International Arctic Research Center

Data collected by the International Arctic Buoy Programme from 1979 to 1998 are analyzed to obtain statistics of sea level pressure (SLP) and sea ice motion (SIM). The annual and seasonal mean fields agree with those obtained in previous studies of Arctic climatology. The data show a 3-hPa decrease in decadal mean SLP over the central Arctic Ocean between 1979-88 and 1989-98. This decrease in SLP drives a cyclonic trend in SIM, which resembles the structure of the Arctic Oscillation (AO).

Key observational indicators of climate change in the Arctic, most spanning a 47 year period demonstrate fundamental changes among nine key elements of the Arctic system. We find that, coherent with increasing air temperature, there is an intensification of the hydrological cycle, evident from increases in humidity, precipitation, river discharge, glacier equilibrium line altitude and land ice wastage. Downward trends continue in sea ice thickness (and extent) and spring snow cover extent and duration, while near-surface permafrost continues to warm. Several of the climate indicators exhibit a significant statistical correlation with air temperature or precipitation, reinforcing the notion thatincreasing air temperatures and precipitation are drivers of major changes in various components of the Arctic system. To progress beyond a presentation of the Arctic physical climate changes, we find a correspondence between air temperature and biophysical indicators such as tundra biomass and identify numerous biophysical disruptions with cascading effects throughout the trophic levels. These include: increased delivery of organic matter and nutrients to Arctic near-coastal zones; condensed flowering and pollination plant species periods; timing mismatch between plant flowering and pollinators; increased plant vulnerability to insect disturbance; increased shrub biomass; increased ignition of wildfires; increased growing season CO 2 uptake, with counterbalancing increases in shoulder season and winter CO 2 emissions; increased carbon cycling, regulated by local hydrology and permafrost thaw; conversion between terrestrial and aquatic ecosystems; and shifting animal distribution and demographics. The Arctic

Snow depth and density were measured at Soviet drifting stations on multiyear Arctic sea ice. Measurements were made daily at fixed stakes at the weather station and once- or thrice-monthly at 10-m intervals on a line beginning about 500 m from the station buildings and extending outward an additional 500 or 1000 m. There were 31 stations, with lifetimes of 1–7 yr. Analyses are performed here for the 37 years 1954–91, during which time at least one station was always reporting. Snow depth at the stakes was sometimes higher than on the lines, and sometimes lower, but no systematic trend of snow depth was detected as a function of distance from the station along the 1000-m lines that would indicate an influence of the station. To determine the seasonal progression of snow depth for each year at each station, priority was given to snow lines if available; otherwise the fixed stakes were used, with an offset applied if necessary. The ice is mostly free of snow during August. Snow accumulates rapidly in September and October, moderately in November, very slowly in December and January, then moderately again from February to May. This pattern is exaggerated in the Greenland–Ellesmere sector, which shows almost no net accumulation from November to March. The Chukchi region shows a steadier accumulation throughout the autumn, winter, and spring. The average snow depth of the multiyear ice region reaches a maximum of 34 cm (11 g cm−2) in May. The deepest snow is just north of Greenland and Ellesmere Island, peaking in early June at more than 40 cm, when the snow is already melting north of Siberia and Alaska. The average snow density increases with time throughout the snow accumulation season, averaging 300 kg m−3, with little geographical variation. Usually only two stations were in operation in any particular year, so there is insufficient information to obtain the geographical pattern of interannual variations. Therefore, to represent the geographical and seasonal variation of snow depth, a two-dimensional quadratic function is fitted to all data for a particular month, irrespective of year. Interannual anomalies for each month of each year are obtained relative to the long-term mean snow depth for the geographical location of the station operating in that particular year. The computed interannual variability (IAV) of snow depth in May is 6 cm, but this is larger than the true IAV because of inadequate geographical sampling. Weak negative trends of snow depth are found for all months. The largest trend is for May, the month of maximum snow depth, a decrease of 8 cm over 37 yr, apparently due to a reduction in accumulation-season snowfall.

