Articles | Volume 25, issue 18
https://doi.org/10.5194/acp-25-11275-2025
© 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/acp-25-11275-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Sep 2025
Research article |
| 25 Sep 2025
| 25 Sep 2025
Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model
Department of Geography and Atmospheric Science, University of Kansas, Lawrence, KS 66045, USA
David B. Mechem
Department of Geography and Atmospheric Science, University of Kansas, Lawrence, KS 66045, USA
Yi Jin
Naval Research Laboratory, Monterey, CA 93943, USA
Virendra P. Ghate
Argonne National Laboratory, Lemont, IL 60439, USA
James F. Booth
Department of Earth and Atmospheric Sciences, City University of New York, City College, New York, NY 10031, USA
Department of Earth and Environmental Sciences, City University of New York, The Graduate Center, New York, NY 10031, USA
Related authors
No articles found.
Ziyu Chen, Philip M. Orton, James F. Booth, Thomas Wahl, Arthur DeGaetano, Joel Kaatz, and Radley M. Horton
Hydrol. Earth Syst. Sci., 29, 3101–3117, https://doi.org/10.5194/hess-29-3101-2025, https://doi.org/10.5194/hess-29-3101-2025, 2025
Short summary
Short summary
Urban flooding can be driven by rain and storm surge or the combination of the two, which is called compound flooding. In this study, we analyzed hourly historical rain and surge data for New York City to provide a more detailed statistical analysis than prior studies of this topic. The analyses reveal that tropical cyclones (e.g., hurricanes) have potential for causing more extreme compound floods than other storms, while extratropical cyclones cause less extreme, more frequent compound events.
Jungmin Lee, Virendra P. Ghate, Arka Mitra, Lee M. Miller, Raghavendra Krishnamurthy, and Ulrike Egerer
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-108, https://doi.org/10.5194/wes-2025-108, 2025
Preprint under review for WES
Short summary
Short summary
This study compares weather model predictions to real-world measurements of wind and clouds off California's coast, where offshore wind farms are planned. It finds the model often underestimates wind speeds in cloudy conditions and shows larger errors in clear skies. These results highlight when and where the model is most accurate, helping improve wind forecasts and support better planning for offshore wind energy projects.
Arka Mitra, Virendra Ghate, and Raghavendra Krishnamurthy
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-55, https://doi.org/10.5194/wes-2025-55, 2025
Revised manuscript under review for WES
Short summary
Short summary
This study introduces a new metric to quantify the spatiotemporal variability of wind resources and a novel numerical technique to locate the optimal wind resource within a large wind farm. The new metric and the novel optimization technique are applied to assist in the pre-construction wind resource assessments of two Californian offshore wind energy areas. This optimization is stable for a diverse choice of wind turbines and is easily scalable and adaptable to any other offshore location.
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Jane, James F. Booth, Hanbeen Kim, and Gabriele Villarini
Nat. Hazards Earth Syst. Sci., 24, 4091–4107, https://doi.org/10.5194/nhess-24-4091-2024, https://doi.org/10.5194/nhess-24-4091-2024, 2024
Short summary
Short summary
When assessing the likelihood of compound flooding, most studies ignore that it can arise from different storm types with distinct statistical characteristics. Here, we present a new statistical framework that accounts for these differences and shows how neglecting these can impact the likelihood of compound flood potential.
Maria P. Cadeddu, Virendra P. Ghate, David D. Turner, and Thomas E. Surleta
Atmos. Chem. Phys., 23, 3453–3470, https://doi.org/10.5194/acp-23-3453-2023, https://doi.org/10.5194/acp-23-3453-2023, 2023
Short summary
Short summary
We analyze the variability in marine boundary layer moisture at the Eastern North Atlantic site on a monthly and daily temporal scale and examine its fundamental role in the control of boundary layer cloudiness and precipitation. The study also highlights the complex interaction between large-scale and local processes controlling the boundary layer moisture and the importance of the mesoscale spatial distribution of vapor to support convection and precipitation.
William J. Shaw, Larry K. Berg, Mithu Debnath, Georgios Deskos, Caroline Draxl, Virendra P. Ghate, Charlotte B. Hasager, Rao Kotamarthi, Jeffrey D. Mirocha, Paytsar Muradyan, William J. Pringle, David D. Turner, and James M. Wilczak
Wind Energ. Sci., 7, 2307–2334, https://doi.org/10.5194/wes-7-2307-2022, https://doi.org/10.5194/wes-7-2307-2022, 2022
Short summary
Short summary
This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.
Katherine L. Towey, James F. Booth, Alejandra Rodriguez Enriquez, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 22, 1287–1300, https://doi.org/10.5194/nhess-22-1287-2022, https://doi.org/10.5194/nhess-22-1287-2022, 2022
Short summary
Short summary
Coastal flooding due to storm surge from tropical cyclones is a significant hazard. The influence of tropical cyclone characteristics, including its proximity, intensity, path angle, and speed, on the magnitude of storm surge is examined along the eastern United States. No individual characteristic was found to be strongly related to how much surge occurred at a site, though there is an increased likelihood of high surge occurring when tropical cyclones are both strong and close to a location.
Justin A. Covert, David B. Mechem, and Zhibo Zhang
Atmos. Chem. Phys., 22, 1159–1174, https://doi.org/10.5194/acp-22-1159-2022, https://doi.org/10.5194/acp-22-1159-2022, 2022
Short summary
Short summary
Stratocumulus play an important role in Earth's radiative balance. The simulation of these cloud systems in climate models is difficult due to the scale at which cloud microphysical processes occur compared with model grid sizes. In this study, we use large-eddy simulation to analyze subgrid-scale variability of cloud water and its implications on a cloud water to drizzle model enhancement factor E. We find current values of E may be too large and that E should be vertically dependent in models.
