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On unravelling mechanism of interplay between cloud and large scale circulation: a grey area in climate science

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Abstract

The interaction between cloud and large scale circulation is much less explored area in climate science. Unfolding the mechanism of coupling between these two parameters is imperative for improved simulation of Indian summer monsoon (ISM) and to reduce imprecision in climate sensitivity of global climate model. This work has made an effort to explore this mechanism with CFSv2 climate model experiments whose cloud has been modified by changing the critical relative humidity (CRH) profile of model during ISM. Study reveals that the variable CRH in CFSv2 has improved the nonlinear interactions between high and low frequency oscillations in wind field (revealed as internal dynamics of monsoon) and modulates realistically the spatial distribution of interactions over Indian landmass during the contrasting monsoon season compared to the existing CRH profile of CFSv2. The lower tropospheric wind error energy in the variable CRH simulation of CFSv2 appears to be minimum due to the reduced nonlinear convergence of error to the planetary scale range from long and synoptic scales (another facet of internal dynamics) compared to as observed from other CRH experiments in normal and deficient monsoons. Hence, the interplay between cloud and large scale circulation through CRH may be manifested as a change in internal dynamics of ISM revealed from scale interactive quasi-linear and nonlinear kinetic energy exchanges in frequency as well as in wavenumber domain during the monsoon period that eventually modify the internal variance of CFSv2 model. Conversely, the reduced wind bias and proper modulation of spatial distribution of scale interaction between the synoptic and low frequency oscillations improve the eastward and northward extent of water vapour flux over Indian landmass that in turn give feedback to the realistic simulation of cloud condensates attributing improved ISM rainfall in CFSv2.

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References

  • Abhilash S, Sahai AK, Pattanaik S, De S (2013) Predictability during active break phases of Indian summer monsoon in an ensemble prediction system using climate forecast system. J Atmos Solar Terres Phys. https://doi.org/10.1016/j.jastp.2013.03.017, 13–23

  • Abhilash S, Sahai AK, Borah N, Chattopadhyay R, joseph S, Sharmila S, De S, Goswami BN, Arun Kumar (2014) Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2. Clim Dyn 1–15. https://doi.org/10.1007/s00382-013-2045-9

  • Agarwal NK, Naik SS, De S, Sahai AK (2016) Why are the Indian monsoon transients short-lived and less intensified during droughts vis-à-vis good monsoon years? An inspection through scale interactive energy exchanges in frequency domain. Int J Climatol 36:2958–2978. https://doi.org/10.1002/joc.4531 DOI

    Article  Google Scholar 

  • Boer GJ (1984) A spectral analysis of predictability and error in an operational forecast system. Mon Weather Rev 112:1183–1197

    Article  Google Scholar 

  • Bony S et al (2015) Clouds, circulation and climate sensitivity. Nat Geosci. https://doi.org/10.1038/NGEO2398

    Google Scholar 

  • Charney JG, Shukla J (1981) Predictability of monsoons. In: Lighthill J, Pearce RP (eds) Monsoon dynamics. Cambridge University Press, Cambridge, pp 99–109

    Chapter  Google Scholar 

  • Clough SA, Shephard MW, Mlawer EJ, Delamere JS, Iacono MJ, Cady-Pereira K, Boukabara S, Brown PD (2005) Atmospheric radiative transfer modeling: a summary of the AER codes. J Quant Spectrosc Radiat Transf 91:233–244

    Article  Google Scholar 

  • Dakshinamurti J, Keshavamurty RN (1976) On Oscillations of period around one month in the Indain summer monsoon. Indian J Met Hydrol Geophys 27:201–203

    Google Scholar 

  • De S (2010a) Role of nonlinear scale interactions in limiting dynamical prediction of lower tropospheric boreal summer intraseasonal oscillations. J Geophys Res 115(D21127):1–18. https://doi.org/10.1029/2010JD013955

    Google Scholar 

  • De S (2010b) Investigating origin of the inadequate medium range predictability of the lower tropospheric ultra-long waves in tropics. J Earth Syst Sci 119:783–802. https://doi.org/10.1007/s12040-010-0059-9

    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 forecasts?: evaluation through thermodynamical and dynamical aspects. Clim Dyn 46:1197–1222. https://doi.org/10.1007/s00382-015-2640-z

