Box, J. E. et al. Key indicators of Arctic climate change: 1971–2017. Environ. Res. Lett. 14, 045010 (2019).
Google Scholar
Previdi, M., Smith, K. L. & Polvani, L. M. Arctic amplification of climate change: a review of underlying mechanisms. Environ. Res. Lett. 16, 093003 (2021).
Google Scholar
Rantanen, M. et al. The Arctic has warmed nearly four times faster than the globe since 1979. Commun. Earth Environ. 3, 1–10 (2022).
Google Scholar
Stroeve, J. & Notz, D. Changing state of Arctic sea ice across all seasons. Environ. Res. Lett. 13, 103001 (2018).
Google Scholar
Kopec, B. G., Feng, X., Michel, F. A. & Posmentier, E. S. Influence of sea ice on Arctic precipitation. Proc. Natl. Acad. Sci. 113, 46–51 (2016).
Google Scholar
Smith, S. L., O’Neill, H. B., Isaksen, K., Noetzli, J. & Romanovsky, V. E. The changing thermal state of permafrost. Nat. Rev. Earth Environ. 3, 10–23 (2022).
Google Scholar
Overland, J. et al. The urgency of Arctic change. Polar Sci. 21, 6–13 (2019).
Google Scholar
Post, E. et al. The polar regions in a 2 °C warmer world. Sci. Adv. 5, eaaw9883 (2019).
Google Scholar
Ciavarella, A. et al. Prolonged Siberian heat of 2020 almost impossible without human influence. Clim. Change 166, 9 (2021).
Google Scholar
Dobricic, S., Russo, S., Pozzoli, L., Wilson, J. & Vignati, E. Increasing occurrence of heat waves in the terrestrial Arctic. Environ. Res. Lett. 15, 024022 (2020).
Google Scholar
Graham, R. M. et al. Increasing frequency and duration of Arctic winter warming events. Geophys. Res. Lett. 44, 6974–6983 (2017).
Google Scholar
Knight, J. & Harrison, S. The impacts of climate change on terrestrial Earth surface systems. Nat. Clim. Change 3, 24–29 (2013).
Google Scholar
Pearson, R. G. et al. Shifts in Arctic vegetation and associated feedbacks under climate change. Nat. Clim. Change 3, 673–677 (2013).
Google Scholar
Beck, P. S. A. et al. Changes in forest productivity across Alaska consistent with biome shift. Ecol. Lett. 14, 373–379 (2011).
Reichle, L. M., Epstein, H. E., Bhatt, U. S., Raynolds, M. K. & Walker, D. A. Spatial Heterogeneity of the Temporal Dynamics of Arctic Tundra Vegetation. Geophys. Res. Lett. 45, 9206–9215 (2018).
Google Scholar
Sturm, M., Racine, C. & Tape, K. Increasing shrub abundance in the Arctic. Nature 411, 546–547 (2001).
Google Scholar
Myers-Smith, I. H. et al. Complexity revealed in the greening of the Arctic. Nat. Clim. Change 10, 106–117 (2020).
Google Scholar
Phoenix, G. K. & Bjerke, J. W. Arctic browning: extreme events and trends reversing arctic greening. Glob. Change Biol. 22, 2960–2962 (2016).
Google Scholar
Seddon, A. W. R., Macias-Fauria, M., Long, P. R., Benz, D. & Willis, K. J. Sensitivity of global terrestrial ecosystems to climate variability. Nature 531, 229–232 (2016).
Google Scholar
Jentsch, A., Kreyling, J. & Beierkuhnlein, C. A new generation of climate-change experiments: events, not trends. Front. Ecol. Environ. 5, 365–374 (2007).
Virkkala, A.-M. et al. Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties. Glob. Change Biol. 27, 4040–4059 (2021).
Google Scholar
Elith, J. & Leathwick, J. R. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annu. Rev. Ecol. Evol. Syst. 40, 677–697 (2009).
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).
Google Scholar
Rienecker, M. M. et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Clim. 24, 3624–3648 (2011).
Google Scholar
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).
Karger, D. N., Schmatz, D. R., Dettling, G. & Zimmermann, N. E. High-resolution monthly precipitation and temperature time series from 2006 to 2100. Sci. Data 7, 248 (2020).
Vega, G. C., Pertierra, L. R. & Olalla-Tárraga, M. Á. MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling. Sci. Data 4, 170078 (2017).
Niittynen, P., Heikkinen, R. K. & Luoto, M. Snow cover is a neglected driver of Arctic biodiversity loss. Nat. Clim. Change 8, 997–1001 (2018).
Google Scholar
Slatyer, R. A., Umbers, K. D. L. & Arnold, P. A. Ecological responses to variation in seasonal snow cover. Conserv. Biol. 36, e13727 (2022).
Serreze, M. C. et al. Arctic rain on snow events: bridging observations to understand environmental and livelihood impacts. Environ. Res. Lett. 16, 105009 (2021).
