Skip to main content

Advertisement

Log in

Role of convective and microphysical processes on the simulation of monsoon intraseasonal oscillation

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

The study explores the role of ice-phase microphysics and convection for the better simulation of Indian summer monsoon rainfall (ISMR) and monsoon intraseasonal oscillation (MISO). Sensitivity experiments have been performed with coupled climate model- CFSv2 using different microphysics (with and without ice phase processes) and convective [Simple Arakawa Schubert (SAS), new SAS (NSAS)] parameterization schemes. Results reveal that the ice phase microphysics parameterization scheme performs better in the simulation of active and break composites of the ISMR as compared to ice-free runs. The difference between ice (ICE) and ice-free run (NOICE) can be attributed to the availability of copious cloud condensate at the upper level. Better representation of upper-level cloud condensate in ICE run (i.e., with ice phase microphysics) leads to correct representation of specific humidity in active and break spells. Proper depiction of upper-level cloud condensate further leads to realistic modulation of atmospheric circulation and better simulation of convection (as represented by OLR) in active and break spells of ICE run. As a result, better simulation of active and break occurs in the ICE run. In contrast, NOICE run (i.e., with warm phase microphysics) fails to depict upper-level cloud condensate in the active phase. It leads to an improper representation of specific humidity. Circulation features are also unrealistic, and convection is suppressed in the active phase. As a result, the active phase is not adequately simulated in the NOICE run. NOICE run composites during active spells depict the overestimation of the ascending branch of Hadley circulation as compared to MERRA reanalysis, which is relatively better in ICE run. NOICE run composites during active spells depict the overestimation of the ascending branch of Walker circulation as compared to MERRA reanalysis, which is further improved in ICE runs. The north–south space–time spectra of daily rainfall anomaly are also better captured by ICE run as compared to NOICE run. Results indicate that ice-phase processes are more important for capturing the difference between active and break composites, while convection parameterization is relatively more important for the intraseasonal variance analyses. Further improvements in ice microphysics parameterization with better convection schemes in models will be helpful for the betterment of MISO and will lead to the improved simulation of monsoon.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  • Abhik S, Mukhopadhyay P, Goswami BN (2014) Evaluation of mean and intraseasonal variability of Indian summer monsoon simulation in ECHAM5: identification of possible source of bias. Clim Dyn 43:389–406

    Google Scholar 

  • Abhik S, Krishna RPM, Mahakur M, GanaiM MP, 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 Mod Earth Syst 9:1002–1029

    Google Scholar 

  • Abhilash S, Sahai AK, Pattnaik S, Goswami BN, Kumar A (2014) Extended range prediction of active-break spells of Indian summer monsoon rainfall using an ensemble prediction system in NCEP climate forecast system. Int J Climatol 34:98–113. https://doi.org/10.1002/joc.3668

    Article  Google Scholar 

  • Abish B, Joseph PV, Johannessen OM (2013) Weakening trend of the tropical easterly jet stream of the Boreal Summer Monsoon Season 1950–2009. J Clim 26:9408–9414. https://doi.org/10.1175/jcli-d-13-00440.1

    Article  Google Scholar 

  • Adler RF, Huffman GJ, Chang A et al (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–Present). J Hydrometeorol 4:1147–1167

    Google Scholar 

  • Annamalai H, Slingo JM (2001) Active/break cycles: diagnosis of the intraseasonal variability of the Asian Summer Monsoon. Clim Dyn 18:85–102. https://doi.org/10.1007/s003820100161

    Article  Google Scholar 

  • Anthes RA (1977) A cumulus parameterization scheme utilizing a one-dimensional cloud model. Mon Weather Rev 105:270–286. https://doi.org/10.1175/1520-0493(1977)

    Article  Google Scholar 

  • Arakawa A, Schubert WH (1974) Interaction of a cumulus cloud ensemble with the large-scale environment, part I. J Atmos Sci 31:674–701

