Articles | Volume 6, issue 2
https://doi.org/10.5194/wcd-6-431-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-6-431-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Moisture transport axes: a unifying definition for tropical moisture exports, atmospheric rivers, and warm moist intrusions
Clemens Spensberger
CORRESPONDING AUTHOR
Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Kjersti Konstali
Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Thomas Spengler
Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Related authors
Henrik Auestad, Clemens Spensberger, Andrea Marcheggiani, Paulo Ceppi, Thomas Spengler, and Tim Woollings
Weather Clim. Dynam., 5, 1269–1286, https://doi.org/10.5194/wcd-5-1269-2024, https://doi.org/10.5194/wcd-5-1269-2024, 2024
Short summary
Short summary
Latent heating due to condensation can influence atmospheric circulation by strengthening or weakening horizontal temperature contrasts. Strong temperature contrasts intensify storms and imply the existence of strong upper tropospheric winds called jets. It remains unclear whether latent heating preferentially reinforces or abates the existing jet. We show that this disagreement is attributable to how the jet is defined, confirming that latent heating reinforces the jet.
Clemens Spensberger
Weather Clim. Dynam., 5, 659–669, https://doi.org/10.5194/wcd-5-659-2024, https://doi.org/10.5194/wcd-5-659-2024, 2024
Short summary
Short summary
It is well-established that variations in convection in the tropical Indo-Pacific can influence weather in far-away regions. In this idea, I argue that the main theory used to explain this influence over large distances is incomplete. I propose hypotheses that could lead the way towards a more fundamental explanation and outline a novel approach that could be used to test the hypotheses I raise. The suggested approach might be useful to address also other long-standing questions.
Clemens Spensberger, Trond Thorsteinsson, and Thomas Spengler
Geosci. Model Dev., 15, 2711–2729, https://doi.org/10.5194/gmd-15-2711-2022, https://doi.org/10.5194/gmd-15-2711-2022, 2022
Short summary
Short summary
In order to understand the atmosphere, we rely on a hierarchy of models ranging from very simple to very complex. Comparing different steps in this hierarchy usually entails comparing different models. Here we combine two such steps that are commonly used in one modelling framework. This makes comparisons both much easier and much more direct.
Clio Michel, Erica Madonna, Clemens Spensberger, Camille Li, and Stephen Outten
Weather Clim. Dynam., 2, 1131–1148, https://doi.org/10.5194/wcd-2-1131-2021, https://doi.org/10.5194/wcd-2-1131-2021, 2021
Short summary
Short summary
Climate models still struggle to correctly represent blocking frequency over the North Atlantic–European domain. This study makes use of five large ensembles of climate simulations and the ERA-Interim reanalyses to investigate the Greenland blocking frequency and one of its drivers, namely cyclonic Rossby wave breaking. We particularly try to understand the discrepancies between two specific models, out of the five, that behave differently.
Leonidas Tsopouridis, Thomas Spengler, and Clemens Spensberger
Weather Clim. Dynam., 2, 953–970, https://doi.org/10.5194/wcd-2-953-2021, https://doi.org/10.5194/wcd-2-953-2021, 2021
Short summary
Short summary
Comparing simulations with realistic and smoothed SSTs, we find that the intensification of individual cyclones in the Gulf Stream and Kuroshio regions is only marginally affected by reducing the SST gradient. In contrast, we observe a reduced cyclone activity and a shift in storm tracks. Considering differences of the variables occurring within/outside of a radius of any cyclone, we find cyclones to play only a secondary role in explaining the mean states differences among the SST experiments.
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, https://doi.org/10.5194/gmd-13-6165-2020, 2020
Short summary
Short summary
The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
Andrea Marcheggiani and Thomas Spengler
EGUsphere, https://doi.org/10.5194/egusphere-2025-3855, https://doi.org/10.5194/egusphere-2025-3855, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Cold air outbreaks, where cold polar air flows over warmer oceans, help restore midlatitude atmospheric temperature gradients near strong ocean currents, supporting storm formation. Using a novel method, we show that moderate outbreaks cover less than 15 % of the Gulf Stream region but explain up to 40 % of near-surface variability. In the North Pacific, they are more extensive and still account for a large share of variability, highlighting their key role in shaping storm tracks.
