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Role of autoconversion process in assessing the low-level clouds over the southern Indian Ocean in Climate Forecast System (CFS) version 2

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Abstract

The sensitivity of a modified realistic critical droplet radius concerning the rain autoconversion process on the simulation of low-level clouds over the southern Indian Ocean (SIO) has been investigated. Two simulations are performed with the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) model, one (CFSCR) with default physically based cloud scheme (WRF single-moment 6-class microphysics scheme (WSM6)) and the other with modified CFSCR (CFSCR-Mod). In CFSCR-Mod, the critical droplet radius as a function of the rain autoconversion process is revised. Keeping in mind the variability of cloud condensation nuclei (CCN) over the land and ocean, the critical droplet radius is put differently over land and ocean. The fidelity of both the models in simulating SIO low-level clouds is evaluated concerning different observational and re-analysis products. Observations exhibit the prominent occurrence of low-level clouds over the SIO in the 30–10°S latitudinal and 80–100°E longitudinal belt. The analysis reveals that CFSCR-Mod has a better fidelity to capturing low-level clouds due to its more realistic autoconversion process and realistic cloud microphysics.

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Availability of data and material

The model outputs used in this study are archived at IITM, Pune, and can be accessed from the corresponding author upon request

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References

  • Abhik S, Krishna RPM, Mahakur M, Ganai M, Mukhopadhyay P, Dudhia J (2017) Revised cloud processes to improve the mean and intraseasonal variability of Indian summer monsoon in climate forecast system: part 1. J Adv Model Earth Syst 3078:1–28

    Google Scholar 

  • Ahlgrimm M, Köhler M (2010) Evaluation of trade cumulus in the ECMWF model with observations from CALIPSO. Mon Weather Rev 138:3071–3083. https://doi.org/10.1175/2010MWR3320.1

    Article  Google Scholar 

  • Andreae MO, Rosenfeld D, Artaxo P, Costa AA, Frank GP, Longo KM, Silva-Dias MAF (2004) Smoking rain clouds over the Amazon. Science. 303:1337–1342

    Article  Google Scholar 

  • Berg W, L’Ecuyer T, van den Heever S (2008) Evidence for the impact of aerosols on the onset and microphysical properties of rainfall from a combination of satellite observations and cloud-resolving model simulations. J Geophys Res 113:D14S23. https://doi.org/10.1029/2007JD009649

    Article  Google Scholar 

  • Bony S, Dufresne JL (2005) Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys Res Lett 32(L20):806. https://doi.org/10.1029/2005GL023,851

    Article  Google Scholar 

  • Bony S, Collins WD, Fillmore DW (2000) Indian Ocean low clouds during winter monsoon. J Clim 13:2,028–2,043

    Article  Google Scholar 

  • Boucher O, Treut HL, Baker MB (1995) Precipitation and radiation modelling in a GCM: Introduction of cloud microphysical processes. J Geophys Res 100(16):395–16,414

    Google Scholar 

  • Boutle IA, Morcrette CJ (2010) Parametrization of area cloud fraction. Atmos Sci Lett 11:283–289. https://doi.org/10.1002/asl.293

    Article  Google Scholar 

  • Bretherton CS, McCaa JR, Grenier H (2004) A new parameterization for shallow cumulus convection and its application to marine subtropical cloud-topped boundary layers. Part II: regional simulations of marine boundary layer clouds. Mon Weather Rev 132:883–896. https://doi.org/10.1175/1520-0493(2004)132<0883:ANPFSC>2.0.CO;2

    Article  Google Scholar 

  • Chen C, Cotton WR (1987) The physics of the marine statocumulus-capped mixed layer. J Atmos Sci 44:2951–2977

  • Chen T, Rossow WB, Zhang YC (2000) Radiative effect of cloud-type variations. J Clim 13:264–286

    Article  Google Scholar 

  • Dai A, Trenberth KE (2004) The diurnal cycle and its depiction in the community climate system model. J Clim 17:930–951

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S et al (2011) The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597. https://doi.org/10.1002/qj.828

  • Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107

    Article  Google Scholar 

  • Golaz JC, Salzmann M, Donner LJ, Horowitz LW, Ming Y, Zhao M (2011) Sensitivity of the aerosol indirect effect to subgrid variability in the cloud parameterization of the GFDL Atmosphere General Circulation Model AM3. J Clim 24:3145–3160. https://doi.org/10.1175/2010JCLI3945.1

    Article  Google Scholar 

  • Griffies SM, Harrison MJ, Pacanowski RC, Rosatia (2004) A technical guide to MOM4. GFDL Ocean Gr Tech Rep 5:371

    Google Scholar 

  • Guo H, Liu Y, Penner JE (2008) Does the threshold representation associated with the autoconversion process matter? Atmos Chem Phys 8:1225–1230