    Google Scholar 

  • Baisya H, Pattnaik S, Hazra V, Sisodiya A, Rai D (2018) Ramifications of atmospheric humidity on monsoon depressions over the Indian subcontinent. Sci Rep. https://doi.org/10.1038/s41598-018-28365-2

    Article  Google Scholar 

  • Bergeron T (1935) On the physics of clouds and precipitation. ProcesVerbaux de l’Association de Météorologie. International Union of Geodesy and Geophysics, Brussles, pp 156–178

    Google Scholar 

  • Betts A, Miller M (1986) A new convective adjustment scheme, Part II: single column tests using GATE wave, BOMEX, ATEX and arctic air-mass data sets. Q J R Meteorol Soc 112:693–709. https://doi.org/10.1256/smsqj.47307

    Article  Google Scholar 

  • Bombardi RJ, Schneider EK, Marx L, Halder S, Singh B, Tawfik AB, Dirmeyer PA, Kinter JL (2015) Improvements in the representation of the Indian summer monsoon in the NCEP climate forecast system version 2. Clim Dyn 45:2485–2498

    Google Scholar 

  • Bony S, Stevens B, Jakob DM et al (2015) Clouds, circulation and climate sensitivity. Nat Geosci 8:261–268. https://doi.org/10.1038/ngeo2398

    Article  Google Scholar 

  • Boyle JS, Klein SA, Lucas DD et al (2015) The parametric sensitivity of CAM5s MJO. J Geophys Res Atmos 120:1424–1444

    Google Scholar 

  • Cess RD (1989) Gauging water-vapour feedback. Nature 342:736–737

    Google Scholar 

  • Chakraborty A, Nanjundiah RS (2014) Role of orography in modulating space–time scales of convection over South Asia. Theoret Appl Climatol 116:549–564. https://doi.org/10.1007/s00704-013-0963-4

    Article  Google Scholar 

  • Chatterjee P, Goswami BN (2004) Structure, genesis and scale selection of the tropical quasi-biweekly mode. Q J R Meteorol Soc 130:1171–1194

    Google Scholar 

  • Chaudhari HS, Shinde M, Oh J (2010) Understanding of anomalous Indian Summer Monsoon rainfall of 2002 and 1994. Q Int 213:20–32

    Google Scholar 

  • Chaudhari HS, Pokhrel S, MohantyS SSK (2013) Seasonal prediction of Indian summer monsoon in NCEP coupled and uncoupled model. Theor App Climatol 114:459–477

    Google Scholar 

  • Chaudhari HS, Hazra A, Saha SK, Dhakate A, Pokhrel S (2016a) Indian summer monsoon simulations with CFSv2: a microphysics perspective. Theor App Climatol 125:253–269

    Google Scholar 

  • Chaudhari HS, Pokhrel S, Rahman H, Dhakate A, Saha SK, Pentakota S, Gairola RM (2016b) Influence of upper ocean on Indian summer monsoon rainfall: studies by observation and NCEP climate forecast system (CFSv2). Theor App Climatol 125:413–426

    Google Scholar 

  • Chaudhari HS, Hazra A, Pokhrel S, Saha SK, Talluri SS (2018) Simulation of extreme Indian summer monsoon years in coupled model intercomparison project phase 5 models: role of cloud processes. Int J Climatol 39:901–920. https://doi.org/10.1002/joc.5851

    Article  Google Scholar 

  • Choudhury AD, Krishnan R (2011) Dynamical response of the South Asian monsoon trough to latent heating from stratiform and convective precipitation. J Atmos Sci 68:1347–1363. https://doi.org/10.1175/2011jas3705.1

    Article  Google Scholar 

  • Clough S, Shephard M, Mlawer E et al (2005) Atmospheric radiative transfer modeling: a summary of the AER codes. J Quant Spectrosc Radiat Transfer 91:233–244. https://doi.org/10.1016/j.jqsrt.2004.05.058

    Article  Google Scholar 

  • De S, Hazra A, Chaudhari HS (2016) Does the modification in “critical relative humidity” of NCEP CFSv2 dictate Indian mean summer monsoon forecast? Evaluation through thermodynamical and dynamical aspects. Clim Dyn 46:1197–1222