Chris Weijenborg and Thomas Spengler
EGUsphere, https://doi.org/10.5194/egusphere-2024-3404, https://doi.org/10.5194/egusphere-2024-3404, 2024
Short summary
Short summary
The swift succession of storms, referred to as cyclone clustering, is often associated with weather extremes. We introduce a detection scheme for these events and subdivide these into two types. One type is associated with storms that follow each other in space, whereas the other type requires a proximity over time. Cyclone clustering is more frequent during winter and the first type is associated with stronger storms, suggesting that the two types emerge due to different mechanisms.
Henrik Auestad, Clemens Spensberger, Andrea Marcheggiani, Paulo Ceppi, Thomas Spengler, and Tim Woollings
Weather Clim. Dynam., 5, 1269–1286, https://doi.org/10.5194/wcd-5-1269-2024, https://doi.org/10.5194/wcd-5-1269-2024, 2024
Short summary
Short summary
Latent heating due to condensation can influence atmospheric circulation by strengthening or weakening horizontal temperature contrasts. Strong temperature contrasts intensify storms and imply the existence of strong upper tropospheric winds called jets. It remains unclear whether latent heating preferentially reinforces or abates the existing jet. We show that this disagreement is attributable to how the jet is defined, confirming that latent heating reinforces the jet.
Fumiaki Ogawa and Thomas Spengler
Weather Clim. Dynam., 5, 1031–1042, https://doi.org/10.5194/wcd-5-1031-2024, https://doi.org/10.5194/wcd-5-1031-2024, 2024
Short summary
Short summary
The exchange of energy and moisture between the atmosphere and ocean is maximised along strong meridional contrasts in sea surface temperature, such as across the Gulf Stream and Kuroshio. We find that these strong meridional contrasts confine and determine the position of evaporation and precipitation, as well as storm occurrence and intensity. The general intensity of the water cycle and storm activity, however, is determined by the underlying absolute sea surface temperature.
Clemens Spensberger
Weather Clim. Dynam., 5, 659–669, https://doi.org/10.5194/wcd-5-659-2024, https://doi.org/10.5194/wcd-5-659-2024, 2024
Short summary
Short summary
It is well-established that variations in convection in the tropical Indo-Pacific can influence weather in far-away regions. In this idea, I argue that the main theory used to explain this influence over large distances is incomplete. I propose hypotheses that could lead the way towards a more fundamental explanation and outline a novel approach that could be used to test the hypotheses I raise. The suggested approach might be useful to address also other long-standing questions.
Christiane Duscha, Juraj Pálenik, Thomas Spengler, and Joachim Reuder
Atmos. Meas. Tech., 16, 5103–5123, https://doi.org/10.5194/amt-16-5103-2023, https://doi.org/10.5194/amt-16-5103-2023, 2023
Short summary
Short summary
We combine observations from two scanning Doppler lidars to obtain new and unique insights into the dynamic processes inherent to atmospheric convection. The approach complements and enhances conventional methods to probe convection and has the potential to substantially deepen our understanding of this complex process, which is crucial to improving our weather and climate models.
Andrea Marcheggiani and Thomas Spengler
Weather Clim. Dynam., 4, 927–942, https://doi.org/10.5194/wcd-4-927-2023, https://doi.org/10.5194/wcd-4-927-2023, 2023
Short summary
Short summary
There is a gap between the theoretical understanding and model representation of moist diabatic effects on the evolution of storm tracks. We seek to bridge this gap by exploring the relationship between diabatic and adiabatic contributions to changes in baroclinicity. We find reversed behaviours in the lower and upper troposphere in the maintenance of baroclinicity. In particular, our study reveals a link between higher moisture availability and upper-tropospheric restoration of baroclinicity.
Stephen Outten, Camille Li, Martin P. King, Lingling Suo, Peter Y. F. Siew, Hoffman Cheung, Richard Davy, Etienne Dunn-Sigouin, Tore Furevik, Shengping He, Erica Madonna, Stefan Sobolowski, Thomas Spengler, and Tim Woollings
Weather Clim. Dynam., 4, 95–114, https://doi.org/10.5194/wcd-4-95-2023, https://doi.org/10.5194/wcd-4-95-2023, 2023
Short summary
Short summary
Strong disagreement exists in the scientific community over the role of Arctic sea ice in shaping wintertime Eurasian cooling. The observed Eurasian cooling can arise naturally without sea-ice loss but is expected to be a rare event. We propose a framework that incorporates sea-ice retreat and natural variability as contributing factors. A helpful analogy is of a dice roll that may result in cooling, warming, or anything in between, with sea-ice loss acting to load the dice in favour of cooling.