Abstract The Arctic Ocean is a fundamental node in the global hydrological cycle and the ocean's thermohaline circulation. We here assess the system's key functions and processes: (1) the delivery of fresh and low‐salinity waters to the Arctic Ocean by river inflow, net precipitation, distillation during the freeze/thaw cycle, and Pacific Ocean inflows; (2) the disposition (e.g., sources, pathways, and storage) of freshwater components within the Arctic Ocean; and (3) the release and export of freshwater components into the bordering convective domains of the North Atlantic. We then examine physical, chemical, or biological processes which are influenced or constrained by the local quantities and geochemical qualities of freshwater; these include stratification and vertical mixing, ocean heat flux, nutrient supply, primary production, ocean acidification, and biogeochemical cycling. Internal to the Arctic the joint effects of sea ice decline and hydrological cycle intensification have strengthened coupling between the ocean and the atmosphere (e.g., wind and ice drift stresses, solar radiation, and heat and moisture exchange), the bordering drainage basins (e.g., river discharge, sediment transport, and erosion), and terrestrial ecosystems (e.g., Arctic greening, dissolved and particulate carbon loading, and altered phenology of biotic components). External to the Arctic freshwater export acts as both a constraint to and a necessary ingredient for deep convection in the bordering subarctic gyres and thus affects the global thermohaline circulation. Geochemical fingerprints attained within the Arctic Ocean are likewise exported into the neighboring subarctic systems and beyond. Finally, we discuss observed and modeled functions and changes in this system on seasonal, annual, and decadal time scales and discuss mechanisms that link the marine system to atmospheric, terrestrial, and cryospheric systems.

Arctic cyclone activity is investigated in the context of climate change and variability by using a modified automated cyclone identification and tracking algorithm, which differs from previously used algorithms by single counting each cyclone. The investigation extends earlier studies by lengthening the time period to 55 yr with a 6-hourly time resolution, by documenting the seasonality and the dominant temporal modes of variability of cyclone activity, and by diagnosing regional activity as quantified by the cyclone activity index (CAI). The CAI integrates information on cyclone intensity, frequency, and duration into a comprehensive index of cyclone activity. Arctic cyclone activity has increased during the second half of the twentieth century, while midlatitude activity generally decreased from 1960 to the early 1990s, in agreement with previous studies. New findings include the following. 1) The number and intensity of cyclones entering the Arctic from the midlatitudes has increased, suggesting a shift of storm tracks into the Arctic, particularly in summer. 2) Positive tendencies of midlatitude cyclone activity before and after the 1960-93 period of decreasing activity correlate most strongly with variations of cyclone activity in the North Atlantic and Eurasian sectors. 3) Synchronized phase and amplitude variations in cyclone activity over the Arctic Ocean (70-90N) and the Arctic marginal zone (60-70N) play a critical role in determining the variations of cyclone activity in the Arctic as a whole. 4) Arctic cyclone activity displays significant low-frequency variability, with a negative phase in the 1960s and a positive phase in the 1990s, upon which 7.8-and 4.1-yr oscillations are superimposed. The 7.8-yr signal generally corresponds to the alternation of the cyclonic and anticyclonic regimes of the Arctic sea ice and ocean motions.

The statistics of surface air temperature observations obtained from buoys, manned drifting stations, and meteorological land stations in the Arctic during 1979-97 are analyzed. Although the basic statistics agree with what has been published in various climatologies, the seasonal correlation length scales between the observations are shorter than the annual correlation length scales, especially during summer when the inhomogeneity between the ice-covered ocean and the land is most apparent. During autumn, winter, and spring, the monthly mean correlation length scales are approximately constant at about 1000 km; during summer, the length scales are much shorter, that is, as low as 300 km. These revised scales are particularly important in the optimal interpolation of data on surface air temperature (SAT) and are used in the analysis of an improved SAT dataset called International Arctic Buoy Programme/Polar Exchange at the Sea Surface (IABP/POLES). Compared to observations from land stations and the Russian North Pole drift stations, the IABP/POLES dataset has higher correlations and lower rms errors than previous SAT fields and provides better temperature estimates, especially during summer in the marginal ice zones. In addition, the revised correlation length scales allow data taken at interior land stations to be included in the optimal interpretation analysis without introducing land biases to grid points over the ocean. The new analysis provides 12-h fields of air temperatures on a 100-km rectangular grid for all land and ocean areas of the Arctic region for the years 1979-97.

