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Arctic Report Card: Update for 2022
The warming Arctic reveals shifting seasons, widespread disturbances, and the value of diverse observations
Archive of previous Arctic Report Cards
2022 Arctic Report Card

References

Surface Air Temperature

Ballinger, T. J., and Coauthors, 2021: Surface air temperature. Arctic Report Card 2021, T. A. Moon, M. L. Druckenmiller, and R. L. Thoman, Eds., https://doi.org/10.25923/53xd-9k68.

Chylek, P., C. Folland, J. D. Klett, M. Wang, N. Hengartner, G. Lesins, and M. K. Dubey, 2022: Annual mean Arctic amplification 1970-2020: Observed and simulated by CMIP6 climate models. Geophys. Res. Lett., 49, e2022GL099371, https://doi.org/10.1029/2022GL099371.

England, M. R., I. Eisenman, N. J. Lutsko, and T. J. W. Wagner, 2021: The recent emergence of Arctic amplification. Geophys. Res. Lett., 48, e2021GL094086, https://doi.org/10.1029/2021GL094086.

Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Q. J. Roy. Meteor. Soc., 146, 1999-2049, https://doi.org/10.1002/qj.3803.

Hansen, J., R. Ruedy, M. Sato, and K. Lo, 2010: Global surface temperature change. Rev. Geophys., 48, RG4004, https://doi.org/10.1029/2010RG000345.

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Osborn, T. J., P. D. Jones, D. H. Lister, C. P. Morice, I. R. Simpson, J. P. Winn, E. Hogan, and I. C. Harris, 2021: Land surface air temperature variations across the globe updated to 2019: the CRUTEM5 dataset. J. Geophys. Res.-Atmos., 126, e2019JD032352, https://doi.org/10.1029/2019JD032352.

Previdi, M., K. L. Smith, and L. M. Polvani, 2021: Arctic amplification of climate change: a review of underlying mechanisms. Environ. Res. Lett., 16, 093003, https://doi.org/10.1088/1748-9326/ac1c29.

Rantanen, M., A. Y. Karpechko, A. Lipponen, K. Nordling, O. Hyvärinen, K. Ruosteenoja, T. Vihma, and A. Laaksonen, 2022: The Arctic has warmed nearly four times faster than the globe since 1979. Commun. Earth Env., 3, 168, https://doi.org/10.1038/s43247-022-00498-3.

Walsh, J. E., T. J. Ballinger, E. S. Euskirchen, E. Hanna, J. Mård, J. E. Overland, H. Tangen, and T. Vihma, 2020: Extreme weather and climate events in northern areas: A review. Earth-Sci. Rev., 209, 103324, https://doi.org/10.1016/j.earscirev.2020.103324.

Yu, Y., W. Xiao, Z. Zhang, X. Cheng, F. Hui, and J. Zhao, 2021: Evaluation of 2-m air temperature and surface temperature from ERA5 and ERA-I using buoy observations in the arctic during 2010-2020. Remote Sens., 13, 2813, https://doi.org/10.3390/rs13142813.

Terrestrial Snow Cover

Brown, R. D., and C. Derksen, 2013: Is Eurasian October snow cover extent increasing? Environ. Res. Lett., 8, 024006, https://doi.org/10.1088/1748-9326/8/2/024006.

Brown, R., and Coauthors, 2017: Arctic terrestrial snow cover. In: Snow, Water, Ice and Permafrost in the Arctic (SWIPA) 2017. pp. 25-64. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway.

Brun, E., V. Vionnet, A. Boone, B. Decharme, Y. Peings, R. Valette, F. Karbou, and S. Morin, 2013: Simulation of Northern Eurasian local snow depth, mass, and density using a detailed snowpack model and meteorological reanalyses. J. Hydrometeor., 14, 203-219, https://doi.org/10.1175/JHM-D-12-012.1.

Estilow, T. W., A. H. Young, and D. A. Robinson, 2015: A long-term Northern Hemisphere snow cover extent data record for climate studies and monitoring. Earth Syst. Sci. Data, 7, 137-142, https://doi.org/10.5194/essd-7-137-2015.

