Bayesian modeling and significant features exploration in wavelet power spectra

This study proposes and justifies a Bayesian approach to modeling wavelet coefficients and finding statistically significant features in wavelet power spectra. The approach utilizes ideas elaborated in scale-space smoothing methods and wavelet data analysis. We treat each scale of the discrete wavelet decomposition as a sequence of independent random variables and then apply Bayes' rule for constructing the posterior distribution of the smoothed wavelet coefficients. Samples drawn from the posterior are subsequently used for finding the estimate of the true wavelet spectrum at each scale. The method offers two different significance testing procedures for wavelet spectra. A traditional approach assesses the statistical significance against a red noise background. The second procedure tests for homoscedasticity of the wavelet power assessing whether the spectrum derivative significantly differs from zero at each particular point of the spectrum. Case studies with simulated data and climatic time-series prove the method to be a potentially useful tool in data analysis

Variability and climate sensitivity of fast ice extent in the north-eastern Kara Sea

This work investigates the temporal and spatial variation of shore-fast ice extent in the north-eastern part of the Kara Sea during 1953–1990 and its sensitivity to interannual variability of the regional climate. The area of fast ice in spring months shows a bimodal distribution. This indicates the existence of two different regimes of fast ice formation driven by the system of prevailing winds. The westward wind transport during the cold season gives larger fast ice extent while the eastward wind transport suppresses the expansion of fast ice. There is a significant correlation (ca. –0.55) between the average winter temperature and the area of fast ice. Linear trends for time records of shore-fast ice area in spring show a decrease during 1953–1990. This decrease is most pronounced in April: the mean fast ice area in April is 12 % lower in 1988–1990 compared to 1953–55. A comparison of fast ice regimes for two particular years— 1979 and 1985—revealed a significant influence of cyclone activity on fast ice development over the course of the cold season. It is shown that partial break-ups of fast ice in spring 1985 are associated with the passage of cyclones across the area of fast ice

Environmental changes in Krossfjorden, Svalbard, since 1950 : Benthic foraminiferal and stable isotope evidence

Environmental changes for the past ca. 50 years were studied in a short sediment core from inner Krossfjorden, Svalbard, investigating benthic foraminifera and stable isotopes (delta O-18, delta C-13). A depth-age model based on anthropogenic Cs-137 time markers indicates that record covers the period from 1955 to 2007 and has sediment accumulation rates of ca. 0.3 to 1 cm/year. The benthic foraminifera are arctic and/or common in glaciomarine environments. Six fauna assemblages were identified using stratigraphically constrained cluster analysis. Benthic foraminiferal fauna assemblages are mainly dominated by Cassidulina reniforme. Elphidium clavatum is dominant from 1973 to 1986 and 2002 to 2007, likely due to greater turbidity in the water column. We interpret the increased percentages of Spiroplectammina biformis over the same intervals to reflect a slightly lower salinity probably caused by meltwater. During a short time period, 1970 to 1973, Stainforthia concava dominates the benthic foraminiferal fauna interpreted to reflect increased productivity within a marginal ice zone. Other species as Islandiella norcrossi, Nonionellina labradorica, Islandiella helenae, and Melonis barleanus also indicate more nutrient-rich waters are present but not very abundant throughout the record probably due to the glacier proximal position of the study site. The stable isotope record (delta O-18) shows lighter values from 2001 to 2007, which seem to correlate well with oceanographic monitoring data showing increasing core temperatures of West Spitsbergen Current.Peer reviewe

Snow contribution to first-year and second-year Arctic sea ice mass balance north of Svalbard

The salinity and water oxygen isotope composition (δ18O) of 29 first-year (FYI) and second-year (SYI) Arctic sea ice cores (total length 32.0 m) from the drifting ice pack north of Svalbard were examined to quantify the contribution of snow to sea ice mass. Five cores (total length 6.4 m) were analyzed for their structural composition, showing variable contribution of 10–30% by granular ice. In these cores, snow had been entrained in 6–28% of the total ice thickness. We found evidence of snow contribution in about three quarters of the sea ice cores, when surface granular layers had very low δ18O values. Snow contributed 7.5–9.7% to sea ice mass balance on average (including also cores with no snow) based on δ18O mass balance calculations. In SYI cores, snow fraction by mass (12.7–16.3%) was much higher than in FYI cores (3.3–4.4%), while the bulk salinity of FYI (4.9) was distinctively higher than for SYI (2.7). We conclude that oxygen isotopes and salinity profiles can give information on the age of the ice and enables distinction between FYI and SYI (or older) ice in the area north of Svalbard

