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Additional file 1. Histotical and projected C stocks and fluxes.

These data sets provide the WRF [1] calculated wind data for Pritzwalk (onshore) and FINO3 (offshore) as Python dictionaries. Additionally, the files contain k-means cluster objects derived from these profiles. These data sets were used for power assessment and design exploration of Airborne Wind Energy Systems using the awebox [2] optimization toolbox. WRF setups are described in detail and used in publication [3,4,5]. Wind data are interpolated to fixed heights of: [10, 28, 50, 70, 90, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 700, 800, 1000, 1200] meters above ground. Onshore wind data: Location lat: 53° 10.78' N; long: 12° 11.35' E Time: 1 September 2015 - 31 August 2016 Timestep: 10 min Offshore wind data: Location lat: 55° 11.7' N, long: 7° 9.5' E Time: 1 September 2013 - 31 August 2014 Timestep: 10 min The clusters are derived from both horizontal wind velocity components using the scikit-learn’s k-means clustering algorithm [6]. For our purposes, wind vectors were rotated such that the main wind speed always points in the same direction (u_main,u_deviation). [1]: Weather Research and Forecasting Model [2]: awebox [3]: Improving mesoscale wind speed forecasts using lidar-based observation nudging for airborne wind energy systems [4]: Offshore and onshore ground-generation airborne wind energy power curve characterization [5]:Ground-generation airborne wind energy design space exploration [6]: sklearn.cluster.KMeans

Select monthly climate data for provinces in Canada. Monthly data includes mean temperature, maximum temperatures, minimum temperature, snow, precipitation, HDD, CDD, and Trade.

Rapid, ongoing permafrost thaw of peatlands in the discontinuous permafrost zone is exposing a globally significant store of soil carbon (C) to microbial processes. Mineralisation and release of this peat C to the atmosphere as greenhouse gases is a potentially important feedback to climate change. Here we investigated the effects of permafrost thaw on peat C at a peatland complex in western Canada. We collected 15 complete peat cores (between 2.7 abd 4.5 m deep) along four chronosequences, from elevated permafrost plateaus to saturated thermokarst bogs that thawed up to 600 years ago. The peat cores were analysed for peat C storage and peat quality, as indicated by decomposition proxies (FTIR and C/N ratios) and potential decomposability using a 200-day aerobic incubation. Our results suggest net C loss following thaw, with average total peat C stocks decreasing by ~19.3 +/- 7.2 kg C m-2 over <600 years (~13% loss). Average post-thaw accumulation of new peat at the surface over the same period was ~13.1 +/- 2.5 kg C m-2. We estimate ~19% (+/- 5.8%) of deep peat (>40 cm below surface) C is lost following thaw (average 26 +/- 7.9 kg C m-2 over <600 years). Our FTIR analysis shows peat below the thaw transition in thermokarst bogs is slightly more decomposed than peat of a similar type and age in permafrost plateaus, but we found no significant changes to the quality or lability of deeper peat across the chronosequences. Our incubation results also showed no increase in C mineralisation of deep peat across the chronosequences. While these limited changes in peat quality in deeper peat following permafrost thaw highlight uncertainty in the exact mechanisms and processes for C loss, our analysis of peat C stocks shows large C losses following permafrost thaw in peatlands in western Canada.

This repository contains the raw data of the inputs and results presented in the paper "Electrification of light-duty vehicle fleet alone will not meet mitigation targets" published in Nature Climate Change (2020) by Alexandre Milovanoff, I. Daniel Posen, and Heather L. MacLean (Department of Civil & Mineral Engineering, University of Toronto).