Gelaro, R., and Coauthors, 2017: The Modern-era retrospective analysis for research and applications, Version 2 (MERRA-2). J. Climate, 30, 5419-5454, https://doi.org/10.1175/JCLI-D-16-0758.1.

GMAO (Global Modeling and Assimilation Office), 2015: MERRA-2tavg1_2d_lnd_Nx:2d, 1-Hourly, Time-Averaged, Single-Level, Assimilation, Land Surface Diagnostics V5.12.4, Goddard Earth Sciences Data and Information Services Center (GESDISC), accessed: 16 August 2022, https://doi.org/10.5067/RKPHT8KC1Y1T.

Luojus, K., and Coauthors, 2022: ESA Snow Climate Change Initiative (Snow_cci): Snow Water Equivalent (SWE) level 3C daily global climate research data package (CRDP) (1979 – 2020), version 2.0. NERC EDS Centre for Environmental Data Analysis, accessed: 16 August 2022, https://doi.org/10.5285/4647cc9ad3c044439d6c643208d3c494.

Meredith, M., and Coauthors, 2019: Polar Regions. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, H. -O. Pörtner, and co-editors, in press, https://www.ipcc.ch/srocc/.

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Mudryk, L. R., P. J. Kushner, C. Derksen, and C. Thackeray, 2017: Snow cover response to temperature in observational and climate model ensembles. Geophys. Res. Lett., 44, 919-926, https://doi.org/10.1002/2016GL071789.

Mudryk, L., M. Santolaria-Otín, G. Krinner, M. Ménégoz, C. Derksen, C. Brutel-Vuilmet, M. Brady, and R. Essery, 2020: Historical Northern Hemisphere snow cover trends and projected changes in the CMIP6 multi-model ensemble. Cryosphere, 14, 2495-2514, https://doi.org/10.5194/tc-14-2495-2020.

Muñoz Sabater, J., 2019: ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), accessed 8 September 2022, https://doi.org/10.24381/cds.e2161bac.

Robinson, D. A., T. W. Estilow, and NOAA CDR Program, 2012: NOAA Climate Data Record (CDR) of Northern Hemisphere (NH) Snow Cover Extent (SCE), Version 1 [r01]. NOAA National Centers for Environmental Information, accessed: 16 August 2022, https://doi.org/10.7289/V5N014G9.

U.S. National Ice Center, 2008: IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions, Version 1. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center, accessed: 22 Aug 2022, https://doi.org/10.7265/N52R3PMC.

Precipitation

Becker, A., P. Finger, A. Meyer-Christoffer, B. Rudolf , K. Schamm, U. Schneider, and M. Ziese, 2013: A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901-present. Earth Syst. Sci. Data, 5(1), 71-99, https://doi.org/10.5194/essd-5-71-2013.

Hersbach, H. B., and Coauthors, 2020: The ERA5 global reanalysis. Q. J. Roy. Meteor. Soc., 146, 1999-2049, https://doi.org/10.1002/qj.3803.

Hurtado, S. I., 2020: RobustLinearReg: Robust Linear Regressions. R package version 1.2.0, https://CRAN.R-project.org/package=RobustLinearReg.

IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 2-6, https://doi.org/10.1017/9781009157896, in press.

Kusunoki, S., R. Mizuta R., and M. Hosaka, 2015: Future changes in precipitation intensity over the Arctic projected by a global atmospheric model with a 60-km grid size. Polar Sci., 9, 277-292, https://doi.org/10.1016/j.polar.2015.08.001.

Loeb, N. A., A. Crawford, J. C. Stroeve, and J. Hanesiak, 2022: Extreme precipitation in the eastern Canadian Arctic and Greenland: An evaluation of atmospheric reanalyses. Front. Env. Sci., 10, 866929, https://doi.org/10.3389/fenvs.2022.866929.

McCrystall, M., J. Stroeve, M. C. Serreze, B. C. Forbes, and J. Screen, 2021: New climate models reveal faster and larger increases in Arctic precipitation than previously projected. Nat. Commun., 12(1), 6765, https://doi.org/10.1038/s41467-021-27031-y.

Schneider, U., P. Finger, E. Rustemeier, M. Ziese, and S. Hänsel, 2022: Global precipitation analysis products of the GPCC, https://opendata.dwd.de/climate_environment/GPCC/PDF/GPCC_intro_products_v2022.pdf.