The role of time in ecology has a long history of investigation, but ecologists have largely restricted their attention to the influence of concurrent abiotic conditions on rates and magnitudes of important ecological processes. Recently, however, ecologists have improved their understanding of ecological processes by explicitly considering the effects of antecedent conditions. To broadly help in studying the role of time, we evaluate the length, temporal pattern, and strength of memory with respect to the influence of antecedent conditions on current ecological dynamics. We developed the stochastic antecedent modelling (SAM) framework as a flexible analytic approach for evaluating exogenous and endogenous process components of memory in a system of interest. We designed SAM to be useful in revealing novel insights promoting further study, illustrated in four examples with different degrees of complexity and varying time scales: stomatal conductance, soil respiration, ecosystem productivity, and tree growth. Models with antecedent effects explained an additional 18-28% of response variation compared to models without antecedent effects. Moreover, SAM also enabled identification of potential mechanisms that underlie components of memory, thus revealing temporal properties that are not apparent from traditional treatments of ecological time-series data and facilitating new hypothesis generation and additional research.

Using a parameterization for internal wave energy flux in a hydrodynamic model for the tides, we estimate the global distribution of tidal energy available for enhanced turbulent mixing. A relation for the diffusivity of vertical mixing is formulated for regions where internal tides dissipate their energy as turbulence. We assume that 30 ± 10% of the internal tide energy flux dissipates as turbulence near the site of generation, consistent with an estimate based on microstructure observations from a mid‐ocean ridge site. Enhanced levels of mixing are modeled to decay away from topography, in a manner consistent with these observations. Parameterized diffusivities are shown to resemble observed abyssal mixing rates, with estimated uncertainties comparable to standard errors associated with budget and microstructure methods.

The GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well asaerosol and rain data characterising atmospherictrace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-σ data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 25 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017.

The influence of realistic Arctic sea ice anomalies on the atmosphere during winter is investigated with version 3.6 of the Community Climate Model (CCM3.6). Model experiments are performed for the winters with the most (1982/83) and least (1995/96) Arctic ice coverage during 1979-99, when ice concentration estimates were available from satellites. The experiments consist of 50-member ensembles: using large ensembles proved critical to distinguish the signal from noise.

Recent record lows of Arctic summer sea ice extent are found to be triggered by the Arctic atmospheric Dipole Anomaly (DA) pattern. This local, second–leading mode of sea–level pressure (SLP) anomaly in the Arctic produced a strong meridional wind anomaly that drove more sea ice out of the Arctic Ocean from the western to the eastern Arctic into the northern Atlantic during the summers of 1995, 1999, 2002, 2005, and 2007. In the 2007 summer, the DA also enhanced anomalous oceanic heat flux into the Arctic Ocean via Bering Strait, which accelerated bottom and lateral melting of sea ice and amplified the ice–albedo feedback. A coupled ice–ocean model was used to confirm the historical record lows of summer sea ice extent.