Michael P. Jensen, Virendra P. Ghate, Dié Wang, Diana K. Apoznanski, Mary J. Bartholomew, Scott E. Giangrande, Karen L. Johnson, and Mandana M. Thieman
Atmos. Chem. Phys., 21, 14557–14571, https://doi.org/10.5194/acp-21-14557-2021, https://doi.org/10.5194/acp-21-14557-2021, 2021
Short summary
Short summary
This work compares the large-scale meteorology, cloud, aerosol, precipitation, and thermodynamics of closed- and open-cell cloud organizations using long-term observations from the astern North Atlantic. Open-cell cases are associated with cold-air outbreaks and occur in deeper boundary layers, with stronger winds and higher rain rates compared to closed-cell cases. These results offer important benchmarks for model representation of boundary layer clouds in this climatically important region.
Zhibo Zhang, Qianqian Song, David B. Mechem, Vincent E. Larson, Jian Wang, Yangang Liu, Mikael K. Witte, Xiquan Dong, and Peng Wu
Atmos. Chem. Phys., 21, 3103–3121, https://doi.org/10.5194/acp-21-3103-2021, https://doi.org/10.5194/acp-21-3103-2021, 2021
Short summary
Short summary
This study investigates the small-scale variations and covariations of cloud microphysical properties, namely, cloud liquid water content and cloud droplet number concentration, in marine boundary layer clouds based on in situ observation from the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign. We discuss the dependence of cloud variations on vertical location in cloud and the implications for warm-rain simulations in the global climate models.
Cited articles
Abel, S. J., Boutle, I. A., Waite, K., Fox, S., Brown, P. R. A., Cotton, R., Lloyd, G., Choularton, T. W., and Bower, K. N.: The Role of Precipitation in Controlling the Transition from Stratocumulus to Cumulus Clouds in a Northern Hemisphere Cold-Air Outbreak, J. Atmos. Sci., 74, 2293–2314, https://doi.org/10.1175/JAS-D-16-0362.1, 2017. a, b
Ackerman, A. S., vanZanten, M. C., Stevens, B., Savic-Jovcic, V., Bretherton, C. S., Chlond, A., Golaz, J.-C., Jiang, H., Khairoutdinov, M., Krueger, S. K., Lewellen, D. C., Lock, A., Moeng, C.-H., Nakamura, K., Petters, M. D., Snider, J. R., Weinbrecht, S., and Zulauf, M.: Large-Eddy Simulations of a Drizzling, Stratocumulus-Topped Marine Boundary Layer, Mon. Weather Rev., 137, 1083–1110, https://doi.org/10.1175/2008MWR2582.1, 2009. a, b
Albrecht, B. A., Randall, D. A., and Nicholls, S.: Observations of Marine Stratocumulus Clouds During FIRE, B. Am. Meteorol. Soc., 69, 618–626, https://doi.org/10.1175/1520-0477(1988)069<0618:OOMSCD>2.0.CO;2, 1988. a
Albrecht, B. A., Bretherton, C. S., Johnson, D., Scubert, W. H., and Frisch, A. S.: The Atlantic Stratocumulus Transition Experiment—ASTEX, B. Am. Meteorol. Soc., 76, 889–904, https://doi.org/10.1175/1520-0477(1995)076<0889:TASTE>2.0.CO;2, 1995. a
Bauer, M., Tselioudis, G., and Rossow, W. B.: A New Climatology for Investigating Storm Influences in and on the Extratropics, J. Appl. Meteorol. Clim., 55, 1287–1303, https://doi.org/10.1175/JAMC-D-15-0245.1, 2016. a, b, c
Bodas-Salcedo, A., Williams, K. D., Field, P. R., and Lock, A. P.: The Surface Downwelling Solar Radiation Surplus over the Southern Ocean in the Met Office Model: The Role of Midlatitude Cyclone Clouds, J. Climate, 25, 7467–7486, https://doi.org/10.1175/JCLI-D-11-00702.1, 2012. a, b, c
Bony, S. and Dufresne, J.: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, 2005GL023851, https://doi.org/10.1029/2005GL023851, 2005. a
Boutle, I. A., Beare, R. J., Belcher, S. E., Brown, A. R., and Plant, R. S.: The Moist Boundary Layer under a Mid-latitude Weather System, Bound.-Lay. Meteorol., 134, 367–386, https://doi.org/10.1007/s10546-009-9452-9, 2010. a, b, c, d
Bretherton, C. S. and Wyant, M. C.: Moisture Transport, Lower-Tropospheric Stability, and Decoupling of Cloud-Topped Boundary Layers, J. Atmos. Sci., 54, 148–167, https://doi.org/10.1175/1520-0469(1997)054<0148:MTLTSA>2.0.CO;2, 1997. a, b, c, d
Bretherton, C. S., Austin, P., and Siems, S. T.: Cloudiness and Marine Boundary Layer Dynamics in the ASTEX Lagrangian Experiments. Part II: Cloudiness, Drizzle, Surface Fluxes, and Entrainment, J. Atmos. Sci., 52, 2724–2735, https://doi.org/10.1175/1520-0469(1995)052<2724:CAMBLD>2.0.CO;2, 1995. a
Bryan, G. H., Wyngaard, J. C., and Fritsch, J. M.: Resolution Requirements for the Simulation of Deep Moist Convection, Mon. Weather Rev., 131, 2394–2416, https://doi.org/10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2, 2003. a