Sillmann J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh, 2013: Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J. Geophys. Res.-Atmos., 118, 2473-2493, https://doi.org/10.1002/jgrd.50188.

Walsh, J. E., T. J. Ballinger, E. S. Euskirchen, E. Hanna, J. Mård, J. E. Overland, H. Tangen, and T. Vihma, 2020: Extreme weather and climate events in northern areas: A review. Earth-Sci. Rev., 209, 103324, https://doi.org/10.1016/j.earscirev.2020.103324.

White, J., J. E. Walsh, and R. L. Thoman, Jr., 2021: Using Bayesian statistics to detect trends in Alaskan precipitation. Int. J. Climatol., 41(3), 2045-2059, https://doi.org/10.1002/joc.6946.

Ye, H., D. Yang, A. Behrangi, S. L. Stuefer, X. Pan, E. Mekis, Y. Dibike, and J. E. Walsh, 2021: Precipitation Characteristics and Changes. Chapter 2 in Arctic Hydrology, Permafrost and Ecosystems (D. Yang and D.L. Kane, Eds.), Springer Nature Switzerland, 914 pp., https://doi.org/10.1007/978-3-030-50930-9_2.

Yu, L., and S. Zhong, 2021: Trends in Arctic seasonal and extreme precipitation in recent decades. Theor. Appl. Climatol., 145, 1541-1559, https://doi.org/10.1007/s00704-021-03717-7.

Greenland Ice Sheet

Box, J. E., D. van As, and K. Steffen, 2017: Greenland, Canadian and Icelandic land ice albedo grids (2000-2016). GEUS Bull., 38, 53-56, https://doi.org/10.34194/geusb.v38.4414.

Hopwood, M. J., and Coauthors, 2020: Review article: How does glacier discharge affect marine biogeochemistry and primary production in the Arctic? Cryosphere, 14, 1347-1383, https://doi.org/10.5194/tc-14-1347-2020.

Kokhanovsky, A., J. E. Box, B. Vandecrux, K. D. Mankoff, M. Lamare, A. Smirnov, and M. Kern, 2020: The determination of snow albedo from satellite measurements using fast atmospheric correction technique. Remote Sens., 12, 234, https://doi.org/10.3390/rs12020234.

MacFerrin, M., and Coauthors, 2019: Rapid expansion of Greenland’s low-permeability ice slabs. Nature, 573, 403-407, https://doi.org/10.1038/s41586-019-1550-3.

Mankoff, K. D., A. Solgaard, W. Colgan, A. P. Ahlstrøm, S. A. Khan, and R. S. Fausto, 2020: Greenland ice sheet solid ice discharge from 1986 through March 2020. Earth Syst. Sci. Data, 12, 1367-1383, https://doi.org/10.5194/essd-12-1367-2020.

Mankoff, K. D., and Coauthors, 2021: Greenland ice sheet mass balance from 1840 through next week. Earth Syst. Sci. Data, 13, 5001-5025, https://doi.org/10.5194/essd-13-5001-2021.

Morlighem, M., and Coauthors, 2017: BedMachine v3: Complete bed topography and ocean bathymetry mapping of Greenland from multibeam echo sounding combined with mass conservation. Geophys. Res. Lett., 44(21), 11051-11061, https://doi.org/10.1002/2017GL074954.

Mote, T. L., 2007: Greenland surface melt trends 1973-2007: Evidence of a large increase in 2007. Geophys. Res. Lett., 34, L22507, https://doi.org/10.1029/2007GL031976.

Mouginot, J., and Coauthors, 2019: Forty-six years of Greenland ice sheet mass balance from 1972 to 2018. P. Natl. Acad. Sci., 116(19), 9239-9244, https://doi.org/10.1073/pnas.1904242116.

Ryan, J. C., L. C. Smith, D. van As, S. W. Cooley, M. G. Cooper, L. H. Pitcher, and A. Hubbard, 2019: Greenland ice sheet surface melt amplified by snowline migration and bare ice exposure. Sci. Adv., 5, eaav3738, https://doi.org/10.1126/sciadv.aav3738.

van As, D., R. S. Fausto, J. Cappelen, R. S. van de Wa, R. J. Braithwaite, H. Machguth, and PROMICE project team, 2016: Placing Greenland ice sheet ablation measurements in a multi-decadal context. GEUS Bull., 35, 71-74, https://doi.org/10.34194/geusb.v35.4942.