    Article  Google Scholar 

  • Ek M, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley JD (2003) Implementation of Noah land-surface model advances in the NCEP operational mesoscale Eta model. J Geophys Res 108:8851. https://doi.org/10.1029/2002JD003296

    Article  Google Scholar 

  • Gadgil S, Rajeevan M, Nanjundiah R (2005) Monsoon prediction—why yet another failure? Curr Sci 88:1389–1400

    Google Scholar 

  • Goswami BB, Krishna RPM, Mukhopadhyay P, Khairoutdinov M, Goswami BN (2015) Simulation of the Indian summer monsoon in the superparameterized climate forecast system version 2: preliminary results. J Clim 28:8988–9012. https://doi.org/10.1175/JCLI-D-14-00607.1

    Article  Google Scholar 

  • Goswami BB, Khouider B, Phani R, Mukhopadhyay P, Majda A (2016) Improving synoptic and intraseasonal variability in CFSv2 via stochastic representation of organized convection. Geophys Res Lett. https://doi.org/10.1002/2016GL071542

  • Griffies SM, Harrison MJ, Pacanowski RC, Rosati A (2004) A Technical guide to MOM4, GFDL Ocean Group Technical Report 5, p 337

  • Hayashi Y (1980) Estimation of non-linear energy transfer spectra by the cross spectral method. J Atmos Sci 37:299–307

    Article  Google Scholar 

  • Hazra A, Chaudhari HS, Pokhrel S, Saha Subodh K (2016) Indian summer monsoon precipitating clouds: role of microphysical process rates. Clim Dyn 46:2551–2571. https://doi.org/10.1007/s00382-015-2717-8

    Article  Google Scholar 

  • Held IM, Hoskins BJ (1985) Large-scale eddies and the general circulation of the troposphere. Adv Geophys 28A:3–31

    Article  Google Scholar 

  • Hong S-Y, Pan H-L (1998) Convective trigger function for a mass-flux cumulus parameterization scheme. Mon Weather Rev 126:2599–2620

    Article  Google Scholar 

  • Iacono MJ, Mlawer EJ, Clough SA, Morcrette JJ (2000) Impact of an improved longwave radiation model, RRTM, on the energy budget and thermodynamic properties of the NCAR Community Climate Model, CCM3. J Geophys Res 105:14873–14890

    Article  Google Scholar 

  • Jung T (2005) Systematic errors of the atmospheric circulations in the ECMWF forecasting system. Q J R Meteorol Soc 131:1045–1073. https://doi.org/10.1256/qj.04.93

    Article  Google Scholar 

  • Kanamitsu M (1985) A study of predictability of ECMWF operational forecast model in the tropics. J Met Soc Jpn 63:779–804

    Article  Google Scholar 

  • Kanamitsu M, Saha S (1995) Spectral budget of short range forecast error of NMC MRF model. Mon Weather Rev 123:1834–1850

    Article  Google Scholar 

  • Kang IS, Shukla J (2006) Dynamical seasonal prediction and predictability of the monsoon. In: Wang B (ed) Section 15, The Asian Monsoon. Springer, USA

    Google Scholar 

  • Kang IS, Lee JY, Park CK (2004) Potential predictability of summer mean precipitation in a dynamical seasonal prediction system with systematic error correction. J Clim 17:834–844

    Article  Google Scholar 

  • Kripalani RH, Kulkarni A, Sabade SS, Revadekar JV, Patwardhan SK, Kulkarni JR (2004) Intra-seasonal oscillations during monsoon 2002 and 2003. Curr Sci 87:325–331

    Google Scholar 

  • Krishnamurti TN, Ardanuy P (1980) The 10 to 20 day westward propagating mode and breaks in the monsoon. Tellus 32:15–26

    Google Scholar 

  • Krishnamurti TN, Subrahmanyam D (1982) The 30–50 day mode at 850 Mb during MONEX. J Atmos Sci 39:2088–2095

    Article  Google Scholar 

  • Krishnamurti TN, Chakraborty DR, Cubucku N, Stefanova L, Kumar TSVV. (2003) A mechanism of the Madden–Julian Oscillation based on interactions in frequency domain. Q J R Meteorol Soc 129:2559–2590

    Article  Google Scholar 

  • Kulkarni A, Kripalani RH, Sabade SS, Rajeevan M (2011) Role of intra-seasonal oscillations in modulating Indian summer monsoon rainfall. Clim Dyn 36:1005–1021

