Connections between sub-cloud coherent updrafts and the life cycle of maritime shallow cumulus clouds in large eddy simulation

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Albright, A. L., Bony, S., Stevens, B., & Vogel, R. (2022). Observed subcloud-layer 572 moisture and heat budgets in the trades. Journal of the Atmospheric Sciences, 573 79 , 2363–2385. doi: https://doi.org/10.1175/JAS-D-21-0337.1 574 Angevine, W. M., Olson, J., Gristey, J. J., Glenn, I., Feingold, G., & Turner, D. D. 575 (2020). Scale awareness, resolved circulations, and practical limits in the 576 mynn-edmf boundary layer and shallow cumulus scheme. Monthly Weather 577 Review, 148 , 4629–4639. doi: https://doi.org/10.1175/MWR-D-20-0066.1 578 Betts, A. K. (1973). Non-precipitating cumulus convection and its parameteriza579 tion. Quart. J. Roy. Soc. Meteor., 99 , 178-196. doi: https://doi.org/10.1002/ 580 qj.49709941915 581 Blyth, A. M., Lasher-Trapp, S. G., & Cooper, W. A. (2005). A study of thermals in 582 cumulus clouds. Quart. J. Roy. Meteor. Soc., 131 , 1171-1190. doi: https://doi 583 .org/10.1256/qj.03.180 584 Bony, S., & Dufresne, J.-L. (2005). Marine boundary layer clouds at the heart of 585 tropical cloud feedback uncertainties in climate models. Geophys. Res. Lett , 586 32 , L20806. doi: 10.1029/2005GL023851 587 Brient, F., Schneider, T., Tan, Z., Bony, S., Qiu, X., & Hall, A. (2016). Shallowness 588 of tropical low clouds as a predictor of climate models’ response to warming. 589 Clim. Dyn., 47 , 433-449. doi: https://doi.org/10.1007/s00382-015-2846-0 590 Brown, A. R., Cederwall, R. T., Chlond, A., Duynkerke, P. G., Golaz, J.-C., 591 Khairoutdinov, M., . . . Stevens, B. (2002). Large-eddy simulation of the 592 diurnal cycle of shallow cumulus convection over land. Quarterly Journal 593 of the Royal Meteorological Society, 128 , 1075-1093. doi: https://doi.org/ 594 10.1256/003590002320373210 595 Brown, N., Lepper, A., Weiland, M., Hill, A., & Shipway, B. (2018). In situ data 596 analytics for highly scalable cloud modelling on cray machines. Concurr. Com597 put. Pract. Exp., 30 , e4331. doi: https://doi.org/10.1256/qj.04.101 598 Brown, N., Lepper, A., Weiland, M., Hill, A., Shipway, B., Maynard, C., . . . Rezny, 599 M. (2015). A highly scalable Met Office NERC Cloud model. In Proceedings of 600 the 3rd International Conference on Exascale Applications and Software-EASC 601 2015. Edinburgh, UK, April 2015 , 132-137. 602 Chen, J., Hagos, S., Feng, Z., Fast, J. D., & Xiao, H. (2023). The role of cloud-cloud 603 interaction in the life cycle of shallow cumulus clouds. J. Atmos. Sci., 80 , 671– 604 686. doi: https://doi.org/10.1175/JAS-D-22-0004.1 605 Chen, S. S., & Houze Jr, R. A. (1997). Diurnal variation and life-cycle deep convec606 tive systems over the tropical pacific warm pool. Quart. J. Roy. Meteor. Soc., 607 123 , 357-388. doi: https://doi.org/10.1002/qj.49712353806 608 Cho, H.-R. (1977). Contributions of cumulus cloud life-cycle effects to the large609 scale heat and moisture budget equations. Journal of the Atmospheric Sci610 ences, 34 , 87-97. doi: https://doi.org/10.1175/1520-0469(1977)034⟨0087: 611 COCCLC⟩2.0.CO;2 –21– manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES) 612 Couvreux, F., Hourdin, F., & Rio, C. (2010). Resolved versus parameterized 613 boundary-layer plumes. part i: A parameterization-oriented conditional sam614 pling in large-eddy simulations. Boundary-Layer Meteorol., 134 , 441–458. doi: 615 