Abstract Changing climate in northern regions is causing permafrost to thaw with major implications for the global mercury (Hg) cycle. We estimated Hg in permafrost regions based on in situ measurements of sediment total mercury (STHg), soil organic carbon (SOC), and the Hg to carbon ratio (R HgC ) combined with maps of soil carbon. We measured a median STHg of 43 ± 30 ng Hg g soil −1 and a median R HgC of 1.6 ± 0.9 μg Hg g C −1 , consistent with published results of STHg for tundra soils and 11,000 measurements from 4,926 temperate, nonpermafrost sites in North America and Eurasia. We estimate that the Northern Hemisphere permafrost regions contain 1,656 ± 962 Gg Hg, of which 793 ± 461 Gg Hg is frozen in permafrost. Permafrost soils store nearly twice as much Hg as all other soils, the ocean, and the atmosphere combined, and this Hg is vulnerable to release as permafrost thaws over the next century. Existing estimates greatly underestimate Hg in permafrost soils, indicating a need to reevaluate the role of the Arctic regions in the global Hg cycle.

Polar ice-core records suggest that an arctic or boreal source was responsible for more than 30% of the large increase in global atmospheric methane (CH4) concentration during deglacial climate warming; however, specific sources of that CH4 are still debated. Here we present an estimate of past CH4 flux during deglaciation from bubbling from thermokarst (thaw) lakes. Based on high rates of CH4 bubbling from contemporary arctic thermokarst lakes, high CH4 production potentials of organic matter from Pleistocene-aged frozen sediments, and estimates of the changing extent of these deposits as thermokarst lakes developed during deglaciation, we find that CH4 bubbling from newly forming thermokarst lakes comprised 33 to 87% of the high-latitude increase in atmospheric methane concentration and, in turn, contributed to the climate warming at the Pleistocene-Holocene transition.

The greatest impacts of climate change on ecosystems, wildlife and humans often arise from extreme events rather than changes in climatic means. Northern high latitudes, including the Arctic, experience a variety of climate-related extreme events, yet there has been little attempt to synthesize information on extreme events in this region. This review surveys work on various types of extreme events in northern high latitudes, addressing (1) the evidence for variations and changes based on analyses of recent historical data and (2) projected changes based primarily on studies utilizing global climate models. The survey of extreme weather and climate events includes temperature, precipitation, snow, freezing rain, atmospheric blocking, cyclones, and wind. The survey also includes cryospheric and biophysical impacts: sea ice rapid loss events, Greenland Ice Sheet melt, floods, drought, wildfire, coastal erosion, terrestrial ecosystems, and marine ecosystems. Temperature and sea ice rank at the high end of the spectra of evidence for change and confidence in future change, while drought, flooding and cyclones rank at the lower end. Research priorities identified on the basis of this review include greater use of high-resolution models and observing system enhancements that target extreme events. There is also a need for further work on attribution, impacts on ecosystems and humans, and thresholds or tipping points that may be triggered by extreme events in high latitudes.

Arctic climate system change has accelerated tremendously since the beginning of this century, and a strikingly extreme sea‐ice loss occurred in summer 2007. However, the greenhouse‐gas‐emissions forcing has only increased gradually and the driving role in Arctic climate change of the positively‐polarized Arctic/North Atlantic Oscillation (AO/NAO) trend has substantially weakened. Although various contributing factors have been examined, the fundamental physical process, which orchestrates these contributors to drive the acceleration and the latest extreme event, remains unknown. We report on drastic, systematic spatial changes in atmospheric circulations, showing a sudden jump from the conventional tri‐polar AO/NAO to an unprecedented dipolar leading pattern, following accelerated northeastward shifts of the AO/NAO centers of action. These shifts provide an accelerating impetus for the recent rapid Arctic climate system changes, perhaps shedding light on recent arguments about a tipping point of global‐warming‐forced climate change in the Arctic. The radical spatial shift is a precursor to the observed extreme change event, demonstrating skilful information for future prediction.