    Article  Google Scholar 

  • Gupta AK, Rajeev K, Sijikumar S (2017) Day-night changes in the altitude distribution, physical properties and radiative impact of low-altitude clouds over the stratocumulus-dominated subtropical oceans. J Atmos Solar Terr Phys 161:118–126. https://doi.org/10.1016/j.jastp.2017.06.021

    Article  Google Scholar 

  • Han J, Pan H-L (2011) Revision of convection and vertical diffusion schemes in the NCEP Global Forecast System. Weather Forecast 26:520–533. https://doi.org/10.1175/WAF-D-10-05038.1

    Article  Google Scholar 

  • Hannay C, Williamson DL, Hack JJ, Kiehl JT, Olson JG, Klein SA, Bretherton CS, Köhler M (2009) Evaluation of forecasted southeast Pacific stratocumulus in the NCAR, GFDL, and ECMWF models. J Clim 22:2871–2889

    Article  Google Scholar 

  • Hanson HP (1991) Marine stratocumulus climatologies. Int J Climatol 11:147–164

    Article  Google Scholar 

  • Hong S, Lim J (2006) The WRF single-moment 6-class microphysics scheme (WSM6). J Korean Meteorol Soc 42:129–151

    Google Scholar 

  • Hong SY, Dudhia J, Chen SH (2004) A revised approach to ice microphysical processes for bulk parameterization of cloud and precipitation. Mon Weather Rev 132:103–120. https://doi.org/10.1175/1520-0493(2004)1322.0.CO;2

    Article  Google Scholar 

  • Jiang X, Waliser DE, Li JL, Woods C (2011) Vertical cloud structures of the boreal summer intraseasonal variability based on CloudSat observations and ERA-interim reanalysis. ClimDyn 36:2219–2232. https://doi.org/10.1007/s00382-010-0853-8

    Article  Google Scholar 

  • Klein SA (1997) Synoptic variability of low-cloud properties and meteorological parameters in the subtropical trade wind boundary layer. J Clim 10:2018–2039.https://doi.org/10.1175/1520-0442(1997)010<2018:SVOLCP>2.0.CO;2

    Article  Google Scholar 

  • Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Clim 6:1587–1606

    Article  Google Scholar 

  • Klein SA, Hartmann DL, Norris JR (1995) On the relationships among low-cloud structure, sea surface temperature, and atmospheric circulation in the summertime northeast Pacific. J Clim 8:1140–1155

    Article  Google Scholar 

  • Kubar TL, Waliser DE, Li JL (2011) Boundary layer and cloud structure controls on tropical low cloud cover using A-Train satellite data and ECMWF analyses. J Clim 24:194–215. https://doi.org/10.1175/2010JCLI3702.1

    Article  Google Scholar 

  • Kubar TL, Waliser DE, Li JL, Jiang X (2012) On the annual cycle, variability, and correlations of oceanic low-topped clouds with large-scale circulation using aqua MODIS and ERA-interim. J Clim 25:6152–6174. https://doi.org/10.1175/JCLI-D-11-00478.1

    Article  Google Scholar 

  • Kulkarni JR et al (2012) Cloud aerosol interaction and precipitation enhancement experiment (CAIPEEX): Overview and preliminary results. Curr Sci 102:413–425

    Google Scholar 

  • L’Ecuyer TS, Berg W, Haynes J, Lebsock M, Takemura T (2009) Global observations of aerosol impacts on precipitation occurrence in warm maritime clouds. J Geophys Res: Atmos 114(D9)

  • Lebsock MD, Stephens GL, Kummerow C (2008) Multisensor satellite observations of aerosol effects on warm clouds. J Geophys Res 113:D15205. https://doi.org/10.1029/2008JD009876

    Article  Google Scholar 

  • Li F, Rosa D, Collins WD, Wehner MF (2012) Superparameterization: A better way to simulate regional extreme precipitation? J Adv Model Earth Syst 4(M04002). https://doi.org/10.1029/2011ms000106

  • Liebmann B, Smith CA (1996) Description of a complete (interpolated) outgoing longwave radiation dataset. Bull Am Meteorol Soc 77:1275–1277

    Google Scholar 

  • Ma CC, Mechoso CR, Robertson AW, Arakawa A (1996) Peruvian stratus clouds and the tropical Pacific circulation: a coupled ocean-atmosphere GCM study. J Clim 9:1635–1645

    Article  Google Scholar 

  • Mace GG, Zhang Q (2014) The CloudSat radar-lidar geometrical profile product (RL-GeoProf): updates, improvements, and selected results. J Geophys Res Atmos 119:9441–9462. https://doi.org/10.1002/2013JD021374

