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The impact of revised simplified Arakawa–Schubert convection parameterization scheme in CFSv2 on the simulation of the Indian summer monsoon

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Abstract

Keeping the systematic bias of the climate forecast system model version 2 (CFSv2) in mind, an attempt is made to improve the Indian summer monsoon (ISM) rainfall variability in the model from diurnal through daily to seasonal scale. Experiments with default simplified Arakawa–Schubert (SAS) and a revised SAS schemes are carried out to make 15 years climate run (free run) to evaluate the model fidelity with revised SAS as compared to default SAS. It is clearly seen that the revised SAS is able to reduce some of the biases of CFSv2 with default SAS. Improvement is seen in the annual seasonal cycle, onset and withdrawal but most importantly the rainfall probability distribution function (PDF) has improved significantly. To understand the reason behind the PDF improvement, the diurnal rainfall simulation is analysed and it is found that the PDF of diurnal rainfall has significantly improved with respect to even a high resolution CFSv2 T382 version. In the diurnal run with revised SAS, the PDF of rainfall over central India has remarkably improved. The improvement of diurnal cycle of total rainfall has actually been contributed by the improvement of diurnal cycle of convection and associated convective rainfall. This is reflected in outgoing longwave radiation and high cloud diurnal cycle. This improvement of convective cycle has resolved a long standing problem of dry bias by CFSv2 over Indian land mass and wet bias over equatorial Indian Ocean. Besides the improvement, there are some areas where there are still scopes for further development. The cold tropospheric temperature bias, low cloud fractions need further improvement. To check the role of shallow convection, another free run is made with revised SAS along with shallow convection (SC). The major difference between the new and old SC schemes lies in the heating and cooling behavior in lower-atmospheric layers above the planetary boundary layer. However, the inclusion of revised SC scheme could not show much improvement as compared to revised SAS with deep convection. Thus, it seems that revised SAS with deep convection can be a potentially better parameterization scheme for CFSv2 in simulating ISM rainfall variability.

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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. doi:10.1007/s00382-013-1824-7

    Article  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. doi:10.1002/joc.3668

    Article  Google Scholar 

  • Ajayamohan RS, Boualem Khouider, Majda AJ (2014) Simulation of monsoon intraseasonal oscillations in a coarse resolution aquaplanet GCM. Geophys Res Let. doi:10.1002/2014GL060662

    Google Scholar 

  • Dirmeyer PA et al (2010) Simulating the hydrologic diurnal cycle in global climate models: resolution versus parameterization. Center for Ocean–Land–Atmosphere Studies Tech. Rep. 304

  • Barker HW, Stephens GL, Fu Q (1999) The sensitivity of domain averaged solar fluxes to assumptions about cloud geometry. Q J R Meteorol Soc 125:2127–2152

    Article  Google Scholar 

  • Betts AK, Jakob C (2002) Evaluation of the diurnal cycle of precipitation, surface thermodynamics, and surface fluxes in the ECMWF model using LBA data. J Geophys Res 107:8045. doi:10.1029/2001JD000427

    Article  Google Scholar 

  • Chattopadhyay R, Goswami BN, Sahai AK, Fraedrich K (2009) Role of stratiform rainfall in modifying the northward propagation of monsoon intraseasonal oscillation. J Geophys Res 114:1–15. doi:10.1029/2009JD011869

    Google Scholar 

  • Chaudhari HS, Shinde MA, Oh JH (2010) Understanding of anomalous Indian summer monsoon rainfall of 2002 and 1994. Quat Int 213:20–32

    Article  Google Scholar 

  • Chaudhari HS, Pokhrel S, Saha SK, Dhakate A, Yadav RK, Salunke K, Mahapatra S, Sabeerali CT, Rao AS (2013) Model biases in long coupled runs of NCEP CFS in the context of Indian summer monsoon. Int J Climatol 33:1057–1069. doi:10.1002/joc.3489

    Article  Google Scholar 

  • Collins WD (2001) Parameterization of generalized cloud overlap for radiative calculations in general circulation models. J Atmos Sci 58:3224–3242