    Google Scholar 

  • De S, Agarwal NK, Hazra A, Chaudhari HS, Sahai AK (2019) On unravelling mechanism of interplay between cloud and large scale circulation: a grey area in climate science. Clim Dyn 46:1197–1222

    Google Scholar 

  • Diao M, Bryan GH, Morrison H, Jensen JB (2017) Ice nucleation parameterization and relative humidity distribution in idealized squall-line simulations. J Atmos Sci 74:2761–2787

    Google Scholar 

  • Ek MB, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley JD (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res 1089(D22):8851

    Google Scholar 

  • Ferrier BS, Lin Y, Black T, Rogers E, DiMego G (2002) Implementation of a new grid-scale cloud and precipitation scheme in the NCEP Eta model. In: Preprints, 15th conference on numerical weather prediction, San Antonio, TX, American Meteorological Society, pp 280–283

  • Field PR, Heymsfield AJ (2015) Importance of snow to global precipitation. Geophy Res Lett 42:9512–9520. https://doi.org/10.1002/2015gl065497

    Article  Google Scholar 

  • Fu D, Guo X, Liu C (2011) Effects of cloud microphysics on monsoon convective system and its formation environments over the South China Sea: a two-dimensional cloud-resolving modeling study. J Geophy Res. https://doi.org/10.1029/2010jd014662

    Article  Google Scholar 

  • Gadgil S (2007) The Indian monsoon. Resonance 12:4–20. https://doi.org/10.1007/s12045-007-0045-y

    Article  Google Scholar 

  • Ganai M, Mukhopadhyay P, Krishna RPM, Mahakur M (2015) The impact of revised simplified Arakawa-Schubert convection parameterization scheme in CFSv2 on the simulation of the Indian summer monsoon. Clim Dyn 45:881–902. https://doi.org/10.1007/s00382-014-2320-4

    Article  Google Scholar 

  • Ganai M, Krishna RPM, Mukhopadhyay P, Mahakur M (2016) The impact of revised simplified Arakawa-Schubert scheme on the simulation of mean and diurnal variability associated with active and break phases of Indian summer monsoon using CFSv2. J Geophys Res Atmos 121:9301–9323. https://doi.org/10.1002/2016jd025393

    Article  Google Scholar 

  • Gettelman A, Collins WD, Fetzer EJ et al (2006) Climatology of upper-tropospheric relative humidity from the atmospheric infrared sounder and implications for climate. J Clim 19:6104–6121. https://doi.org/10.1175/jcli3956.1

    Article  Google Scholar 

  • Goswami BN (1994) Dynamical predictability of seasonal monsoon rainfall: problems and prospects. Proc Indian Natl Sci Acad 60:101–120

    Google Scholar 

  • Goswami BN (1998) Interannual variations of Indian summer monsoon in a GCM: external conditions versus internal feedbacks. J Clim 11:501–522

    Google Scholar 

  • Goswami BN, Krishnamurthy V, Aamalai H (1999) A broad-scale circulation index for the interannual variability of the Indian summer monsoon. Q J R Meteorol Soc 125:611–633

    Google Scholar 

  • Goswami BB, Mani NJ, Mukhopadhyay P et al (2011) Monsoon intraseasonal oscillations as simulated by the superparameterized community atmosphere model. J Geophys Res Atmos. https://doi.org/10.1029/2011jd015948

    Article  Google Scholar 

  • Goswami BB, Khouider B, Phani R et al (2017) Implementation and calibration of a stochastic multicloud convective parameterization in the NCEP Climate Forecast System (CFSv2). J Adv Model Earth Syst 9:1721–1739. https://doi.org/10.1002/2017ms001014

    Article  Google Scholar 

  • Griffies SM, Gnanadesikan A, Dixon KW et al (2005) Formulation of an ocean model for global climate simulations. Ocean Sci 1:45–79. https://doi.org/10.5194/os-1-45-2005

