i.e. they are assigned the same relative
importance for the annual balance. This was achieved by standardising summer
temperature and winter precipitation and subtracting standardised summer
temperature from standardised winter precipitation, as the two variables have
opposed influences.
Annual mass balances were modelled using linear models with one (summer)
temperature and one (winter) precipitation variable as independent variables.
In a first step, we tested interactions between (summer) temperature and
(winter) precipitation and quadratic terms for significance. F-tests
indicated that neither interaction terms, nor quadratic terms were
significant (
The linear regression equation
The intercept of the regression model is zero, and more importantly The standard regression coefficients are now comparable and are “a means
of assessing the relative importance of each explanatory variable
For standardized variables, calculus with
Hence the standard regression coefficients, which are the relative importance of (in our case) winter precipitation and summer temperature for annual balance only depend on the correlations among winter precipitation, summer temperature and annual balance.
The difference between linear models and the climate index is that winter
precipitation and summer temperature are individually weighted when using
linear models, whereas the two independent variables are equally weighted
when employing the climate index. Hence, the relative importances of summer
temperature and winter precipitation are allowed to be different using
linear models, whereas they are artificially kept similar using climate
index models. Linear models were compared to models based on climate indices
using
In contrast to
In contrast to linear models, where coefficients link independent and
dependent variables, this linking is achieved by a smoothing term in
additive models
With the three statistical models proposed, we assume that errors in mass balance measurements are random and that climate data are error free. If the errors in mass balance measurements contain a systematic component, the estimates of relative importance of summer temperature and winter precipitation for annual balance are biased. If annual balances are systematically overestimated, the relative importance of summer temperature for annual balance is systematically underestimated.
All the models were tested by calculating leave-one-out cross-validation
(jack-knifing, e.g. Efron and Gong, 1983) and h-block cross-validation
(Burman et al., 1994) where h-samples are left out on either side of the
sample to be predicted. In this study we set
After running models for the entire observation period, we wanted to
assess if the relative importance of summer temperature and winter
precipitation changed through time and if these changes were consistent
among the glaciers. For this purpose, we ran models in 25-year moving
windows. The significance of changes in variance explained was again tested
with
Preliminary analysis in running windows showed changes of relative importance of summer temperature and winter precipitation for annual balances that were consistent for all glaciers in southern Norway. We therefore assessed if these results were influenced by two large-scale patterns of oceanic and atmospheric variability over the north Atlantic realm. The North Atlantic Oscillation (NAO), an atmospheric pattern with an approximately decadal cyclicity (Hurrell et al., 2001; Wanner et al., 2001) and the Atlantic Multidecadal Oscillation (AMO), a pattern in sea-surface temperature that is linked to changes in thermohaline ocean circulation with a cyclicity of 65–70 years (Schlesinger and Ramankutty, 1994; Trenberth and Shea, 2006). The NAO mainly influences the strength and tracks of the westerlies and thereby the amount of winter precipitation in north-western Europe.
Additive model for Ålfotbreen.
Nesje et al. (2000) and Marzeion and Nesje (2012) found strong and
significant (
Considering the period 1946–2010, the average monthly November through April
precipitation in Bergen was 230 mm for the years with above-median NAO-index
and 170 mm in the years with below-median NAO-index, which is significantly
lower (
The longest mass balance series started in 1946. The AMO was generally
positive from ca. 1930–1962 and from 1997 to the present, whereas it was
negative between 1963 and 1996. In the negative subset of the AMO, the
correlation between the NAO-index and extended winter precipitation in Bergen
was
All calculations were done in R (R Core Team, 2014) and its add-on packages lmodel2 (Legendre, 2014), and mgcv (Wood, 2014).
Table of most parsimonious statistical models. Input variables used
and model types are indicated along with apparent and cross-validated
variance explained. Cross-validated mean absolute deviations and relative
importance of summer temperature (LM Coef
The employed statistical models explained large proportions of the variance
of annual mass balances (Table 1). For the maritime glaciers, the models
explained more than 70 % of the variance. The variance explained for
continental glaciers varied between 50 and 70 %. Table 1 shows input
variables, model types, variance explained by the most parsimonious models
and standard regression coefficients of linear models (i.e. the relative
importance of summer temperature and winter precipitation) and their Bayesian
credible intervals. Cross-validated
For Storbreen, Engabreen and Storglaciären, the statistical models using
climate indices as input variables were most parsimonious. These are the only
glaciers where standard regression coefficients of linear models were not
different (Table 1). Hence, linear models were also assigning about similar weights to
summer temperature and winter precipitation for these three glaciers. For the
maritime glaciers Rembesdalsskåka and Nigardsbreen, linear models
indicated a higher relative importance of winter precipitation than of summer
temperature, whereas for the continental glaciers Hellstugubreen and
Gråsubreen, the relative importance of summer temperature was higher than
the relative importance of winter precipitation. For the maritime
Ålfotbreen, an additive model explained significantly (
Temporal changes of relative importance of summer temperature and winter precipitation are shown in Fig. 3b–i. The relative importance of winter precipitation, as indicated by standard regression coefficients of winter precipitation in 25-year running windows, was lowest at the end of the observation period. The relative importance of summer temperature, as indicated by standard regression coefficients of summer temperature in 25-year running windows, increased towards the end of the observation period (Fig. 3b–i).
