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Lauer, Melanie; Viceto, Carolina; Gorodetskaya, Irina V: Arctic Atmospheric Rivers catalog based on ERA5 reanalysis from 1979 to 2020 [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.979916 (dataset in review)

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Abstract:
The dataset includes hourly-detected Arctic Atmospheric River (AR) shapes from 1979 to 2020, based on the ERA5 reanalysis product (Hersbach et al., 2020). We use the ERA5 specific humidity and temperature from 1000 hPa up to 300 hPa in the Northern Hemisphere (from equator to 90°N) as input variables for applying the algorithm. To detect ARs, we used the polar-specific algorithm developed by Gorodetskaya et al. (2014, 2020), originally designed for Antarctica's cold and dry conditions and later adapted to the Arctic by Viceto et al. (2022). This detection algorithm relies on the vertically integrated water vapor (IWV). It considers both a threshold calculated using the moisture holding capacity of the polar troposphere (represented by an integral of saturation specific humidity, IWVsat) and geometric constraints. An object is classified as an AR if the IWV exceeds the IWVsat-related threshold for at least 2000 km within a maximum width of 40 longitudes, and it reaches or crosses 70°N. To apply the algorithm, we first determined the input variables—IWV and IWVsat—and then used them within the algorithm. The resulting hourly output files were combined into yearly netCDF files, each containing the detected Arctic AR shapes as a mask.
Keyword(s):
Arctic; atmospheric river; ERA5
References:
Gorodetskaya, Irina V; Silva, Tiago; Schmithüsen, Holger; Hirasawa, N (2020): Atmospheric River Signatures in Radiosonde Profiles and Reanalyses at the Dronning Maud Land Coast, East Antarctica. Advances in Atmospheric Sciences, 37(5), 455-476, https://doi.org/10.1007/s00376-020-9221-8
Hersbach, Hans; Bell, B; Berrisford, Paul; Hirahara, Shoji; Horányi, A; Muñoz-Sabater, Joaquín; Nicolas, J; Peubey, C; Radu, R; Schepers, D; Simmons, Adrian; Soci, C; Abdalla, Saleh; Abellan, Xavier; Balsamo, Gianpaolo; Bechtold, P; Biavati, G; Bidlot, J; Bonavita, Massimo; De Chiara, Giovanna; Dahlgren, Per; Dee, Dick; Diamantakis, Michail; Dragani, R; Flemming, Johannes; Forbes, Richard; Fuentes, Manuel; Geer, Alan; Haimberger, Leo; Healy, Sean; Hogan, Robin J; Hólm, Elías; Janisková, Marta; Keeley, Sarah; Laloyaux, Patrick; Lopez, Philippe; Lupu, Cristina; Radnoti, Gabor; de Rosnay, Patricia; Rozum, I; Vamborg, Freja; Villaume, Sebastian; Thépaut, Jean-Noël (2020): The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999-2049, https://doi.org/10.1002/qj.3803
Lauer, Melanie; Rinke, Annette; Gorodetskaya, Irina V; Sprenger, Michael; Mech, Mario; Crewell, Susanne (2023): Influence of atmospheric rivers and associated weather systems on precipitation in the Arctic. Atmospheric Chemistry and Physics, 23(15), 8705-8726, https://doi.org/10.5194/acp-23-8705-2023
Viceto, Carolina; Gorodetskaya, Irina V; Rinke, Annette; Maturilli, Marion; Rocha, Alfredo; Crewell, Susanne (2022): Atmospheric rivers and associated precipitation patterns during the ACLOUD and PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model. Atmospheric Chemistry and Physics, 22(1), 441-463, https://doi.org/10.5194/acp-22-441-2022
Project(s):
Funding:
German Research Foundation (DFG), grant/award no. 268020496: TRR 172: ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms
Coverage:
Latitude: 90.000000 * Longitude: 0.000000
Date/Time Start: 1979-01-01T00:00:00 * Date/Time End: 2020-01-01T00:00:00
Event(s):
pan-Arctic * Latitude: 90.000000 * Longitude: 0.000000 * Location: Arctic
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1DATE/TIMEDate/TimeLauer, MelanieGeocode
2netCDF filenetCDFLauer, Melanie
3netCDF file (File Size)netCDF (Size)BytesLauer, Melanie
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0) (License comes into effect after moratorium ends)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
42 data points

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