Wehrlé, A., J. E. Box, A. M. Anesio, and R. S. Fausto, 2021: Greenland bare ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bull., 47, 5284, https://doi.org/10.34194/geusb.v47.5284.

Sea Ice

Cavalieri, D. J., C. L. Parkinson, P. Gloersen, and H. J. Zwally, 1996 (updated yearly): Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1. NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, CO, USA, accessed 27 August 2022, https://doi.org/10.5067/8GQ8LZQVL0VL.

Comiso, J. C., W. N. Meier, and R. Gersten, 2017: Variability and trends in the Arctic sea ice cover: Results from different techniques. J. Geophys. Res., 122, 6883-6900, https://doi.org/10.1002/2017JC012768.

Fetterer, F., K. Knowles, W. N. Meier, M. Savoie, and A. K. Windnagel, 2017 (updated daily): Sea Ice Index, Version 3. NSIDC: National Snow and Ice Data Center, Boulder, CO, USA, accessed 2 October 2022, https://doi.org/10.7265/N5K072F8.

Ivanova, N., O. M. Johannessen, L. T. Pedersen, and R. T. Tonboe, 2014: Retrieval of Arctic sea ice parameters by satellite passive microwave sensors: A comparison of eleven sea ice concentration algorithms. IEEE Trans. Geosci. Rem. Sens., 52(11), 7233-7246, https://doi.org/10.1109/TGRS.2014.2310136.

Kern, S., T. Lavergne, D. Notz, L. T. Pedersen, R. T. Tonboe, R. Saldo, and A. M.Sørensen, 2019: Satellite passive microwave sea-ice concentration data set intercomparison: closed ice and ship-based observations. Cryosphere, 13, 3261-3307, https://doi.org/10.5194/tc-13-3261-2019.

Lavergne, T., and Coauthors, 2019: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records. Cryosphere, 13, 49-78, https://doi.org/10.5194/tc-13-49-2019.

Meier, W. N., J. S. Stewart, H. Wilcox, M. A. Hardman, and D. J. Scott, 2021: Near-Real-Time DMSP SSMIS Daily Polar Gridded Sea Ice Concentrations, Version 2 [Data Set]. NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, CO, USA, accessed 2 October 2022, https://doi.org/10.5067/YTTHO2FJQ97K.

Petty, A. A., N. T. Kurtz, R. Kwok, T. Markus, and T. A. Neumann, 2020: Winter Arctic sea ice thickness from ICESat-2 freeboards. J. Geophys. Res.-Oceans, 125, e2019JC015764, https://doi.org/10.1029/2019JC015764.

Petty, A. A., N. Kurtz, R. Kwok, T. Markus, and T. A. Neumann, 2021: ICESat-2 L4 Monthly Gridded Sea Ice Thickness, Version 1. NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, CO, USA, accessed 9 September 2022, https://doi.org/10.5067/CV6JEXEE31HF.

Petty, A. A., N. Keeney, A. Cabaj, P. Kushner, and M. Bagnardi, 2022: Winter Arctic sea ice thickness from ICESat-2: upgrades to freeboard and snow loading estimates and an assessment of the first three winters of data collection. Cryosphere Discuss, https://doi.org/10.5194/tc-2022-39, in review.

Ricker, R., S. Hendricks, L. Kaleschke, X. Tian-Kunze, J. King, and C. Haas, 2017: A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data. Cryosphere, 11, 1607-1623, https://doi.org/10.5194/tc-11-1607-2017.

Sumata, H., L. de Steur, S. Gerland, D. V. Divine, and O. Pavlova, 2022: Unprecedented decline of Arctic sea ice outflow in 2018. Nat. Comm., 13, 1747, https://doi.org/10.1038/s41467-022-29470-7.

Tschudi, M., W. N. Meier, J. S. Stewart, C. Fowler, and J. Maslanik, 2019a: EASE-Grid Sea Ice Age, Version 4. [March, 1984-2020]. NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, CO, USA, accessed 1 September 2022, https://doi.org/10.5067/UTAV7490FEPB.

