Found 2670 publications. Showing page 68 of 267:
Interactions between the atmosphere, cryosphere, and ecosystems at northern high latitudes
The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date, aiming to strengthen research and innovation regarding climate change issues in the Nordic region. CRAICC gathered more than 100 scientists from all Nordic countries in a virtual centre with the objectives of identifying and quantifying the major processes controlling Arctic warming and related feedback mechanisms, outlining strategies to mitigate Arctic warming, and developing Nordic Earth system modelling with a focus on short-lived climate forcers (SLCFs), including natural and anthropogenic aerosols.
The outcome of CRAICC is reflected in more than 150 peer-reviewed scientific publications, most of which are in the CRAICC special issue of the journal Atmospheric Chemistry and Physics. This paper presents an overview of the main scientific topics investigated in the centre and provides the reader with a state-of-the-art comprehensive summary of what has been achieved in CRAICC with links to the particular publications for further detail. Faced with a vast amount of scientific discovery, we do not claim to completely summarize the results from CRAICC within this paper, but rather concentrate here on the main results which are related to feedback loops in climate change–cryosphere interactions that affect Arctic amplification.
2019
A number of studies have shown that assimilation of satellite derived soil moisture using the ensemble Kalman Filter (EnKF) can improve soil moisture estimates, particularly for the surface zone. However, the EnKF is computationally expensive since an ensemble of model integrations have to be propagated forward in time. Here, assimilating satellite soil moisture data from the Soil Moisture Active Passive (SMAP) mission, we compare the EnKF with the computationally cheaper ensemble Optimal Interpolation (EnOI) method over the contiguous United States (CONUS). The background error–covariance in the EnOI is sampled in two ways: (i) by using the stochastic spread from an ensemble open-loop run, and (ii) sampling from the model spinup climatology. Our results indicate that the EnKF is only marginally superior to one version of the EnOI. Furthermore, the assimilation of SMAP data using the EnKF and EnOI is found to improve the surface zone correlation with in situ observations at a 95% significance level. The EnKF assimilation of SMAP data is also found to improve root-zone correlation with independent in situ data at the same significance level; however this improvement is dependent on which in situ network we are validating against. We evaluate how the quality of the atmospheric forcing affects the analysis results by prescribing the land surface data assimilation system with either observation corrected or model derived precipitation. Surface zone correlation skill increases for the analysis using both the corrected and model derived precipitation, but only the latter shows an improvement at the 95% significance level. The study also suggests that assimilation of satellite derived surface soil moisture using the EnOI can correct random errors in the atmospheric forcing and give an analysed surface soil moisture close to that of an open-loop run using observation derived precipitation. Importantly, this shows that estimates of soil moisture could be improved using a combination of assimilating SMAP using the computationally cheap EnOI while using model derived precipitation as forcing. Finally, we assimilate three different Level-2 satellite derived soil moisture products from the European Space Agency Climate Change Initiative (ESA CCI), SMAP and SMOS (Soil Moisture and Ocean Salinity) using the EnOI, and then compare the relative performance of the three resulting analyses against in situ soil moisture observations. In this comparison, we find that all three analyses offer improvements over an open-loop run when comparing to in situ observations. The assimilation of SMAP data is found to perform marginally better than the assimilation of SMOS data, while assimilation of the ESA CCI data shows the smallest improvement of the three analysis products.
2019
2019
We present here emissions estimated from a newly developed emission model for residential wood combustion (RWC) at high spatial and temporal resolution, which we name the MetVed model. The model estimates hourly emissions resolved on a 250 m grid resolution for several compounds, including particulate matter (PM), black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) in Norway for a 12-year period. The model uses novel input data and calculation methods that combine databases built with an unprecedented high level of detail and near-national coverage. The model establishes wood burning potential at the grid based on the dependencies between variables that influence emissions: i.e. outdoor temperature, number of and type and size of dwellings, type of available heating technologies, distribution of wood-based heating installations and their associated emission factors. RWC activity with a 1 h temporal profile was produced by combining heating degree day and hourly and weekday activity profiles reported by wood consumers in official statistics. This approach results in an improved characterisation of the spatio-temporal distribution of wood use, and subsequently of emissions, required for urban air quality assessments. Whereas most variables are calculated based on bottom-up approaches on a 250 m spatial grid, the MetVed model is set up to use official wood consumption at the county level and then distributes consumption to individual grids proportional to the physical traits of the residences within it. MetVed combines consumption with official emission factors that makes the emissions also upward scalable from the 250 m grid to the national level.
The MetVed spatial distribution obtained was compared at the urban scale to other existing emissions at the same scale. The annual urban emissions, developed according to different spatial proxies, were found to have differences up to an order of magnitude. The MetVed total annual PM2.5 emissions in the urban domains compare well to emissions adjusted based on concentration measurements. In addition, hourly PM2.5 concentrations estimated by an Eulerian dispersion model using MetVed emissions were compared to measurements at air quality stations. Both hourly daily profiles and the seasonality of PM2.5 show a slight overestimation of PM2.5 levels. However, a comparison with black carbon from biomass burning and benzo(a)pyrene measurements indicates higher emissions during winter than that obtained by MetVed. The accuracy of urban emissions from RWC relies on the accuracy of the wood consumption (activity data), emission factors and the spatio-temporal distribution. While there are still knowledge gaps regarding emissions, MetVed represents a vast improvement in the spatial and temporal distribution of RWC.
