CO2-induced heat source changes over the Tibetan Plateau in boreal summer-Part I: the total effects of increased CO2

Abstract

The concentration of CO2 in the atmosphere has been increasing, but its effects on the heat source (HS) over the Tibetan Plateau (TP) are unclear. Aimed at understanding these effects, at first, present study evaluated the CMIP5 (phase 5 of the Coupled Model Intercomparison Project) models and found that their multi-model ensemble (MME) reproduces the spatial pattern of the HS over the TP during June–September (hereafter JJAS) in observation reasonably well. Then, we used the MME to investigate the response of the JJAS HS over the TP to increased CO2. In response to increased CO2, the JJAS HS increases significantly. In terms of the response pattern and TP-averaged results, the increase in HS is mainly contributed by the latent heating (LH), which is due to moisture increases (with the lower level stronger than the upper level) and evaporation intensification led by CO2 change. The leading two intermodel spreads feature a nearly uniform structure and a central-southeastern TP dipole structure, respectively, and account for half of the total intermodel variance. The latent heating is mainly responsible for the spreads. The intensified radiative cooling of the atmosphere slightly dampen the TP-averaged HS increases. Over the TP, when CO2 increases, the atmospheric column above warms. Accordingly, the net longwave radiation flux out of the atmosphere column enhances, resulting in the intensified radiative cooling over the TP.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  1. Abe M, Hori M, Yasunari T, Kitoh A (2013) Effects of the Tibetan Plateau on the onset of the summer monsoon in South Asia: the role of the air-sea interaction. J Geophys Res Atmos 118(4):1760–1776. https://doi.org/10.1002/jgrd.50210

    Article  Google Scholar 

  2. Adler RF, Huffman GJ, Chang A, Ferraro R, Xie P-P, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present). J Hydrometeor 4(6):1147–1167

    Article  Google Scholar 

  3. Becker A, Finger P, Meyer-Christoffer A, Rudolf B, Schamm K, Schneider U, Ziese M (2013) A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present. Earth Syst Sci Data 5(1):71–99. https://doi.org/10.5194/essd-5-71-2013

    Article  Google Scholar 

  4. Boos WR, Kuang Z (2010) Dominant control of the South Asian monsoon by orographic insulation versus plateau heating. Nature 463(7278):218–222

    Article  Google Scholar 

  5. Byrne MP, O’Gorman PA (2016) Understanding decreases in land relative humidity with global warming: conceptual model and GCM simulations. J Clim 29(24):9045–9061. https://doi.org/10.1175/jcli-d-16-0351.1

    Article  Google Scholar 

  6. Chou C, Neelin JD, Chen CA, Tu JY (2009) Evaluating the “rich-get-richer” mechanism in tropical precipitation change under global warming. J Clim 22(8):1982–2005

    Article  Google Scholar 

  7. Du Y, Xie SP, Huang G, Hu K (2009) Role of air–sea interaction in the longpersistence of El Niño-induced North Indian Ocean warming. J Clim 22(8):2023–2038

    Article  Google Scholar 

  8. Duan AM, Wu GX (2008) Weakening trend in the atmospheric heat source over the Tibetan Plateau during recent decades. Part I: observations. J Clim 21:3149–3164

    Article  Google Scholar 

  9. Duan AM, Wu GX (2009) Weakening trend in the atmospheric heat source over the Tibetan Plateau during recent decades Part II: connection with climate warming. J Clim 22(15):4197–4212. https://doi.org/10.1175/2009jcli2699.1

    Article  Google Scholar 

  10. Endo H, Kitoh A (2014) Thermodynamic and dynamic effects on regional monsoon rainfall changes in a warmer climate. Geophys Res Lett 41(5):1704–1710. https://doi.org/10.1002/2013gl059158