Cadeddu, M. P., Marchand, R., Orlandi, E., Turner, D. D., and Mech, M.: Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities, IEEE T. Geosci. Remote, 55, 6468–6481, https://doi.org/10.1109/TGRS.2017.2728699, 2017. a
Cadeddu, M. P., Ghate, V. P., and Mech, M.: Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds, Atmos. Meas. Tech., 13, 1485–1499, https://doi.org/10.5194/amt-13-1485-2020, 2020. a
Cadeddu, M. P., Ghate, V. P., Turner, D. D., and Surleta, T. E.: Boundary layer moisture variability at the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic observatory during marine conditions, Atmos. Chem. Phys., 23, 3453–3470, https://doi.org/10.5194/acp-23-3453-2023, 2023. a, b
Carlson, T. N.: Airflow Through Midlatitude Cyclones and the Comma Cloud Pattern, Mon. Weather Rev., 108, 1498–1509, https://doi.org/10.1175/1520-0493(1980)108<1498:ATMCAT>2.0.CO;2, 1980. a
Clothiaux, E. E., Ackerman, T. P., Mace, G. G., Moran, K. P., Marchand, R. T., Miller, M. A., and Martner, B. E.: Objective Determination of Cloud Heights and Radar Reflectivities Using a Combination of Active Remote Sensors at the ARM CART Sites, J. Appl. Meteorol., 39, 645–665, https://doi.org/10.1175/1520-0450(2000)039<0645:ODOCHA>2.0.CO;2, 2000. a
de Szoeke, S. P., Verlinden, K. L., Yuter, S. E., and Mechem, D. B.: The Time Scales of Variability of Marine Low Clouds, J. Climate, 29, 6463–6481, https://doi.org/10.1175/JCLI-D-15-0460.1, 2016. a, b, c
Eissner, J.: COAMPS-transect-analysis v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.17137173, 2025. a
Eleuterio, D. P., Wang, Q., and Rados, K.: Diagnostic boundary layer height for cloud-topped boundary layers in a mesoscale model, Research Paper, Naval Postgraduate School, Monterey, CA, https://www.researchgate.net/publication/242245878_Diagnostic_boundary_layer_height_for_cloud-topped_boundary_layers_in_A_mesoscale_model (last access: 16 September 2025), 2004. a, b
Field, P. R., Cotton, R. J., McBeath, K., Lock, A. P., Webster, S., and Allan, R. P.: Improving a convection‐permitting model simulation of a cold air outbreak, Q. J. Roy. Meteor. Soc., 140, 124–138, https://doi.org/10.1002/qj.2116, 2014. a, b
Field, P. R., Brožková, R., Chen, M., Dudhia, J., Lac, C., Hara, T., Honnert, R., Olson, J., Siebesma, P., De Roode, S., Tomassini, L., Hill, A., and McTaggart‐Cowan, R.: Exploring the convective grey zone with regional simulations of a cold air outbreak, Q. J. Roy. Meteor. Soc., 143, 2537–2555, https://doi.org/10.1002/qj.3105, 2017. a, b, c
Flynn, D. and Morris, V.: tsiskycover (b1), ARM Data Center [data set], https://doi.org/10.5439/1992207, 2000. a, b
Fu, Q. and Liou, K. N.: On the Correlated k – Distribution Method for Radiative Transfer in Nonhomogeneous Atmospheres, J. Atmos. Sci., 49, 2139–2156, https://doi.org/10.1175/1520-0469(1992)049<2139:OTCDMF>2.0.CO;2, 1992. a
Geerts, B., Giangrande, S. E., McFarquhar, G. M., Xue, L., Abel, S. J., Comstock, J. M., Crewell, S., DeMott, P. J., Ebell, K., Field, P., Hill, T. C. J., Hunzinger, A., Jensen, M. P., Johnson, K. L., Juliano, T. W., Kollias, P., Kosovic, B., Lackner, C., Luke, E., Lüpkes, C., Matthews, A. A., Neggers, R., Ovchinnikov, M., Powers, H., Shupe, M. D., Spengler, T., Swanson, B. E., Tjernström, M., Theisen, A. K., Wales, N. A., Wang, Y., Wendisch, M., and Wu, P.: The COMBLE Campaign: A Study of Marine Boundary Layer Clouds in Arctic Cold-Air Outbreaks, B. Am. Meteorol. Soc., 103, E1371–E1389, https://doi.org/10.1175/BAMS-D-21-0044.1, 2022. a
Ghate, V. P., Miller, M. A., and DiPretore, L.: Vertical velocity structure of marine boundary layer trade wind cumulus clouds, J. Geophys. Res., 116, D16206, https://doi.org/10.1029/2010JD015344, 2011. a
Ghate, V. P., Cadeddu, M. P., Zheng, X., and O’Connor, E.: Turbulence in The Marine Boundary Layer and Air Motions Below Stratocumulus Clouds at the ARM Eastern North Atlantic Site, J. Appl. Meteorol. Clim., 60, 1495–1510, https://doi.org/10.1175/JAMC-D-21-0087.1, 2021. a
Harrold, T. W.: Mechanisms influencing the distribution of precipitation within baroclinic disturbances, Q. J. Roy. Meteor. Soc., 99, 232–251, https://doi.org/10.1002/qj.49709942003, 1973. a