https://doi.org/10.1007/s10546-009-9456-5 616 Dawe, J. T., & Austin, P. H. (2012). Statistical analysis of an les shallow cumu617 lus cloud ensemble using a cloud tracking algorithm. Atmos. Chem. Phys., 12 , 618 1101–1119. doi: https://doi.org/10.5194/acp-12-1101-2012 619 Denby, L., Bo¨ing, S. J., Parker, D. J., Ross, A. N., & Tobias, S. M. (2022). Char620 acterising the shape, size, and orientation of cloud-feeding coherent boundary621 layer structures. Quarterly Journal of the Royal Meteorological Society, 148 , 622 499-519. doi: https://doi.org/10.1002/qj.4217 623 Endo, S., Zhang, D., Vogelmann, A. M., Kollias, P., Lamer, K., Oue, M., . . . 624 Romps, D. M. (2019). Reconciling differences between large-eddy simula625 tions and doppler lidar observations of continental shallow cumulus cloud626 base vertical velocity. Geophysical Research Letters, 11539-11547. doi: 627 https://doi.org/10.1029/2019GL084893 628 Fletcher, J. K., & Bretherton, C. S. (2010). Evaluating boundary layer-based mass 629 flux closures using cloud-resolving model simulations of deep convection. Jour630 nal of the Atmospheric Sciences, 67 , 2212-2225. doi: https://doi.org/10.1175/ 631 2010jas3328.1 632 Golaz, J.-C., Larson, V. E., & Cotton, W. R. (2002). A pdf-based model for 633 boundary layer clouds. part I: Method and model description. J. Atmos. 634 Sci., 59 , 3540–3551. doi: https://doi.org/10.1175/1520-0469(2002)059⟨3540: 635 APBMFB⟩2.0.CO;2 636 Grant, A. L. M. (2006). The cumulus-capped boundary layer. II: Interface fluxes. 637 Quart. J. Roy. Meteor. Soc., 132 , 1405–1422. doi: https://doi.org/10.1256/qj 638 .04.170 639 Gregory, D., & Rowntree, P. R. (1990). A mass flux convection scheme with 640 representation of cloud ensemble characteristics and stability-dependent 641 closure. Monthly Weather Review, 118 (7), 1483-1506. doi: 10.1175/ 642 1520-0493(1990)118⟨1483:AMFCSW⟩2.0.CO;2 643 Griewank, P. J., Heus, T., Lareau, N. P., & Neggers, R. A. J. (2020). Size depen644 dence in chord characteristics from simulated and observed continental shallow 645 cumulus. Atmospheric Chemistry and Physics, 20 (17), 10211–10230. Re646 trieved from https://acp.copernicus.org/articles/20/10211/2020/ doi: 647 10.5194/acp-20-10211-2020 648 Griewank, P. J., Heus, T., & Neggers, R. A. J. (2022). Size-dependent charac649 teristics of surface-rooted three-dimensional convective objects in continental 650 shallow cumulus simulations. Journal of Advances in Modeling Earth Systems, 651 14 , 2021MS002612. doi: https://doi.org/10.1029/2021MS002612 652 Gu, J.-F., Plant, R. S., & Holloway, C. E. (2023). Moist halo region of shallow 653 cumulus clouds in large eddy simulations. Quart. J. Roy. Soc. Meteor., 149 , 654 e2020GL090460. doi: submitted 655 Gu, J.-F., Plant, R. S., & Holloway, C. E. (2024). Connections between sub-cloud 656 coherent structures and the life cycle of maritime shallow cumulus clouds in 657 large eddy simulation. , [Dataset] Zenodo. doi: https://zenodo.org/record/ 658 8300016 659 Gu, J.-F., Plant, R. S., Holloway, C. E., & Muetzelfeldt, M. (2020). Pressure drag 660 for shallow cumulus clouds: from thermals to the cloud ensemble. Geophys. 