    Article  Google Scholar 

  11. He B, Liu YM, Wu GX, Wang ZQ, Bao Q (2019a) The role of air-sea interactions in regulating the thermal effect of the Tibetan-Iranian Plateau on the Asian summer monsoon. Clim Dyn 52(7–8):4227–4245. https://doi.org/10.1007/s00382-018-4377-y

    Article  Google Scholar 

  12. He C, Wang Z, Zhou T, Li T (2019b) Enhanced latent heating over the Tibetan Plateau as a key to the enhanced East Asian summer monsoon circulation under a warming climate. J Clim 32(11):3373–3388. https://doi.org/10.1175/jcli-d-18-0427.1

    Article  Google Scholar 

  13. Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. J Clim 19(21):5686–5699. https://doi.org/10.1175/Jcli3990.1

    Article  Google Scholar 

  14. Hu Q, Jiang D, Fan G (2015) Climate change projection on the Tibetan Plateau: results of CMIP5 models. Chin J Atmos Sci 2:42–52. https://doi.org/10.3878/j.issn.1006-9895.1406.13325

    Article  Google Scholar 

  15. Huang J, Wang T, Wang W, Li Z, Yan H (2014) Climate effects of dust aerosols over East Asian arid and semiarid regions. J Geophys Res Atmos 119(19):11398–11416. https://doi.org/10.1002/2014jd021796

    Article  Google Scholar 

  16. Huang J, Ma J, Guan X, Li Y, He Y (2019) Progress in semi-arid climate change studies in China. Adv Atmos Sci 36(9):922–937. https://doi.org/10.1007/s00376-018-8200-9

    Article  Google Scholar 

  17. Kamae Y, Ogura T, Watanabe M, Xie SP, Ueda H (2016) Robust cloud feedback over tropical land in a warming climate. J Geophys Res Atmos 121(6):2593–2609. https://doi.org/10.1002/2015jd024525

    Article  Google Scholar 

  18. Kanamitsu M, Ebisuzaki W, Woollen J, Yang SK, Hnilo JJ, Fiorino M, Potter GL (2002) NCEP-DOE AMIP-II reanalysis (R-2). Bull Am Meteor Soc 83(11):1631–1643. https://doi.org/10.1175/bams-83-11-1631

    Article  Google Scholar 

  19. Kang L, Huang J, Chen S, Wang X (2016) Long-term trends of dust events over Tibetan Plateau during 1961–2010. Atmos Environ 125:188–198. https://doi.org/10.1016/j.atmosenv.2015.10.085

    Article  Google Scholar 

  20. Kitoh A (2004) Effects of mountain uplift on East Asian Summer Climate investigated by a coupled atmosphere ocean GCM. J Clim 17(4):783–802

    Article  Google Scholar 

  21. Kobayashi S, Ota Y, Harada Y, Ebita A, Moriya M, Onoda H, Onogi K, Kamahori H, Kobayashi C, Endo H, Miyaoka K, Takahashi K (2015) The JRA-55 Reanalysis: general specifications and basic characteristics. J Meteor Soc Japan 93(1):5–48. https://doi.org/10.2151/jmsj.2015-001

    Article  Google Scholar 

  22. Laine A, Nakamura H, Nishii K, Miyasaka T (2014) A diagnostic study of future evaporation changes projected in CMIP5 climate models. Clim Dyn 42(9–10):2745–2761. https://doi.org/10.1007/s00382-014-2087-7

    Article  Google Scholar 

  23. Lee JY, Wang B, Seo KH, Ha KJ, Kitoh A, Liu J (2015) Effects of mountain uplift on global monsoon precipitation. Asia-Pacific J Atmos Sci 51(3):275–290. https://doi.org/10.1007/s13143-015-0077-2

    Article  Google Scholar 

  24. Li C, Yanai M (1996) The onset and interannual variability of the asian summer monsoon in relation to land-sea thermal contrast. J Clim 9(2):358–375. https://doi.org/10.1175/1520-0442