    Article  Google Scholar 

  • Ham S, Hong S (2013) Sensitivity of simulated intraseasonal oscillation to four convective parameterization schemes in a coupled climate model. Asia Pac J Atmos Sci 49:483–496

    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

    Google Scholar 

  • Hazra A, Chaudhari HS, Rao SA, Goswami BN, Dhakate A, Pokhrel S, Saha SK (2015) Impact of revised cloud microphysical scheme in CFSv2 on the simulation of the Indian summer monsoon. Int J Climatol 35:4738–4755. https://doi.org/10.1002/joc.4320

    Article  Google Scholar 

  • Hazra A, Chaudhari HS, Pokhrel S, Saha SK (2016) Indian summer monsoon precipitating clouds: role of microphysical process rates. Clim Dyn 46:2551–2571

    Google Scholar 

  • Hazra A, Chaudhari HS, Saha SK, Pokhrel S (2017a) Effect of cloud microphysics on Indian summer monsoon precipitating clouds: a coupled climate modeling study. J Geophy Res Atmos 122:3786–3805. https://doi.org/10.1002/2016jd026106

    Article  Google Scholar 

  • Hazra A, Chaudhari HS, Saha SK, Pokhrel S, Goswami BN (2017b) Progress towards achieving the challenge of indian summer monsoon climate simulation in a coupled ocean-atmosphere model. J Adv Model Earth Syst 9:2268–2290. https://doi.org/10.1002/2017ms000966

    Article  Google Scholar 

  • Hong S-Y, Dudhia J, Chen S-H (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132:103–120

    Google Scholar 

  • Hu Y, Winker D, Vaughan M et al (2009) CALIPSO/CALIOP Cloud phase discrimination algorithm. J Atmos Oceanic Technol 26:2293–2309. https://doi.org/10.1175/2009jtecha1280.1

    Article  Google Scholar 

  • Iacono MJ, Mlawer EJ, Clough SA, Morcrette J-J (2000) Impact of an improved longwave radiation model, RRTM, on the energy budget and thermodynamic properties of the NCAR community climate model, CCM3. J Geophy Res Atmos 105:14873–14890. https://doi.org/10.1029/2000jd900091

    Article  Google Scholar 

  • Joseph PV, Sijikumar S (2004) Intraseasonal variability of the low-level jet stream of the asian summer monsoon. J Clim 17:1449–1458

    Google Scholar 

  • Kanamitsu M, Ebisuzaki W, Woollen J et al (2002) NCEP–DOE AMIP-II reanalysis (R-2). Bull Am Meteorol Soc 83:1631–1644. https://doi.org/10.1175/bams-83-11-1631

    Article  Google Scholar 

  • Kang H-S, Hong S-Y (2008) Sensitivity of the simulated East Asian summer monsoon climatology to four convective parameterization schemes. J Geophys Res. https://doi.org/10.1029/2007jd009692

    Article  Google Scholar 

  • Kim Y-J, Arakawa A (1995) Improvement of orographic gravity wave parameterization using a mesoscale gravity wave model. J Atmos Sci 52:1875–1902

    Google Scholar 

  • Krishna RPM, Rao SA, Srivastava A et al (2019) Impact of convective parameterization on the seasonal prediction skill of Indian summer monsoon. Clim Dyn 53:6227–6243. https://doi.org/10.1007/s00382-019-04921-y

    Article  Google Scholar 

  • Krishna Kumar K, Hoerling M, Rajagopalan B (2005) Advancing dynamical prediction of Indian monsoon rainfall. Geophy Res Lett 32:L08704. https://doi.org/10.1029/2004GL021979

    Article  Google Scholar 

  • Krishnamurti TN, Bhalme HN (1976) Oscillations of a monsoon system. Part I. Observational aspects. J Atmos Sci 33:1937–1954

    Google Scholar 

  • Krishnamurti TN, Bedi HS, Subramaniam M (1989) The summer monsoon of 1987. J Clim 2:321–340