Tim Woollings, Camille Li, Marie Drouard, Etienne Dunn-Sigouin, Karim A. Elmestekawy, Momme Hell, Brian Hoskins, Cheikh Mbengue, Matthew Patterson, and Thomas Spengler
Weather Clim. Dynam., 4, 61–80, https://doi.org/10.5194/wcd-4-61-2023, https://doi.org/10.5194/wcd-4-61-2023, 2023
Short summary
Short summary
This paper investigates large-scale atmospheric variability in polar regions, specifically the balance between large-scale turbulence and Rossby wave activity. The polar regions are relatively more dominated by turbulence than lower latitudes, but Rossby waves are found to play a role and can even be triggered from high latitudes under certain conditions. Features such as cyclone lifetimes, high-latitude blocks, and annular modes are discussed from this perspective.
Clemens Spensberger, Trond Thorsteinsson, and Thomas Spengler
Geosci. Model Dev., 15, 2711–2729, https://doi.org/10.5194/gmd-15-2711-2022, https://doi.org/10.5194/gmd-15-2711-2022, 2022
Short summary
Short summary
In order to understand the atmosphere, we rely on a hierarchy of models ranging from very simple to very complex. Comparing different steps in this hierarchy usually entails comparing different models. Here we combine two such steps that are commonly used in one modelling framework. This makes comparisons both much easier and much more direct.
Clio Michel, Erica Madonna, Clemens Spensberger, Camille Li, and Stephen Outten
Weather Clim. Dynam., 2, 1131–1148, https://doi.org/10.5194/wcd-2-1131-2021, https://doi.org/10.5194/wcd-2-1131-2021, 2021
Short summary
Short summary
Climate models still struggle to correctly represent blocking frequency over the North Atlantic–European domain. This study makes use of five large ensembles of climate simulations and the ERA-Interim reanalyses to investigate the Greenland blocking frequency and one of its drivers, namely cyclonic Rossby wave breaking. We particularly try to understand the discrepancies between two specific models, out of the five, that behave differently.
Leonidas Tsopouridis, Thomas Spengler, and Clemens Spensberger
Weather Clim. Dynam., 2, 953–970, https://doi.org/10.5194/wcd-2-953-2021, https://doi.org/10.5194/wcd-2-953-2021, 2021
Short summary
Short summary
Comparing simulations with realistic and smoothed SSTs, we find that the intensification of individual cyclones in the Gulf Stream and Kuroshio regions is only marginally affected by reducing the SST gradient. In contrast, we observe a reduced cyclone activity and a shift in storm tracks. Considering differences of the variables occurring within/outside of a radius of any cyclone, we find cyclones to play only a secondary role in explaining the mean states differences among the SST experiments.
Kristine Flacké Haualand and Thomas Spengler
Weather Clim. Dynam., 2, 695–712, https://doi.org/10.5194/wcd-2-695-2021, https://doi.org/10.5194/wcd-2-695-2021, 2021
Short summary
Short summary
Given the recent focus on the influence of upper tropospheric structure in wind and temperature on midlatitude weather, we use an idealised model to investigate how structural modifications impact cyclone development. We find that cyclone intensification is less sensitive to these modifications than to changes in the amount of cloud condensation, suggesting that an accurate representation of the upper-level troposphere is less important for midlatitude weather than previously anticipated.
Patrick Johannes Stoll, Thomas Spengler, Annick Terpstra, and Rune Grand Graversen
Weather Clim. Dynam., 2, 19–36, https://doi.org/10.5194/wcd-2-19-2021, https://doi.org/10.5194/wcd-2-19-2021, 2021
Short summary
Short summary
Polar lows are intense meso-scale cyclones occurring at high latitudes. The research community has not agreed on a conceptual model to describe polar-low development. Here, we apply self-organising maps to identify the typical ambient sub-synoptic environments of polar lows and find that they can be described as moist-baroclinic cyclones that develop in four different environments characterised by the vertical wind shear.