    Article  Google Scholar 

  • Lorenz EN (1969) The predictability of a flow which possesses many scales of motion. Tellus 21:289–308

    Article  Google Scholar 

  • Mooley DA, Shukla J (1987) Characteristics of the westward moving summer monsoon low pressure systems over the Indian region and its relationship with the monsoon rainfall. Department of Meteorology, University of Maryland, College Park

    Google Scholar 

  • Moorthi S, Sun R, Xiao H, Mechoso RC (2010) Southeast Pacific low-cloud simulation in the NCEP GFS: role of vertical mixing and shallow convection. NCEP Office Note 463, p 28. http://www.emc.ncep.noaa.gov/officenotes/FullTOC.html#2000

  • Niranjan Kumar K, Rajeevan M, Pai DS, Srivastava AK, Preethi B (2013) On the observed variability of monsoon droughts over India. Weather Clim Extremes 1:42–50

    Article  Google Scholar 

  • Palmer TN (1994) Chaos and predictability in forecasting the monsoon. Proc Indian Natl Sci Acad 60:57–66

    Google Scholar 

  • Pan HL, Wu WS (1995) Implementing a mass flux convective parameterization package for the NMC Medium-Range Forecast model. NMC Off Note 409:40

    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. https://doi.org/10.1007/s00382-013-1662-7

    Article  Google Scholar 

  • Preethi B, Revadekar JV, Kripalani RH (2011) Anomalous behaviour of Indian summer monsoon 2009. J Earth Syst Sci 120:783–794

    Article  Google Scholar 

  • Quass 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 Gephys Res 117:D09208. https://doi.org/10.1029/2012JD017495

    Google Scholar 

  • Rowell DP (1998) Assessing potential seasonal predictability with an ensemble of multidecadal GCM simulations. J Clim 11:109–120

    Article  Google Scholar 

  • Saha S, Moorthi S, Pan H-L, Wu X, Wang J, Nadiga S, Tripp P, Kistler R, Woollen J, Behringer D, Liu H, Stokes D, Grumbine R, Gayno G, Wang J, Hou YT, Chuang HY, Juang H-MH, Sela J, Iredell M, Treadon R, Kleist D, Delst PV, Keyser D, Derber J, Ek M, Meng J, Wei H, Yang R, Lord S, Dool HVD, Kumar A, Wang W, Long C, Chelliah M, Xue Y, Huang B, Schemm JK, Ebisuzaki W, Lin R, Xie P, Chen M, Zhou S, Higgins W, Zou CZ, Liu Q, Chen Y, Han Y, Cucurull L, Reynolds RW, Rutledge G, Goldberg M (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol 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, Mendez MP, van den Dool H, Zhang Q, Wang W, Chen M, Becker E (2013) The NCEP climate forecast system version 2. J Clim. https://doi.org/10.1175/JCLI-D-12-00823.1

    Google Scholar 

  • Saha SK, Sujith K, Pokhrel S, Chaudhari HS, Hazra A (2017), Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEP CFSv2, J Adv Model Earth Syst 9 https://doi.org/10.1002/2016MS000845

  • Saltzman B (1957) Equations governing the energetics of the large scales of atmospheric turbulence in the domain of wave number. J Meteorol 14:513–523

    Article  Google Scholar 

  • Shepherd TG (2014) Atmospheric circulation as a source of uncertainty in climate change projections. Nat Geosci 7:703–708 https://doi.org/10.1038/NGEO2253

    Article  Google Scholar 

  • Sikka DR (1980) Some aspects of large-scale fluctuations of summer monsoon rainfall over India in relation to fluctuations in the planetary and regional scale circulation parameters. Proc Ind Acad Sci (Earth Planet Sci) 89:179–195

    Google Scholar 

  • Sikka DR (2006) A study on the monsoon low pressure systems over the Indian region and their relationship with drought and excess monsoon seasonal rainfall. COLA Technical Report CTR217

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

    Article  Google Scholar 

  • Slingo A, Wilderspin RC, Brentnall SJ (1987) Simulation of the diurnal cycle of outgoing longwave radiation with an atmospheric GCM. Mon Weather Rev 115:1451–1457