Tschudi, M., W. N. Meier, and J. S. Stewart, 2019b: Quicklook Arctic Weekly EASE-Grid Sea Ice Age, Version 1. [March, 2021]. NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, CO, USA, accessed 3 October 2022, https://doi.org/10.5067/2XXGZY3DUGNQ.

Tschudi, M. A., W. N. Meier, and J.S. Stewart, 2020: An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC). Cryosphere, 14, 1519-1536, https://doi.org/10.5194/tc-14-1519-2020.

Sea Surface Temperature

Huang, B., C. Liu, V. Banzon, E. Freeman, G. Graham, B. Hankins, T. Smith, and H. Zhang, 2021: Improvements of the Daily Optimum Interpolation Sea Surface Temperature (DOISST) Version 2.1. J. Climate, 34(8), 2923-2939, https://doi.org/10.1175/JCLI-D-20-0166.1.

Meier, W. N., F. Fetterer, A. K. Windnagel, and J. S. Stewart, 2021a: NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 4. [1982-2021]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center, accessed 10 September 2022, https://doi.org/10.7265/efmz-2t65.

Meier, W. N., F. Fetterer, A. K. Windnagel, and J. S. Stewart, 2021b: Near-Real-Time NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 2. [1982-2021], accessed 10 September 2022, https://doi.org/10.7265/tgam-yv28.

Peng, G., W. N. Meier, D. J. Scott, and M. H. Savoie, 2013: A long-term and reproducible passive microwave sea ice concentration data record for climate studies and monitoring. Earth Syst. Sci. Data, 5, 311-318, https://doi.org/10.5194/essd-5-311-2013.

Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes, and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 1609-1625, https://doi.org/10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2.

Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax, 2007: Daily high-resolution-blended analyses for sea surface temperature. J. Climate, 20, 5473-5496, https://doi.org/10.1175/2007JCLI1824.1, and see http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.oisst.v2.html.

Stroh, J. N., G. Panteleev, S. Kirillov, M. Makhotin, and N. Shakhova, 2015: Sea-surface temperature and salinity product comparison against external in situ data in the Arctic Ocean. J. Geophys. Res.-Oceans, 120, 7223-7236, https://doi.org/10.1002/2015JC011005.

Timmermans, M. -L., and Z. M. Labe, 2021: Sea surface temperature. Arctic Report Card 2021, T. A. Moon, M. L. Druckenmiller, and R. L. Thoman, Eds., https://doi.org/10.25923/2y8r-0e49.

Arctic Ocean Primary Productivity: The Response of Marine Algae to Climate Warming and Sea Ice Decline

Ardyna, M., M. Babin, E. Devered, A. Forest, M. Gosselin, P. Raimbault, and J. -É. Tremblay, 2017: Shelf-basin gradients shape ecological phytoplankton niches and community composition in the coastal Arctic Ocean (Beaufort Sea). Limnol. Oceanogr., 62, 2113-2132, https://doi.org/10.1002/lno.10554.

Ardyna M., and Coauthors, 2020: Under-ice phytoplankton blooms: Shedding light on the “invisible” part of Arctic primary production. Front. Mar. Sci., 7, 608032, https://doi.org/10.3389/fmars.2020.608032.

Behrenfeld, M. J., and P. G. Falkowski, 1997: Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnol. Oceanogr., 42(1), 1-20, https://doi.org/10.4319/lo.1997.42.1.0001.

Bouman, H. A., T. Jackson, S. Sathyendranath, and T. Platt, 2020: Vertical structure in chlorophyll profiles: influence on primary production in the Arctic Ocean. Philos. Trans. Roy. Soc. A, 378, 20190351, https://doi.org/10.1098/rsta.2019.0351.

Comiso, J. C., 2015: Variability and trends of the global sea ice covers and sea level: Effects on physicochemical parameters. Climate and Fresh Water Toxins, L. M. Botana, M. C. Lauzao, and N. Vilarino, Eds., De Gruyter, Berlin, Germany, https://doi.org/10.1515/9783110333596-003.