2019
2019
Highly unusual open fires burned in western Greenland between 31 July and 21 August 2017, after a period of warm, dry and sunny weather. The fires burned on peatlands that became vulnerable to fires by permafrost thawing. We used several satellite data sets to estimate that the total area burned was about 2345 ha. Based on assumptions of typical burn depths and emission factors for peat fires, we estimate that the fires consumed a fuel amount of about 117 kt C and emitted about 23.5 t of black carbon (BC) and 731 t of organic carbon (OC), including 141 t of brown carbon (BrC). We used a Lagrangian particle dispersion model to simulate the atmospheric transport and deposition of these species. We find that the smoke plumes were often pushed towards the Greenland ice sheet by westerly winds, and thus a large fraction of the emissions (30 %) was deposited on snow- or ice-covered surfaces. The calculated deposition was small compared to the deposition from global sources, but not entirely negligible. Analysis of aerosol optical depth data from three sites in western Greenland in August 2017 showed strong influence of forest fire plumes from Canada, but little impact of the Greenland fires. Nevertheless, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar data showed that our model captured the presence and structure of the plume from the Greenland fires. The albedo changes and instantaneous surface radiative forcing in Greenland due to the fire emissions were estimated with the SNICAR model and the uvspec model from the libRadtran radiative transfer software package. We estimate that the maximum albedo change due to the BC and BrC deposition was about 0.007, too small to be measured. The average instantaneous surface radiative forcing over Greenland at noon on 31 August was 0.03–0.04 W m−2, with locally occurring maxima of 0.63–0.77 W m−2 (depending on the studied scenario). The average value is up to an order of magnitude smaller than the radiative forcing from other sources. Overall, the fires burning in Greenland in the summer of 2017 had little impact on the Greenland ice sheet, causing a small extra radiative forcing. This was due to the – in a global context – still rather small size of the fires. However, the very large fraction of the emissions deposited on the Greenland ice sheet from these fires could contribute to accelerated melting of the Greenland ice sheet if these fires become several orders of magnitude larger under future climate.
2019
2019
Snow initialization has been previously investigated as a potential source of predictability atthe subseasonal‐to‐seasonal (S2S) timescale in winter and spring, through its local radiative,thermodynamical, and hydrological feedbacks. However, previous studies were conducted with low‐topmodels over short periods only. Furthermore, the potential role of the land surface‐stratosphere connectionupon the S2S predictability had remained unclear. To this end, we have carried out twin 30‐memberensembles of 2‐month (November and December) retrospective forecasts over the period 1985–2016, witheither realistic or degraded snow initialization. A high‐top version of the Norwegian Climate PredictionModel is used, based on the Whole Atmosphere Community Climate Model, to insure improved couplingwith the stratosphere. In a composite difference of high versus low initial Eurasian snow, the surfacetemperature is strongly impacted by the presence of snow, and wave activityfluxes into the stratosphere areenhanced at a 1‐month lag, leading to a weakened polar vortex. Focusing further on 7 years characterized bya strongly negative phase of the Arctic Oscillation, wefind a weak snow feedback contributing to themaintenance of the negative Arctic Oscillation. By comparing the twin forecasts, we extracted the predictiveskill increment due to realistic snow initialization. The prediction of snow itself is greatly improved, andthere is increased skill in surface temperature over snow‐covered land in thefirst 10 days, and localized skillincrements in the mid‐latitude transition regions on the southernflanks of the snow‐covered land areas, atlead times longer than 30 days.
2019
This study investigated relationships between organohalogen compound (OHC) exposure, feeding habits, and pathogen exposure in a recovering population of Atlantic walruses (Odobenus rosmarus rosmarus) from the Svalbard Archipelago, Norway. Various samples were collected from 39 free-living, apparently healthy, adult male walruses immobilised at three sampling locations during the summers of 2014 and 2015. Concentrations of lipophilic compounds (polychlorinated biphenyls, organochlorine pesticides and polybrominated diphenyl ethers) were analysed in blubber samples, and concentrations of perfluoroalkylated substances (PFASs) were determined in plasma samples. Stable isotopes of carbon and nitrogen were measured in seven tissue types and surveys for three infectious pathogens were conducted. Despite an overall decline in lipophilic compound concentrations since this population was last studied (2006), the contaminant pattern was similar, including extremely large inter-individual variation. Stable isotope ratios of carbon and nitrogen showed that the variation in OHC concentrations could not be explained by some walruses consuming higher trophic level diets, since all animals were found to feed at a similar trophic level. Antibodies against the bacteria Brucella spp. and the parasite Toxoplasma gondii were detected in 26% and 15% of the walruses, respectively. Given the absence of seal-predation, T. gondii exposure likely took place via the consumption of contaminated bivalves. The source of exposure to Brucella spp. in walruses is still unknown. Parapoxvirus DNA was detected in a single individual, representing the first documented evidence of parapoxvirus in wild walruses. Antibody prevalence was not related to contaminant exposure. Despite this, dynamic relationships between diet composition, contaminant bioaccumulation and pathogen exposure warrant continuing attention given the likelihood of climate change induced habitat and food web changes, and consequently OHC exposure, for Svalbard walruses in the coming decades.
2019
2019