Global transition towards renewable energy production has increased the demand for new and more flexible hydropower operations. Before management and stakeholders can make informed choices on potential mitigations, it is essential to understand how the hydropower reservoir ecosystems respond to water level regulation (WLR) impacts that are likely modified by the reservoirs' abiotic and biotic characteristics. Yet, most reservoir studies have been case-specific, which hampers large-scale planning, evaluation and mitigation actions across various reservoir ecosystems. Here, we investigated how the effect of the magnitude, frequency and duration of WLR on fish populations varies along environmental gradients. We used biomass, density, size, condition and maturation of brown trout (Salmo trutta L.) in Norwegian hydropower reservoirs as a measure of ecosystem response, and tested for interacting effects of WLR and lake morphometry, climatic conditions and fish community structure. Our results showed that environmental drivers modified the responses of brown trout populations to different WLR patterns. Specifically, brown trout biomass and density increased with WLR magnitude particularly in large and complex-shaped reservoirs, but the positive relationships were only evident in reservoirs with no other fish species. Moreover, increasing WLR frequency was associated with increased brown trout density but decreased condition of individuals within the populations. WLR duration had no significant impacts on brown trout, and the mean weight and maturation length of brown trout showed no significant response to any WLR metrics. Our study demonstrates that local environmental characteristics and the biotic community strongly modify the hydropower-induced WLR impacts on reservoir fishes and ecosystems, and that there are no one-size-fits-all solutions to mitigate environmental impacts. This knowledge is vital for sustainable planning, management and mitigation of hydropower operations that need to meet the increasing worldwide demand for both renewable energy and ecosystem services delivered by freshwaters. Data of environmental characteristics and brown trout populations in 102 Norwegian hydropower reservoirsThe data contains field-collected data of brown trout populations in 102 Norwegian reservoirs with variable environmental characteristics. The brown trout data (i.e. response variables) include estimates of: "Biomass" (grams of fish per 100m2 net per night); "Density" (number of fish per 100m2 net per night); "Mean weight" (mean wet mass in grams); "Mean condition" (mean Fulton's condition factor); and "Mean maturity length" (mean total length of mature females in millimeters). All abbreviations for different variables (columns) are explained in the paper. Many reservoirs ("Lake") have various names, some including Norwegian letters (æ, ø & å). Hence, we recommend to use coordinate data (EPSG:4326; "decimalLongitude" and "decimalLatitude") and Norwegian national lake ID numbers ("Lake_nr"; managed by the Norwegian Water Resources and Energy Directorate; www.nve.no) to locate the reservoirs. The variables "Year", "Month" and "Day" refer to times when survey fishing was conducted. Lake morphometry data ("A"=surface area, "SD"=shoreline development) is obtained from NVE database. The lake climatic and catchment data ("T"=mean July air temperature, "NDVI"= Normalized Difference Vegetation Index, and "SL"=terrain slope) is obtained and measured as described by Finstad et al. (2014; DOI: 10.1111/ele.12201). Other abbreviations include: "FC"=presence of other fish species (1=absent, 2=present); "GS"=gillnet series (1=Nordic, 2=Jensen); and "ST"=brown trout stocking (0=no stocking, 1=stocking). The water level regulation (WLR) metrics include: ): "WLR_magnitude"= maximum regulation amplitude; "WLR_frequency"=relative proportion of weeks with a sudden rise or drop in water level; and "WLR_duration"=the relative proportion of weeks with exceptionally low water levels.Data-in_doi.org-10.1016-j.scitotenv.2017.10.268.xlsx