Comiso, J. C., W. N. Meier, and R. Gersten, 2017: Variability and trends in the Arctic Sea ice cover: Results from different techniques. J. Geophys. Res.-Oceans, 122, 6883-6900, https://doi.org/10.1002/2017JC012768.

Cooper L. W., and J. M. Grebmeier, 2022: A chlorophyll biomass time-series for the Distributed Biological Observatory in the context of seasonal sea ice declines in the Pacific Arctic region. Geosciences, 12(8), 307, https://doi.org/10.3390/geosciences12080307.

Crawford, A. D., K. M. Krumhardt, N. S. Lovenduski, G. L. Van Dijken, and K. R. Arrigo, 2020: Summer high-wind events and phytoplankton productivity in the Arctic Ocean. J. Geophys. Res.-Oceans, 125, e2020JC016565, https://doi.org/10.1029/2020jc016565.

Frey, K. E., J. C. Comiso, L. W. Cooper, J. M. Grebmeier, and L. V. Stock, 2021: Arctic ocean primary productivity: The response of marine algae to climate warming and sea ice decline. Arctic Report Card 2021, T. A. Moon, M. L. Druckenmiller, and R. L. Thoman, Eds., https://doi.org/10.25923/kxhb-dw16.

Gaffey, C. B., K. E. Frey, L. W. Cooper, and J. M. Grebmeier, 2022: Phytoplankton bloom stages estimated from chlorophyll pigment proportions suggest delayed summer production in low sea ice years in the northern Bering Sea. PLoS ONE, 17, e0267586, https://doi.org/10.1371/journal.pone.0267586.

Holding, J. M., and Coauthors, 2015: Temperature dependence of CO2-enhanced primary production in the European Arctic Ocean. Nat. Climate Change, 5, 1079-1082, https://doi.org/10.1038/nclimate2768.

Hopwood, M. J., and Coauthors, 2020: Review article: How does glacier discharge affect marine biogeochemistry and primary production in the Arctic? Cryosphere, 14, 1347-1383, https://doi.org/10.5194/tc-14-1347-2020.

Lewis, K. M., and K. R. Arrigo, 2020: Ocean color algorithms for estimating chlorophyll a, CDOM absorption, and particle backscattering in the Arctic Ocean. J. Geophys. Res.-Oceans, 125, e2019JC015706, https://doi.org/10.1029/2019JC015706.

Mundy, C. J., and Coauthors, 2009: Contribution of under-ice primary production to an ice edge upwelling phytoplankton bloom in the Canadian Beaufort Sea. Geophys. Res. Lett., 36, L17601, https://doi.org/10.1029/2009GL038837.

Popova, E. E., A. Yool, A. C. Coward, Y. K. Aksenov, S. G. Alderson, A. de Cuevas, and T. R. Anderson, 2010: Control of primary production in the Arctic by nutrients and light: insights from a high-resolution ocean general circulation model. Biogeosciences, 7, 3569-3591, https://doi.org/10.5194/bg-7-3569-2010.

Terhaar, J., R. Lauerwald, P. Regnier, N. Gruber, and L. Bopp, 2021: Around one third of current Arctic Ocean primary production sustained by rivers and coastal erosion. Nat. Comm., 12, 169, https://doi.org/10.1038/s41467-020-20470-z.

von Appen, W. J., and Coauthors, 2021: Sea-ice derived meltwater stratification slows the biological carbon pump: results from continuous observations. Nat. Comm., 12, 7309, https://doi.org/10.1038/s41467-021-26943-z.

Tundra Greenness

Berner, L. T., and S. J. Goetz, 2022: Satellite observations document trends consistent with a boreal forest biome shift. Glob. Change Biol., 28(10), 3275-3292, https://doi.org/10.1111/gcb.16121.

Bhatt, U. S., and Coauthors, 2021: Climate drivers of Arctic tundra variability and change using an indicators framework. Environ. Res. Lett., 16, 055019, https://doi.org/10.1088/1748-9326/abe676.

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Satellite Record of Pan-Arctic Maritime Ship Traffic

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Lake Ice

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Arctic Geese of North America

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Arctic Pollinators

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Gillespie M. A. K., and Coauthors, 2020b: Status and trends of terrestrial arthropod abundance and diversity in the North Atlantic region of the Arctic. Ambio, 49, 718-731, https://doi.org/10.1007/s13280-019-01162-5.