Google Scholar
López, J., Way, D. A. & Sadok, W. Systemic effects of rising atmospheric vapor pressure deficit on plant physiology and productivity. Glob. Change Biol. 27, 1704–1720 (2021).
Google Scholar
Ennos, A. R. Wind as an ecological factor. Trends Ecol. Evol. 12, 108–111 (1997).
Google Scholar
Muñoz-Sabater, J. et al. ERA5-Land: a state-of-the-art global reanalysis dataset for land applications. Earth Syst. Sci. Data 13, 4349–4383 (2021).
Google Scholar
Boussetta, S. et al. ECLand: The ECMWF Land Surface Modelling System. Atmosphere 12, 723 (2021).
Google Scholar
Munõz-Sabater, J. ERA5-Land hourly data from 1981 to present. ECMWF https://doi.org/10.24381/cds.e2161bac (2019).
Munõz-Sabater, J. ERA5-Land hourly data from 1950 to 1980. ECMWF https://doi.org/10.24381/cds.e2161bac (2021).
Hoyer, S. & Hamman, J. xarray: N-D labeled Arrays and Datasets in Python. J. Open Res. Softw. 5, 10 (2017).
Sen, P. K. Estimates of the Regression Coefficient Based on Kendall’s Tau. J. Am. Stat. Assoc. 63, 1379–1389 (1968).
Google Scholar
Theil, H. A rank-invariant method of linear and polynomial regression analysis I, II and III. Indag. Math. 173 (1950).
Hussain, M. M. & Mahmud, I. pyMannKendall: a python package for non parametric Mann Kendall family of trend tests. J. Open Source Softw. 4, 1556 (2019).
Google Scholar
Aalto, J. et al. High-resolution analysis of observed thermal growing season variability over northern Europe. Clim. Dyn. 58, 1477–1493 (2022).
Zhou, B., Zhai, P., Chen, Y. & Yu, R. Projected changes of thermal growing season over Northern Eurasia in a 1.5 °C and 2 °C warming world. Environ. Res. Lett. 13, 035004 (2018).
Google Scholar
Barichivich, J., Briffa, K. R., Osborn, T. J., Melvin, T. M. & Caesar, J. Thermal growing season and timing of biospheric carbon uptake across the Northern Hemisphere. Glob. Biogeochem. Cycles 26 (2012).
Wu, F., Jiang, Y., Wen, Y., Zhao, S. & Xu, H. Spatial synchrony in the start and end of the thermal growing season has different trends in the mid-high latitudes of the Northern Hemisphere. Environ. Res. Lett. 16, 124017 (2021).
Google Scholar
Ruosteenoja, K., Räisänen, J., Venäläinen, A. & Kämäräinen, M. Projections for the duration and degree days of the thermal growing season in Europe derived from CMIP5 model output. Int. J. Climatol. 36, 3039–3055 (2016).
Niittynen, P. & Luoto, M. The importance of snow in species distribution models of arctic vegetation. Ecography 41, 1024–1037 (2018).
McMaster, G. S. & Wilhelm, W. W. Growing degree-days: one equation, two interpretations. Agric. For. Meteorol. 87, 291–300 (1997).
Google Scholar
Körner, C. Plant adaptation to cold climates. F1000Research 5, F1000 Faculty Rev-2769 (2016).
Niittynen, P. et al. Fine-scale tundra vegetation patterns are strongly related to winter thermal conditions. Nat. Clim. Change 10, 1143–U134 (2020).
Google Scholar
Cohen, J., Ye, H. & Jones, J. Trends and variability in rain-on-snow events. Geophys. Res. Lett. 42, 7115–7122 (2015).
Google Scholar
Mooney, P. A. & Li, L. Near future changes to rain-on-snow events in Norway. Environ. Res. Lett. 16, 064039 (2021).
Google Scholar
Preece, C., Callaghan, T. V. & Phoenix, G. K. Impacts of winter icing events on the growth, phenology and physiology of sub-arctic dwarf shrubs. Physiol. Plant. 146, 460–472 (2012).
Google Scholar
Putkonen, J. & Roe, G. Rain-on-snow events impact soil temperatures and affect ungulate survival. Geophys. Res. Lett. 30, (2003).
Treharne, R., Bjerke, J. W. & Tømmervik, H. & Phoenix, G. K. Development of new metrics to assess and quantify climatic drivers of extreme event driven Arctic browning. Remote Sens. Environ. 243, 111749 (2020).
Google Scholar
Bokhorst, S. et al. Impacts of extreme winter warming events on plant physiology in a sub-Arctic heath community. Physiol. Plant. 140, 128–140 (2010).
Google Scholar
Russo, S., Sillmann, J. & Fischer, E. M. Top ten European heatwaves since 1950 and their occurrence in the coming decades. Environ. Res. Lett. 10, 124003 (2015).
Google Scholar
Alduchov, O. A. & Eskridge, R. E. Improved Magnus Form Approximation of Saturation Vapor Pressure. J. Appl. Meteorol. Climatol. 35, 601–609 (1996).
