Skip to main content

Advertisement

SpringerLink
Log in

Indian summer monsoon simulations in successive generations of the NCAR Community Atmosphere Model

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Four generations of the NCAR Community Atmosphere Model (CAM3, 4, 5, and 6) are used to assess model upgrades to the Indian summer monsoon rainfall (ISMR) simulations. The total precipitation simulation in CAM3 is significantly overestimated over the western equatorial Indian Ocean, Arabian Sea, and southwest Bay of Bengal (BoB), and underestimated over the northern BoB due to overestimated convective and underestimated large-scale precipitation, respectively. In the subsequent CAM versions, the simulation of total precipitation has improved, except for the wet bias over the Western Ghats and Himalayan foothills, which has deteriorated due to increased convective and large-scale precipitation, respectively. The improvement in total precipitation simulation over the northern BoB is found in successive CAM versions from the increased heating and drying of the troposphere. CAM3 overestimates the frequency of low precipitation rates and underestimates the frequency of high precipitation rates, which is improved in CAM4, but deteriorated further in subsequent CAM versions. The model development cycle from CAM3 to CAM6 also led to a substantial improvement in most ISMR-associated circulation features, except for the successive overestimation in the low-level monsoon jet due to a strengthened easterly shear of zonal wind. The simulation of subtropical westerly and tropical easterly jets has become more reliable in subsequent CAM versions. In addition, we find successive improvements in the monsoon intra-seasonal oscillation (MISO), associated internal dynamics, and the east-west and north-south heat source. However, some important biases (e.g., the eastward component of MISO, monsoon low-level jet, excessive precipitation over Himalayan foothills, early monsoon onset) need to be alleviated for more realistic ISM simulations by improving further the cloud microphysical and moist processes in the future CAM versions.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

Data availability

The observed data used in this study is publicly available, and the model-simulated data can be obtained from the corresponding author.

References

  • Abhik S, Halder M, Mukhopadhyay P, Jiang X, Goswami BN (2013) A possible new mechanism for northward propagation of boreal summer intra-seasonal oscillations based on TRMM and MERRA reanalysis. Clim Dyn 40:1611–1624

    Article  Google Scholar 

  • Albani S, Mahowald N, Perry A, Scanza R, Zender C, Heavens N, Maggi V, Kok J, Otto-Bleisner B (2014) Improved dust representation in the Community Atmosphere Model. J Adv Model Earth Syst 6:541–570. https://doi.org/10.1002/2013MS000279

    Article  Google Scholar 

  • Anand A, Mishra SK, Sahany S, Bhowmick M, Rawat JS, Dash SK (2018) Indian summer monsoon simulations: usefulness of increasing horizontal resolution, manual tuning, and semi-automatic tuning in reducing present-day model biases. Sci Rep 8:3522. https://doi.org/10.1038/s41598-018-21865-1

    Article  Google Scholar 

  • Annamalai H, Hamilton K, Sperber KR (2007) The South Asian summer monsoon and its relationship with ENSO in the IPCC AR4 simulations. J Clim 20:1071–1092. https://doi.org/10.1175/JCLI4035

    Article  Google Scholar 

  • Annamalai H, Slingo JM (2001) Active/break cycles: diagnosis of the intra-seasonal variability of the Asian summer monsoon. Clim Dyn 18:85–102

    Article  Google Scholar 

  • Bogenschutz PA, Gettelman A, Hannay C, Larson VE, Neale RB, Craig C, Chen CC (2018) The path to CAM6: coupled simulations with CAM5.4 and CAM5.5. Geosci Model Dev 11:235–255. https://doi.org/10.5194/gmd-11-235-2018

    Article  Google Scholar 

  • Bogenschutz PA, Gettelman A, Morrison H, Larson VE, Craig C, Schanen DP (2013) Higher-order turbulence closure and its impact on climate simulations in the Community Atmosphere Model. J Clim 26(23):9655–9676

    Article  Google Scholar 

  • Bollasina M, Nigam S (2009) Indian Ocean SST, evaporation, and precipitation during the South Asian summer monsoon in IPCC-AR4 coupled simulations. Clim Dyn 33:1017–1032. https://doi.org/10.1007/s00382-008-0477-4

    Article  Google Scholar 

  • Bretherton CS, Park S (2009) A new moist turbulence parameterization in the Community Atmosphere Model. J Clim 22:3422–3448