    Article  Google Scholar 

  • Mechoso CR, Robertson AW, Barth N, Davey MK, Delecluse P, Gent PR, Ineson S, Kirtman B, Latif M, Treut HL, Nagai T, Neelin JD, Philander SGH, Polcher J, Schopf PS, Stockdale T, Suarez MJ, Terray L, Thual O, Tribbia JJ (1995) The seasonal cycle over the tropical Pacific in coupled ocean-atmosphere general circulation models. Mon Weather Rev 123:2825–2838

    Article  Google Scholar 

  • Moorthi S, Pan HL, Caplan P (2001) Changes to the 2001 NCEP operational MRF/AVN global analysis/forecast system. NWS Tech Proced Bull 484:14

    Google Scholar 

  • Norris JR, Klein SA (2000) Low cloud type over the ocean from surface observations. Part III: relationship to vertical motion and the regional surface synoptic environment. J Clim 13:245–256. https://doi.org/10.1175/1520-0442(2000)013<0245:LCTOTO>2.0.CO;2

    Article  Google Scholar 

  • Pawlowska H, Brenguier JL (2003) An observational study of drizzle formation in stratocumulus clouds for general circulation model (GCM) parameterizations. J Geophys Res 108(D15):8630. https://doi.org/10.1029/2002JD002679

    Article  Google Scholar 

  • Randall DA, Wood RA, Bony S, et al (2007) Climate models and their evaluation. Clim Chang 2007 Phys Sci Basis Contrib Work Gr I to Fourth Assess Rep Intergov Panel Clim Chang 591–662. https://doi.org/10.1016/j.cub.2007.06.045

  • Rasch PJ, Kristjdnsson JE (1998) A comparison of the CCM3 model climate using diagnosed and predicted condensate parameterizations. J Clim 11:1587–1614

    Article  Google Scholar 

  • Reynolds RW, Smith TM, Liu C, Chelton DB, Casey KS, Schlax MG (2007) Daily high-resolution-blended analyses for sea surface temperature. J Clim 20:5473–5496. https://doi.org/10.1175/2007JCLI1824.1

    Article  Google Scholar 

  • Rosenfeld D (1999) TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall. Geophys Res Lett 26(20):3105–3108

    Article  Google Scholar 

  • Rosenfeld D, Lahav R, Khain A, Pinsky M (2002) The role of sea spray in cleansing air pollution over ocean via cloud processes. Science. 297:1667–1670

    Article  Google Scholar 

  • Rosenfeld D. Zhu Y, Wang M, Zheng Y, Goren T, Yu S (2019) Aerosol-driven droplet concentrations dominate coverage and water of oceanic low level clouds. In: Science https://doi.org/10.1126/science.aav0566

  • Rotstayn LD (1997) A physically based scheme for the treatment of stratiform clouds and precipitation in large-scale models, I, description and evaluation of the microphysical processes. Q J R Meteorol Soc 123:1227–1282

    Google Scholar 

  • Rotstayn LD (1998) A physically based scheme for the treatment of stratiform clouds and precipitation in large-scale models, II, comparison of modelled and observed climatological fields. Q J R Meteorol Soc 124:389–415

    Google Scholar 

  • Rotstayn LD (2000) On the “tuning” of autoconversion parameterizations in climate models. J Geophys Res 105(15):495–15,507

    Google Scholar 

  • Roy K, Mukhopadhyay P, Murali Krishna RP et al (2019) Sensitivity of climate models in relation to the “pool of inhibited cloudiness” over South of the Bay of Bengal. Int J Climatol:1–17. https://doi.org/10.1002/joc.6423

  • Roy K, Mukhopadhyay P, Murali Krishna RP et al (2020) Assessment of climate models in relation to the low-level clouds over the Southern Indian Ocean. Q J R Meteorol Soc 146:3306–3325. https://doi.org/10.1002/qj.3847

    Article  Google Scholar 

  • Rudich Y, Khersonsky O, Rosenfeld D (2002) Treating clouds with a grain of salt. Geophys Res Lett 29:2060–17-4. https://doi.org/10.1029/2002GL016055

    Article  Google Scholar 

  • Rutledge SA, Hobbs PV (1983) The mesoscale and microscale structure and organization of clouds and precipitation in extratropical cyclones: VIII: a model for the seeder-feeder process in warm-frontal rain bands. J Atmos Sci 40:1185–1206. https://doi.org/10.1175/1520-0469(1983)0402.0.CO;2

    Article  Google Scholar 

  • Saha S (2010) The NCEP Climate Forecast System Reanalysis. Bull Am Meteorol Soc 91:1015–1057. https://doi.org/10.1175/2010Bams3001.1

    Article  Google Scholar 

  • Saha S, Coauthors (2006) The NCEP Climate Forecast System. J Climate 19:3483–3517