661 Res. Lett , 47 , e2020GL090460. doi: https://doi.org/10.1029/2020GL090460 662 Heus, T., Jonker, H. J. J., den Akker, H. E. A. V., Griffith, E. J., Koutek, M., 663 & Post, F. H. (2009). A statistical approach to the life cycle analysis of 664 cumulus clouds selected in a virtual reality environment. Journal of Geo665 physical Research: Atmospheres, 114 , D06208. doi: https://doi.org/10.1029/ 666 2008JD010917 –22– manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES) 667 Heus, T., & Seifert, A. (2013). Automated tracking of shallow cumulus clouds in 668 large domain. Geosci. Model Dev., 6 , 1261–1273. doi: https://doi.org/10.5194/ 669 gmd-6-1261-2013 670 Jiang, H., Xue, H., Teller, A., Feingold, G., & Levin, Z. (2006). Aerosol effects 671 on the lifetime of shallow cumulus. Geophysical Research Letters, 33 . doi: 672 https://doi.org/10.1029/2006GL026024 673 Kain, J. S. (2004). The kain-fritsch convective parameterization: An update. Jour674 nal of Applied Meteorology and Climatology, 43 , 170-181. doi: https://doi.org/ 675 10.1175/1520-0450(2004)043⟨0170:TKCPAU⟩2.0.CO;2 676 Kairoutdinov, M. F., & Randall, D. A. (2002). Similarity of deep continen677 tal cumulus convection as revealed by a three-dimensional cloud-resolving 678 model. J. Atmos. Sci., 59 , 2550-2566. doi: https://doi.org/10.1175/ 679 1520-0469(2002)059⟨2550:SODCCC⟩2.0.CO;2 680 Kuang, Z., & Bretherton, C. S. (2006). A mass-flux scheme view of a hgih-resolution 681 simulation of a transition from shallow to deep cumulus convection. J. Atmos. 682 Sci., 63 , 1895-1909. doi: https://doi.org/10.1175/JAS3723.1 683 Lareau, N. P., Zheng, Y., & Klein, S. A. (2018). Observed boundary layer controls 684 on shallow cumulus at the arm southern great plains site. Journal of the Atmo685 spheric Sciences, 75 (7), 2235–2255. 686 Larson, V. E. (2017). Clubb-silhs: A parameterization of subgrid variability in the 687 atmosphere. arXiv. doi: 1711.03675v3 688 Larson, V. E., & Golaz, J.-C. (2005). Using probability density functions to derive 689 consistent closure relationships among higher-order moments. Mon. Wea. Rev., 690 133 , 1023–1042. doi: https://doi.org/10.1175/MWR2902.1 691 Larson, V. E., Golaz, J.-C., & Cotton, W. R. (2002). Small-scale and mesoscale 692 variability of scalars in cloudy boundary layers: Joint probability density 693 functions. J. Atmos. Sci., 59 , 3519–3539. doi: https://doi.org/10.1175/ 694 1520-0469(2002)059⟨3519:SSAMVI⟩2.0.CO;2 695 LeMone, M. A., Angevine, W. M., Bretherton, C. S., Chen, F., Dudhia, J., Fe696 dorovich, E., . . . Weil, J. (2019). 100 years of progress in boundary layer 697 meteorology. Meteorological Monographs, 59 , 9.1–9.85. doi: https://doi.org/ 698 10.1175/AMSMONOGRAPHS-D-18-0013.1 699 LeMone, M. A., & Pennell, W. T. (1976). The relationship of trade wind cumulus 700 distribution to subcloud layer fluxes and structure. Monthly Weather Re701 view, 104 , 524–539. doi: https://doi.org/10.1175/1520-0493(1976)104⟨0524: 702 TROTWC⟩2.0.CO;2 703 Lilly, D. K. (1962). On the numerical simulation of buoyant convection. Tellus, 14 , 704 2153–3490. doi: http://dx.doi.org/10.1111/j.2153-3490.1962.tb00128.x 705 Maason-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., P´ean, C., Berger, S., . . . 706 Zhou(eds.), B. (2021). Ipcc, 2021: Climate change 2021: The physical science 707 basis. Cambridge University Press, Cambridge, United Kingdom and New 708 York, NY, USA. doi: https://doi.org/10.1017/9781009157896 709 Muetzelfeldt, M. (2020). Designs for representing shear-induced cloud field organiza710 tion in a convection parametrization scheme. PhD thesis, 245pp. (Department 711 of Meteorology, University of Reading) 712 Neggers, R. A. J. (2015). Exploring bin-macrophysics models for moist convective 713 transport and clouds. Journal of Advances in Modeling Earth Systems, 