Winter precipitation was more important than summer temperature for the annual balance of continental glaciers in southern Norway (STO, HEL, and GR) for the 25-year windows centred between 1977 and 1985. For STO, the period of higher relative importance of winter precipitation than relative importance of summer temperature was extended up to the 25-year window centred around 1990 (Fig. 3e). For the maritime glaciers in southern Norway, the Bayesian credible intervals of the standard regression coefficients (relative importances) were not overlapping for 25-year windows centred before 1990, but were overlapping for the last five running windows.
Standard deviation ratios. Ratios between standard deviations of
winter balances (sBw) and annual balances (sBa, sBw
Coefficients of determination (
Storbreen indicated about equal importance of winter precipitation and summer temperature for 25-year windows ending prior to 1990 (Fig. 3e). The relative importance of summer temperature was higher than the relative importance of winter precipitation for 25-year windows centred in the first half of the 1970s for Storglaciären (Fig. 3i).
The mass balance models for years with above- and below-median NAO-index, respectively, were different in terms of variance explained and in terms of relative importance assigned to summer temperature and winter precipitation. They also differed from models covering the entire measurement period.
For years with above-median NAO, models for Ålfotbreen,
Rembesdalsskåka, Nigardsbreen and Storbreen explained as much of the
variance of the mass balance as models for the entire data series, whereas
for Hellstugubreen and Gråsubreen, the variance explained was reduced
compared to the models for the entire period. Interestingly, for
Ålfotbreen standard regression coefficients for winter precipitation and
summer temperature were not different. For the phase with below-median
NAO-index, models for Ålfotbreen, Rembesdalsskåka and Nigardsbreen
explained less of the variance than in the entire period and standard
regression coefficients for precipitation and temperature were not different,
whereas models for Gråsubreen and Hellstugubreen explained more of the
variance than in the entire period, and together with Storbreen displayed a
higher importance of summer temperature than winter precipitation. The two
glaciers with long data series had an average mass loss of 0.54 m water
equivalents per year (m w.e. yr
For all glaciers, except for ALF, the ratio sBs
Correlations between NAO-index and winter and annual balance were different
for the subsets of years with above and below-median NAO-index (Fig. 5). For
glaciers in southern Norway, the correlation between NAO-index and winter and
annual balance was higher than for the entire time series for years with
above-median NAO-index and was lower than for the entire series for years
with below-median NAO-index. For NIG, STO, HEL, GR, ENG and STORGL the
correlation coefficients among NAO-index and Ba and Bw were not significant
at the
Changes in relative importances of winter precipitation and summer
temperature were also found for the AMO
We used simple statistical models that are only taking into account summer temperature and winter precipitation to model annual mass balances. Even though these models are simplistic, they explain large proportions of the variance of annual balances, and are therefore appropriate to estimate relative importance of summer temperature and winter precipitation for annual balances. The model performance is increased for coastal maritime glaciers. This might have several reasons: (i) precipitation is highly variable in space and therefore precipitation from Bergen is possibly more appropriate for coastal glaciers than for continental glaciers. Still, using precipitation from meteorological stations closer to the continental glaciers did not improve the model performance for continental glaciers. (ii) Processes not represented in our model are more important in summer (radiation) than in winter (wind redistribution of snow).
Climate sensitivities of Engabreen (Schuler et al., 2005), Rembesdalsskåka (Giesen and Oerlemans, 2010) and Storbreen (Andreassen and Oerlemans, 2009) show that summer balances are largely unaffected by changes in precipitation, which suggest minor importance of summer precipitation for summer balance. Still other important components such as the direct effect of radiation are not entirely accounted for when only using summer temperature to model ablation. Our models do not take into account the hypsometry of glaciers, which might be important in transitional seasons, where accumulation and ablation can occur simultaneously on one glacier (e.g. Schuler et al., 2005). Although our models do not account for these processes we get coefficients of determination similar to the values found by Rasmussen and Conway (2005) who used degree day models and RMSEPs lower or comparable to RMSEPs found by Engelhardt et al. (2013). This good performance of statistical models is probably due to the distinct accumulation and ablation seasons on Scandinavian glaciers i.e. most accumulation occurring during winter and most ablation taking place during summer. In areas with less distinct accumulation and ablation seasons, statistical models using seasonally averaged climate variables will not perform well.