    Google Scholar 

  • Krishnan R, Kumar V, Sugi M, Yoshimura J (2009) Internal feedbacks from monsoon-midlatitude interactions during droughts in the Indian Summer Monsoon. J Atmos Sci 66:553–578. https://doi.org/10.1175/2008jas2723.1

    Article  Google Scholar 

  • Kruegera SK, Fua Q, Lioua KN, Chin HN (1995) Improvements of an ice-phase microphysics parameterization for use in numerical simulations of tropical convection. J Appl Meteorol 34:281–287. https://doi.org/10.1175/1520-0450-34.1.281

    Article  Google Scholar 

  • Kulkarni A, Kripalani RH (1998) Rainfall patterns over India: classification with fuzzy c-means method. Theor Appl Climatol 59:137–146. https://doi.org/10.1007/s007040050019

    Article  Google Scholar 

  • Kumar S, Hazra A, Goswami BN (2014) Role of interaction between dynamics, thermodynamics and cloud microphysics on summer monsoon precipitating clouds over the Myanmar Coast and the Western Ghats. Clim Dyn 43:911–924. https://doi.org/10.1007/s00382-013-1909-3

    Article  Google Scholar 

  • Kumar S, Arora A, Chattopadhyay R, Hazra A, Rao SA, Goswami BN (2017) Seminal role of stratiform clouds in large-scale aggregation of tropical rain in boreal summer monsoon intraseasonal oscillations. Clim Dyn 48:999–1015. https://doi.org/10.1007/s00382-016-3124-5

    Article  Google Scholar 

  • Li J, Wu K, Li F et al (2017) Effects of latent heat in various cloud microphysics processes on autumn rainstorms with different intensities on Hainan Island, China. Atmos Res 189:47–60

    Google Scholar 

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

    Google Scholar 

  • Liu X, Xie S, Ghan SJ (2007) Evaluation of a new mixed-phase cloud microphysics parameterization with CAM3 single-column model and M-PACE observations. Geophy Res Lett 34:L23712

    Google Scholar 

  • Liu D, Yang B, Zhang Y et al (2018) Combined impacts of convection and microphysics parameterizations on the simulations of precipitation and cloud properties over Asia. Atmos Res 212:172–185

    Google Scholar 

  • Lord SJ (1982) Interaction of a cumulus cloud ensemble with large-scale environment. Part III: semi-prognostic test of the Arakawa–Schubert cumulus parameterization. J Atmos Sci 39:88–103

    Google Scholar 

  • Lott F, Miller MJ (1997) A new subgrid-scale orographic drag parameterization: its formulation and testing. Q J R Meteorol Soc 123:101–127. https://doi.org/10.1256/smsqj.53703

    Article  Google Scholar 

  • Lund IA (1963) Map-pattern classification by statistical methods. J Appl Meteorol 2:56–65

    Google Scholar 

  • Mandke SK, Sahai AK, Shinde MA, Joseph S, Chattopadhyay R (2007) Simulated changes in active/break spells during the Indian summer monsoon due to enhanced CO2 concentrations: assessment from selected coupled atmosphere–ocean global climate models. Int J Climatol 27:837–859. https://doi.org/10.1002/joc.1440

    Article  Google Scholar 

  • Mccumber M, Tao W-K, Simpson J, Pencb R, Soong ST (1991) Comparison of ice-phase microphysical parameterization schemes using numerical simulations of tropical convection. J Appl Meteorol 30:985–1004. https://doi.org/10.1175/1520-0450-30.7.985

    Article  Google Scholar 

  • Mlawer EJ, Taubman SJ, Brown PD, IaconoMJ CSA (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophy Res Atmos 102:16663–16682. https://doi.org/10.1029/97jd00237

    Article  Google Scholar 

  • Mukhopadhyay P, Taraphdar S, Goswami BN, Krishnakumar K (2010) Indian summer monsoon precipitation climatology in a high-resolution regional climate model: impacts of convective parameterization on systematic biases. Weather Forecast 25:369–387. https://doi.org/10.1175/2009waf2222320.1

    Article  Google Scholar 

  • Murakami T (1976) Analysis of summer monsoon fluctuations over India. J Meteorol Soc Jpn 54:15–31. https://doi.org/10.2151/jmsj1965.54.1_15

