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Intense, southward low-level winds are common in Nares Strait, between Ellesmere Island and northern Greenland. The steep topography along Nares Strait leads to channelling effects, resulting in an along-strait flow. This research study presents a 30-year climatology of the flow regime from simulations of the COSMO-CLM climate model. The simulations are available for the winter periods (November–April) 1987/88 to 2016/17, and thus, cover a period long enough to give robust long-term characteristics of Nares Strait. The horizontal resolution of 15 km is high enough to represent the complex terrain and the meteorological conditions realistically. The 30-year climatology shows that LLJs associated with gap flows are a climatological feature of Nares Strait. The maximum of the mean 10-m wind speed is around 12 m s-1 and is located at the southern exit of Smith Sound. The wind speed is strongly related to the pressure gradient. Single events reach wind speeds of 40 m s-1 in the daily mean. The LLJs are associated with gap flows within the narrowest parts of the strait under stably stratified conditions, with the main LLJ occurring at 100–250 m height. With increasing mountain Froude number, the LLJ wind speed and height increase. The frequency of strong wind events (>20 m s-1 in the daily mean) for the 10 m wind shows a strong interannual variability with an average of 15 events per winter. Channelled winds have a strong impact on the formation of the North Water polynya.

Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combination with atmospheric reanalysis data have proven to be a strong tool to monitor large and regularly forming polynyas and to resolve narrow thin-ice areas (i.e., leads) along the shelf-breaks and across the entire Arctic Ocean. However, the selection of the atmospheric data sets has a large influence on derived polynya characteristics due to their impact on the calculation of the heat loss to the atmosphere, which is determined by the local thin-ice thickness. In order to overcome this methodical ambiguity, we present a MODIS-assisted temperature adjustment (MATA) algorithm that yields corrections of the 2 m air temperature and hence decreases differences between the atmospheric input data sets. The adjustment algorithm is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies on the developed algorithm and present time series of polynya characteristics in the winter season 2019/2020. It shows that the application of the empirically derived correction decreases the difference between different utilized atmospheric products significantly from 49% to 23%. Additional filter strategies are applied that aim at increasing the capability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites. More generally, the winter of 2019/2020 features high polynya activity in the eastern Arctic and less activity in the Canadian Arctic Archipelago, presumably as a result of the particularly strong polar vortex in early 2020.

International audience; With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore crosscutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge.The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

The parameterization of the boundary layer is a challenge for regional climate models of the Arctic. In particular, the stable boundary layer (SBL) over Greenland, being the main driver for substantial katabatic winds over the slopes, is simulated differently by different regional climate models or using different parameterizations of the same model. However, verification data sets with high-resolution profiles of the katabatic wind are rare. In the present paper, detailed aircraft measurements of profiles in the katabatic wind and automatic weather station data during the experiment KABEG (Katabatic wind and boundary-layer front experiment around Greenland) in April and May 1997 are used for the verification of the regional climate model COSMO-CLM (CCLM) nested in ERA-Interim reanalyses. CCLM is used in a forecast mode for the whole Arctic with 15 km resolution and is run in the standard configuration of SBL parameterization and with modified SBL parameterization. In the modified version, turbulent kinetic energy (TKE) production and the transfer coefficients for turbulent fluxes in the SBL are reduced, leading to higher stability of the SBL. This leads to a more realistic representation of the daily temperature cycle and of the SBL structure in terms of temperature and wind profiles for the lowest 200 m.

For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H 2 O and CO 2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H 2 O and CO 2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO 2 fluxes was less robust than for H 2 O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration-evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated page1112 negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