    Article  Google Scholar 

  25. Li XQ, Ting MF, Li CH, Henderson N (2015) Mechanisms of Asian summer monsoon changes in response to anthropogenic forcing in CMIP5 models. J Clim 28(10):4107–4125. https://doi.org/10.1175/jcli-d-14-00559.1

    Article  Google Scholar 

  26. Liu Y, Hoskins B, Blackburn M (2007) Impact of Tibetan orography and heating on the summer flow over Asia. J Meteor Soc Japan 85:1–19. https://doi.org/10.2151/jmsj.85B.1

    Article  Google Scholar 

  27. Luo H, Yanai M (1984) The large-scale circulation and heat sources over the Tibetan plateau and surrounding areas during the early summer of 1979. Part II: heat and moisture budgets. Mon Weather Rev 112(5):966–989

    Article  Google Scholar 

  28. O’Gorman PA, Muller CJ (2010) How closely do changes in surface and column water vapor follow Clausius-Clapeyron scaling in climate change simulations? Environ Res Lett. https://doi.org/10.1088/1748-9326/5/2/025207

    Article  Google Scholar 

  29. Qu X, Huang G, Zhu L (2019) The CO2-induced sensible heat changes over the Tibetan Plateau from November to April. Clim Dyn 53(9–10):5623–5635. https://doi.org/10.1007/s00382-019-04887-x

    Article  Google Scholar 

  30. Riahi K, Rao S, Krey V, Cho C, Chirkov V, Fischer G, Kindermann G, Nakicenovic N, Rafaj P (2011) RCP 8.5—a scenario of comparatively high greenhouse gas emissions. Clim Change 109(1–2):33–57. https://doi.org/10.1007/s10584-011-0149-y

    Article  Google Scholar 

  31. Robinson DA, Dewey KF, Heim RR (1993) Global snow cover monitoring: an update. Bull Am Meteor Soc 74(9):1689–1696. https://doi.org/10.1175/1520-0477(1993)074%3c1689:Gscmau%3e2.0.Co;2

    Article  Google Scholar 

  32. Sampe T, Xie SP (2010) Large-scale dynamics of the Meiyu-Baiu Rainband: environmental forcing by the westerly jet. J Clim 23(1):113–134. https://doi.org/10.1175/2009JCLI3128.1

    Article  Google Scholar 

  33. Song JH, Kang HS, Byun YH, Hong SY (2010) Effects of the Tibetan Plateau on the Asian summer monsoon: a numerical case study using a regional climate model. Int J Climatol 30(5):743–759. https://doi.org/10.1002/joc.1906

    Article  Google Scholar 

  34. Stocker TF, Qin D, Plattner GK, Alexander LV, Allen SK, Bindoff NL, Bréon FM, Church JA, Cubasch U, Emori S (2013) Technical summary. In: Stocker TF, Qin D, Plattner G-K et al (eds) Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, p 79

  35. Su F, Duan X, Chen D, Hao Z, Cuo L (2013) Evaluation of the global climate models in the CMIP5 over the Tibetan Plateau. J Clim 26(10):3187–3208. https://doi.org/10.1175/jcli-d-12-00321.1

    Article  Google Scholar 

  36. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos 106(D7):7183–7192

    Article  Google Scholar 

  37. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteor Soc 93(4):485–498. https://doi.org/10.1175/BAMS-D-11-00094.1

    Article  Google Scholar 

  38. Thomson AM, Calvin KV, Smith SJ, Kyle GP, Volke A, Patel P, Delgado-Arias S, Bond-Lamberty B, Wise MA, Clarke LE (2011) RCP4 5: a pathway for stabilization of radiative forcing by 2100. Clim Change 109(1):77–94

    Article  Google Scholar 

  39. Wang B, Ding Q (2008) Global monsoon: dominant mode of annual variation in the tropics. Dyn Atmos Oceans 44(3–4):165–183. https://doi.org/10.1016/j.dynatmoce.2007.05.002