    Article  Google Scholar 

  • Brunner L, Pendergrass AG, Lehner F, Merrifield AL, Lorenz R, Knutti R (2020) Reduced global warming from CMIP6 projections when weighting models by performance and independence. Earth Syst Dynam 11:995–1012. https://doi.org/10.5194/esd-11-995-2020

    Article  Google Scholar 

  • Chen L et al (2022) Variability of indian monsoon and its forcing mechanisms since late quaternary. Front Earth Sci 10. https://doi.org/10.3389/feart.2022.977250

  • Choudhury BA, Rajesh PV, Zahan Y et al (2022) Evolution of the Indian summer monsoon rainfall simulations from CMIP3 to CMIP6 models. Clim Dyn 58:2637–2662. https://doi.org/10.1007/s00382-021-06023-0

    Article  Google Scholar 

  • Collin WD, Rasch PJ, Boville BA, Hack JJ, McCaa JR, Williamson DL, Kiehl JT, Briegleb B, Bitz C, Lin SJ, Zhang M, Dai Y (2004) Description of the NCAR Community Atmosphere Model (CAM3). Technical Report NCAR/TN-464+STR National Center for Atmospheric Research Boulder Colorado 80307-3000, 226 pp

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

    Article  Google Scholar 

  • Danabasoglu G, Lamarque JF, Bacmeister J, Bailey DA, DuVivier AK, Edwards J (2020) The community earth system model version 2 (CESM2). J Adv Model Earth Syst 12:e2019MS001916. https://doi.org/10.1029/2019MS001916

    Article  Google Scholar 

  • Dee D et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. https://doi.org/10.1002/qj.828

    Article  Google Scholar 

  • Dong T, Dong W (2021) Evaluation of extreme precipitation over Asia in CMIP6 models. Clim Dyn 57:1751–1769. https://doi.org/10.1007/s00382-021-05773-1

    Article  Google Scholar 

  • Dunning CM, Turner AG, Brayshaw DJ (2015) The impact of monsoon intra-seasonal variability on renewable power generation in India. Environ Res Lett 10:064002. https://doi.org/10.1088/1748-9326/10/6/064002

    Article  Google Scholar 

  • Eyring V et al (2019) Taking climate model evaluation to the next level. Nat Clim Change 9(2):102–110

    Article  Google Scholar 

  • Gadgil S (2003) The Indian monsoon and its variability. Annu Rev Earth Planet Sci 31(1):429–467

  • Gadgil S, Gadgil S (2006) The Indian Monsoon, GDP and agriculture. Econo Polit Weekly 41:4887–4895

    Google Scholar 

  • Gadgil S, Kumar KR (2006) The Asian monsoon-agriculture and economy. Asian Monsoon:651–683

  • Gadgil S, Sajani S (1998) Monsoon precipitation in the AMIP runs. Clim Dyn 14:659–6889. https://doi.org/10.1007/s003820050248

    Article  Google Scholar 

  • Geller MA, Zhou T, Ruedy R, Aleinov I, Nararenko L, Tausnev NL, Sun S, Kelley M, Cheng Y (2011) New gravity wave treatments for GISS climate models. J Clim 24(15):3989–4002

    Article  Google Scholar 

  • Gent PR, Yeager S, Neale RB, Levis S, Bailey D (2009) Improvements in a half degree atmopshere/land version of the CCSM. Clim Dynam 79:25–58

    Google Scholar 

  • Gettelman A, Hegglin MI, Son SW, Kim J, Fujiwara M, Birner T et al (2010) Multimodel assessment of the upper troposphere and lower stratosphere: tropics and global trends. J Geophys Res Atmos 115(D3)

  • Gettelman A, Morrison H (2015) Advanced two-moment bulk microphysics for global models. Part I: off-line tests and comparison with other schemes. J Clim 28(3):1268–1287

    Article  Google Scholar 

  • Goswami BN (1998) Interannual variations of Indian summer monsoon in a GCM: external conditions versus internal feedbacks. J Clim 11(4):501–522

    Article  Google Scholar 

  • Goswami BN (2011) South Asian summer monsoon. In: Lau WK-M, Waliser DE (eds) Intra-seasonal variability of the atmosphere-Ocean climate system, 2nd edn. Springer, Berlin, pp 21–72