    Article  Google Scholar 

  • Dai A (2006) Precipitation characteristics in eighteen coupled climate models. J Clim 19:4605–4630

    Article  Google Scholar 

  • Dai AF, Trenberth KE (2004) The diurnal cycle and its depiction in the community climate system model. J Clim 17:930–995

    Article  Google Scholar 

  • Duchon CE (1979) Lanczos filtering in one and two dimensions. J Appl Meteorol 18:1016–1022

    Article  Google Scholar 

  • Ek MB, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarplay JD (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res 108(D22):8851. doi:10.1029/2002JD003296

    Article  Google Scholar 

  • Fennessy MJ, Kinter JL III, Kirtman B, Marx L, Nigam S, Schneider E, Shukla J, Straus D, Vernekar A, Xue X, Zhou J (1994) The simulated Indian monsoon: a GCM sensitivity study. J Clim 7:33–43

    Article  Google Scholar 

  • Findlater J (1969) A major low-level air current near the Indian Ocean during the northern summer. Q J R Meteorol Soc 95:362–380

    Article  Google Scholar 

  • Gadgil S (2003) The Indian monsoon and its variability. Ann Rev Earth Planet Sci 31:429–467

    Article  Google Scholar 

  • Gadgil S, Gadgil S (2006) The Indian monsoon, GDP and agriculture. Econ Polit Wkly XLI:4887–4895

    Google Scholar 

  • Gadgil S, Sajani S (1998) Monsoon precipitation in the AMIP runs. Clim Dyn 14:659–689

    Article  Google Scholar 

  • Gates WL, Boyle J, Covey C, Dease C, Doutriaux C, Drach R, Fiorino M, Gleckler P, Hnilo J, Marlais S, Phillips T, Potter G, Santer BD, Sperber KR, Taylor K, Williams D (1999) An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I). Bull Am Meteor Soc 80:29–55

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Goswami BN (2005) South Asian summer monsoon. In: Lau WK-M, Waliser DE (eds) Intraseasonal variability of the atmosphere ocean climate system. Springer, Berlin, pp 19–61

    Chapter  Google Scholar 

  • Goswami BN, Xavier PK (2005) Dynamics of internal interannual variability of the Indian summer monsoon in a GCM. J Geophys Res 110:D24104. doi:10.1029/2005JD006042

    Article  Google Scholar 

  • Goswami BB, Mukhopadhyay P, Khairoutdinov M, Goswami BN (2013) Simulation of Indian summer monsoon intraseasonal oscillations in a superparameterized coupled climate model: need to improve the embedded cloud resolving model. Clim Dyn 41:1497–1507. doi:10.1007/s00382-012-1563-1

    Article  Google Scholar 

  • Goswami BB, Deshpande MS, Mukhopadhyay P, Saha SK, Rao AS, Murthugudde R, Goswami BN (2014) Simulation of monsoon intraseasonal variability in NCEP CFSv2 and its role on systematic bias. Clim Dyn 1–21. doi:10.1007/s00382-014-2089-5

  • Griffies SM, Harrison MJ, Pacanowski RC, Rosati A (2004) A technical guide to MOM4,GFDL ocean group technical report 5, GFDL, pp 337

  • Hack JJ, Keihl JT, Hurrell JW (1998) The hydrologic and thermodynamic characteristic of the NCAR CCM3. J Clim 11:1179–1206

    Article  Google Scholar 

  • Haddad ZS, Short DA, Durden SL, Im E, Hensley S, Grable MB, Black RA (1997a) A new parametrization of the rain drop size distribution. IEEE Trans Geosci Remote Sens 35:532–539. doi:10.1109/36.581961

    Article  Google Scholar 

  • Haddad ZS, Smith EA, Kummerow CD, Iguchi T, Farrar MR, Durden SL, Alves M, Olson WS (1997b) The TRMM ‘day-1’ radar/radiometer combined rain-profiling algorithm. J Meteorol Soc Jpn 75:799–809