    Article  Google Scholar 

  • Murakami T (1980) Temporal variations of satellite-observed outgoing longwave radiation over the winter monsoon region. Part II: short-period (4–6 day) oscillations. Mon Weather Rev 108:427–444

    Google Scholar 

  • Naidu C, Krishna KM, Rao SR, Bhanu Kumar OSRU, Durgalakshmi K, Ramakrishna SSVS (2011) Variations of Indian summer monsoon rainfall induce the weakening of easterly jet stream in the warming environment? Global Planet Change 75:21–30. https://doi.org/10.1016/j.gloplacha.2010.10.001

    Article  Google Scholar 

  • Nithya K, Manoj MG, Mohankumar K (2017) Effect of El Niño/La Niña on tropical easterly jet stream during Asian summer monsoon season. Int J Climatol 37:4994–5004. https://doi.org/10.1002/joc.5137

    Article  Google Scholar 

  • Noda AT, Satoh M, Yamada Y, Kodama C, Miyakawa T, Seiki T (2015) Cold and warm rain simulated using a global nonhydrostatic model without cumulus parameterization and their responses to global warming. J Meteorol Soc Jpn 93:181–197

    Google Scholar 

  • Parthasarathy B, Munot A, Kothawale D (1988) Regression model for estimation of Indian food grain production from summer monsoon rainfall. Agric For Meteorol 42:167–182

    Google Scholar 

  • Pattnaik S, Abhilash S, De S et al (2013) Influence of convective parameterization on the systematic errors of climate forecast system (CFS) model over the Indian monsoon region from an extended range forecast perspective. Clim Dyn 41:341–365. https://doi.org/10.1007/s00382-013-1662-7

    Article  Google Scholar 

  • Prasad KD, Verma RK (1985) Large-scale features of satellite-derived outgoing long-wave radiation in relation to monsoon circulation over the Indian region. Int J Climatol 5:297–306. https://doi.org/10.1002/joc.3370050306

    Article  Google Scholar 

  • Quaas J (2012) Evaluating the “critical relative humidity” as a measure of subgrid-scale variability of humidity in general circulation model cloud cover parameterizations using satellite data. J Geophys Res Atmos 117:D09208. https://doi.org/10.1029/2012JD017495

    Article  Google Scholar 

  • Rahman SH, Simon B (2006) Summer monsoon intraseasonal oscillation over eastern Arabian sea—as revealed by TRMM microwave imager products. J Earth Syst Sci 115:575–586. https://doi.org/10.1007/bf02702910

    Article  Google Scholar 

  • Rajeevan M, Gadgil S, Bhate J (2010) Active and break spells of the Indian summer monsoon. J Earth Syst Sci 119:229–247. https://doi.org/10.1007/s12040-010-0019-4

    Article  Google Scholar 

  • Rajeevan M, Unnikrishnan CK, Preethi B (2012) Evaluation of the ENSEMBLES multi-model seasonal forecasts of Indian summer monsoon variability. Clim Dyn 38:2257–2274

    Google Scholar 

  • Raju PVS, Mohanty UC, Bhatla R (2005) Onset characteristics of the southwest monsoon over India. Int J Climatol 25:167–182. https://doi.org/10.1002/joc.1121

    Article  Google Scholar 

  • RieneckerMM SMJ, Gelaro R et al (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24:3624–3648

    Google Scholar 

  • Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Am Meteorol Soc 80:2261–2287

    Google Scholar 

  • Saha SK, Pokhrel S, Chaudhari HS (2013) Influence of Eurasian snow on Indian summer monsoon in NCEP CFSv2 freerun. Clim Dyn 41:1801–1815. https://doi.org/10.1007/s00382-012-1617-4

    Article  Google Scholar 

  • Saha S, Moorthi S, Wu X et al (2014a) 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 