  • Goswami BN, Annamalai H, Krishnamurthy V (1999) A broad scale circulation index for inter-annual variability of the Indian summer monsoon. Quart J Roy Meteor Soc 125:611–633. https://doi.org/10.1002/qj.49712555412

    Article  Google Scholar 

  • Goswami BN, Chakravorty S (2017) Dynamics of the Indian summer monsoon climate. Oxford Research Encyclopedia

    Book  Google Scholar 

  • Guo H, Golaz JC, Donner LJ, Wyman B, Zhao M, Ginoux P (2015) CLUBB as a unified cloud parameterization: opportunities and challenges. Geophys Res Lett 42:4540–4547

    Article  Google Scholar 

  • Hack JJ (1994) Parameterization of moist convection in the National Center for Atmospheric Research Community Climate Model (CCM2). J Geophys Res 99:5551–5568

    Article  Google Scholar 

  • He, J., & Alapaty, K. (2018) Precipitation partitioning in multiscale atmospheric simulations: impacts of stability restoration methods. J Geophys Res Atmos, 123(18), 10-185.

  • Holtslag AAM, Boville BA (1993) Local versus nonlocal boundary-layer diffusion in a global climate model. J Clim 6:1825–1842

    Article  Google Scholar 

  • Hou M, Tang Y (2022) Recent progress in simulating two types of ENSO–from CMIP5 to CMIP6. Front Marine Sci 9

  • Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Hong Y, Bowman KP, Stocker EF (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8(1):38–55

    Article  Google Scholar 

  • Iacono M, Delamere J, Mlawer E, Shephard M, Clough S, Collins W (2008) Radiative forcing by long-lived greenhouse gases: calculations with the aer radiative transfer models. J Geophys Res

  • Jain S, Salunke P, Mishra SK (2019) Performance of CMIP5 models in the simulation of Indian summer monsoon. Theor Appl Climatol 137:1429–1447. https://doi.org/10.1007/s00704-018-2674-3

    Article  Google Scholar 

  • Jiang X, Li T, Wang B (2004) Structures and mechanisms of the northward propagating boreal summer intra-seasonal oscillation. J Clim 17:1022–1039

    Article  Google Scholar 

  • Jiang X, Waliser DE, Li JL, Woods C (2011) Vertical cloud structures of the boreal summer intra-seasonal variability based on CloudSat observations and ERA-interim reanalysis. Clim Dyn 36:2219–2232

    Article  Google Scholar 

  • Knutti R, Masson D, Gettelman A (2013) Climate model genealogy: generation CMIP5 and how we got there. Geophys Res Lett 40:1194–1199. https://doi.org/10.1002/grl.50256

    Article  Google Scholar 

  • Koteswaram P (1958) The easterly jet stream in the tropics. Tellus 10(1):43–57. https://doi.org/10.1111/j.2153-3490.1958.tb01984.x

    Article  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

    Article  Google Scholar 

  • Kummerow C, Barnes W, Kozu T, Shiue J, Simpson J (1998) The tropical rainfall measuring mission (TRMM) sensor package. J Atmos Oceanic Technol 15(3):809–817

    Article  Google Scholar 

  • Lauer A, Jones C, Eyring V, Evaldsson M, Hagemann S, Mäkelä J, Martin G, Roehrig R, Wang S (2018) Process-level improvements in CMIP5 models and their impact on tropical variability, the Southern Ocean, and monsoons. Earth Syst Dynam 9:33–67. https://doi.org/10.5194/esd-9-33-2018

    Article  Google Scholar 

  • Liu X, Ma PL, Wang H, Tilmes S, Singh B, Easter RC, ... Rasch PJ (2016) Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model. Geosci Model Dev 9(2):505–522

  • Lott F et al (2014) Kelvin and Rossby-gravity wave packets in the lower stratosphere of some high-top CMIP5 models. J Geophys Res Atmos 119:2156–2173

    Article  Google Scholar 

  • Meehl GA et al (2007) The WCRP CMIP3 multimodel dataset —a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394

    Article  Google Scholar 

  • Morrison H, Gettelman A (2008) A new two-moment bulk stratiform cloud microphysics scheme in the NCAR Community Atmosphere Model (CAM3), Part I: Description and numerical tests. J Clim 21(15):3642–3659

    Article  Google Scholar 

  • Neale RB, Richter J, Park S, Lauritzen PH, Vavrus SJ, Rasch PJ, Zhang M (2013) The mean climate of the Community Atmosphere Model (CAM4) in forced SST and fully coupled experiments. J Clim 26:5150–5168