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Lessons from Oceans Melting Greenland, a NASA Airborne Mission

An, L., E. Rignot, M. Wood, J. K. Willis, J. Mouginot, and S. A. Khan, 2020: Ocean melting of the Zachariae Isstrøm and Nioghalvfjerdsfjorden glaciers, northeast Greenland. P. Natl. Acad. Sci., 118(2), e2015483118, https://doi.org/10.1073/pnas.2015483118.

Choi, Y., and Coauthors, 2021: Ice dynamics will remain a primary driver of Greenland ice sheet mass loss over the next century. Commun. Earth Env., 2, 26, https://doi.org/10.1038/s43247-021-00092-z.

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Khazendar, A., and Coauthors, 2019: Interruption of two decades of Jakobshavn Isbræ acceleration and thinning as regional ocean cools. Nat. Geosci., 12, 277-283, https://doi.org/10.1038/s41561-019-0329-3.

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Rignot, E., and Coauthors, 2021: Retreat of Humboldt Gletscher, north Greenland, driven by undercutting from a warmer ocean. Geophys. Res. Lett., 48, e2020GL091342, https://doi.org/10.1029/2020GL091342.

Snow, T., and Coauthors, 2021: More than skin deep: Sea surface temperature as a means of inferring Atlantic Water variability on the southeast Greenland continental shelf near Helheim Glacier. J. Geophys. Res.-Oceans, 126(4), https://doi.org/10.1029/2020JC016509.

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Wood, M., and Coauthors, 2021: Ocean forcing drives glacier retreat in Greenland. Sci. Adv., 7, eaba7282, https://doi.org/10.1126/sciadv.aba7282.

Partnering in Search of Answers: Seabird Die-offs in the Bering and Chukchi Seas

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Will, A., and Coauthors, 2020b: The breeding seabird community reveals that recent sea ice loss in the Pacific Arctic does not benefit piscivores and is detrimental to planktivores. Deep-Sea Res., Pt. II, 181-182, 104902, https://doi.org/10.1016/j.dsr2.2020.104902.

Consequences of Rapid Environmental Arctic Change for People

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Harper, S. L., C. Wright, S. Masina, and S. Coggins, 2020: Climate change, water, and human health in the Arctic. Water Secur., 10, 100062, https://doi.org/10.1016/j.wasec.2020.100062.

Huntington, H. P., M. Nelson, and L. T. Quakenbush, 2016: Traditional knowledge regarding ringed seals, bearded seals, and walrus near Shishmaref, Alaska. Final report to the Eskimo Walrus Commission, the Ice Seal Committee, and the Bureau of Ocean Energy Management for contract #M13PC00015. 9 pp.

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Johnson, N., and Coauthors, 2021: The Impact of COVID-19 on Food Access for Alaska Natives in 2020. Arctic Report Card 2021, T. A. Moon, M. L. Druckenmiller, and R. L. Thoman, Eds., https://doi.org/10.25923/5cb7-6h06.

Kelly, B. P., and A. M. Fisher, 2021: Complex collaboration tools for a sustainable Arctic. Wither the Arctic Ocean? Research, Knowledge Needs, and Development en Route to the New Arctic, P. Wassman, Ed., Fundación BBVA, 43-51.

Landrum, L., and M. M. Holland, 2020: Extremes become routine in an emerging new Arctic. Nat. Climate Change, 10, 1108-1115, https://doi.org/10.1038/s41558-020-0892-z.

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Schaeffer, J. Q., 2021: Climate change and its impacts on Indigenous People. Science, Technology and the Path Forward for a New Arctic, J. Kim & O. Young, Eds., Korea Maritime Institute & East-West Center, 118-125.

York, A., U. S. Bhatt, E. Gargulinski, Z. Grabinski, P. Jain, A. Soja, R. L. Thoman, and R. Ziel, 2020: Wildfire in High Northern Latitudes. Arctic Report Card 2020, R. L. Thoman, J. Richter-Menge, and M. L. Druckenmiller, Eds., https://doi.org/10.25923/2gef-3964.

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