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

A Calypso Square gravity core AMD15-Casq1 (543 cm) and corresponding box core (40 cm) were collected in 2015 from the central north NOW (77°15.035’ N, 74°25.500’ W, 692 m water depth) (Figure 1) during the ArcticNet Leg 4a, onboard the Canadian Coast Guard Ship Amundsen. Core chronology: The core chronology is based on 11 accelerator mass spectrometry (AMS) dates on mollusc shells from the Calypso core, and 210Pb and 137Cs measurements on 20 samples from the box core (see Jackson et al. (2021) for more details). Here, all radiocarbon dates were calibrated using the latest marine calibration curve (Marine20; Heaton et al., 2020; Table S1). In Jackson et al. (2021), and using the Marine13 calibration curve, a local reservoir correction of 140 ± 60 years was applied based on measurements from a live marine mollusc specimen collected from the NOW before the mid-1950’s (McNeely & Brennan, 2005). Using the Marine20 calibration curve, this specimen now yields a reservoir offset of –4 ± 60 years. In line with this reduced reservoir offset for the Marine 20 (vs. Marine13) calibration curve, and owing to the lack of a regional ΔR term for the polynya (Pieńkowski et al., 2023), no additional reservoir age correction (i.e., ΔR=0) was applied. A mixed age-depth model was constructed using the bacon-package in R (Blaauw & Christen, 2011). Accordingly, the composite core covers the last ca. 3800 cal years BP. We note that the new calibration only resulted in negligible changes compared to the age model presented in Jackson et al. (2021). Diatom analyses: Sediment samples for diatom analysis were prepared following the protocol described in Crosta et al. (2020). Approximately 0.3 g of dry sediment was treated with an oxidative solution composed of hydrogen peroxide (H2O2), distilled water and tetrasodium pyrophosphate (decahydrate, Na4O7P2-10H2O) in a warm bath (~65°C) for several hours until the reaction ceased. The residue was then rinsed repeatedly with distilled water by centrifugation (7 min at 1200 rpm). Hydrochloric acid (HCl, 30%) was used to remove the carbonate content. The residue was again rinsed several times until neutral pH, and microscopy slides were mounted in Naphrax©. In each sample, ca. 300 diatom valves were identified to the lowest taxonomic level possible. Resting spores of Chaetoceros were counted, but not included in the relative abundance calculations. Census counts were done using a light microscope (Olympus BX53, UNB) with dark field, phase contrast optics and oil immersion, at 1000X magnification. We followed the counting rules presented in Crosta and Koç (2007): specimens were counted when at least half of the valve was observed, with the exception of Rhizosolenia and Thalassiothrix taxa that were only counted when the spine-like proboscis or appendix was visible, respectively. The Pikialasorsuaq (North Water polynya) is an area of local and global cultural and ecological significance. However, over the last decades, the region has been subject to rapid warming and, in some recent years, the seasonal ice arch that has historically defined the polynya’s northern boundary has failed to form. Both factors are deemed to alter the polynya’s ecosystem functioning. To understand how climate-induced changes to the Pikialasorsuaq impact the basis of the marine food web, we explored diatom community-level responses to changing conditions, from a sediment core spanning the last 3800 years. Four metrics were used: total diatom concentrations, taxonomic composition, mean size, and diversity. Generalized additive model statistics highlight significant changes at ca. 2400, 2050, 1550, 1200, and 130 cal years BP, all coeval with known transitions between colder and warmer intervals of the Late Holocene, and regime shifts in the Pikialasorsuaq. Notably, a weaker/contracted polynya during the Roman Warm Period and Medieval Climate Anomaly caused the diatom community to reorganize via shifts in species composition, with the presence of larger taxa but lower diversity, and significantly reduced export production. This study underlines the high sensitivity of primary producers to changes in the polynya dynamics and illustrates that the strong pulse of early-spring cryopelagic diatoms that makes the Pikialasorsuaq exceptionally productive may be jeopardized by rapid warming and associated Nares Strait ice arch destabilization. Future alterations to the phenology of primary producers may disproportionately impact higher trophic levels and keystone species in this region, with implications for Indigenous Peoples and global diversity.  # Marine diatoms record Late Holocene regime shifts in the Pikialasorsuaq ecosystem [https://doi.org/10.5061/dryad.cz8w9gj8p](https://doi.org/10.5061/dryad.cz8w9gj8p) This dataset includes diatom counts (relative abundances, %) from core AMD15-Casq1. Diatoms were analyzed at a 1 to 10 cm sampling interval, which corresponds to an effective age resolution ranging from ca. 3 to 64 years (mean: 31 years). Absolute abundances are reported in valves per g of dry sediment. Fluxes were calculated by combining diatom concentrations (valves and spores g-1) with mass accumulation rates (g cm-2 yr-1). ## Description of the data and file structure Diatom data are presented against depth and modelled age (years BP) in the sediment archive. ## Sharing/Access information n/a ## Code/Software n/a