  • Saha SB, Roy SS, Bhowmik SKR, Kundu PK (2014b) Intra-seasonal variability of cloud amount over the Indian subcontinent during the monsoon season as observed by TRMM precipitation radar. Geofizika. https://doi.org/10.15233/gfz.2014.31.2

    Article  Google Scholar 

  • Saha SK, Pokhrel S, Chaudhari HS, Dhakate A, Shewale S, Sabeerali CT, Salunke S, Hazra A, Mohapatra S, Rao SA (2014c) Improved simulation of Indian summer monsoon in latest NCEP climate forecast system free run. Int J Climatol 34:1628–1641. https://doi.org/10.1002/joc.3791

    Article  Google Scholar 

  • Saha SK, Hazra A, Pokhrel S, Chaudhari HS, Sujith K, Rai A, Rahaman H, Goswami BN (2019) Unraveling the mystery of indian summer monsoon prediction: improved estimate of predictability limit. J Geophys Res Atmos. https://doi.org/10.1029/2018jd030082

    Article  Google Scholar 

  • Sikka DR, Gadgil S (1980) On maximum cloud zone and ITCZ over Indian longitude during the southwest monsoon. Mon Weather Rev 108:1840–1853

    Google Scholar 

  • Song X, Zhang GJ (2011) Microphysics parameterization for convective clouds in a global climate model: description and single-column model tests. J Geophys Res. https://doi.org/10.1029/2010jd014833

    Article  Google Scholar 

  • Straka JM, Anderson JR (1993) Numerical simulations of microburst-producing storms: some results from storms observed during COHMEX. J Atmos Sci 50:1329–1348. https://doi.org/10.1175/1520-0469(1993)050

    Article  Google Scholar 

  • Sud YC, Walker GK (1999) Microphysics of clouds with the relaxed Arakawa-Schubert scheme (McRAS). Part I: design and evaluation with GATE phase III data. J Atmos Sci 56:3196–3220. https://doi.org/10.1175/1520-0469(1999)056

    Article  Google Scholar 

  • Sundqvist H (1988) Parameterization of condensation and associated clouds in models for weather prediction and general circulation simulation. In: Schlesinger ME (ed) Physically-based modelling and simulation of climate and climatic change-part-I. Kluwer Academic Publishers, Berlin, pp 433–461. https://doi.org/10.1007/978-94-009-3041-4_10

    Chapter  Google Scholar 

  • Sundqvist H, Berge E, Kristjansson JE (1989) Condensation and cloud studies with mesoscale numerical weather prediction model. Mon Weather Rev 117:1641–1757

    Google Scholar 

  • Tang X, Chen B (2006) Cloud types associated with the Asian summer monsoons as determined from MODIS/TERRA measurements and a comparison with surface observations. Geophy Res Lett 33:L07814. https://doi.org/10.1029/2006GL026004

    Article  Google Scholar 

  • Tao W-K, Moncrieff MW (2009) Multiscale cloud system modeling. Rev Geophys 47:RG4002

    Google Scholar 

  • Tao W-K, Simpson J (1989) Modeling study of a tropical squall-type convective line. J Atmos Sci 46:177–202

    Google Scholar 

  • Thompson A, Stefanova L, Krishnamurti TN (2008) Baroclinic splitting of jets. Meteorol Atmos Phys 100:257–274

    Google Scholar 

  • Turner AG, Slingo JM (2008) Subseasonal extremes of precipitation and active-break cycles of the Indian summer monsoon in a climate-change scenario. Q J R Meteorol Soc 135:549–567. https://doi.org/10.1002/qj.401

    Article  Google Scholar 

  • Udelhofen PM, Hartmann DL (1995) Influence of tropical cloud systems on the relative humidity in the upper troposphere. J Geophy Res 100:7423–7440. https://doi.org/10.1029/94jd02826

    Article  Google Scholar 

  • Umakanth U, Kesarkar AP, Raju A, Rao SVB (2015) Representation of monsoon intraseasonal oscillations in regional climate model: sensitivity to convective physics. Clim Dyn 47:895–917. https://doi.org/10.1007/s00382-015-2878-5