Droughts and heat waves deeply interact with the exchange of energy and matter between land surface and atmosphere. The conditions associated with a combined heat wave and drought can have positive or negative effects on the sensible heat flux (H), latent heat flux (LE), and net flux of CO2 (NEE). In return, while each of these fluxes can exert different local feedbacks on temperature, atmospheric humidity and soil moisture, all of them result in bulk heating of the troposphere (H and LE through direct local and indirect non-local heat transfer, and NEE through radiative forcing). H is positively affected by increased solar irradiation, but can be supressed by advection of warm air diminishing the gradient between surface and air temperature. Potential LE is positively affected by irradiation, temperature and water vapour pressure deficit, but actual LE can be suppressed by stomatal closure of plants and by reduced soil moisture from low rainfall and high past LE. NEE is the result of plant photosynthesis (GPP) and plant and soil respiration (R), both of which can be enhanced by high temperatures or irradiation, and suppressed by drought. Focusing on direct measurements mostly by a network of Eddy-Covariance (EC) stations of the ICOS (www.icosri.eu), TERENO (www.tereno.net) and other networks, we hypothesize that the net effect of the 2018 event at a site, and thus its feedback on global warming, depends on the balance between co-existing positive and negative effects of the combined heat wave and drought on the respective fluxes. Variables such as albedo, growing degreedays (GDD), soil moisture and ecosystem-level water use efficiency help to separate these co-existing positive and negative effects from each other. Preliminary results indicate different degrees of heterogeneity between sites fordifferent variables. As expected, reduced precipitation and soil moisture, as well as increased GDD, could be found at almost all sites in the affected region. NEE was mostly less negative, indicating a weaker sink or even a source forCO2, as expected from past studies on earlier events. The network density and number of site-years available now confirms that this was true for all major ecosystem types - forest, grassland and (rainfed) cropland, and resultedin increased atmospheric CO2 concentrations. However, notable exceptions occurred at elevated low mountain range sites and during early stages of the event, supporting the hypothesis of a balance between positive andnegative effects, where the former may prevail at strongly energy-limited sites with a usually large water surplus. H was mostly above-average, indicating that local heat production contributed to the event and was typically notsuppressed by warm air advection. LE as well as inferred GPP and R reacted most heterogeneously across sites, demonstrating the large discrepancy between potentially high fluxes due to high irradiation and temperature on theone hand, and suppression by water shortage on the other hand. Despite the variability in LE, its relation to NEE was such that ecosystem-level water use was less efficient than usual at the majority of sites through reduced CO2uptake.

Forest ecosystems in the mid latitudes are a sink for atmospheric carbon dioxide (CO$_2$) and thus play an important role in the global carbon cycle [1]. Deforestation has a major impact on the CO$_2$ exchange between the forested ecosystem and the atmosphere. After deforestation, the former forest sink becomes a source for CO$_2$. We present seven years of CO$_2$ flux measurements sampled above a 70 year old spruce monoculture, of which 9 ha was partially deforested three years after the measurement started, in order to promote the natural succession towards deciduous forest.The measurements were carried out in the Wüstebach research site, a small headwater catchment (38.5 ha) within the TERENO (TERrestrial ENvironmental Observatories) network in the Eifel National Park Germany (50°30'N, 06°19'E, 595-629 m a.s.l.). An EC system, mounted on the top of a 37.8 m high tower, continuously samples fluxes of momentum, sensible heat, latent heat and CO$_2$. After the partial deforestation, a second EC station was installed in the middle of the clearcut and operated simultaneously to the forest station. Full time series and annual carbon budgets of the net ecosystem exchange of CO$_2$ (NEE) and its components gross primary production (GPP) and total ecosystem respiration were calculated by using gap filling and flux partitioning methods. Besides the NEE and its components, we also considered the measured soil respiration and compare the climate effect of changed CO$_2$ sequestration with the biophysical effect of changed albedo.In contrast to the deforested area, annual sums of NEE measured above the forest showed a strong carbon sink with small inter-annual variability. In the first year after partial deforestation, regrowth on the deforested area consisted mainly of grasses and shrub vegetation while since the second year also growth of new trees (predominantly mountain ash) increased. The recovering vegetation is reflected in the annual sums of NEE, which decreased from a carbon source of + 500 g C m-2 y-1 towards neutral over the past four years, due to an increase in the photosynthetically activities.References:[1] IPCC. Climate Change 2013: The Physical Science Basis. (eds Stocker, T. F. et al.) Cambridge Univ. Press, (2014).