The application of statistical models using seasonally average climate as
input variables seems especially interesting for two areas of application:
Regions where only seasonal climate data are available (especially
precipitation data) this problem can be overcome by using reanalysis data
(e.g. Rasmussen and Conway, 2005). Rasmussen and Conway (2005) used
reanalysis data for other reasons than lack of station data. Palaeoclimate studies where reconstructed climate data are at maximum
available at monthly resolution. For example Steiner et al. (2008) estimated
the relative importance of changes in seasonally averaged precipitation and
temperature during advance and retreat periods of Nigardsbreen and Lower
Grindelwald Glacier (Swiss Alps) using artificial neural networks.
Our results showed, as also demonstrated in other studies (Andreassen and
Oerlemans, 2009; Giesen and Oerlemans, 2010; Laumann and Nesje, 2009a, b,
2014; Oerlemans, 1992), that the annual glacier mass balance on near coastal,
maritime glaciers was mainly controlled by winter precipitation and that the
annual mass balance on the inland, continental glaciers was mainly controlled
by summer temperature (Andreassen et al., 2005; Nesje et al., 1995). Hence,
standard regression coefficients of linear models are shown to be good
estimators of the relative importance of summer temperature and winter
precipitation for annual balances. The relative importance as determined by
standard regression coefficients display similar patterns as the standard
deviation ratios presented by Andreassen et al. (2005) and are also shown in
Fig 4. The exceptions are NIG and STO. For NIG, standard regression
coefficients indicate higher relative importance of winter precipitation
compared to summer temperature, but standard deviation ratios are similar.
Standard regression coefficients suggest equal relative importance of summer
temperature and winter precipitation for STO, whereas the standard deviation
ratio sBs
As shown in this study, the relative importance of summer temperature and winter precipitation for annual balances is not constant in time. Temporal changes in relative importance of summer temperature and winter precipitation are consistent for all of southern Norway (Fig. 3), suggesting common large-scale forcing of the relative importance of summer temperature and winter precipitation.
Maritime glaciers had a consistently positive mass balance between 1988 and 1996 and continental glaciers were no longer loosing mass (Fig. 3a, Nesje et al., 2000; Andreassen et al., 2005; Nesje and Matthews, 2012). Looking at the 25-year windows centred between 1978 and 1984, we found that winter precipitation was more important than summer temperature for all glaciers including the continental glaciers in southern Norway, although the differences were not significant for the continental Gråsubreen. For the three continental glaciers in southern Norway, this phase was characterised by a marked decrease in relative importance of summer temperature and a marked increase in relative importance of winter precipitation.
In this phase, the AMO-index was consistently negative and the NAO-indexes were consistently positive between 1988 and 1996 (Fig. 3). In tendency, negative AMO indices were associated with reduced summer temperatures over Europe and positive NAO-indexes were associated with increased zonal flow in winter, entailing more winter precipitation in Northern Europe. Hence, the large-scale oceanic and atmospheric patterns were favourable for glacier growth.
As another example, in the 2000s all glaciers except Engabreen and Nigardsbreen generally experienced negative mass balances and mass balances of Engabreen and Nigardsbreen were at equilibrium. In this period, the importance of summer temperature for the annual mass balance was increased (Fig. 3), even though 25-year windows centred around 1997 still contained the years 1988–1996 with their transient mass surplus. The increasing relative importance of summer temperature and decreasing relative importance of winter precipitation for the annual balance at the end of the measurement period is consistent with more negative summer balances and less positive winter balances found for glaciers in southern Norway (e.g. Engelhardt et al. 2013). The AMO-index changed sign in the late 1990s and summer temperatures were in general higher than between 1985 and 1995.
For glaciers in the European Alps, Huss et al. (2010) found pronounced mass loss during phases of positive AMO-index and mass gain in phases of negative AMO-index, which is similar to findings in this study. The phases of increased glacier melt are, however, not simultaneous in the Swiss Alps and in Scandinavia. In the Swiss Alps, a pronounced mass loss lasting to the present day started in the late 1980s, whereas continental glaciers in Scandinavia lost mass between the start of the measurements and 1987 and all glaciers in Scandinavia lost mass after about 1998. This difference is most probably caused by the fact that changes in melt rates are most influential for mass balances in the Alps (Huss et al., 2010), whereas a decade with predominantly positive NAO-indexes began in the late 1980s (1988/1989 winter) associated with increased relative importance of winter precipitation for Scandinavian glaciers (Fig. 3). This is in line with Marzeion and Nesje (2012) who found a positive correlation between the NAO and glaciers in southern Scandinavia, while a weak anti-correlation was found for the western Alps. This anti-correlation was diminishing towards east. Six et al. (2001) point out that anti-correlations between glacier mass balances in the alps and Scandinavia are mainly found in decadally smoothed data and attribute this to the NAO, whereas only weak anti-correlations are found using annual data.