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, https://doi.org/10.5194/gmd-13-6165-2020, 2020
Short summary
Short summary
The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
Cited articles
Armon, M., de Vries, A. J., Marra, F., Peleg, N., and Wernli, H.: Saharan rainfall climatology and its relationship with surface cyclones, Weather and Climate Extremes, 43, 100638, https://doi.org/10.1016/j.wace.2023.100638, 2024. a
Atmospheric River Tracking Method Intercomparison Project: ARTMIP Tier 2 Catalogues ERA5 Reanalysis, Climate Data Gateway at NCAR [data set], https://doi.org/10.26024/rawv-yx53, 2022. a
Azad, R. and Sorteberg, A.: Extreme daily precipitation in coastal western Norway and the link to atmospheric rivers, J. Geophys. Res.-Atmos., 122, 2080–2095, https://doi.org/10.1002/2016JD025615, 2017. a, b, c
Berry, G., Thorncroft, C., and Hewson, T.: African Easterly Waves during 2004 – Analysis Using Objective Techniques, Mon. Weather Rev., 135, 1251–1267, https://doi.org/10.1175/MWR3343.1, 2007. a
Binder, H., Boettcher, M., Grams, C. M., Joos, H., Pfahl, S., and Wernli, H.: Exceptional Air Mass Transport and Dynamical Drivers of an Extreme Wintertime Arctic Warm Event, Geophys. Res. Lett., 44, 12028–12036, https://doi.org/10.1002/2017GL075841, 2017. a, b
Blamey, R. C., Ramos, A. M., Trigo, R. M., Tomé, R., and Reason, C. J. C.: The Influence of Atmospheric Rivers over the South Atlantic on Winter Rainfall in South Africa, J. Hydrometeorol., 19, 127–142, https://doi.org/10.1175/JHM-D-17-0111.1, 2018. a
Chang, E. K. M., Lee, S., and Swanson, K. L.: Storm Track Dynamics, J. Climate, 15, 2163–2183, https://doi.org/10.1175/1520-0442(2002)015<02163:STD>2.0.CO;2, 2002. a
Collow, A. B. M., Shields, C. A., Guan, B., Kim, S., Lora, J. M., McClenny, E. E., Nardi, K., Payne, A., Reid, K., Shearer, E. J., Tomé, R., Wille, J. D., Ramos, A. M., Gorodetskaya, I. V., Leung, L. R., O'Brien, T. A., Ralph, F. M., Rutz, J., Ullrich, P. A., and Wehner, M.: An Overview of ARTMIP's Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and Their Associated Precipitation, J. Geophys. Res.-Atmos., 127, e2021JD036155, https://doi.org/10.1029/2021JD036155, 2022. a, b
Dacre, H. F., Clark, P. A., Martinez-Alvarado, O., Stringer, M. A., and Lavers, D. A.: How Do Atmospheric Rivers Form?, B. Am. Meteorol. Soc., 96, 1243–1255, https://doi.org/10.1175/BAMS-D-14-00031.1, 2015. a
Dacre, H. F., Martínez-Alvarado, O., and Mbengue, C. O.: Linking Atmospheric Rivers and Warm Conveyor Belt Airflows, J. Hydrometeorol., 20, 1183–1196, https://doi.org/10.1175/JHM-D-18-0175.1, 2019. a, b
Dezfuli, A.: Rare Atmospheric River Caused Record Floods across the Middle East, B. Am. Meteorol. Soc., 101, E394–E400, https://doi.org/10.1175/BAMS-D-19-0247.1, 2020. a
Gimeno, L., Algarra, I., Eiras-Barca, J., Ramos, A. M., and Nieto, R.: Atmospheric river, a term encompassing different meteorological patterns, WIREs Water, 8, e1558, https://doi.org/10.1002/wat2.1558, 2021. a
Griffith, H. V., Wade, A. J., Lavers, D. A., and Watts, G.: Atmospheric river orientation determines flood occurrence, Hydrol. Process., 34, 4547–4555, https://doi.org/10.1002/hyp.13905, 2020. a, b
Guan, B. and Waliser, D. E.: Detection of atmospheric rivers: Evaluation and application of an algorithm for global studies, J. Geophys. Res.-Atmos., 120, 12514–12535, https://doi.org/10.1002/2015JD024257, 2015. a, b