    Google Scholar 

  • Han J, Pan H-L (2011) Revision of convection and vertical diffusion schemes in the NCEP global forecast system. Wea Forecast 26:520–533. doi:10.1175/WAF-D-10-05038.1

    Article  Google Scholar 

  • Hong SY, Pan HL (1998) Convective trigger function for a mass flux cumulus parameterization scheme. Mon Wea Rev 126:2599–2620

    Article  Google Scholar 

  • Houze RAJ (1989) Observed structure of mesoscale convective systems and implications for large-scale heating. Q J R Meteorol Soc 115:425–461

    Article  Google Scholar 

  • Hoyos CD, Webster PJ (2007) The role of intraseasonal variability in the nature of Asian monsoon precipitation. J Clim 20(17):4402–4424

    Article  Google Scholar 

  • Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Stocker EF, Wolff DB (2007) The TRMM multisatellite precipitation analysis: quasi-global, multi-year, combined-sensor precipitation estimates at fine scale. J Hydrometeorol 8:33–55

    Article  Google Scholar 

  • Iguchi T, Kozu T, Meneghini R, Awaka J, Okamoto K (2000) Rain profiling algorithm for the TRMM precipitation radar. J Appl Meteorol 39:2038–2052

    Article  Google Scholar 

  • Inness PM, Slingo JM, Woolnough SJ, Neale RB, Pope VD (2001) Organization of tropical convection in a GCM with varying vertical resolution; implications for the simulation of the Madden–Julian oscillation. Clim Dyn 17:777–793. doi:10.1007/s003820000148

    Article  Google Scholar 

  • Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetma A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471. doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2

    Article  Google Scholar 

  • Kang I-S, Jin K, Wang B, Lau K-M, Shukla J, Krishnamurthy V, Schubert S, Wailser D, Stern W, Kitoh A, Meehl G, Kanamitsu G, Galin V, Satyan V, Park C-K, Liu Y (2002) Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs. Clim Dyn 19:383–395. doi:10.1007/s00382-002-0245-9

    Article  Google Scholar 

  • Kemball-Cook S, Wang B, Fu X (2002) Simulation of the intraseasonal oscillation in the ECHAM-4 model: the impact of coupling with an ocean model. J Atmos Sci 59:1433–1453. doi:10.1175/1520-0469(2002)059<1433:SOTIOI>2.0.CO;2

    Article  Google Scholar 

  • Kim H-M, Kang I-S, Wang B, Lee J-Y (2008) Interannual variations of the boreal summer intraseasonal variability predicted by ten atmosphere–ocean coupled models. Clim Dyn 30:485–496. doi:10.1007/s00382-007-0292-3

    Article  Google Scholar 

  • Kim H-M, Webster PJ, Curry JA (2012) Seasonal prediction skill of ECMWF system 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter. Clim Dyn 39:2957–2973. doi:10.1007/s00382-012-1364-6

    Article  Google Scholar 

  • Kripalani RH, Kulkarni A, Sabade SS, Khandekar ML (2003) Indian monsoon variability in a global warming scenario. Nat Hazards 29:189–206

    Article  Google Scholar 

  • Krishna Kumar K (2005) Advancing dynamical prediction of Indian monsoon rainfall. Geophys Res Lett 32:L08704. doi:10.1029/2004GL021979

    Article  Google Scholar 

  • Kug J-S, Kang I-S, Choi D-H (2008) Seasonal climate predictability with tier-one and tier-two prediction systems. Clim Dyn 31:403–416. doi:10.1007/s00382-007-0264-7

    Article  Google Scholar 

  • Kummerow C, Hong Y, Olson WS, Yang S, Adler RF, McCollum J, Ferraro R, Petty G, Shin DB, Wilheit TT (2001) The evolution of the Goddard profile algorithm (GPROF) for rainfall estimation from passive microwave sensors. J Appl Meteorol 40:1801–1820

    Article  Google Scholar 

  • Lee Drbohlav H-K, Krishnamurthy V (2010) Spatial structure, forecast errors, and predictability of the south Asian monsoon in CFS monthly retrospective forecasts. J Clim 23:4750–4769