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.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hewson, T. D.: Objective fronts, Meteorol. Appl., 5, 37–65, https://doi.org/10.1017/S1350482798000553, 1998. a, b
Hodur, R. M.: The Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), Mon. Weather Rev., 125, 1414–1430, https://doi.org/10.1175/1520-0493(1997)125<1414:TNRLSC>2.0.CO;2, 1997. a, b
Houze, R. A., Hobbs, P. V., Biswas, K. R., and Davis, W. M.: Mesoscale Rainbands in Extratropical Cyclones, Mon. Weather Rev., 104, 868–878, https://doi.org/10.1175/1520-0493(1976)104<0868:MRIEC>2.0.CO;2, 1976. a
Hurrell, J. W.: Decadal Trends in the North Atlantic Oscillation: Regional Temperatures and Precipitation, Science, 269, 676–679, https://doi.org/10.1126/science.269.5224.676, 1995. a
Ilotoviz, E., Ghate, V. P., and Raveh‐Rubin, S.: The Impact of Slantwise Descending Dry Intrusions on the Marine Boundary Layer and Air‐Sea Interface Over the ARM Eastern North Atlantic Site, J. Geophys. Res.-Atmos., 126, e2020JD033879, https://doi.org/10.1029/2020JD033879, 2021. a, b
Johnson, K., Giangrande, S., and Toto, T.: KAZRARSCL-c0-All-inclusive data stream, ARM Data Center [data set], https://doi.org/10.5439/1393437, 2014. a, b
Jones, C. R., Bretherton, C. S., and Leon, D.: Coupled vs. decoupled boundary layers in VOCALS-REx, Atmos. Chem. Phys., 11, 7143–7153, https://doi.org/10.5194/acp-11-7143-2011, 2011. a, b, c
Juliano, T. W., Coggon, M. M., Thompson, G., Rahn, D. A., Seinfeld, J. H., Sorooshian, A., and Lebo, Z. J.: Marine Boundary Layer Clouds Associated with Coastally Trapped Disturbances: Observations and Model Simulations, J. Atmos. Sci., 76, 2963–2993, https://doi.org/10.1175/JAS-D-18-0317.1, 2019. a
Kain, J. S. and Fritsch, J. M.: A One-Dimensional Entraining/Detraining Plume Model and Its Application in Convective Parameterization, J. Atmos. Sci., 47, 2784–2802, https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2, 1990. a
Kazemirad, M. and Miller, M. A.: Summertime Post-Cold-Frontal Marine Stratocumulus Transition Processes over the Eastern North Atlantic, J. Atmos. Sci., 77, 2011–2037, https://doi.org/10.1175/JAS-D-19-0167.1, 2020. a, b
Keeler, E., Burk, K., and Kyrouac, J.: Balloon-borne sounding system (BBSS), WNPN output data, ARM Data Center [data set], https://doi.org/10.5439/1595321, 2022. a, b
Kessler, E.: On the Distribution and Continuity of Water Substance in Atmospheric Circulations, in: On the Distribution and Continuity of Water Substance in Atmospheric Circulations, American Meteorological Society, Boston, MA, 1–84, ISBN 978-1-935704-36-2, https://doi.org/10.1007/978-1-935704-36-2_1, 1969. a, b, c, d, e, f
Khairoutdinov, M. and Kogan, Y.: A New Cloud Physics Parameterization in a Large-Eddy Simulation Model of Marine Stratocumulus, Mon. Weather Rev., 128, 229–243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2, 2000. a
Klein, S. A. and Hartmann, D. L.: The Seasonal Cycle of Low Stratiform Clouds, J. Climate, 6, 1587–1606, https://doi.org/10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2, 1993. a, b
Kyrouac, J., Shi, Y., and Tuftedal, M.: met.b1, ARM Data Center [data set], https://doi.org/10.5439/1786358, 2021. a, b
Lamraoui, F., Booth, J. F., Naud, C. M., Jensen, M. P., and Johnson, K. L.: The Interaction Between Boundary Layer and Convection Schemes in a WRF Simulation of Post Cold Frontal Clouds Over the ARM East North Atlantic Site, J. Geophys. Res.-Atmos., 124, 4699–4721, https://doi.org/10.1029/2018JD029370, 2019. a
Li, X.-Y., Wang, H., Chen, J., Endo, S., George, G., Cairns, B., Chellappan, S., Zeng, X., Kirschler, S., Voigt, C., Sorooshian, A., Crosbie, E., Chen, G., Ferrare, R. A., Gustafson, W. I., Hair, J. W., Kleb, M. M., Liu, H., Moore, R., Painemal, D., Robinson, C., Scarino, A. J., Shook, M., Shingler, T. J., Thornhill, K. L., Tornow, F., Xiao, H., Ziemba, L. D., and Zuidema, P.: Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part I: Case Setup and Sensitivities to Large-Scale Forcings, J. Atmos. Sci., 79, 73–100, https://doi.org/10.1175/JAS-D-21-0123.1, 2022. a
Liu, S. and Liang, X.-Z.: Observed Diurnal Cycle Climatology of Planetary Boundary Layer Height, J. Climate, 23, 5790–5809, https://doi.org/10.1175/2010JCLI3552.1, 2010. a
Long, C., Slater, D., and Tooman, T. P.: Total sky imager model 880 status and testing results, Pacific Northwest National Laboratory Richland, WA, USA, https://doi.org/10.2172/1020735, 2001. a