Heitmann, K., Sprenger, M., Binder, H., Wernli, H., and Joos, H.: Warm conveyor belt characteristics and impacts along the life cycle of extratropical cyclones: case studies and climatological analysis based on ERA5, Weather Clim. Dynam., 5, 537–557, https://doi.org/10.5194/wcd-5-537-2024, 2024. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., A., H., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023a. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., A., H., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023b. a
Inda-Díaz, H. A., O'Brien, T. A., Zhou, Y., and Collins, W. D.: Constraining and Characterizing the Size of Atmospheric Rivers: A Perspective Independent From the Detection Algorithm, J. Geophys. Res.-Atmos., 126, e2020JD033746, https://doi.org/10.1029/2020JD033746, 2021. a
Knippertz, P.: Tropical–extratropical interactions related to upper-level troughs at low latitudes, Dynam. Atmos. Oceans, 43, 36–62, https://doi.org/10.1016/j.dynatmoce.2006.06.003, 2007. a, b, c
Knippertz, P. and Wernli, H.: A Lagrangian Climatology of Tropical Moisture Exports to the Northern Hemispheric Extratropics, J. Climate, 23, 987–1003, https://doi.org/10.1175/2009JCLI3333.1, 2010. a, b, c
Konstali, K., Spengler, T., Spensberger, C., and Sorteberg, A.: Linking Future Precipitation Changes to Weather Features in CESM2-LE, J. Geophys. Res.-Atmos., 129, e2024JD041190, https://doi.org/10.1029/2024JD041190, 2024a. a, b, c, d
Konstali, K., Spensberger, C., Spengler, T., and Sorteberg, A.: Global Attribution of Precipitation to Weather Features, J. Climate, 37, 1181–1196, https://doi.org/10.1175/JCLI-D-23-0293.1, 2024b. a, b
Läderach, A. and Sodemann, H.: A revised picture of the atmospheric moisture residence time, Geophys. Res. Lett., 43, 924–933, https://doi.org/10.1002/2015GL067449, 2016. a
Lavers, D. A., Villarini, G., Allan, R. P., Wood, E. F., and Wade, A. J.: The detection of atmospheric rivers in atmospheric reanalyses and their links to British winter floods and the large-scale climatic circulation, J. Geophys. Res.-Atmos., 117, D20106, https://doi.org/10.1029/2012JD018027, 2012. a
Madonna, E., Wernli, H., Joos, H., and Martius, O.: Warm Conveyor Belts in the ERA-Interim Dataset (1979–2010). Part I: Climatology and Potential Vorticity Evolution, J. Climate, 27, 3–26, https://doi.org/10.1175/JCLI-D-12-00720.1, 2014. a, b, c
Maranan, M., Fink, A. H., and Knippertz, P.: Rainfall types over southern West Africa: Objective identification, climatology and synoptic environment, Q. J. Roy. Meteor. Soc., 144, 1628–1648, https://doi.org/10.1002/qj.3345, 2018. a
Massoud, E., Massoud, T., Guan, B., Sengupta, A., Espinoza, V., De Luna, M., Raymond, C., and Waliser, D.: Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA), Water, 12, 2863, https://doi.org/10.3390/w12102863, 2020. a
Mattingly, K. S., Mote, T. L., and Fettweis, X.: Atmospheric River Impacts on Greenland Ice Sheet Surface Mass Balance, J. Geophys. Res.-Atmos., 123, 8538–8560, https://doi.org/10.1029/2018JD028714, 2018. a, b, c
Montini, T. L., Jones, C., and Carvalho, L. M. V.: The South American Low-Level Jet: A New Climatology, Variability, and Changes, J. Geophys. Res.-Atmos., 124, 1200–1218, https://doi.org/10.1029/2018JD029634, 2019. a
Mundhenk, B. D., Barnes, E. A., and Maloney, E. D.: All-Season Climatology and Variability of Atmospheric River Frequencies over the North Pacific, J. Climate, 29, 4885–4903, https://doi.org/10.1175/JCLI-D-15-0655.1, 2016. a
Nellikkattil, A. B., Lemmon, D., O'Brien, T. A., Lee, J.-Y., and Chu, J.-E.: Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets, Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, 2024. a
