High-resolution provenance of desert dust deposited on Mt. Elbrus, Caucasus in 2009–2012 using snow pit and firn core records

The first record of dust deposition events on Mt. Elbrus, Caucasus Mountains derived from a snow pit and a shallow firn core is presented for the 2009–2012 period. A combination of isotopic analysis, SEVIRI red-greenblue composite imagery, MODIS atmospheric optical depth fields derived using the Deep Blue algorithm, air mass trajectories derived using the HYSPLIT model and analyses of meteorological data enabled identification of dust source regions with high temporal (hours) and spatial (ca. 20–100 km) resolution. Seventeen dust deposition events were detected; fourteen occurred in March–June, one in February and two in October. Four events originated in the Sahara, predominantly in northeastern Libya and eastern Algeria. Thirteen events originated in the Middle East, in the Syrian Desert and northern Mesopotamia, from a mixture of natural and anthropogenic sources. Dust transportation from Sahara was associated with vigorous Saharan depressions, strong surface winds in the source region and mid-tropospheric southwesterly flow with daily winds speeds of 20–30 m s−1 at 700 hPa level. Although these events were less frequent than those originating in the Middle East, they resulted in higher dust concentrations in snow. Dust transportation from the Middle East was associated with weaker depressions forming over the source region, high pressure centred over or extending towards the Caspian Sea and a weaker southerly or southeasterly flow towards the Caucasus Mountains with daily wind speeds of 12–18 m s−1 at 700 hPa level. Higher concentrations of nitrates and ammonium characterised dust from the Middle East deposited on Mt. Elbrus in 2009 indicating contribution of anthropogenic sources. The modal values of particle size distributions ranged between 1.98 µm and 4.16 µm. Most samples were characterised by modal values of 2.0– 2.8 µm with an average of 2.6 µm and there was no signifi- cant difference between dust from the Sahara and the Middle East.

The depression of tropical snow lines at the Last Glacial Maximum: what can we learn from climate and model experiments?

Analyses of simulations of the last glacial maximum (LGM) made with 17 atmospheric general circulation models (AGCMs) participating in the Paleoclimate Modelling Intercomparison Project, and a high-resolution (T106) version of one of the models (CCSR1), show that changes in the elevation of tropical snowlines (as estimated by the depression of the maximum altitude of the 0 °C isotherm) are primarily controlled by changes in sea-surface temperatures (SSTs). The correlation between the two variables, averaged for the tropics as a whole, is 95%, and remains >80% even at a regional scale. The reduction of tropical SSTs at the LGM results in a drier atmosphere and hence steeper lapse rates. Changes in atmospheric circulation patterns, particularly the weakening of the Asian monsoon system and related atmospheric humidity changes, amplify the reduction in snowline elevation in the northern tropics. Colder conditions over the tropical oceans combined with a weakened Asian monsoon could produce snowline lowering of up to 1000 m in certain regions, comparable to the changes shown by observations. Nevertheless, such large changes are not typical of all regions of the tropics. Analysis of the higher resolution CCSR1 simulation shows that differences between the free atmospheric and along-slope lapse rate can be large, and may provide an additional factor to explain regional variations in observed snowline changes.

Global snow mass measurements and the effect of stratigraphic detail on inversion of microwave brightness temperatures

Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method then it is equivalent to ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model.

Assessing the sensitivities of a distributed snow model to forcing data resolution

Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.

Automated artifact removal from the electroencephalogram; a comparative study

Contamination of the electroencephalogram (EEG) by artifacts greatly reduces the quality of the recorded signals. There is a need for automated artifact removal methods. However, such methods are rarely evaluated against one another via rigorous criteria, with results often presented based upon visual inspection alone. This work presents a comparative study of automatic methods for removing blink, electrocardiographic, and electromyographic artifacts from the EEG. Three methods are considered; wavelet, blind source separation (BSS), and multivariate singular spectrum analysis (MSSA)-based correction. These are applied to data sets containing mixtures of artifacts. Metrics are devised to measure the performance of each method. The BSS method is seen to be the best approach for artifacts of high signal to noise ratio (SNR). By contrast, MSSA performs well at low SNRs but at the expense of a large number of false positive corrections.