Louis, J.-F.: A parametric model of vertical eddy fluxes in the atmosphere, Bound.-Lay. Meteorol., 17, 187–202, 1979. a
McCoy, I. L., Wood, R., and Fletcher, J. K.: Identifying Meteorological Controls on Open and Closed Mesoscale Cellular Convection Associated with Marine Cold Air Outbreaks, J. Geophys. Res.-Atmos., 122, 11678–11702, https://doi.org/10.1002/2017JD027031, 2017. a, b, c
Mechem, D. B. and Kogan, Y. L.: Simulating the Transition from Drizzling Marine Stratocumulus to Boundary Layer Cumulus with a Mesoscale Model, Mon. Weather Rev., 131, 2342–2360, https://doi.org/10.1175/1520-0493(2003)131<2342:STTFDM>2.0.CO;2, 2003. a, b
Mechem, D. B., Kogan, Y. L., and Schultz, D. M.: Large-Eddy Observation of Post-Cold-Frontal Continental Stratocumulus, J. Atmos. Sci., 67, 3368–3383, https://doi.org/10.1175/2010JAS3389.1, 2010. a, b
Mechem, D. B., Yuter, S. E., and de Szoeke, S. P.: Thermodynamic and Aerosol Controls in Southeast Pacific Stratocumulus, J. Atmos. Sci., 69, 1250–1266, https://doi.org/10.1175/JAS-D-11-0165.1, 2012. a, b
Mechem, D. B., Wittman, C. S., Miller, M. A., Yuter, S. E., and de Szoeke, S. P.: Joint Synoptic and Cloud Variability over the Northeast Atlantic near the Azores, J. Appl. Meteorol. Clim., 57, 1273–1290, https://doi.org/10.1175/JAMC-D-17-0211.1, 2018. a, b
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, https://doi.org/10.1029/RG020i004p00851, 1982. a
Minnis, P., Sun-Mack, S., Young, D. F., Heck, P. W., Garber, D. P., Chen, Y., Spangenberg, D. A., Arduini, R. F., Trepte, Q. Z., Smith, W. L., Ayers, J. K., Gibson, S. C., Miller, W. F., Hong, G., Chakrapani, V., Takano, Y., Liou, K.-N., Xie, Y., and Yang, P.: CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data – Part I: Algorithms, IEEE T. Geosci. Remote, 49, 4374–4400, https://doi.org/10.1109/TGRS.2011.2144601, 2011. a
Morrison, H., Van Lier‐Walqui, M., Fridlind, A. M., Grabowski, W. W., Harrington, J. Y., Hoose, C., Korolev, A., Kumjian, M. R., Milbrandt, J. A., Pawlowska, H., Posselt, D. J., Prat, O. P., Reimel, K. J., Shima, S., Van Diedenhoven, B., and Xue, L.: Confronting the Challenge of Modeling Cloud and Precipitation Microphysics, J. Adv. Model. Earth Sy., 12, e2019MS001689, https://doi.org/10.1029/2019MS001689, 2020. a
Muradyan, P. and Ermold, B.: 1290-MHz Radar Wind Profiler: Low Mode Wind Averages, ARM Data Center [data set], https://doi.org/10.5439/1663214, 2021. a, b
Myers, T. A. and Norris, J. R.: Observational Evidence That Enhanced Subsidence Reduces Subtropical Marine Boundary Layer Cloudiness, J. Climate, 26, 7507–7524, https://doi.org/10.1175/JCLI-D-12-00736.1, 2013. a
Naud, C. M., Posselt, D. J., and Van Den Heever, S. C.: A CloudSat–CALIPSO View of Cloud and Precipitation Properties across Cold Fronts over the Global Oceans, J. Climate, 28, 6743–6762, https://doi.org/10.1175/JCLI-D-15-0052.1, 2015. a, b
Naud, C. M., Booth, J. F., and Lamraoui, F.: Post Cold Frontal Clouds at the ARM Eastern North Atlantic Site: An Examination of the Relationship Between Large‐Scale Environment and Low‐Level Cloud Properties, J. Geophys. Res.-Atmos., 123, 12117–12132, https://doi.org/10.1029/2018JD029015, 2018a. a, b, c, d
Naud, C. M., Booth, J. F., Lebsock, M., and Grecu, M.: Observational Constraint for Precipitation in Extratropical Cyclones: Sensitivity to Data Sources, J. Appl. Meteorol. Clim., 57, 991–1009, https://doi.org/10.1175/JAMC-D-17-0289.1, 2018b. a
Naud, C. M., Jeyaratnam, J., Booth, J. F., Zhao, M., and Gettelman, A.: Evaluation of Modeled Precipitation in Oceanic Extratropical Cyclones Using IMERG, J. Climate, 33, 95–113, https://doi.org/10.1175/JCLI-D-19-0369.1, 2020. a
Nelson, K. J., Mechem, D. B., and Kogan, Y. L.: Evaluation of Warm-Rain Microphysical Parameterizations in Mesoscale Simulations of the Cloudy Marine Boundary Layer, Mon. Weather Rev., 144, 2137–2154, https://doi.org/10.1175/MWR-D-15-0266.1, 2016. a, b
Neu, U., Akperov, M. G., Bellenbaum, N., Benestad, R., Blender, R., Caballero, R., Cocozza, A., Dacre, H. F., Feng, Y., Fraedrich, K., Grieger, J., Gulev, S., Hanley, J., Hewson, T., Inatsu, M., Keay, K., Kew, S. F., Kindem, I., Leckebusch, G. C., Liberato, M. L. R., Lionello, P., Mokhov, I. I., Pinto, J. G., Raible, C. C., Reale, M., Rudeva, I., Schuster, M., Simmonds, I., Sinclair, M., Sprenger, M., Tilinina, N. D., Trigo, I. F., Ulbrich, S., Ulbrich, U., Wang, X. L., and Wernli, H.: IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms, B. Am. Meteorol. Soc., 94, 529–547, https://doi.org/10.1175/BAMS-D-11-00154.1, 2013. a