Newell, R. E., Newell, N. E., Zhu, Y., and Scott, C.: Tropospheric rivers? – A pilot study, Geophys. Res. Lett., 19, 2401–2404, https://doi.org/10.1029/92GL02916, 1992. a
O'Brien, T. A., Wehner, M. F., Payne, A. E., Shields, C. A., Rutz, J. J., Leung, L.-R., Ralph, F. M., Collow, A., Gorodetskaya, I., Guan, B., Lora, J. M., McClenny, E., Nardi, K. M., Ramos, A. M., Tomé, R., Sarangi, C., Shearer, E. J., Ullrich, P. A., Zarzycki, C., Loring, B., Huang, H., Inda-Díaz, H. A., Rhoades, A. M., and Zhou, Y.: Increases in Future AR Count and Size: Overview of the ARTMIP Tier 2 CMIP5/6 Experiment, J. Geophys. Res.-Atmos., 127, e2021JD036013, https://doi.org/10.1029/2021JD036013, 2022. a
Papritz, L. and Dunn-Sigouin, E.: What Configuration of the Atmospheric Circulation Drives Extreme Net and Total Moisture Transport Into the Arctic, Geophys. Res. Lett., 47, e2020GL089769, https://doi.org/10.1029/2020GL089769, 2020. a, b
Papritz, L., Hauswirth, D., and Hartmuth, K.: Moisture origin, transport pathways, and driving processes of intense wintertime moisture transport into the Arctic, Weather Clim. Dynam., 3, 1–20, https://doi.org/10.5194/wcd-3-1-2022, 2022. a, b
Park, C., Son, S.-W., and Kim, H.: Distinct Features of Atmospheric Rivers in the Early Versus Late East Asian Summer Monsoon and Their Impacts on Monsoon Rainfall, J. Geophys. Res.-Atmos., 126, e2020JD033537, https://doi.org/10.1029/2020JD033537, 2021. a, b
Poveda, G., Jaramillo, L., and Vallejo, L. F.: Seasonal precipitation patterns along pathways of South American low-level jets and aerial rivers, Water Resour. Res., 50, 98–118, https://doi.org/10.1002/2013WR014087, 2014. a
Ralph, F. M., Neiman, P. J., and Rotunno, R.: Dropsonde Observations in Low-Level Jets over the Northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: Mean Vertical-Profile and Atmospheric-River Characteristics, Mon. Weather Rev., 133, 889–910, https://doi.org/10.1175/MWR2896.1, 2005. a
Reid, K. J., King, A. D., Lane, T. P., and Hudson, D.: Tropical, Subtropical, and Extratropical Atmospheric Rivers in the Australian Region, J. Climate, 35, 2697–2708, https://doi.org/10.1175/JCLI-D-21-0606.1, 2022. a, b
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: Climatological Characteristics of Atmospheric Rivers and Their Inland Penetration over the Western United States, Mon. Weather Rev., 142, 905–921, https://doi.org/10.1175/MWR-D-13-00168.1, 2014. a
Rutz, J. J., Shields, C. A., Lora, J. M., Payne, A. E., Guan, B., Ullrich, P., O'Brien, T., Leung, L. R., Ralph, F. M., Wehner, M., Brands, S., Collow, A., Goldenson, N., Gorodetskaya, I., Griffith, H., Kashinath, K., Kawzenuk, B., Krishnan, H., Kurlin, V., Lavers, D., Magnusdottir, G., Mahoney, K., McClenny, E., Muszynski, G., Nguyen, P. D., Prabhat, M., Qian, Y., Ramos, A. M., Sarangi, C., Sellars, S., Shulgina, T., Tome, R., Waliser, D., Walton, D., Wick, G., Wilson, A. M., and Viale, M.: The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology, J. Geophys. Res.-Atmos., 124, 13777–13802, https://doi.org/10.1029/2019JD030936, 2019. a, b, c, d
Sellars, S. L., Gao, X., and Sorooshian, S.: An Object-Oriented Approach to Investigate Impacts of Climate Oscillations on Precipitation: A Western United States Case Study, J. Hydrometeorol., 16, 830–842, https://doi.org/10.1175/JHM-D-14-0101.1, 2015. a
Serreze, M. C., Crawford, A. D., and Barrett, A. P.: Extreme daily precipitation events at Spitsbergen, an Arctic Island, Int. J. Climatol., 35, 4574–4588, https://doi.org/10.1002/joc.4308, 2015. a