Long-term monitoring of landfast sea ice extent and thickness in Kongsfjorden, and related applications (FastIce)

Landfast sea ice covers the inner parts of Kongsfjorden, Svalbard, for a limited time in winter and spring months, being an important feature for the physical and biological fjord systems. Systematic fast-ice monitoring for Kongsfjorden, as a part of a long-term project at the Norwegian Polar Institute (NPI) was started in 2003, with some more sporadic observations from 1997 to 2002. It includes the ice extent mapping and in situ measurements of ice and snow thickness, and freeboard at several sites in the fjord. The permanent presence of NPI personnel in Ny-Ålesund Research Station enables regular in situ fast-ice thickness measurements as long as the fast ice is accessible. Further, daily visits to the observatory on the mountain Zeppelinfjellet close to Ny-Ålesund, allow regular ice extent observations (weather, visibility, and daylight permitting). Data collected within this standardized monitoring programme have contributed to a number of studies. Monitoring of the sea-ice conditions in Kongsfjorden can be used to demonstrate and investigate phenomena related to climate change in the Arctic

Revised ΔR values for the Barents Sea and its archipelagos as a pre-requisite for accurate and robust marine-based 14C chronologies

The calibration of marine 14C dates requires the incorporation of regionally specific marine reservoir offsets known as ΔR, essential for accurate and meaningful inter-archive comparisons. Revised, regional ΔR (‘ΔRR’) values for the Barents Sea are presented for molluscs and cetaceans for the two latest iterations of the marine calibration curve, based on previously published pre-bomb live-collected and radiocarbon-dated samples (‘ΔRL’; molluscs: n = 16; cetaceans: n = 18). Molluscan ΔRR, determined for four broad regional oceanographic settings, are: western Svalbard (including Bjørnøya), −61 ± 37 14C yrs (Marine20), 94 ± 38 14C yrs (Marine13); Franz Josef Land, −277 ± 57 14C yrs (Marine20), −122 ± 38 14C yrs (Marine13); Novaya Zemlya, −156 ± 73 14C yrs (Marine20), 0 ± 76 14C yrs (Marine13); northern Norway, −86 ± 39 14C yrs (Marine20), 74 ± 24 14C yrs (Marine13). Molluscan ΔRR values are considered applicable to other marine carbonate materials (e.g., foraminifera, ostracods). Cetacean ΔRR are determined for toothed (n = 10) and baleen (n = 8) whales, and a combined toothed-baleen group (n = 18): toothed, −161 ± 41 14C yrs (Marine20), 1 ± 41 14C yrs (Marine13); baleen, −158 ± 43 14C yrs (Marine20), 8 ± 41 14C yrs (Marine13); combined baleen-toothed whales, −160 ± 41 14C yrs (Marine20), 4 ± 49 14C yrs (Marine13). Where identification and separation of baleen and toothed whales is impossible the combined ΔRR term may be used. However, we explicitly discourage the application of existing cetacean ΔRR terms to other marine mammals. Our new ΔRR values are applicable for as long as those broad oceanographic conditions (circulation and ventilation) have persisted, i.e., through the Holocene. We recommend using the latest iteration of the marine calibration curve, Marine20, which seems to better capture the time-variant nature of R compared to Marine13. More ΔRL datapoints for both molluscs and cetaceans would improve the accuracy and precision of ΔRR. In the meantime, our new ΔR terms facilitate the calibration of marine 14C dates across the region, paving the way for meaningful and accurate late Quaternary histories and inter-regional comparisons.publishedVersio

Atmospheric-driven state transfer of shore-fast ice in the northeastern Kara Sea

Frequencies of observed occurrences of shore-fast ice in the northeastern Kara Sea for each month during 1953–1990 reveal a multimodality of shore-fast ice extent in late winter and spring. The fast ice extent exhibits mainly three different configurations (modes) associated with the regional topography of coasts and islands. These modes show fast ice areas equal to approximately 98 ± 6, 122 ± 6, and 136 ± 8 1000 km2. Analysis of the time series of fast ice extent shows that favorable conditions for expansion of fast ice seaward in winter and spring are met if the atmospheric circulation over the northeastern Kara Sea is controlled by the Arctic high, resulting in offshore winds and a significant (up to 6ºC) decrease of the monthly mean surface air temperature. In contrast, the penetration of the Icelandic low into the Kara Sea, accompanied by Arctic cyclones coming from the west, is responsible for the partial breakup and decrease of fast ice extent in winter or spring