    Article  Google Scholar 

  40. Wang B, Wu R, Lau KM (2001) Interannual variability of the Asian summer monsoon: contrasts between the Indian and the western North Pacific-east Asian monsoons. J Clim 14(20):4073–4090. https://doi.org/10.1175/1520-0442(2001)014%3c4073:Ivotas%3e2.0.Co;2

    Article  Google Scholar 

  41. Wang H, Xie SP, Kosaka Y, Liu QY, Du Y (2019) Dynamics of Asian summer monsoon response to anthropogenic aerosol forcing. J Clim 32(3):843–858. https://doi.org/10.1175/jcli-d-18-0386.1

    Article  Google Scholar 

  42. Wu G, Liu Y, He B, Bao Q, Duan A, Jin FF (2012) Thermal controls on the Asian summer monsoon. Sci Rep 2:404. https://doi.org/10.1038/srep00404

    Article  Google Scholar 

  43. Yang K, Koike T, Ye BS (2006) Improving estimation of hourly, daily, and monthly solar radiation by importing global data sets. Agric For Meteorol 137(1–2):43–55. https://doi.org/10.1016/j.agrformet.2006.02.001

    Article  Google Scholar 

  44. Yao TD, Thompson L, Yang W, Yu WS, Gao Y, Guo XJ, Yang XX, Duan KQ, Zhao HB, Xu BQ, Pu JC, Lu AX, Xiang Y, Kattel DB, Joswiak D (2012) Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings. Nat Clim Change 2(9):663–667. https://doi.org/10.1038/Nclimate1580

    Article  Google Scholar 

  45. Ye D-Z, Wu G-X (1998) The role of the heat source of the Tibetan Plateau in the general circulation. Meteorol Atmos Phys 67(1–4):181–198

    Article  Google Scholar 

  46. Zhao Y, Duan AM, Wu GX, Sun RZ (2019) Response of the Indian Ocean to the Tibetan Plateau thermal forcing in late spring. J Clim 32(20):6917–6938. https://doi.org/10.1175/jcli-d-18-0880.1

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, the climate modeling groups listed in Table 1 and the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison for making the CMIP5 output available for present analysis. Besides, the authors wish to thank four anonymous reviewers for the insightful comments that lead to a significant improvement to the manuscript. The study was supported by the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (Grant no. 2019QZKK0102), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20060501), the National Natural Science Foundation of China (41831175, 41530425) and Key Deployment Project of Centre for Ocean Mega-Research of Science, Chinese Academy of Sciences (COMS2019Q03).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Xia Qu.

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 material 1 (PDF 542 kb)

Appendix: The responses of shortwave radiation fluxes

Appendix: The responses of shortwave radiation fluxes

In response to increased CO2, the increase of net shortwave radiation flux into the atmosphere column above the TP is 4.5 W m−2. The detailed responses of the shortwave radiation fluxes are provided below:

The surface downwelling shortwave radiation flux In response to increased CO2, this radiation flux decreases during JJAS. The TP-averaged decrease of the CMIP5 MME is 6.8 W m−2 in the 1%CO2 results (Fig. 3). The response of the downwelling shortwave radiation at the TP surface features a dipole pattern, with a distinct decrease over the central TP and slight increase over the southeastern and northwestern TP (Fig. 11a). Comparison of the decrease in the all-sky results with the clear-sky results indicates that the inclusion of cloud–radiation feedback does not significantly alter the TP-averaged responses (Fig. 3), but enlarges the uncertainty. The fact that the clear-sky downwelling shortwave radiation uniformly decreases at the TP surface (figure not shown) implies that the inclusion of cloud–radiation feedback slightly modifies the response pattern of the downwelling shortwave radiation at the TP surface. For the reduction in the average of the downwelling shortwave radiation at the TP surface, the intensification of atmospheric absorption of shortwave may be responsible. This intensified absorption is probably led by atmosphere wetting. In response to increased CO2, the moisture increases due to the atmospheric warming. The water vapor is able to absorb shortwave (Yang et al. 2006).