Google Scholar
Grossiord, C. et al. Plant responses to rising vapor pressure deficit. New Phytol. 226, 1550–1566 (2020).
Yuan, W. et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth. Sci. Adv. 5, eaax1396 (2019).
Google Scholar
De Frenne, P. et al. Forest microclimates and climate change: Importance, drivers and future research agenda. Glob. Change Biol. 27, 2279–2297 (2021).
Google Scholar
Berner, L. T. et al. Summer warming explains widespread but not uniform greening in the Arctic tundra biome. Nat. Commun. 11, 4621 (2020).
Google Scholar
Berner, L. T., Jantz, P., Tape, K. D. & Goetz, S. J. Tundra plant above-ground biomass and shrub dominance mapped across the North Slope of Alaska. Environ. Res. Lett. 13, 035002 (2018).
Google Scholar
Walker, D. A. et al. Phytomass, LAI, and NDVI in northern Alaska: Relationships to summer warmth, soil pH, plant functional types, and extrapolation to the circumpolar Arctic. J. Geophys. Res. Atmospheres 108, (2003).
Williams, C. M., Henry, H. A. L. & Sinclair, B. J. Cold truths: how winter drives responses of terrestrial organisms to climate change. Biol. Rev. 90, 214–235 (2015).
Peng, S. et al. Change in snow phenology and its potential feedback to temperature in the Northern Hemisphere over the last three decades. Environ. Res. Lett. 8, 014008 (2013).
Google Scholar
Wheeler, J. A. et al. Increased spring freezing vulnerability for alpine shrubs under early snowmelt. Oecologia 175, 219–229 (2014).
Google Scholar
Zhu, L., Ives, A. R., Zhang, C., Guo, Y. & Radeloff, V. C. Climate change causes functionally colder winters for snow cover-dependent organisms. Nat. Clim. Change 9, 886–893 (2019).
Google Scholar
Vitasse, Y. et al. ‘Hearing’ alpine plants growing after snowmelt: ultrasonic snow sensors provide long-term series of alpine plant phenology. Int. J. Biometeorol. 61, 349–361 (2017).
Google Scholar
Kling, M. M. & Ackerly, D. D. Global wind patterns and the vulnerability of wind-dispersed species to climate change. Nat. Clim. Change 10, 868–875 (2020).
Google Scholar
Dial, R. J., Maher, C. T., Hewitt, R. E. & Sullivan, P. F. Sufficient conditions for rapid range expansion of a boreal conifer. Nature 608, 546–551 (2022).
Google Scholar
Nathan, R. et al. Mechanisms of long-distance dispersal of seeds by wind. Nature 418, 409–413 (2002).
Google Scholar
Sakai, A. Mechanism of Desiccation Damage of Conifers Wintering in Soil-Frozen Areas. Ecology 51, 657–664 (1970).
Wilson, J. W. Notes on Wind and its Effects in Arctic-Alpine Vegetation. J. Ecol. 47, 415–427 (1959).
Rantanen, M. et al. Bioclimatic atlas of the terrestrial Arctic, figshare, https://doi.org/10.6084/m9.figshare.c.6216368 (2023).
Räisänen, J. Snow conditions in northern Europe: the dynamics of interannual variability versus projected long-term change. The Cryosphere 15, 1677–1696 (2021).
Google Scholar
Xu, J., Ma, Z., Yan, S. & Peng, J. Do ERA5 and ERA5-land precipitation estimates outperform satellite-based precipitation products? A comprehensive comparison between state-of-the-art model-based and satellite-based precipitation products over mainland China. J. Hydrol. 605, 127353 (2022).
Behrangi, A., Singh, A., Song, Y. & Panahi, M. Assessing Gauge Undercatch Correction in Arctic Basins in Light of GRACE Observations. Geophys. Res. Lett. 46, 11358–11366 (2019).
Google Scholar
Menne, M. J., Williams, C. N., Gleason, B. E., Rennie, J. J. & Lawrimore, J. H. The Global Historical Climatology Network Monthly Temperature Dataset, Version 4. J. Clim. 31, 9835–9854 (2018).
Google Scholar
Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E. & Houston, T. G. An Overview of the Global Historical Climatology Network-Daily Database. J. Atmospheric Ocean. Technol. 29, 897–910 (2012).
Google Scholar
Atlaskin, E. & Vihma, T. Evaluation of NWP results for wintertime nocturnal boundary-layer temperatures over Europe and Finland. Q. J. R. Meteorol. Soc. 138, 1440–1451 (2012).
Google Scholar
Lindsay, R., Wensnahan, M., Schweiger, A. & Zhang, J. Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic. J. Clim. 27, 2588–2606 (2014).
Google Scholar
Wang, C., Graham, R. M., Wang, K., Gerland, S. & Granskog, M. A. Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution. The Cryosphere 13, 1661–1679 (2019).
Google Scholar
Wesslén, C. et al. The Arctic summer atmosphere: an evaluation of reanalyses using ASCOS data. Atmospheric Chem. Phys. 14, 2605–2624 (2014).
Google Scholar
Source: Ecology - nature.com