Shearer, E. J., Nguyen, P., Sellars, S. L., Analui, B., Kawzenuk, B., Hsu, K.-L., and Sorooshian, S.: Examination of Global Midlatitude Atmospheric River Lifecycles Using an Object-Oriented Methodology, J. Geophys. Res.-Atmos., 125, e2020JD033425, https://doi.org/10.1029/2020JD033425, 2020. a
Shields, C. A., Wille, J. D., Marquardt Collow, A. B., Maclennan, M., and Gorodetskaya, I. V.: Evaluating Uncertainty and Modes of Variability for Antarctic Atmospheric Rivers, Geophys. Res. Lett., 49, e2022GL099577, https://doi.org/10.1029/2022GL099577, 2022. a
Shields, C. A., Payne, A. E., Shearer, E. J., Wehner, M. F., O'Brien, T. A., Rutz, J. J., Leung, L. R., Ralph, F. M., Marquardt Collow, A. B., Ullrich, P. A., Dong, Q., Gershunov, A., Griffith, H., Guan, B., Lora, J. M., Lu, M., McClenny, E., Nardi, K. M., Pan, M., Qian, Y., Ramos, A. M., Shulgina, T., Viale, M., Sarangi, C., Tomé, R., and Zarzycki, C.: Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment, Geophys. Res. Lett., 50, e2022GL102091, https://doi.org/10.1029/2022GL102091, 2023. a
Sodemann, H. and Stohl, A.: Moisture Origin and Meridional Transport in Atmospheric Rivers and Their Association with Multiple Cyclones, Mon. Weather Rev., 141, 2850–2868, https://doi.org/10.1175/MWR-D-12-00256.1, 2013. a, b, c
Sodemann, H., Wernli, H., Knippertz, P., Cordeira, J. M., Dominguez, F., Guan, B., Hu, H., Ralph, F. M., and Stohl, A.: Structure, Process, and Mechanism, Springer International Publishing, 15–43, https://doi.org/10.1007/978-3-030-28906-5_2, ISBN 978-3-030-28906-5, 2020. a, b
Sorteberg, A. and Walsh, J. E.: Seasonal cyclone variability at 70° N and its impact on moisture transport into the Arctic, Tellus A, 60, 570–586, https://doi.org/10.1111/j.1600-0870.2007.00314.x, 2008. a
Spensberger, C.: Dynlib: A library of diagnostics, feature detection algorithms, plotting and convenience functions for dynamic meteorology, Zenodo [software], https://doi.org/10.5281/zenodo.10471187, 2024a. a
Spensberger, C.: ERA5 moisture transport axis detections, Norstore [data set], https://doi.org/10.11582/2024.00178, 2024b. a
Spensberger, C.: ERA5 normalised moisture transport axis detections, Norstore [data set], https://doi.org/10.11582/2025.00001, 2025. a
Spensberger, C. and Sprenger, M.: Beyond cold and warm: an objective classification for maritime midlatitude fronts, Q. J. Roy. Meteor. Soc., 144, 261–277, https://doi.org/10.1002/qj.3199, 2018. a
Stohl, A., Forster, C., and Sodemann, H.: Remote sources of water vapor forming precipitation on the Norwegian west coast at 60° N – a tale of hurricanes and an atmospheric river, J. Geophys. Res.-Atmos., 113, D05102, https://doi.org/10.1029/2007JD009006, 2008. a
Sultan, B. and Janicot, S.: The West African Monsoon Dynamics. Part II: The “Preonset” and “Onset” of the Summer Monsoon, J. Climate, 16, 3407–3427, https://doi.org/10.1175/1520-0442(2003)016<3407:TWAMDP>2.0.CO;2, 2003. a
Ullrich, P. A. and Zarzycki, C. M.: TempestExtremes: a framework for scale-insensitive pointwise feature tracking on unstructured grids, Geosci. Model Dev., 10, 1069–1090, https://doi.org/10.5194/gmd-10-1069-2017, 2017. a, b, c
Ullrich, P. A., Zarzycki, C. M., McClenny, E. E., Pinheiro, M. C., Stansfield, A. M., and Reed, K. A.: TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets, Geosci. Model Dev., 14, 5023–5048, https://doi.org/10.5194/gmd-14-5023-2021, 2021. a
Viale, M. and Nuñez, M. N.: Climatology of Winter Orographic Precipitation over the Subtropical Central Andes and Associated Synoptic and Regional Characteristics, J. Hydrometeorol., 12, 481–507, https://doi.org/10.1175/2010JHM1284.1, 2011. a