FORCe: fully online and automated artifact removal for brain-computer interfacing

A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing. The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g. electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged auto-mutual information clustering (LAMIC) and Fully automated statistical thresholding (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.

A 2000-year annual record of snow accumulation rates for Law Dome, East Antarctica

Accurate high-resolution records of snow accumulation rates in Antarctica are crucial for estimating ice sheet mass balance and subsequent sea level change. Snowfall rates at Law Dome, East Antarctica, have been linked with regional atmospheric circulation to the mid-latitudes as well as regional Antarctic snowfall. Here, we extend the length of the Law Dome accumulation record from 750 years to 2035 years, using recent annual layer dating that extends to 22 BCE. Accumulation rates were calculated as the ratio of measured to modelled layer thicknesses, multiplied by the long-term mean accumulation rate. The modelled layer thicknesses were based on a power-law vertical strain rate profile fitted to observed annual layer thickness. The periods 380–442, 727–783 and 1970–2009 CE have above-average snow accumulation rates, while 663–704, 933–975 and 1429–1468 CE were below average, and decadal-scale snow accumulation anomalies were found to be relatively common (74 events in the 2035-year record). The calculated snow accumulation rates show good correlation with atmospheric reanalysis estimates, and significant spatial correlation over a wide expanse of East Antarctica, demonstrating that the Law Dome record captures larger-scale variability across a large region of East Antarctica well beyond the immediate vicinity of the Law Dome summit. Spectral analysis reveals periodicities in the snow accumulation record which may be related to El Niño–Southern Oscillation (ENSO) and Interdecadal Pacific Oscillation (IPO) frequencies.

Re-creation of heathland on improved pasture using topsoil removal and sulphur amendments: edaphic drivers and impacts on ericoid mycorrhizas

Understanding the factors that drive successful re-creation and restoration of lowland heaths is crucially important for achieving the long-term conservation of this threatened habitat type. In this study we investigated the changes in soil chemistry, plant community and interactions between Calluna vulgaris and symbiotic ericoid mycorrhizas (ERM) that occurred when improved pasture was subjected to one of three treatments (i) acidification with elemental sulphur (ii) acidification with ferrous sulphur (iii) removal of the topsoil. We found that the soil stripping treatment produced the greatest reduction in available phosphate but did not decrease soil pH. Conversely, acidification with elemental sulphur decreased pH but increased availability of phosphate and potentially toxic cations. The elemental sulphur treatment produced plant communities that most closely resembled those on surrounding heaths and acid grasslands. The most important driver was low pH and concomitant increased availability of potentially toxic cations. Plant community development was found to be little related to levels of available soil phosphate, particularly at low pH. The elemental sulphur treatment also produced the best germination and growth of C. vulgaris over 4–5 years. However, this treatment was found to inhibit the development of symbiotic relationships between C. vulgaris and ERM. This may affect the long-term persistence of re-created vegetation and its interactions with other components of heathland communities.

Snow-albedo feedback and Swiss spring temperature trends

We quantify the effect of the snow-albedo feedback on Swiss spring temperature trends using daily temperature and snow depth measurements from six station pairs for the period 1961–2011. We show that the daily mean 2-m temperature of a spring day without snow cover is on average 0.4 °C warmer than one with snow cover at the same location. This estimate is comparable with estimates from climate modelling studies. Caused by the decreases in snow pack, the snow-albedo feedback amplifies observed temperature trends in spring. The influence is small and confined to areas around the upward-moving snow line in spring and early summer. For the 1961–2011 period, the related temperature trend increases are in the order of 3–7 % of the total observed trend.

Impact of Northern Hemisphere snow on the Arctic Ocean in a climate model

A present day control integration performed with the Hadley Centre's coupled climate model HadGEM1.2 experiences a large salinity bias in the Arctic Ocean when compared to in situ observations. Such a large salinity bias may have implications for both Arctic and Atlantic Ocean circulation. Large differences are seen between the runoff in HadGEM and the observations from the Global Runoff Data Centre, in particular in the Lena catchment, which could account for this salinity bias. We suggest that this discrepancy in runoff is, at least in part, due to a lack of snow accumulation in the model. The model climatology is very different to those obtained by remote sensing, such as the Global Snow Water Equivalent Climatology (NSIDC) and GlobSnow (ESA).