7 (4), 714 2079-2104. doi: https://doi.org/10.1002/2015MS000502 715 Neggers, R. A. J., & Griewank, P. J. (2021). A binomial stochastic framework for 716 efficiently modeling discrete statistics of convective populations. Journal of Ad717 vances in Modeling Earth Systems, 13 , e2020MS002229. doi: https://doi.org/ 718 10.1029/2020MS002229 719 Neggers, R. A. J., & Griewank, P. J. (2022). A decentralized approach for model720 ing organized convection based on thermal populations on microgrids. Journal 721 of Advances in Modeling Earth Systems, 14 , e2022MS003042. doi: https://doi –23– manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES) 722 .org/10.1029/2022MS003042 723 Neggers, R. A. J., Jonker, H. J. J., & Siebesma, A. P. (2003). Size statistics of cu724 mulus cloud populations in large-eddy simulations. Journal of the Atmospheric 725 Sciences, 60 , 1060-1074. doi: https://doi.org/10.1175/1520-0469(2003)60⟨1060: 726 SSOCCP⟩2.0.CO;2 727 Neggers, R. A. J., Stevens, B., & Neelin, J. D. (2006). A simple equilibrium model 728 for shallow-cumulus-topped mixed layers. Theoretical and Computational Fluid 729 Dynamics, 20 (5-6), 305-322. 730 Nicholls, S., & LeMone, M. A. (1980). The fair weather boundary layer in gate: The 731 relationship of subcloud fluxes and structure to the distribution and enhance732 ment of cumulus clouds. Journal of the Atmospheric Sciences, 37 , 2051–2067. 733 doi: https://doi.org/10.1175/1520-0469(1980)037⟨2051:TFWBLI⟩2.0.CO;2 734 O¨ ktem, R., Prabhat, Lee, J., Thomas, A., Zuidema, P., & Romps, D. M. (2014). 735 Stereo photogrammetry of oceanic clouds. Journal of Atmospheric and Oceanic 736 Technology, 41 (7), 1482–1502. 737 Olson, J. B., Kenyon, J. S., Angevine, W. M., Brown, J. M., Pagowski, M., & Suselj, 738 K. (2019). A description of the mynn–edmf scheme and coupling to other 739 components in wrf-arw. NOAA Tech. Memo., OAR GSD-61 , 42 pp. 740 Plant, R. S. (2009). Statistical properties of cloud lifecycles in cloud-resolving mod741 els. Atmos. Chem. Phys., 9 , 2195–2205. doi: https://doi.org/10.5194/acp-9 742 -2195-2009 743 Rio, C., & Hourdin, F. (2008). A thermal plume model for the convective boundary 744 layer: Representation of cumulus clouds. Journal of the Atmospheric Sciences, 745 65 , 407–425. doi: https://doi.org/10.1175/2007JAS2256.1 746 Romps, D. M., & O¨ ktem, R. (2018, December). Observing clouds in 4d with mul747 tiview stereophotogrammetry. Bulletin of the American Meteorological Society, 748 99 (12), 2575–2586. 749 Romps, D. M., O¨ ktem, R., Endo, S., & Vogelmann, A. M. (2021, September). On 750 the lifecycle of a shallow cumulus cloud: Is it a bubble or plume, active or 751 forced? Journal of the Atmospheric Sciences, 78 (9), 2823–2833. 752 Sakradzija, M., & Klocke, D. (2018). Physically constrained stochastic shallow 753 convection in realistic kilometer-scale simulations. Journal of Advances in 754 Modeling Earth Systems, 10 (11), 2755-2776. doi: https://doi.org/10.1029/ 755 2018MS001358 756 Sakradzija, M., Seifert, A., & Heus, T. (2015). Fluctuations in a quasi-stationary 757 shallow cumulus cloud ensemble. Nonlin. Processes Geophys., 22 , 65-85. doi: 758 https://doi.org/10.5194/npg-22-65-2015 759 Scorer, R. S., & Ludlam, F. H. (1953). Bubble theory of penetrative convection. 760 Quart. J. Roy. Meteor. Soc., 79 , 94-103. doi: https://doi.org/10.1002/ 761 qj.49707933908 762 Seelig, T., Deneke, H., Quaas, J., & Tesche, M. (2021). Life cycle of shallow marine 763 cumulus clouds from geostationary satellite observations. Journal of Geophysi764 cal Research: Atmospheres, 126 , e2021JD035577. doi: https://doi.org/10.1029/ 765 2021JD035577 766 Sherwood, S., Bony, S., & Dufresne, J.