Viale, M., Valenzuela, R., Garreaud, R. D., and Ralph, F. M.: Impacts of Atmospheric Rivers on Precipitation in Southern South America, J. Hydrometeorol., 19, 1671–1687, https://doi.org/10.1175/JHM-D-18-0006.1, 2018. a
Viste, E. and Sorteberg, A.: Moisture transport into the Ethiopian highlands, Int. J. Climatol., 33, 249–263, https://doi.org/10.1002/joc.3409, 2013. a
Wick, G. A., Neiman, P. J., and Ralph, F. M.: Description and Validation of an Automated Objective Technique for Identification and Characterization of the Integrated Water Vapor Signature of Atmospheric Rivers, IEEE T. Geosci. Remote, 51, 2166–2176, https://doi.org/10.1109/TGRS.2012.2211024, 2013. a
Wille, J. D., Favier, V., Dufour, A., Gorodetskaya, I. V., Turner, J., Agosta, C., and Codron, F.: West Antarctic surface melt triggered by atmospheric rivers, Nat. Geosci., 12, 911–916, https://doi.org/10.1038/s41561-019-0460-1, 2019. a, b, c
Wille, J. D., Favier, V., Gorodetskaya, I. V., Agosta, C., Kittel, C., Beeman, J. C., Jourdain, N. C., Lenaerts, J. T. M., and Codron, F.: Antarctic Atmospheric River Climatology and Precipitation Impacts, J. Geophys. Res.-Atmos., 126, e2020JD033788, https://doi.org/10.1029/2020JD033788, 2021. a, b
Wille, J. D., Favier, V., Jourdain, N. C., Kittel, C., Turton, J. V., Agosta, C., Gorodetskaya, I. V., Picard, G., Codron, F., Santos, C. L.-D., Amory, C., Fettweis, X., Blanchet, J., Jomelli, V., and Berchet, A.: Intense atmospheric rivers can weaken ice shelf stability at the Antarctic Peninsula, Communications Earth & Environment, 3, 90, https://doi.org/10.1038/s43247-022-00422-9, 2022. a
Wirth, V., Riemer, M., Chang, E. K. M., and Martius, O.: Rossby Wave Packets on the Midlatitude Waveguide – A Review, Mon. Weather Rev., 146, 1965–2001, https://doi.org/10.1175/mwr-d-16-0483.1, 2018. a
Woods, C. and Caballero, R.: The Role of Moist Intrusions in Winter Arctic Warming and Sea Ice Decline, J. Climate, 29, 4473–4485, https://doi.org/10.1175/jcli-d-15-0773.1, 2016. a, b
Woods, C., Caballero, R., and Svensson, G.: Large-scale circulation associated with moisture intrusions into the Arctic during winter, Geophys. Res. Lett., 40, 4717–4721, https://doi.org/10.1002/grl.50912, 2013. a, b
Xu, G., Ma, X., Chang, P., and Wang, L.: Image-processing-based atmospheric river tracking method version 1 (IPART-1), Geosci. Model Dev., 13, 4639–4662, https://doi.org/10.5194/gmd-13-4639-2020, 2020. a
Zhang, Z., Ralph, F. M., and Zheng, M.: The Relationship Between Extratropical Cyclone Strength and Atmospheric River Intensity and Position, Geophys. Res. Lett., 46, 1814–1823, https://doi.org/10.1029/2018GL079071, 2019. a
Zhu, Y. and Newell, R. E.: Atmospheric rivers and bombs, Geophys. Res. Lett., 21, 1999–2002, https://doi.org/10.1029/94GL01710, 1994. a, b, c
Zhu, Y. and Newell, R. E.: A Proposed Algorithm for Moisture Fluxes from Atmospheric Rivers, Mon. Weather Rev., 126, 725–735, https://doi.org/10.1175/1520-0493(1998)126<0725:APAFMF>2.0.CO;2, 1998. a
Short summary
The transport of moisture from warmer and moister to colder and drier regions mainly occurs in brief and narrow bursts. In the mid-latitudes, such bursts are generally referred to as atmospheric rivers; in the Arctic they are often referred to as warm moist intrusions. We introduce a new definition to identify such bursts which is based primarily on their elongated structure. With this more general definition, we show that bursts in moisture transport occur frequently across all climate zones.
The transport of moisture from warmer and moister to colder and drier regions mainly occurs in...