    Article  Google Scholar 

  • Lee MI et al (2007) An analysis of the warm season diurnal cycle over the continental United States and northern Mexico in general circulation models. J Hydrometeor 8:344–366

    Article  Google Scholar 

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

    Google Scholar 

  • Lim K, Hong S, Yoon J, Han J (2014) Simulation of the summer monsoon rainfall over East Asia using the NCEP GFS cumulus parameterization at different horizontal resolutions. Wea Forecast. doi:10.1175/WAF-D-13-00143.1

  • Lin J-L, Weickman KM, Kiladis GN, Mapes BE, Schubert SD, Suarez MJ, Bacmeister JT, Lee M-I (2008) Subseasonal variability associated with Asian summer monsoon simulated by 14 IPCC AR4 coupled GCMs. J Clim 21:4541–4567. doi:10.1175/2008JCLI1816.1

    Article  Google Scholar 

  • Mahakur M, Prabhu A, Sharma AK, Rao VR, Senroy S, Singh R, Goswami BN (2013) High-resolution outgoing longwave radiation dataset from Kalpana-1 satellite during 2004–2012. Curr Sci 105:1124–1133

    Google Scholar 

  • Mooley DA, Parthasarathy B (1984) Fluctuations of All-India summer monsoon rainfall during 1871–1978. Clim Chang 6:287–301

    Article  Google Scholar 

  • Naidu CV, Krishna KM, Rao SR, Kumar OSRUB, Durgalakshmi K, Ramakrishna SSVS (2011) Variations of Indian summer monsoon rainfall induce the weakening of easterly jet stream in the warming environment? Global Planet Chang 33:1017–1032

    Google Scholar 

  • Pan HL, Wu WS (1995) Implementing a mass flux convective parameterization package for the NMC medium-range forecast model. NMC Office Note 409

  • Pattanaik DR, Kumar A (2010) Prediction of summer monsoon rainfall over India using the NCEP climate forecast system. Clim Dyn 34:557–572. doi:10.1007/s00382-009-0648-y

    Article  Google Scholar 

  • Pattnaik S, Abhilash S, De S, Sahai AK, Phani R, Goswami BN (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. doi:10.1007/s00382-013-1662-7

    Article  Google Scholar 

  • Piani C, Haerter JO, Coppola E (2010) Statistical bias correction for daily precipitation in regional climate models over Europe. Theo Appl Climatol 99:187–192

    Article  Google Scholar 

  • Pokhrel S, Rahaman H, Parekh A, Saha SK, Dhakate A, Chaudhari HS, Gairola RM (2012) Evaporation-precipitation variability over Indian Ocean and its assessment in NCEP Climate Forecast System (CFSv2). Clim Dyn 39:2585–2608. doi:10.1007/s00382-012-1542-6

    Article  Google Scholar 

  • Qie X, Wu X, Yuan T, Bian J, Lu D (2014) Comprehensive pattern of deep convective systems over the Tibetan Plateau-South Asian monsoon region based on TRMM data. J Clim 27:6612–6626

    Article  Google Scholar 

  • Rajeevan M, Bhate J (2008) A high resolution daily gridded rainfall data set (1971–2005) for mesoscale meteorological studies. National Climate Centre Research Report (9)

  • Rossow WB, Schiffer RA (1999) Advances in Understanding Clouds from ISCCP. Bull Am Meteor Soc 80:2261–2287

    Article  Google Scholar 

  • Rossow WB, Zhang YC (1995) Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets, 2. Validation and first results. J Geophys Res 100:1167–1197

    Article  Google Scholar 

  • Sabeerali CT, Rao AS, Ajayamohan RS, Murtugudde R (2012) On the relationship between Indian summer monsoon withdrawal and Indo-Pacific SST anomalies before and after 1976/1977 climate shift. Clim Dyn 39:841–859. doi:10.1007/s00382-011-1269-9

    Article  Google Scholar 

  • Sabre M, Hodges K, Laval K, Polcher J, Désalmand F (2000) Simulation of monsoon disturbances in the LMD GCM. Mon Wea Rev 128:3752–3771