The reliability of the global reanalyses in the polar regions is investigated. The overview stems from an April 2006 Scientific Committee on Antarctic Research (SCAR) workshop on the performance of global reanalyses in high latitudes held at the British Antarctic Survey. Overall, the skill is much higher in the Arctic than the Antarctic, where the reanalyses are only reliable in the summer months prior to the modern satellite era. In the Antarctic, large circulation differences between the reanalyses are found primarily before 1979, when vast quantities of satellite sounding data started to be assimilated. Specifically for ERA‐40, this data discontinuity creates a marked jump in Antarctic snow accumulation, especially at high elevations. In the Arctic, the largest differences are related to the reanalyses' depiction of clouds and their associated radiation impacts; ERA‐40 captures the cloud variability much better than NCEP1 and JRA‐25, but the ERA‐40 and JRA‐25 clouds are too optically thin for shortwave radiation. To further contrast the reanalyses skill, cyclone tracking results are presented. In the Southern Hemisphere, cyclonic activity is markedly different between the reanalyses, where there are few matched cyclones prior to 1979. In comparison, only some of the weaker cyclones are not matched in the Northern Hemisphere from 1958–2001, again indicating the superior skill in this hemisphere. Although this manuscript focuses on deficiencies in the reanalyses, it is important to note that they are a powerful tool for climate studies in both polar regions when used with a recognition of their limitations.

Abstract The climate in the Arctic is changing faster than in midlatitudes. This is shown by increased temperatures, loss of summer sea ice, earlier snow melt, impacts on ecosystems, and increased economic access. Arctic sea ice volume has decreased by 75% since the 1980s. Long‐lasting global anthropogenic forcing from carbon dioxide has increased over the previous decades and is anticipated to increase over the next decades. Temperature increases in response to greenhouse gases are amplified in the Arctic through feedback processes associated with shifts in albedo, ocean and land heat storage, and near‐surface longwave radiation fluxes. Thus, for the next few decades out to 2040, continuing environmental changes in the Arctic are very likely, and the appropriate response is to plan for adaptation to these changes. For example, it is very likely that the Arctic Ocean will become seasonally nearly sea ice free before 2050 and possibly within a decade or two, which in turn will further increase Arctic temperatures, economic access, and ecological shifts. Mitigation becomes an important option to reduce potential Arctic impacts in the second half of the 21st century. Using the most recent set of climate model projections ( CMIP5 ), multimodel mean temperature projections show an Arctic‐wide end of century increase of +13°C in late fall and +5°C in late spring for a business‐as‐usual emission scenario ( RCP8 .5) in contrast to +7°C in late fall and +3°C in late spring if civilization follows a mitigation scenario ( RCP4 .5). Such temperature increases demonstrate the heightened sensitivity of the Arctic to greenhouse gas forcing.

Abstract Aims Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

Current consensus on global climate change predicts warming trends driven by anthropogenic forcing, with maximum temperature changes projected in the Northern Hemisphere (NH) high latitudes during winter. Yet, global temperature trends show little warming over the most recent decade or so. For longer time periods appropriate to the assessment of trends, however, global temperatures have experienced significant warming trends for all seasons except winter, when cooling trends exist instead across large stretches of eastern North America and northern Eurasia. Hence, the most recent lapse in global warming is a seasonal phenomenon, prevalent only in boreal winter. Additionally, we show that the largest regional contributor to global temperature trends over the past two decades is land surface temperatures in the NH extratropics. Therefore, proposed mechanisms explaining the fluctuations in global annual temperatures should address this apparent seasonal asymmetry.

Arctic variability is dominated by multi‐decadal fluctuations. Incomplete sampling of these fluctuations results in highly variable arctic surface‐air temperature (SAT) trends. Modulated by multi‐decadal variability, SAT trends are often amplified relative to northern‐hemispheric trends, but over the 125‐year record we identify periods when arctic SAT trends were smaller or of opposite sign than northern‐hemispheric trends. Arctic and northern‐hemispheric air‐temperature trends during the 20th century (when multi‐decadal variablity had little net effect on computed trends) are similar, and do not support the predicted polar amplification of global warming. The possible moderating role of sea ice cannot be conclusively identified with existing data. If long‐term trends are accepted as a valid measure of climate change, then the SAT and ice data do not support the proposed polar amplification of global warming. Intrinsic arctic variability obscures long‐term changes, limiting our ability to identify complex feedbacks in the arctic climate system.