    Article  Google Scholar 

  • Stevens B, Bony S (2013) What are climate models missing? Science 340:1053–1054 https://doi.org/10.1126/science.1237554

    Article  Google Scholar 

  • Suhas E, Neena JM, Goswami BN (2012) Interannual variability of Indian Summer Monsoon arising from interactions between seasonal mean and intraseasonal oscillations. J Atmos Sci 69:1761–1774. https://doi.org/10.1175/JAS-D-11-0211.1

    Article  Google Scholar 

  • Sun R, Moorthi S, Mechoso CR (2010) Simulation of low clouds in the Southeast Pacific by the NCEP GFS: sensitivity to vertical mixing. Atmos Chem Phys 10:12261–12272

    Article  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

    Article  Google Scholar 

  • Walcek CJ, Stockwell WR, Chang JS (1990) Theoretical estimates of the dynamic, radiative, and chemical effects of clouds on tropospheric trace gases. Atmos Res 25:53–69

    Article  Google Scholar 

  • Williamson DL, Keihl JT, Ramanathan V, Dickinson RE, Hack JJ (1987) Description of the NCAR community climate model (CCM). NCAR Tech Note NCAR/TN-285 + STR, National Center for Atmospheric Research, Boulder, CO, p 112

  • Wu X, Moorthi KS, Okomoto K, Pan HL (2005) Sea ice impacts on GFS forecasts at high latitudes. In: Eighth conference on polar meteorology and oceanography. Am Meteorool Soc San Diego, CA 7.4

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

    Article  Google Scholar 

Download references

Acknowledgements

Authors are thankful to Director; IITM for providing constant encouragement to carry out the research work. High Power Computing System (HPCS), Prithvi facility is highly acknowledged. Thanks are due to ERA, CFSR for the free data availability. Authors are also thankful to Brian Doty, COLA for the use of GrADS software. Anonymous reviewers’ comments are also gratefully acknowledged. The model output data for different experiments of CFSv2 are in the archive of national monsoon mission project, Ministry of Earth Science, Govt. of India and may be disseminated after taking permission from appropriate authority.

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Appendix

Appendix

Mathematical equation for error energy growth rate budget:

$$\begin{aligned} &\mathop { \sum }\limits_{n} \left[ {\frac{\partial }{{\partial t}}\left( {\frac{1}{2}{u_e}C_{n}^{2}} \right)+\frac{\partial }{{\partial t}}\left( {\frac{1}{2}{u_e}S_{n}^{2}} \right)+\frac{\partial }{{\partial t}}\left( {\frac{1}{2}{v_e}C_{n}^{2}} \right)+\frac{\partial }{{\partial t}}\left( {\frac{1}{2}{v_e}S_{n}^{2}} \right)} \right]= - \frac{1}{2}\left( {\mathop \sum \limits_{{n=r+s}}^{{}} +\mathop \sum \limits_{{n=r - s}} +\mathop \sum \limits_{{n=s - r}} } \right), \\ & \quad \times \left\{ {\begin{array}{*{20}{c}} {{u_m}{C_n} \cdot {u_e}{C_r}\frac{{\partial {u_e}{C_s}}}{{\partial x}}+{u_m}{C_n} \cdot {v_e}{C_r}\frac{{\partial {v_e}{C_s}}}{{\partial x}}+\frac{1}{2}\frac{{\partial {u_m}{C_n}}}{{\partial x}}{u_e}{C_r} \cdot {u_e}{C_s}+\frac{1}{2}\frac{{\partial {u_m}{C_n}}}{{\partial x}}{v_e}{C_r} \cdot {v_e}{C_s}} \\ {+{v_m}{C_n} \cdot {u_e}{C_r}\frac{{\partial {u_e}{C_s}}}{{\partial y}}+{v_m}{C_n} \cdot {v_e}{C_r}\frac{{\partial {v_e}{C_s}}}{{\partial y}}+\frac{1}{2}\frac{{\partial {v_m}{C_n}}}{{\partial y}}{u_e}{C_r} \cdot {u_e}{C_s}+\frac{1}{2}\frac{{\partial {v_m}{C_n}}}{{\partial y}}{v_e}{C_r} \cdot {v_e}{C_s}} \end{array}} \right\}F, \\ & \quad - \frac{1}{2}\left( { - \mathop \sum \limits_{{n=r+s}} +\mathop \sum \limits_{{n=r - s}} +\mathop \sum \limits_{{n=s - r}} } \right)\left\{ {\begin{array}{*{20}{c}} {{u_m}{C_n} \cdot {u_e}{S_r}\frac{{\partial {u_e}{S_s}}}{{\partial x}}+{u_m}{C_n} \cdot {v_e}{S_r}\frac{{\partial {v_e}{S_s}}}{{\partial x}}+\frac{1}{2}\frac{{\partial {u_m}{C_n}}}{{\partial x}}{u_e}{S_r} \cdot {u_e}{S_s}} \\ {+\frac{1}{2}\frac{{\partial {u_m}{C_n}}}{{\partial x}}{v_e}{S_r} \cdot {v_e}{S_s}+{v_m}{C_n} \cdot {u_e}{S_r}\frac{{\partial {u_e}{S_s}}}{{\partial y}}+{v_m}{C_n} \cdot {v_e}{S_r}\frac{{\partial {v_e}{S_s}}}{{\partial y}}} \\ {+\frac{1}{2}\frac{{\partial {v_m}{C_n}}}{{\partial y}}{u_e}{S_r} \cdot {u_e}{S_s}+\frac{1}{2}\frac{{\partial {v_m}{C_n}}}{{\partial y}}{v_e}{S_r} \cdot {v_e}{S_s}} \end{array}} \right\}L, \\ & \quad - \frac{1}{2}\left( {\mathop \sum \limits_{{n=r+s}} - \mathop \sum \limits_{{n=r - s}} +\mathop \sum \limits_{{n=s - r}} } \right)\left\{ {\begin{array}{*{20}{c}} {{u_m}{S_n} \cdot {u_e}{C_r}\frac{{\partial {u_e}{S_s}}}{{\partial x}}+{u_m}{S_n} \cdot {v_e}{C_r}\frac{{\partial {v_e}{S_s}}}{{\partial x}}+\frac{1}{2}\frac{{\partial {u_m}{S_n}}}{{\partial x}}{u_e}{C_r} \cdot {u_e}{S_s}} \\ {+\frac{1}{2}\frac{{\partial {u_m}{S_n}}}{{\partial x}}{v_e}{C_r} \cdot {v_e}{S_s}+{v_m}{S_n} \cdot {u_e}{C_r}\frac{{\partial {u_e}{S_s}}}{{\partial y}}+{v_m}{S_n} \cdot {v_e}{C_r}\frac{{\partial {v_e}{S_s}}}{{\partial y}}} \\ {+\frac{1}{2}\frac{{\partial {v_m}{S_n}}}{{\partial y}}{u_e}{C_r} \cdot {u_e}{S_s}+\frac{1}{2}\frac{{\partial {v_m}{S_n}}}{{\partial y}}{v_e}{C_r} \cdot {v_e}{S_s}} \end{array}} \right\}U, \\ & \quad - \frac{1}{2}\left( {\mathop \sum \limits_{{n=r+s}} +\mathop \sum \limits_{{n=r - s}} - \mathop \sum \limits_{{n=s - r}} } \right)\left\{ {\begin{array}{*{20}{c}} {{u_m}{S_n} \cdot {u_e}{S_r}\frac{{\partial {u_e}{C_s}}}{{\partial x}}+{u_m}{S_n} \cdot {v_e}{S_r}\frac{{\partial {v_e}{C_s}}}{{\partial x}}+\frac{1}{2}\frac{{\partial {u_m}{S_n}}}{{\partial x}}{u_e}{S_r} \cdot {u_e}{C_s}} \\ {+\frac{1}{2}\frac{{\partial {u_m}{S_n}}}{{\partial x}}{v_e}{S_r} \cdot {v_e}{C_s}+{v_m}{S_n} \cdot {u_e}{S_r}\frac{{\partial {u_e}{C_s}}}{{\partial y}}+{v_m}{S_n} \cdot {v_e}{S_r}\frac{{\partial {v_e}{C_s}}}{{\partial y}}} \\ {+\frac{1}{2}\frac{{\partial {v_m}{S_n}}}{{\partial y}}{u_e}{S_r} \cdot {u_e}{C_s}+\frac{1}{2}\frac{{\partial {v_m}{S_n}}}{{\partial y}}{v_e}{S_r} \cdot {v_e}{C_s}} \end{array}} \right\}X, \\ & \quad - \frac{1}{2}\left( {\mathop \sum \limits_{{n=r+s}} +\mathop \sum \limits_{{n=r - s}} +\mathop \sum \limits_{{n=s - r}} } \right)\left\{ {\begin{array}{*{20}{c}} {\frac{{\partial {u_a}{C_n}}}{{\partial x}}{u_e}{C_r} \cdot {u_e}{C_s}+\frac{{\partial {u_a}{C_n}}}{{\partial y}}{u_e}{C_r} \cdot {v_e}{C_s}+\frac{{\partial {v_a}{C_n}}}{{\partial x}}{u_e}{C_r} \cdot {v_e}{C_s}} \\ {+\frac{{\partial {v_a}{C_n}}}{{\partial y}}{v_e}{C_r} \cdot {v_e}{C_s}} \end{array}} \right\}GE, \\ & \quad - \frac{1}{2}\left( { - \mathop \sum \limits_{{n=r+s}} +\mathop \sum \limits_{{n=r - s}} +\mathop \sum \limits_{{n=s - r}} } \right)\left\{ {\begin{array}{*{20}{c}} {\frac{{\partial {u_a}{C_n}}}{{\partial x}}{u_e}{S_r} \cdot {u_e}{S_s}+\frac{{\partial {u_a}{C_n}}}{{\partial y}}{u_e}{S_r} \cdot {v_e}{S_s}+\frac{{\partial {v_a}{C_n}}}{{\partial x}}{u_e}{S_r} \cdot {v_e}{S_s}} \\ {+\frac{{\partial {v_a}{c_n}}}{{\partial y}}{v_e}{S_r} \cdot {v_e}{S_s}} \end{array}} \right\}NE, \\ & \quad - \frac{1}{2}\left( {\mathop \sum \limits_{{n=r+s}} - \mathop \sum \limits_{{n=r - s}} +\mathop \sum \limits_{{n=s - r}} } \right)\left\{ {\begin{array}{*{20}{c}} {\frac{{\partial {u_a}{S_n}}}{{\partial x}}{u_e}{C_r} \cdot {u_e}{S_s}+\frac{{\partial {u_a}{S_n}}}{{\partial y}}{u_e}{C_r} \cdot {v_e}{S_s}+\frac{{\partial {v_a}{S_n}}}{{\partial x}}{u_e}{C_r} \cdot {v_e}{S_s}} \\ {+\frac{{\partial {v_a}{S_n}}}{{\partial y}}{v_e}{C_r} \cdot {v_e}{S_s}} \end{array}} \right\}RA, \\ & \quad - \frac{1}{2}\left( {\mathop \sum \limits_{{n=r+s}} +\mathop \sum \limits_{{n=r - s}} - \mathop \sum \limits_{{n=s - r}} } \right)\left\{ {\begin{array}{*{20}{c}} {\frac{{\partial {u_a}{S_n}}}{{\partial x}}{u_e}{S_r} \cdot {u_e}{C_s}+\frac{{\partial {u_a}{S_n}}}{{\partial y}}{u_e}{S_r} \cdot {v_e}{C_s}+\frac{{\partial {v_a}{S_n}}}{{\partial x}}{u_e}{S_r} \cdot {v_e}{C_s}} \\ {+\frac{{\partial {v_a}{S_n}}}{{\partial y}}{v_e}{S_r} \cdot {v_e}{C_s}} \end{array}} \right\}TION, \\ & \quad +{\text{ }}{V_e} \cdot R{\text{ }}\left( {RESIDUAL} \right). \\ \end{aligned}$$
(5)

In the above equation, umC, vmC and umS, vmS are the cosine and sine component of zonal and meridional wind field of model output, respectively. Similarly, uaC, vaC and uaS, vaS are the cosine and sine component of zonal and meridional analysis/observed wind field, respectively. The subscript n, r and s represent three wavenumber of participating waves in triad interactions. The left hand side of the equation evaluates the spectral error growth rate term. The extent of flux, generation and residual term are shown by indicating outside the second bracket in the right hand side of above equation.

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De, S., Agarwal, N.K., Hazra, A. et al. On unravelling mechanism of interplay between cloud and large scale circulation: a grey area in climate science. Clim Dyn 52, 1547–1568 (2019). https://doi.org/10.1007/s00382-018-4211-6

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