    Article  Google Scholar 

  • Neale RB, Richter JH, Jochum M (2008) The impact of convection on ENSO: from a delayed oscillator to a series of events. J Clim 21:5904–5924. https://doi.org/10.1175/2008JCLI2244.1

    Article  Google Scholar 

  • Neale RB et al (2010) Description of the NCAR Community Atmosphere Model (CAM 4.0). NCAR Tech Note NCARTN- 485+STR, Boulder, Colorado, USA. pp. 212

  • Neale RB et al (2012) Description of the NCAR Community Atmosphere Model (CAM 5.0). NCAR Tech Note NCARTN- 486+STR, Boulder, Colorado, USA. pp. 274

  • Pai DS et al (2014) Development of a new high spatial resolution (0.25o x 0.25o) long period (1901-2010) daily gridded rainfall data set over India and its comparison with exiting data sets over the region. MAUSAM 65:1–18

    Article  Google Scholar 

  • Park S, Bretherton CS (2009) The University of Washington shallow convection and moist turbulence schemes and their impact on climate simulations with the Community Atmosphere Model. J Clim 22:3449–3469. https://doi.org/10.1175/2008JCLI2557.1

    Article  Google Scholar 

  • Park S, Bretherton CS, Rasch PJ (2014) Integrating cloud processes in the Community Atmosphere Model, version 5. J Clim 27(18):6821–6856

    Article  Google Scholar 

  • Pathak R, Sahany S, Mishra SK (2020) Uncertainty quantification-based cloud parameterization sensitivity analysis in the NCAR Community Atmosphere Model. Sci Rep 10:17499. https://doi.org/10.1038/s41598-020-74441-x

    Article  Google Scholar 

  • Pathak R, Sahany S, Mishra SK (2021) Impact of stochastic entrainment in the NCAR CAM deep convection parameterization on the simulation of South Asian summer monsoon. Clim Dyn 57:3365–3384. https://doi.org/10.1007/s00382-021-05870-1

    Article  Google Scholar 

  • Pathak R, Sahany S, Mishra SK, Dash SK (2019) Precipitation biases in CMIP5 models over the south Asian region. Sci Rep 9:9589. https://doi.org/10.1038/s41598-019-45907-4

    Article  Google Scholar 

  • Ramaswamy C (1962) Breaks in the Indian summer monsoon as a phenomenon of interaction between the easterly and the sub-tropical westerly jet streams. Tellus 14:337349. https://doi.org/10.1111/j.2153-3490.1962.tb01346.x

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Ratna SB, Cherchi A, Joseph PV, Behera S, Abish B, Masina S (2014) Moisture trend over the Arabian sea and its influence on the Indian summer monsoon rainfall. CMCC Res Papers Issue RP0225

  • Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15:1609–1625

    Article  Google Scholar 

  • Richter JH, Rasch PJ (2008) Effects of convective momentum transport on the atmospheric circulation in the Community Atmosphere Model, Version 3. J Clim 21:1487–1499. https://doi.org/10.1175/2007JCLI1789.1

    Article  Google Scholar 

  • Richter JH et al (2020) Progress in simulating the quasi-biennial oscillation in CMIP models. J Geophys Res Atmos 125:e2019JD032362

    Article  Google Scholar 

  • Sahany S, Mishra SK, Pathak R, Rajagoplan B (2018) Spatio-temporal variability of seasonality of rainfall over India. Geophys Res Lett 45(14):7140–7147. https://doi.org/10.1029/2018GL077932

    Article  Google Scholar 

  • Salunke P, Jain S, Mishra SK (2019) Performance of the CMIP5 models in the simulation of the Himalaya-Tibetan Plateau monsoon. Theor Appl Climatol 137:909–928. https://doi.org/10.1007/s00704-018-2644-9

    Article  Google Scholar 

  • Sharmila S, Pillai PA, Joseph S, Roxy M, RPM K, 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. https://doi.org/10.1007/s00382-013-1854-1

    Article  Google Scholar 

  • Siebesma AP, Soares PMM, Teixeira J (2007) A combined eddy-diffusivity mass-flux approach for the convective boundary layer. J Atmos Sci 64(4):1230–1248