Nicholls, S.: The dynamics of stratocumulus: Aircraft observations and comparisons with a mixed layer model, Q. J. Roy. Meteor. Soc., 110, 783–820, https://doi.org/10.1002/qj.49711046603, 1984. a, b
Nicholls, S. and Leighton, J.: An observational study of the structure of stratiform cloud sheets: Part I. Structure, Q. J. Roy. Meteor. Soc., 112, 431–460, https://doi.org/10.1002/qj.49711247209, 1986. a
Norris, J. R. and Klein, S. A.: Low Cloud Type over the Ocean from Surface Observations. Part III: Relationship to Vertical Motion and the Regional Surface Synoptic Environment, J. Climate, 13, 245–256, https://doi.org/10.1175/1520-0442(2000)013<0245:LCTOTO>2.0.CO;2, 2000. a, b
O'Connor, E. J., Hogan, R. J., and Illingworth, A. J.: Retrieving Stratocumulus Drizzle Parameters Using Doppler Radar and Lidar, J. Appl. Meteorol., 44, 14–27, https://doi.org/10.1175/JAM-2181.1, 2005. a
Paltridge, G. W.: Infrared emissivity, short-wave albedo, and the microphysics of stratiform water clouds, J. Geophys. Res., 79, 4053–4058, https://doi.org/10.1029/JC079i027p04053, 1974. a
Platt, C. M. R.: Infrared absorption and liquid water content in stratocumulus clouds, Q. J. Roy. Meteor. Soc., 102, 553–561, https://doi.org/10.1002/qj.49710243305, 1976. a
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S., Schmidli, J., Van Lipzig, N. P. M., and Leung, R.: A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015. a
Rauber, R. M., Stevens, B., Ochs, H. T., Knight, C., Albrecht, B. A., Blyth, A. M., Fairall, C. W., Jensen, J. B., Lasher-Trapp, S. G., Mayol-Bracero, O. L., Vali, G., Anderson, J. R., Baker, B. A., Bandy, A. R., Burnet, E., Brenguier, J.-L., Brewer, W. A., Brown, P. R. A., Chuang, R., Cotton, W. R., Di Girolamo, L., Geerts, B., Gerber, H., Göke, S., Gomes, L., Heikes, B. G., Hudson, J. G., Kollias, P., Lawson, R. R., Krueger, S. K., Lenschow, D. H., Nuijens, L., O'Sullivan, D. W., Rilling, R. A., Rogers, D. C., Siebesma, A. P., Snodgrass, E., Stith, J. L., Thornton, D. C., Tucker, S., Twohy, C. H., and Zuidema, P.: Rain in Shallow Cumulus Over the Ocean: The RICO Campaign, B. Am. Meteorol. Soc., 88, 1912–1928, https://doi.org/10.1175/BAMS-88-12-1912, 2007. a
Raveh-Rubin, S.: Dry Intrusions: Lagrangian Climatology and Dynamical Impact on the Planetary Boundary Layer, J. Climate, 30, 6661–6682, https://doi.org/10.1175/JCLI-D-16-0782.1, 2017. a
Rutledge, S. A. and Hobbs, P.: The Mesoscale and Microscale Structure and Organization of Clouds and Precipitation in Midlatitude Cyclones. VIII: A Model for the “Seeder-Feeder” Process in Warm-Frontal Rainbands, J. Atmos. Sci., 40, 1185–1206, https://doi.org/10.1175/1520-0469(1983)040<1185:TMAMSA>2.0.CO;2, 1983. a
Rémillard, J. and Tselioudis, G.: Cloud Regime Variability over the Azores and Its Application to Climate Model Evaluation, J. Climate, 28, 9707–9720, https://doi.org/10.1175/JCLI-D-15-0066.1, 2015. a
Rémillard, J., Kollias, P., Luke, E., and Wood, R.: Marine Boundary Layer Cloud Observations in the Azores, J. Climate, 25, 7381–7398, https://doi.org/10.1175/JCLI-D-11-00610.1, 2012. a, b
Rémillard, J., Fridlind, A. M., Ackerman, A. S., Tselioudis, G., Kollias, P., Mechem, D. B., Chandler, H. E., Luke, E., Wood, R., Witte, M. K., Chuang, P. Y., and Ayers, J. K.: Use of Cloud Radar Doppler Spectra to Evaluate Stratocumulus Drizzle Size Distributions in Large-Eddy Simulations with Size-Resolved Microphysics, J. Appl. Meteorol. Clim., 56, 3263–3283, https://doi.org/10.1175/JAMC-D-17-0100.1, 2017. a
Savic-Jovcic, V. and Stevens, B.: The Structure and Mesoscale Organization of Precipitating Stratocumulus, J. Atmos. Sci., 65, 1587–1605, https://doi.org/10.1175/2007JAS2456.1, 2008. a, b
Schemm, S. and Sprenger, M.: Frontal‐wave cyclogenesis in the North Atlantic – a climatological characterisation, Q. J. Roy. Meteor. Soc., 141, 2989–3005, https://doi.org/10.1002/qj.2584, 2015. a
Seibert, P.: Review and intercomparison of operational methods for the determination of the mixing height, Atmos. Environ., 34, 1001–1027, https://doi.org/10.1016/S1352-2310(99)00349-0, 2000. a