-L. (2014). Spread in model climate sensitiv767 ity traced to atmospheric convective mixing. Nature, 505 , 31-42. doi: https:// 768 doi.org/10.1038/nature12829 769 Siebesma, A. P., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J., Duynkerke, 770 P. G., . . . Stevens, A. E. (2003). A large eddy simulation intercomparison 771 study of shallow cumulus convection. J. Atmos. Sci., 60 , 1201–1219. doi: 772 https://doi.org/10.1175/1520-0469(2003)60,1201:ALESIS.2.0.CO;2 773 Siebesma, A. P., & Cuijpers, J. W. M. (1995). Evaluation of parametric assumptions 774 for shallow cumulus convection. Journal of the Atmospheric Sciences, 52 , 650- 775 666. doi: https://doi.org/10.1175/1520-0469(1995)052⟨0650:EOPAFS⟩2.0.CO; 776 2 –24– manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES) 777 Siebesma, A. P., & Jonker, H. J. J. (2000). Anomalous scaling of cumulus cloud 778 boundaries. Phys. Rev. Lett., 85 , 214–217. doi: 10.1103/PhysRevLett.85.214 779 Siebesma, A. P., Soares, P. M. M., & Teixeira, J. (2007). A combined eddy780 diffusivity mass-flux approach for the convective boundary layer. J. Atmos. 781 Sci., 64 , 1230–1248. doi: https://doi.org/10.1175/JAS3888.1 782 Smagorinsky, J. (1963). General circulation experiments with the primitive equation: 783 I. the basic experiment. Mon. Wea. Rev., 91 , 99-164. doi: https://doi.org/10 784 .1175/1520-0493(1963)091⟨0099:GCEWTP⟩2.3.CO;2 785 Soares, P. M. M., Miranda, P. M. A., Siebesma, A. P., & Teixeira, J. (2004). 786 An eddy-diffusivity/mass-flux parameterization for dry and shallow cu787 mulus convection. Quart. J. Roy. Meteor. Soc., 130 , 3365–3384. doi: 788 https://doi.org/10.1256/qj.03.223 789 Stein, T. H. M., Hogan, R. J., Hanley, K. E., Nicol, J. C., Lean, H. W., Plant, R. S., 790 . . . Halliwell, C. E. (2014). The three-dimensional morphology of simulated 791 and observed convective storms over southern england. Mon. Wea. Rev., 142 , 792 3264–3283. doi: https://doi.org/10.1175/MWR-D-13-00372.1 793 Stevens, B. (2006). Bulk boundary-layer concepts for simplified models of tropical 794 dynamics. Theoretical and Computational Fluid Dynamics, 20 (5-6), 279-304. 795 Suselj, K., Kurowski, M. J., & Teixeira, J. (2019). A unified eddy-diffusivity/mass796 flux approach for modeling atmospheric convection. J. Atmos. Sci., 76 , 2505– 797 2537. doi: https://doi.org/10.1175/JAS-D-18-0239.1 798 Suselj, K., Teixeira, J., & Metheou, G. (2012). Eddy diffusivity/mass flux and shal799 low cumulus boundary layer: An updraft pdf multiple mass flux scheme. J. At800 mos. Sci., 69 , 1513–1533. doi: https://doi.org/10.1175/JAS-D-11-090.1 801 Tan, Z., Kaul, C. M., Pressel, K. G., Cohen, Y., Schneider, T., & Teixeira, J. (2018). 802 An extended eddy-diffusivity mass-flux scheme for unified representation of 803 subgrid-scale turbulence and convection. J. Adv. Model. Earth Syst., 10 , 804 770–800. doi: https://doi.org/10.1002/2017MS001162 805 van Stratum, B. J. H., de Arellano, J. V., van Heervaarden, C. C., & Ouwersloot, 806 H. G. (2014). Subcloud-layer feedbacks driven by the mass flux of shallow cu807 mulus convection over land. Journal of the Atmospheric Sciences, 71 , 881–895. 