    Article  Google Scholar 

  • Sikka DR (1980) Some aspects of the large-scale fluctuations of summer monsoon rainfall over India in relation to fluctuations in the planetary and regional scale circulation parameters. J Earth Syst Sci 89:179–195. https://doi.org/10.1007/BF02913749

    Article  Google Scholar 

  • Sperber KR, Annamalai H, Kang IS, Kitoh A, Moise A, Turner A, Wang B, Zhou H (2013) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41:2711–2744. https://doi.org/10.1007/s00382-012-1607-6

    Article  Google Scholar 

  • Swapna P, RameshKumar MR (2002) Role of low level flow on the summer monsoon rainfall over the Indian subcontinent during two contrasting monsoon years. J Indian Geophys Uni 6

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498

    Article  Google Scholar 

  • Teixeira J, Stevens B, Bretherton CS, Cederwall R, Doyle JD, Golaz JC, Holtslag AAM, Klein SA, Lundquist JK, Randall DA, Siebesma AP, Soares PMM (2008) Parameterization of the atmospheric boundary layer: a view from just above the inversion. Bull Am Meteorol Soc 89(4):453–458

    Article  Google Scholar 

  • Vavrus S, Waliser D (2008) An improved parameterization for simulating Arctic cloud amount in the CCSM3 climate model. J Clim 21:5673–5687. https://doi.org/10.1175/2008JCLI2299.1

    Article  Google Scholar 

  • Wang B, Xie X (1997) A model for the boreal summer intra-seasonal oscillations. J Atmos Sci 54:72–86

    Article  Google Scholar 

  • Wang Y, Zhang GJ (2016) Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5. J Adv Model Earth Syst 8:1641–1656. https://doi.org/10.1002/2016MS000756

    Article  Google Scholar 

  • 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 

  • Zhang GJ, McFarlane NA (1995) Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmosphere-Ocean 33:407–446

    Article  Google Scholar 

  • Zhou L, Murtugudde R (2014) Impact of northward-propagating intra-seasonal variability on the onset of Indian summer monsoon. J Clim 27:126–139

    Article  Google Scholar 

  • Zhou Z, Xie S (2015) Effects of climatological model biases on the projection of tropical climate change. J Clim 28(24):9909–9917

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to acknowledge NCAR’s climate modeling section (http://www.cgd.ucar.edu/) for developing CAM3, CAM4, CAM5, and CAM6 models. We are thankful to TRMM (https://pmm.nasa.gov/trmm) and ECMWF (https://www.ecmwf.int/en/forecasts/datasets/) for providing the necessary observational and reanalysis datasets publicly. The IITD supercomputing facility is used for computations. NCAR-NCL is used for data analysis, and the climate data operator is used for data processing. This work is partly supported by the DST Centre of Excellence in Climate Modeling at IIT Delhi and through a DST Science and Engineering Research Board (SERB) project (ECR/2015/000229).

Code availability

The climate model used for simulations is freely available at https://www.cesm.ucar.edu/, and the code used for figure generation is available with the corresponding author and can be obtained on request.

Funding

This work is partly supported by the DST Centre of Excellence in Climate Modeling at IIT Delhi and through a DST Science and Engineering Research Board (SERB) project (ECR/2015/000229). Ravi Kumar acknowledges the MTech fellowship from MHRD.

Author information

Authors and Affiliations

  1. Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India

    Ravi Kumar, Raju Pathak, Sandeep Sahany & Saroj K. Mishra

  2. Climate Change Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

    Raju Pathak

  3. Centre for Climate Research Singapore, Singapore, Singapore

    Sandeep Sahany

Authors
  1. Ravi Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Raju Pathak
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sandeep Sahany
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Saroj K. Mishra
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SS and RP designed the study with key inputs from SKM. RK performed the model simulations and worked with RP for analysis. All authors have contributed to writing the manuscript.

Corresponding author

Correspondence to Raju Pathak.

Ethics declarations

Ethics approval

The manuscript is conducted in the ethical manner advised by the Theoretical and Applied Climatology.

Consent to participate

Not applicable.

Consent for publication

The research is scientifically consented to be published.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher’s note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, R., Pathak, R., Sahany, S. et al. Indian summer monsoon simulations in successive generations of the NCAR Community Atmosphere Model. Theor Appl Climatol 153, 977–992 (2023). https://doi.org/10.1007/s00704-023-04514-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-023-04514-0

Search

Navigation