Dielectric sea-ice properties examined by GNSS reflectometry: Findings of the MOSAiC expedition

The dielectric properties of sea ice differ significantly from the open-water surface when we consider the L-band frequency range of GNSS signals. In contrast to water, the signal's penetration into sea ice can reach several decimeters depending on properties like salinity, temperature and thickness. Exploiting these different dielectric properties is a key to use GNSS for sea-ice remote sensing. For this purpose, GNSS reflectometry measurements have been conducted over the Arctic Ocean during the MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate). A combined receiver setup was used that allows the here described reflectometry study and another study for atmosphere sounding. The setup was mounted, in close cooperation with the Alfred-Wegener-Institute (AWI), on the German research icebreaker Polarstern that drifted during nine months of the expedition with the Arctic sea ice. Here, an initial study is presented that focuses on the expedition's first leg in autumn 2019 when the ship started drifting at about 85°N to 87°N in the Siberian Sector of the Arctic. Profiles of seaice reflectivity are derived with daily resolution considering reflection data recorded at left-handed (LH) and right-handed (RH) circular polarization. Respective model predictions of reflectivity are assuming a sea-ice bulk medium or a sea-ice slab. The later allows to include the effect of signal penetration down to the underlying water. Results of comparison between LH profiles and bulk model confirm the reflectivity contrast (about 10 dB) between sea ice and water. The particularly low level of LH reflectivity in the late observation period (December 2019) indicates the presence of low-saline multiyear (MY) ice. A bias due to snow accumulating on the ice surface may occur. A snow-extended reflection model, driven by additional snow data, can help in future for clarification. Anomalies of observed reflectivity with respect to bulk model predictions are especially obvious at lowest elevation angles. According to the model, the slope of profiles at low elevations is about 1.0 to 1.2 dB/°. The observation shows significantly lower values (< 0.5 dB/°) including negative slopes. A comparison of LH results with the ice slab model provides clarification. The anomalies are induced by signal penetration leading to interference pattern of reflections from the ice's surfaceand bottom. Slope retrievals quantify the anomaly and allow a coarse estimation of the mean seaice temperature (about -10°C in December 2019) based on the slab model predictions. Further investigations are needed to better understand sea-ice reflectivity at RH polarization. RH profiles show a response to sea ice and features at low elevation angles that cannot be explained by current reflection models. As a conclusion, GNSS reflectometry is sensitive to dielectric sea-ice properties. Estimates of ice type/salinity and temperature are reported based on LH observation data. These findings will be exploited to further strengthen the application of GNSS signals for sea-ice remote sensing. Future studies on GNSS observations from ships and satellites are anticipated

Sea surface temperature in the Indian sector of the Southern Ocean over the Late Glacial and Holocene

Centennial- and millennial-scale variability of Southern Ocean temperature over the Holocene is poorly known, due to both short instrumental records and sparsely distributed high-resolution temperature reconstructions, with evidence for past temperature variations in the region coming mainly from ice core records. Here we present a high-resolution (similar to 60 year), diatom-based sea surface temperature (SST) reconstruction from the western Indian sector of the Southern Ocean that spans the interval 14.2 to 1.0 ka (calibrated kiloyears before present). During the late deglaciation, the new SST record shows cool temperatures at 14.2-12.9 ka and gradual warming between 12.9 and 11.6 ka in phase with atmospheric temperature evolution. This supports the evolution of the Southern Ocean SST during the deglaciation being linked with a complex combination of processes and drivers associated with reorganisations of atmospheric and oceanic circulation patterns. Specifically, we suggest that Southern Ocean surface warming coincided, within the dating uncertainties, with the reconstructed slowdown of the Atlantic Meridional Overturning Circulation (AMOC), rising atmospheric CO2 levels, changes in the southern westerly winds and enhanced upwelling. During the Holocene the record shows warm and stable temperatures from 11.6 to 8.7 ka followed by a slight cooling and greater variability from 8.7 to 1 ka, with a quasi-periodic variability of 200-260 years identified by spectral analysis. We suggest that the increased variability during the mid- to late Holocene reflects the establishment of centennial variability in SST connected with changes in the high-latitude atmospheric circulation and Southern Ocean convection.Peer reviewe