    Article  Google Scholar 

  • Viswanadhapalli Y, Dasari HP, Dwivedi S et al (2019) Variability of monsoon low-level jet and associated rainfall over India. Int J Climatol 40:1067–1089. https://doi.org/10.1002/joc.6256

    Article  Google Scholar 

  • Wang B (2005) Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophy Res Lett. https://doi.org/10.1029/2005gl022734

    Article  Google Scholar 

  • Wang P-H, Minnis P, Mccormick MP, Kent GS, Skeens KM (1996) A 6-year climatology of cloud occurrence frequency from stratospheric aerosol and gas experiment II observations (1985–1990). J Geophy Res Atmos 101:29407–29429. https://doi.org/10.1029/96jd01780

    Article  Google Scholar 

  • Wang PK, Lin H-M, Su S-H (2010) The impact of ice microphysical processes on the life span of a mid latitude super cell storm. Atmos Res 97:450–461. https://doi.org/10.1016/j.atmosres.2010.05.006

    Article  Google Scholar 

  • Webster PJ, Magaña VO, Palmer TN et al (1998) Monsoons: processes, predictability, and the prospects for prediction. J Geophy Res Oceans 103:14451–14510. https://doi.org/10.1029/97jc02719

    Article  Google Scholar 

  • Wheeler M, Kiladis GN (1999) Convectively coupled equatorial waves: analysis of clouds and temperature in the wavenumber-frequency domain. J Atmos Sci 56:374–399. https://doi.org/10.1175/1520-0469(1999)056

    Article  Google Scholar 

  • Wilson SS, Joseph PV, Mohanakumar K, Johannessen OM (2018) Interannual and long term variability of low level jetstream of the Asian summer monsoon. Tellus A Dyn Meteorol Oceanogr 70:1–9. https://doi.org/10.1080/16000870.2018.1445380

    Article  Google Scholar 

  • Wylie D, Menzel W (1999) Eight years of high cloud statistics using HIRS. J Clim 12:170–184

    Google Scholar 

  • Yang B, Zhang Y, Qian Y et al (2015) Parametric sensitivity analysis for the Asian summer monsoon precipitation simulation in the Beijing Climate Center AGCM, version 2.1. J Clim 28:5622–5644. https://doi.org/10.1175/jcli-d-14-00655.1

    Article  Google Scholar 

  • Yasunari T (1980) A quasi-stationary appearance of 30 to 40 day period in the cloudiness fluctuations during the summer monsoon over India. J Meteorol Soc Jpn Ser II 58:225–229. https://doi.org/10.2151/jmsj1965.58.3_225

    Article  Google Scholar 

  • Zhang D-L (1989) The effect of parameterized ice microphysics on the simulation of vortex circulation with a mesoscale hydrostatic model. Tellus A 41A:132–147. https://doi.org/10.1111/j.1600-0870.1989.tb00371.x

    Article  Google Scholar 

  • Zhang GJ, Song X (2016) Parameterization of microphysical processes in convective clouds in global climate models. Meteorol Monogr 56:12.1–12.18. https://doi.org/10.1175/amsmonographs-d-15-0015.1

    Article  Google Scholar 

  • Zhao Q, Carr FH (1997) A prognostic cloud scheme for operational NWP models. Mon Weather Rev 125:1931–1953

    Google Scholar 

Download references

Acknowledgements

Authors are thankful to Prof. Ravi S. Nanjundiah, Director, Indian Institute of Tropical Meteorology (IITM), for encouraging to carry out this research work. We are thankful to the anonymous reviewers for the improvement in the manuscript. The model simulation is also archived at ‘Aaditya’ HPC system at IITM and available upon request from the corresponding author. The authors have no conflicts of interest to declare.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hemantkumar S. Chaudhari.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 2962 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dutta, U., Chaudhari, H.S., Hazra, A. et al. Role of convective and microphysical processes on the simulation of monsoon intraseasonal oscillation. Clim Dyn 55, 2377–2403 (2020). https://doi.org/10.1007/s00382-020-05387-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-020-05387-z

Navigation