    Article  Google Scholar 

  • Saha S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteor Soc 91:1015–1057

    Article  Google Scholar 

  • Saha S, Moorthi S, Wu X, Wang J, Nadiga S, Tripp P, Behringer D, Hou Y-T, Chuang H-Y, Iredell M, Ek M, Meng J, Yang R, Pena Mendez M, van den Dool H, Zhang Q, Wang W, Chen M, Becker E (2013) The NCEP climate forecast system version 2. J Clim. doi:10.1175/JCLI-D-12-00823.1

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

    Article  Google Scholar 

  • Sahai AK, Abhilash S, Chattopadhyay R, Borah N, Joseph S, Sharmila S, Rajeevan M (2014) High-resolution operational monsoon forecasts: an objective assessment. Clim Dyn 1–12. doi:10.1007/s00382-014-2210-9

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

    Google Scholar 

  • Sharmila S, Pillai SA, Joseph S, Roxy M, Krishna RPM, Chattopadhyay R, Abhilash S, Sahai AK, Goswami BN (2013) Role of ocean-atmosphere interaction on northward propagation of Indian summer monsoon intra-seasonal oscillations (MISO). Clim Dyn 41:1651–1669. doi:10.1007/s00382-013-1854-1

    Article  Google Scholar 

  • Slingo JM, Sperber KR, Boyle JS, Ceron J-P, Dix M, Dugas B, Ebisuzaki W, Fyfe J, Gregory D, Gueremy J-F, Hack J, Harzallah A, Inness P, Kitoh A, Lau WK-M, McAvaney B, Madden R, Matthews A, Palmer TN, Parkas C-K, Randall D, Renno N (1996) Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject. Clim Dyn 12:325–357. doi:10.1007/BF00231106

    Article  Google Scholar 

  • Sperber KR, Annamalai H (2008) Coupled model simulations of boreal summer intraseasonal (30–50 day) variability, Part 1: systematic errors and caution on use of metrics. Clim Dyn 31:345–372. doi:10.1007/s00382-008-0367-9

    Article  Google Scholar 

  • Sperber KR, Palmer TN (1996) Inter-annual tropical rainfall variability in general circulation model simulations associated with the atmospheric model inter-comparison project. J Clim 9:2727–2750

    Article  Google Scholar 

  • Suhas E, Neena JM, Goswami BN (2013) An Indian monsoon intraseasonal oscillations (MISO) index for real time monitoring and forecast verification. Clim Dyn 40:2605–2616. doi:10.1007/s00382-012-1462-5

    Article  Google Scholar 

  • Ueda H, Yasunari T (1998) Role of warming over the Tibetan Plateau in early onset of the summer monsoon over the Bay of Bengal and the South China Sea. J Meteorol Soc Jpn 76:1–12

    Google Scholar 

  • Waliser DE (2006) Intraseasonal variability. In: Wang B (ed) The Asian monsoon, 1st edn. Springer Praxis Books, Berlin, pp 203–257

    Chapter  Google Scholar 

  • Waliser DE, Jin K, Kang I-S, Stern WF, Schubert SD, Wu MLC, Lau K-M, Lee M-I, Krishnamurthy V, Kitoh A, Meehl GA, Galin VY, Satyan V, Mandke SK, Wu G, Liu Y, Park C-K (2003) AGCM simulations of intraseasonal variability associated with the Asian summer monsoon. Clim Dyn 21:423–446. doi:10.1007/s00382-003-0337-1

    Article  Google Scholar 

  • Wang B, Kang I-S, Lee J-Y (2004) Ensemble simulations of Asian-Australian monsoon variability by 11 AGCMs. J Clim 17:803–818. doi:10.1175/1520-0442(2004)017<0803:ESOAMV>2.0.CO;2

    Article  Google Scholar 

  • Wang B, Ding Q, Fu X, Kang I-S, Jin K, Shukla J, Doblas-Reyes F (2005) Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys Res Lett. doi:10.1029/2005GL022734