  • Saha S, Moorthi S, Wu X, Wang J, Nadiga S, Tripp P, Behringer D, Hou YT, Chuang HY, Iredell M, Ek M, Meng J, Yang R, Mendez MP, van den Dool H, Zhang Q, Wang W, Chen M, Becker E (2014) The NCEP climate forecast system version 2. J Clim 27:2185–2208. https://doi.org/10.1175/JCLI-D-12-00823.1

    Article  Google Scholar 

  • Schiffer RA, Rossow WB (1983) The international satellite cloud climatology project (ISCCP): the first project of the world climate research programme. Bull Am Meteorol Soc 64:779–784

    Article  Google Scholar 

  • Slingo JM (1987) The development and verification of a cloud prediction scheme for the ECMWF model. Q J R Meteorol Soc 113:899–927

    Article  Google Scholar 

  • Takahashi H, Suzuki K, Stephens G (2017) Land-ocean differences in the warm rain formation process in satellite observations, ground-based observations, and model simulations. Q J R Meteorol Soc 143:1804–1815. https://doi.org/10.1002/qj.3042

    Article  Google Scholar 

  • Wilson DR, Ballard SP (1999) A microphysically based precipitation scheme for the UK Meteorological Office Unified Model. Q J R Meteorol Soc 125:1607–1636

    Article  Google Scholar 

  • Wood R (2012) Stratocumulus clouds. Mon Weather Rev 140:2373–2423. https://doi.org/10.1175/MWR-D-11-00121.1

    Article  Google Scholar 

  • Wood R, Bretherton CS (2006) On the relationship between stratiform low cloud cover and lower-tropospheric stability. J Clim 19:6425–6432. https://doi.org/10.1175/JCLI3988.1

    Article  Google Scholar 

  • Wood R, Hartmann DL (2006) Spatial variability of liquid water path in marine boundary layer clouds: The importance of mesoscale cellular convection. J Climate 19:1748–1764

  • Xie SP, Miyama T, Wang Y, Xu H, de Szoeke SP, Small RJO, Richards KJ, Mochizuki T, Awaji T (2007) A regional ocean–atmosphere model for eastern Pacific climate: toward reducing tropical biases. J Clim 20:1504–1522

    Article  Google Scholar 

  • Yoo H, Li Z, Hou YT, Lord S, Weng F, Barker HW (2013) Diagnosis and testing of low-level cloud parameterizations for the NCEP/GFS model using satellite and ground-based measurements. Clim Dyn 2013(41):1595–1613. https://doi.org/10.1007/s00382-013-1884-8

    Article  Google Scholar 

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Acknowledgements

CloudSat-CALIPSO merged data sets were obtained from the CloudSat Data Processing Center through its website (www.cloudsat.cira.colostate.edu). We acknowledge ECMWF for providing ERA-interim data sets (http://apps.ecmwf.int/datasets/data/interim-fulldaily/levtype=sfc/). Authors thank the Director, IITM, Pune, for his motivation and encouragement. We would like to sincerely thank the anonymous reviewer and the editor for their valuable comments that helped greatly to improve the manuscript. This study is a part of Ph.D. thesis of Kumar Roy.

Funding

Indian Institute of Tropical Meteorology, Pune, is fully funded by the Ministry of Earth Sciences, Government of India.

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Authors and Affiliations

  1. Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Dr. Homi Bhabha Road, Pashan, Pune, 411008, India

    Kumar Roy, Parthasarathi Mukhopadhyay & R. Phani Murali Krishna

  2. Department of Meteorology and Oceanography, College of Science and Technology, Andhra University, Visakhapatnam, Andhra Pradesh, 530003, India

    Kumar Roy & S. S. V. S. Ramakrishna

  3. Meteorology Facility, TERLS, Vikram Sarabhai Space Centre, ISRO, Thiruvananthapuram, Kerala, 695022, India

    Anish Kumar M. Nair

  4. Department of Space, National Atmospheric Research Laboratory, Gadanki, Andhra Pradesh, 517112, India

    T. Narayana Rao

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Contributions

Conceptualization: Parthasarathi Mukhopadhyay

Model setup and methodology: R Phani, Kumar Roy, Parthasarathi Mukhopadhyay

Formal analyses and investigation: Kumar Roy, Parthasarathi Mukhopadhyay

Writing-original draft preparation: Kumar Roy, Parthasarathi Mukhopadhyay

Writing—review and editing: Anish Kumar M. Nair, T Narayana Rao, SSVS Ramakrishna

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Correspondence to Parthasarathi Mukhopadhyay.

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Roy, K., Mukhopadhyay, P., Krishna, R.P.M. et al. Role of autoconversion process in assessing the low-level clouds over the southern Indian Ocean in Climate Forecast System (CFS) version 2. Theor Appl Climatol 145, 273–284 (2021). https://doi.org/10.1007/s00704-021-03630-z

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