808 doi: https://doi.org/10.1175/JAS-D-13-0192.1 809 vanZanten, M. C., Stevens, B., Nuijens, L., Siebesma, A. P., Ackerman, A. S., 810 Burnet, F., . . . Wyszogrodzki, A. (2011). Controls on precipitation 811 and cloudiness in simulations of trade-wind cumulus as observed during 812 rico. Journal of Advances in Modeling Earth Systems, 3 , M06001. doi: 813 https://doi.org/10.1029/2011MS000056 814 Vial, J., Bony, S., Dufresne, J.-L., & Roehrig, R. (2016). Coupling between lower815 tropospheric convective mixing and low-level clouds: Physical mechanisms and 816 dependence on convection scheme. J. Adv. Model. Earth Syst., 8 , 1892-1911. 817 doi: 10.1002/2016MS000740 818 Vial, J., Bony, S., Stevens, B., & Vogel, R. (2017). Mechanisms and model diversity 819 of trade-wind shallow cumulus cloud feedbacks: A review. Surv. Geophys., 38 , 820 1331-1353. doi: https://doi.org/10.1007/s10712-017-9418-2 821 Vial, J., Dufresne, J.-L., & Bony, S. (2013). On the interpretation of inter-model 822 spread in cmip5 climate sensitivity estimates. Clim. Dyn., 41 , 3339-3362. doi: 823 https://doi.org/10.1007/s00382-013-1725-9 824 Wang, Y., Cheng, X., Fei, J., & Zhou, B. (2022). Modeling the shallow cumulus825 topped boundary layer at gray zone resolutions. Journal of the Atmospheric 826 Sciences, 79 , 2435–2451. doi: https://doi.org/10.1175/JAS-D-21-0339.1 827 Williams, A. G., Zahorowski, W., Chambers, S., Griffiths, A., Hacker, J. M., Ele828 ment, A., & Werczynski, S. (2011). The vertical distribution of radon in clear 829 and cloudy daytime terrestrial boundary layers. Journal of the Atmospheric 830 Sciences, 68 , 155–174. doi: https://doi.org/10.1175/2010JAS3576.1 831 Xie, S., Zhang, M., Boyle, J. S., Cederwall, R. T., Potter, G. L., & Lin, W. (2004). –25– manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES) 832 Impact of a revised convective triggering mechanism on Community Atmo833 sphere Model, Version 2, simulations: Results from short-range weather fore834 casts. J. Geophys. Res., 109 (D14). doi: 10.1029/2004JD004692 835 Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M., 836 Ceppi, P., . . . Taylor, K. E. (2020). Causes of higher climate sensi837 tivity in cmip6 models. Geophys. Res. Lett , 47 , e2019GL085782. doi: 838 https://doi.org/10.1029/2019GL085782 839 Zhang, Y., Klein, S. A., Fan, J., Chandra, A. S., Kollias, P., Xie, S., & Tang, 840 S. (2017). Large-eddy simulation of shallow cumulus over land: A com841 posite case based on arm long-term observations at its southern great 842 plains site. Journal of the Atmospheric Sciences, 74 , 3229–3251. doi: 843 https://doi.org/10.1175/JAS-D-16-0317.1 844 Zhao, M., & Austin, P. H. (2005a). Life cycle of numerically simulated shallow cu845 mulus clouds. part II: Mixing dynamics. Journal of the Atmospheric Sciences, 846 62 , 1291-1310. doi: https://doi.org/10.1175/JAS3415.1 847 Zhao, M., & Austin, P. H. (2005b). Life cycle of numerically simulated shallow 848 cumulus clouds. part I: Transport. Journal of the Atmospheric Sciences, 62 , 849 1269-1290. doi: https://doi.org/10.1175/JAS3414.1 850 Zheng, Y. (2019). Theoretical understanding of the linear relationship between 851 convective updrafts and cloud-base height for shallow cumulus clouds. part I: 852 Maritime conditions. Journal of the Atmospheric Sciences, 76 , 2539-2558. doi: 853 https://doi.org/10.1175/JAS-D-18-0323.1 854 Zheng, Y., Rosenfeld, D., & Li, Z. (2021). Sub-cloud turbulence explains cloud-base 855 updrafts for shallow cumulus ensembles: first observational evidence. Geophys. 856 Res. Lett , 48 , e2020GL091881. doi: https://doi.org/10.1029/2020GL091881 –