    Google Scholar 

  • Wang B, Lee J-Y, Kang I-S, Shukla J, Kug J-S, Kumar A, Schemm J, Luo J-J, Yamagata T, Park C-K (2008) How accurately do coupled climate models predict the leading modes of Asian-Australian monsoon interannual variability? Clim Dyn 30:605–619. doi:10.1007/s00382-007-0310-5

    Article  Google Scholar 

  • Webster PJ, Magana VO, Palmer TN, Shukla J, Tomas RA, Yanai M, Yasunari T (1998) Monsoons: processes, predictability and the prospectus for prediction. J Geophys Res 103:14451–14510

    Article  Google Scholar 

  • Wu X, Liang X, Zhang GJ (2003) Seasonal migration of ITCZ precipitation across the equator: why Can’t GCMs simulate it. Geophys Res Lett 30. doi:10.1029/2003GL017198

  • Xavier PK, Marzin C, Goswami BN (2007) An objective definition of the Indian summer monsoon season and a new perspective on the ENSO-monsoon relationship. Q J R Meteorol Soc 133:749–764

    Article  Google Scholar 

  • Xiouhua F, Lee J-Y, Wang B, Wang W, Vitart V (2013) Intraseasonal forecasting of the Asian summer monsoon in Four operational and research models. J Clim 26:4186–4203. doi:10.1175/JCLI-D-12-00252.1

    Article  Google Scholar 

  • Yanai M, Esbensen S, Chu J-H (1973) Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets. J Atmos Sci 30:611–627. doi:10.1175/1520-0469(1973)030<0611:DOBPOT>2.0.CO;2

    Article  Google Scholar 

  • Yang S, Smith EA (2006) Mechanisms for diurnal variability of global tropical rainfall observed from TRMM. J Clim 19:5190–5226

    Article  Google Scholar 

  • Yang S, Zhang Z, Kousky VE, Higgins RW, Yoo S-H, Liang J, Fan Y (2008) Simulations and seasonal prediction of the Asian summer monsoon in the NCEP climate forecast system. J Clim 21:3755–3775. doi:10.1175/2008JCLI1961.1

    Article  Google Scholar 

  • Yoo H, Li Z, Hou Y-T, 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 41:1595–1613

    Google Scholar 

  • Zhang GJ, Mu M (2005) Simulation of the Madden–Julian oscillation in the NCAR CCM3 using a revised Zhang–McFarlane convection parameterization scheme. J Clim 18:4046–4064. doi:10.1175/JCLI3508.1

    Article  Google Scholar 

  • Zhang C, Dong M, Gualdi S, Hendon HH, Maloney ED, Marshall A, Sperber KR, Wang W (2006) Simulations of the Madden-Julian oscillation in four pairs of coupled and uncoupled global models. Clim Dyn 27:573–592. doi:10.1007/s00382-006-0148-2

    Article  Google Scholar 

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

    Article  Google Scholar 

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Acknowledgments

The Indian Institute of Tropical Meteorology (Pune, India) is fully funded by the Ministry of Earth Sciences, Government of India, New Delhi. We would like to thank India Meteorological Department (IMD), New Delhi for gridded rainfall dataset. We thank the TRMM Science Data and Information System (TSDIS) and the Goddard Distributed Active Archive Center for providing us the TRMM data. We thank the National Center for Environmental Prediction (NCEP) for the reanalysis data used in this paper. We gratefully acknowledge Dr. Shrinivas Moorthi of NCEP/EMC/Global Modeling Branch and Dr. Jongil Han of Wyle Information Systems LLC, and NCEP/EMC, USA for their useful suggestions and discussions towards implementation of revised SAS in CFSv2. Authors thank the anonymous reviewers for the constructive suggestions on the paper which has helped to improve the paper.

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

    Malay Ganai, P. Mukhopadhyay, R. Phani Murali Krishna & M. Mahakur

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Ganai, M., Mukhopadhyay, P., Krishna, R.P.M. et al. 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 (2015). https://doi.org/10.1007/s00382-014-2320-4

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