Clear differences are found between the subsets with above-median and below-median NAO-index. In winters with high NAO-index, stronger westerly flow and increased precipitation is expected (e.g. Wanner et al., 2001). The mass balance models of the maritime glaciers explained more of the total variance with high NAO-index and the relative importance of winter precipitation for the total mass balance was increased. This was according to expectations, as increased winter precipitation is expected to increase the importance of the winter precipitation for mass balance models.
For all glaciers, the correlation between NAO-index and winter and annual mass balance was higher for years with above-median NAO-index (Fig. 5). Additionally, the coefficient of determination between winter balance and NAO-index was decreased for the subset of years with below-median NAO-index (Fig. 5). This means that the reduction in coefficient of determination between NAO-index and annual balance was not only caused by an increased importance of the summer balance for the annual balance, but also by a loss of accordance between NAO-index and winter balance. This loss in accordance is only partly caused by lower accordance among precipitation in Bergen and winter balances, but mainly by a consistently decreased correlation between the NAO-index and precipitation in Bergen. Consequently the NAO-index is only a good predictor for winter balances of glaciers in southern Norway in years with above-median NAO-index. This is reiterating a find by Six et al. (2001), who do not recommend to model glacier mass balances solely based on the NAO-index. Unstable relations between the NAO-index and glacier length changes in Scandinavia as well as in the Alps were also found by Imhof et al. (2011).
For the two glaciers with long mass balance time-series, the influence of the NAO seemed equal to the influence of the AMO, as the difference between the average mass balances in the two NAO levels considered was about equal to the difference in the two AMO states. The AMO states only include consecutive years, whereas individual years were assigned to the NAO-index. The phase between ca. 1987 and 1995 with major mass gain for maritime glaciers and neutral mass balances for continental glaciers was characterised by negative AMO-index and predominantly positive NAO-index, that were both favourable for glaciers.
The relation between AMO and NAO seems rather complex and depends on the timescale considered (Li et al., 2013; Peings and Magnusdottir, 2014). On short timescales, the atmospheric NAO pattern influences the sea surface temperature, whereas on longer timescales, the sea-surface temperature AMO pattern drives the atmospheric NAO. Hence Li et al. (2013) find the NAO to lead the AMO by 16 years and state that the NAO is an excellent predictor for AMO and thereby Northern Hemisphere temperature, whereas Peings and Magnusdottir (2014) find “that the multidecadal fluctuations of the wintertime North Atlantic Oscillation (NAO) are tied to the AMO, with an opposite signed relationship between the polarities of the AMO and the NAO. Our statistical analyses suggest that the AMO signal precedes the NAO by 10–15 years”.
The association of negative AMO and positive NAO seems to be typical (Peings and Magnusdottir 2014), whereas positive AMO favours negative NAO and blocking situations. For the time period 1965–1998, with negative AMO, only 10 years have a negative NAO-index, whereas for the considerably shorter phase 1999–2010 already 6 years had a negative NAO-index. Hence, the two modes favouring glacier mass gain and mass loss, respectively, tended to occur simultaneously. However, the influence of AMO and NAO should not be overestimated, as similar weather patterns still result in different amounts of precipitation and in different levels of temperature (Jacobeit et al., 2003; Kuettel et al., 2011). Kuettel et al. (2011), for instance, attribute 60 % of the changes of winter precipitation over southern Norway between the periods 1900–1949 and 1950–1999 to changes within weather patterns and only 40 % to changes in frequencies of weather patterns.
We used simple statistical models to assess the relative importance of
summer temperature and winter precipitation for annual balances of eight
glaciers in Scandinavia. The relative importances found using statistical
models were comparable to estimates of relative importance obtained using
different methods. Most importantly, the relative importance of summer
temperature and winter precipitation for annual balances varied through
time. Winter precipitation was most important when the Atlantic Multidecadal
Oscillation Index was negative and the North Atlantic Oscillation Index was
positive. Presently, the relative importance of winter precipitation
decreased for all glaciers while the relative importance of summer
temperature was increasing. The influence of NAO and AMO on the relative
importance of summer temperature and winter precipitation for annual balance
was confirmed considering subsets of different NAO and AMO levels, with
increasing relative importance of winter precipitation in years with NAO
We would like to thank two reviewers for comprehensive comments that improved the clarity of this manuscript. We also thank Pascal Hänggi for comments on an earlier version of this manuscript and Heinz Wanner for discussion of large-scale climate patterns as the NAO and the AMO. Edited by: J. O. Hagen