Fig. 11
figure11

The MME response (color shading) of JJAS downwelling shortwave radiation (a units: W m−2), upwelling shortwave radiation (b units: W m−2), albedo (c units: dimensionless) and snow cover (d units:  %) at the surface for the 1%CO2 results. The contours represent elevations of 1500, 3000, 5000 and 6000 m; the lattices indicate the response reaching the 95% significance level. Due to lack of data of snow cover, the following models are not participating in the calculation: ACCESS1-0, ACCESS1-3, BNU-ESM, CCSM4, FGOALS-s2, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, IPSL-CM5A-MR and IPSL-CM5B-LR

The surface upwelling shortwave radiation flux Meanwhile, this shortwave radiation flux decreases more than the downwelling shortwave radiation. In the 1%CO2 results, the averaged surface upwelling shortwave radiation of the CMIP5 MME over the TP decreases by 12.1 W m−2 (Fig. 3). The response of the upwelling shortwave radiation features a nearly uniform weakening at the TP surface (Fig. 11b). The weakening is relatively large at elevations above 3000 m. The upwelling shortwave radiation at the surface is mainly the reflection of the downwelling shortwave radiation. The larger change in the upwelling shortwave radiation than that of the downwelling shortwave radiation indicates that the albedo of the TP surface changes. The albedo of the TP also uniformly reduces, with relatively large magnitude above 3000 m (Fig. 11c). The response pattern of snow cover is almost the same as that of albedo, with the spatial correlation coefficient between them being 0.94. This means that the shrinking of snow cover in response to increased CO2 leads to a reduction in albedo as well as the upwelling shortwave radiation at the TP surface. The inclusion of cloud–radiation feedback may slightly enhance the overall upwelling shortwave radiation at the TP surface, but the enhancement is statistically insignificant (Fig. 3).

The outgoing shortwave radiation flux at the top of the atmosphere Over the TP, this outgoing radiation flux reduces significantly. In the 1%CO2 results, the TP-averaged magnitude of the CMIP5 MME is 9.6 W m−2 (Fig. 3). The TP displays a uniform decrease in this radiation, with relatively large magnitude over the western TP at elevations between 3000 and 5000 m (Fig. 12). The response pattern is similar to that of the upwelling shortwave radiation at the TP surface (Fig. 11b), with a spatial correlation coefficient of 0.63 between the two. It indicates that the reduction of the outgoing shortwave radiation is mainly led by the change in the upwelling shortwave radiation at the TP surface. The discrepancies in the detail may be caused by the masking effect of cloud or the atmospheric absorption to shortwave. Overall, the model results suggest that the inclusion of cloud–radiation feedback may not significantly affect the response of the TP-averaged outgoing shortwave radiation (Fig. 3). But it is important to note that the change in radiative fluxes at the top of atmosphere, resulting from the cloud-radiation feedback, is the largest source of uncertainty in the climate response to CO2 forcing simulated by GCMs because of the unrealistic presentation of cloud processes in the models.

Fig. 12
figure12

The MME response (color shading) of JJAS upwelling shortwave radiation (units: W m−2) at the top of the atmosphere for the 1%CO2 results. The contours represent elevations of 1500, 3000, 5000 and 6000 m; the lattices indicate the response reaching the 95% significance level

The downwelling shortwave radiation flux at the top of the atmosphere It is not analyzed because it barely changes (Fig. 3).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Qu, X., Huang, G. & Zhu, L. CO2-induced heat source changes over the Tibetan Plateau in boreal summer-Part I: the total effects of increased CO2. Clim Dyn (2020). https://doi.org/10.1007/s00382-020-05353-9

Download citation

Keywords

  • The Tibetan Plateau
  • Heat source
  • CO2 increase