Siebesma, A. P., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J., Duynkerke, P. G., Jiang, H., Khairoutdinov, M., Lewellen, D., Moeng, C.-H., Sanchez, E., Stevens, B., and Stevens, D. E.: A Large Eddy Simulation Intercomparison Study of Shallow Cumulus Convection, J. Atmos. Sci., 60, 1201–1219, https://doi.org/10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2, 2003. a
Simmonds, I., Keay, K., and Tristram Bye, J. A.: Identification and Climatology of Southern Hemisphere Mobile Fronts in a Modern Reanalysis, J. Climate, 25, 1945–1962, https://doi.org/10.1175/JCLI-D-11-00100.1, 2012. a, b
Slingo, J. M.: The Development and Verification of A Cloud Prediction Scheme For the Ecmwf Model, Q. J. Roy. Meteor. Soc., 113, 899–927, https://doi.org/10.1002/qj.49711347710, 1987. a
Stein, U. and Alpert, P.: Factor Separation in Numerical Simulations, J. Atmos. Sci., 50, 2107–2115, https://doi.org/10.1175/1520-0469(1993)050<2107:FSINS>2.0.CO;2, 1993. a
Stevens, B., Cotton, W. R., Feingold, G., and Moeng, C.-H.: Large-Eddy Simulations of Strongly Precipitating, Shallow, Stratocumulus-Topped Boundary Layers, J. Atmos. Sci., 55, 3616–3638, https://doi.org/10.1175/1520-0469(1998)055<3616:LESOSP>2.0.CO;2, 1998. a
Stevens, B., Ackerman, A. S., Albrecht, B. A., Brown, A. R., Chlond, A., Cuxart, J., Duynkerke, P. G., Lewellen, D. C., Macvean, M. K., Neggers, R. A. J., Sánchez, E., Siebesma, A. P., and Stevens, D. E.: Simulations of Trade Wind Cumuli under a Strong Inversion, J. Atmos. Sci., 58, 1870–1891, https://doi.org/10.1175/1520-0469(2001)058<1870:SOTWCU>2.0.CO;2, 2001. a
Stevens, B., Moeng, C.-H., Ackerman, A. S., Bretherton, C. S., Chlond, A., De Roode, S., Edwards, J., Golaz, J.-C., Jiang, H., Khairoutdinov, M., Kirkpatrick, M. P., Lewellen, D. C., Lock, A., Müller, F., Stevens, D. E., Whelan, E., and Zhu, P.: Evaluation of Large-Eddy Simulations via Observations of Nocturnal Marine Stratocumulus, Mon. Weather Rev., 133, 1443–1462, https://doi.org/10.1175/MWR2930.1, 2005. a, b, c
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization, Mon. Weather Rev., 136, 5095–5115, https://doi.org/10.1175/2008MWR2387.1, 2008. a
Tiedtke, M., Heckley, W. A., and Slingo, J.: Tropical forecasting at ECMWF: The influence of physical parametrization on the mean structure of forecasts and analyses, Q. J. Roy. Meteor. Soc., 114, 639–664, https://doi.org/10.1002/qj.49711448106, 1988. a
Tornow, F., Ackerman, A. S., Fridlind, A. M., Tselioudis, G., Cairns, B., Painemal, D., and Elsaesser, G.: On the Impact of a Dry Intrusion Driving Cloud-Regime Transitions in a Midlatitude Cold-Air Outbreak, J. Atmos. Sci., 80, 2881–2896, https://doi.org/10.1175/JAS-D-23-0040.1, 2023. a, b, c
vanZanten, M. C., Stevens, B., Nuijens, L., Siebesma, A. P., Ackerman, A. S., Burnet, F., Cheng, A., Couvreux, F., Jiang, H., Khairoutdinov, M., Kogan, Y., Lewellen, D. C., Mechem, D., Nakamura, K., Noda, A., Shipway, B. J., Slawinska, J., Wang, S., and Wyszogrodzki, A.: Controls on precipitation and cloudiness in simulations of trade-wind cumulus as observed during RICO, J. Adv. Modeling Earth Systems, 3, M06001, https://doi.org/10.1029/2011MS000056, 2011. a, b
Wang, J., Rossow, W. B., Uttal, T., and Rozendaal, M.: Variability of Cloud Vertical Structure during ASTEX Observed from a Combination of Rawinsonde, Radar, Ceilometer, and Satellite, Mon. Weather Rev., 127, 2484–2502, https://doi.org/10.1175/1520-0493(1999)127<2484:VOCVSD>2.0.CO;2, 1999. a
Wang, J., Wood, R., Jensen, M. P., Chiu, J. C., Liu, Y., Lamer, K., Desai, N., Giangrande, S. E., Knopf, D. A., Kollias, P., Laskin, A., Liu, X., Lu, C., Mechem, D., Mei, F., Starzec, M., Tomlinson, J., Wang, Y., Yum, S. S., Zheng, G., Aiken, A. C., Azevedo, E. B., Blanchard, Y., China, S., Dong, X., Gallo, F., Gao, S., Ghate, V. P., Glienke, S., Goldberger, L., Hardin, J. C., Kuang, C., Luke, E. P., Matthews, A. A., Miller, M. A., Moffet, R., Pekour, M., Schmid, B., Sedlacek, A. J., Shaw, R. A., Shilling, J. E., Sullivan, A., Suski, K., Veghte, D. P., Weber, R., Wyant, M., Yeom, J., Zawadowicz, M., and Zhang, Z.: Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), B. Am. Meteorol. Soc., 103, E619–E641, https://doi.org/10.1175/BAMS-D-19-0220.1, 2022. a
Wang, S., Wang, Q., and Doyle, J.: Some improvement of Louis surface flux parameterization, in: Preprints, 15th Symp. on Boundary Layers and Turbulence, Wageningen, the Netherlands, Amer. Meteor. Soc, 18 July 2002, vol. 13, https://ams.confex.com/ams/BLT/techprogram/paper_44519.htm (last access: 16 September 2025), 2002. a