Investigating the relationship between Eurasian snow and the Arctic Oscillation with data and models

Recent research suggests Eurasian snow-covered area (SCA) influences the Arctic Oscillation (AO) via the polar vortex. This could be important for Northern Hemisphere winter season forecasting. A fairly strong negative correlation between October SCA and the AO, based on both monthly and daily observational data, has been noted in the literature. While reproducing these previous links when using the same data, we find no further evidence of the link when using an independent satellite data source, or when using a climate model.

Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean–sea ice model

Introducing a parameterization of the interactions between wind-driven snow depth changes and melt pond evolution allows us to improve large scale models. In this paper we have implemented an explicit melt pond scheme and, for the first time, a wind dependant snow redistribution model and new snow thermophysics into a coupled ocean–sea ice model. The comparison of long-term mean statistics of melt pond fractions against observations demonstrates realistic melt pond cover on average over Arctic sea ice, but a clear underestimation of the pond coverage on the multi-year ice (MYI) of the western Arctic Ocean. The latter shortcoming originates from the concealing effect of persistent snow on forming ponds, impeding their growth. Analyzing a second simulation with intensified snow drift enables the identification of two distinct modes of sensitivity in the melt pond formation process. First, the larger proportion of wind-transported snow that is lost in leads directly curtails the late spring snow volume on sea ice and facilitates the early development of melt ponds on MYI. In contrast, a combination of higher air temperatures and thinner snow prior to the onset of melting sometimes make the snow cover switch to a regime where it melts entirely and rapidly. In the latter situation, seemingly more frequent on first-year ice (FYI), a smaller snow volume directly relates to a reduced melt pond cover. Notwithstanding, changes in snow and water accumulation on seasonal sea ice is naturally limited, which lessens the impacts of wind-blown snow redistribution on FYI, as compared to those on MYI. At the basin scale, the overall increased melt pond cover results in decreased ice volume via the ice-albedo feedback in summer, which is experienced almost exclusively by MYI.

Impact of instantaneous sea ice removal in a coupled general circulation model

The impact of extreme sea ice initial conditions on modelled climate is analysed for a fully coupled atmosphere ocean sea ice general circulation model, the Hadley Centre climate model HadCM3. A control run is chosen as reference experiment with greenhouse gas concentration fixed at preindustrial conditions. Sensitivity experiments show an almost complete recovery from total removal or strong increase of sea ice after four years. Thus, uncertainties in initial sea ice conditions seem to be unimportant for climate modelling on decadal or longer time scales. When the initial conditions of the ocean mixed layer were adjusted to ice-free conditions, a few substantial differences remained for more than 15 model years. But these differences are clearly smaller than the uncertainty of the HadCM3 run and all the other 19 IPCC fourth assessment report climate model preindustrial runs. It is an important task to improve climate models in simulating the past sea ice variability to enable them to make reliable projections for the 21st century.

Arctic Snow Microstructure Experiment for the development of snow emission modelling

The Arctic Snow Microstructure Experiment (ASMEx) took place in Sodankylä, Finland in the winters of 2013-2014 and 2014-2015. Radiometric, macro-, and microstructure measurements were made under different experimental conditions of homogenous snow slabs, extracted from the natural seasonal taiga snowpack. Traditional and modern measurement techniques were used for snow macro- and microstructure observations. Radiometric measurements of the microwave emission of snow on reflector and absorber bases were made at frequencies 18.7, 21.0, 36.5, 89.0 and 150.0 GHz, for both horizontal and vertical polarizations. Two measurement configurations were used for radiometric measurements: a reflecting surface and an absorbing base beneath the snow slabs. Simulations of brightness temperatures using two microwave emission models, Helsinki University of Technology (HUT) snow emission model and Microwave Emission Model of Layered Snowpacks (MEMLS), were compared to observed brightness temperatures. RMSE and bias were calculated; with the RMSE and bias values being smallest upon an absorbing base at vertical polarization. Simulations overestimated the brightness temperatures on absorbing base cases at horizontal polarization. With the other experimental conditions, the biases were small; with the exception of the HUT model 36.5 GHz simulation, which produced an underestimation for the reflector base cases. This experiment provides a solid framework for future research on the extinction of microwave radiation inside snow.