Wang, S., O'Neill, L. W., Jiang, Q., de Szoeke, S. P., Hong, X., Jin, H., Thompson, W. T., and Zheng, X.: A regional real-time forecast of marine boundary layers during VOCALS-REx, Atmos. Chem. Phys., 11, 421–437, https://doi.org/10.5194/acp-11-421-2011, 2011. a, b, c
Wang, Z., Li, M., Zhang, S., Small, R. J., Lu, L., Yuan, M., Yong, J., Lin, X., and Wu, L.: The Northern Hemisphere Wintertime Storm Track Simulated in the High‐Resolution Community Earth System Model, J. Adv. Model. Earth Sy., 15, e2023MS003652, https://doi.org/10.1029/2023MS003652, 2023. a
Weisman, M. L., Skamarock, W. C., and Klemp, J. B.: The Resolution Dependence of Explicitly Modeled Convective Systems, Mon. Weather Rev., 125, 527–548, https://doi.org/10.1175/1520-0493(1997)125<0527:TRDOEM>2.0.CO;2, 1997. a
Wood, R.: Stratocumulus Clouds, Mon. Weather Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012. a, b
Wood, R., Wyant, M., Bretherton, C. S., Rémillard, J., Kollias, P., Fletcher, J., Stemmler, J., de Szoeke, S., Yuter, S., Miller, M., Mechem, D., Tselioudis, G., Chiu, J. C., Mann, J. A. L., O’Connor, E. J., Hogan, R. J., Dong, X., Miller, M., Ghate, V., Jefferson, A., Min, Q., Minnis, P., Palikonda, R., Albrecht, B., Luke, E., Hannay, C., and Lin, Y.: Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment, B. Am. Meteorol. Soc., 96, 419–440, https://doi.org/10.1175/BAMS-D-13-00180.1, 2015. a, b
Wyant, M. C., Wood, R., Bretherton, C. S., Mechoso, C. R., Bacmeister, J., Balmaseda, M. A., Barrett, B., Codron, F., Earnshaw, P., Fast, J., Hannay, C., Kaiser, J. W., Kitagawa, H., Klein, S. A., Köhler, M., Manganello, J., Pan, H.-L., Sun, F., Wang, S., and Wang, Y.: The PreVOCA experiment: modeling the lower troposphere in the Southeast Pacific, Atmos. Chem. Phys., 10, 4757–4774, https://doi.org/10.5194/acp-10-4757-2010, 2010. a, b, c
Wyant, M. C., Bretherton, C. S., Wood, R., Carmichael, G. R., Clarke, A., Fast, J., George, R., Gustafson Jr., W. I., Hannay, C., Lauer, A., Lin, Y., Morcrette, J.-J., Mulcahy, J., Saide, P. E., Spak, S. N., and Yang, Q.: Global and regional modeling of clouds and aerosols in the marine boundary layer during VOCALS: the VOCA intercomparison, Atmos. Chem. Phys., 15, 153–172, https://doi.org/10.5194/acp-15-153-2015, 2015. a, b, c
Yau, M. K. and Rogers, R. R.: A Short Course in Cloud Physics, Elsevier Science, Saint Louis, 3rd edn., ISBN 978-0-08-057094-5, 1996. a
Zelinka, M. D., Zhou, C., and Klein, S. A.: Insights from a refined decomposition of cloud feedbacks, Geophys. Res. Lett., 43, 9259–9269, https://doi.org/10.1002/2016GL069917, 2016. a
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po‐Chedley, S., Caldwell, P. M., Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of Higher Climate Sensitivity in CMIP6 Models, Geophys. Res. Lett., 47, e2019GL085782, https://doi.org/10.1029/2019GL085782, 2020. a
Zheng, X., Zhang, Y., Klein, S. A., Zhang, M., Zhang, Z., Deng, M., Tian, J., Terai, C. R., Geerts, B., Caldwell, P., and Bogenschutz, P. A.: Using Satellite and ARM Observations to Evaluate Cold Air Outbreak Cloud Transitions in E3SM Global Storm‐Resolving Simulations, Geophys. Res. Lett., 51, e2024GL109175, https://doi.org/10.1029/2024GL109175, 2024. a, b
Zhu, Z., Bartholomew, M. J., Wang, D., and Shi, Y.: Laser Disdrometer (LD), 2014-02-27 to 2025-04-20, Eastern North 100 Atlantic (ENA), Graciosa Island, Azores, Portugal (C1), ARM Data Center [data set], https://doi.org/10.5439/1973058, 2014. a, b
Zuidema, P., Westwater, E. R., Fairall, C., and Hazen, D.: Ship‐based liquid water path estimates in marine stratocumulus, J. Geophys. Res.-Atmos., 110, 2005JD005833, https://doi.org/10.1029/2005JD005833, 2005. a
Short summary
Low-level clouds have important radiative feedbacks and can occur in a range of meteorological conditions, yet our knowledge and prediction of them are insufficient. We evaluate model forecasts of low-level cloud properties across a cold front and the associated environments that they form in. The model represents the meteorological conditions well and produces broken clouds behind the cold front in areas of strong surface forcing, large stability, and large-scale subsiding motion.
Low-level clouds have important radiative feedbacks and can occur in a range of meteorological...
Altmetrics
Final-revised paper
Preprint