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Theoretical and Applied Climatology

, Volume 138, Issue 3–4, pp 1563–1571 | Cite as

Decadal intensification of local thermal feedback of summer soil moisture over North China

  • Bei Xu
  • Haishan ChenEmail author
  • Chujie Gao
  • Gang Zeng
  • Shanlei Sun
  • Hedi Ma
  • Wenjian Hua
Original Paper
  • 52 Downloads

Abstract

Soil moisture (SM) feedback on climate variables especially temperature is an important aspect in land-atmosphere coupling. Based on the Global Land Data Assimilation System (GLDAS) V2.0 SM data and the gridded observational temperature data, we statistically analyze the thermal feedback of SM over North China (NC). The results show that SM exerts a decreasing trend under the background of evident warming over NC, inducing a decadal enhancement of SM feedbacks on the local temperature and extreme hot events. The SM feedback contributes 6% of the total air temperature variation during 1961–2012, while it reaches 36% after the regional warming during 1994–2012. Such SM affecting temperature is mainly reflected in its feedback on daily maximum temperature, which is also intensified during the warm period. The decadal intensification is also found in the feedback of SM on hot extremes. Further analyses show that the abnormal changes of the latent and sensible heat fluxes caused by the SM anomaly are the main reasons that affect the thermal conditions. Besides, the rising Bowen ratio indicates that upward thermal transfer on the land surface is enhanced in recent years, which suggests that the atmosphere is more sensible to the abnormal heating on the ground. This consequently translates into the decadal intensification of the local thermal feedback of SM in summer over NC.

Notes

Funding information

This work was jointly supported by the National Key R&D Program (2016YFA0600702), the National Science Fund for Distinguished Young Scholars (41625019), the National Natural Science Foundation of China (41230422), the China Postdoctoral Science Foundation (2019M651665), the Open Research Fund of the State Key Laboratory of Loess and Quaternary Geology of China (SKLLQG1806), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

Compliance with ethical standards

Competing interests

The authors declare that they have no conflict of interest.

References

  1. Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank AMG, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Rupa Kumar K, Revadekar J, Griffiths G, Vincent L, Stephenson DB, Burn J, Aguilar E, Brunet M, Taylor M, New M, Zhai P, Rusticucci M, Vazquez-Aguirre JL (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109.  https://doi.org/10.1029/2005jd006290 CrossRefGoogle Scholar
  2. Berg AA, Famiglietti JS, Rodell M, Reichle RH, Jambor U, Holl SL, Houser PR (2005) Development of a hydrometeorological forcing data set for global soil moisture estimation. Int J Climatol 25(13):1697–1714.  https://doi.org/10.1002/joc.1203 CrossRefGoogle Scholar
  3. Bowen IS (1926) The ratio of heat losses by conduction and by evaporation from any water surface. Phys Rev 27(6):779–789.  https://doi.org/10.1103/PhysRev.27.779 CrossRefGoogle Scholar
  4. Brotzge JA, Crawford KC (2003) Examination of the surface energy budget: a comparison of Eddy correlation and Bowen ratio measurement systems. J Hydrometeorol 4(2):160–178.  https://doi.org/10.1175/1525-7541(2003)4<160:EOTSEB>2.0.CO;2 CrossRefGoogle Scholar
  5. Cheng S, Huang J (2016) Enhanced soil moisture drying in transitional regions under a warming climate. J Geophys Res Atmos 121:2542–2555.  https://doi.org/10.1002/2015JD024559 CrossRefGoogle Scholar
  6. Cheng S, Guan X, Huang J, Ji F, Guo R (2015) Long-term trend and variability of soil moisture over East Asia. J Geophys Res Atmos 120:8658–8670.  https://doi.org/10.1002/2015JD023206 CrossRefGoogle Scholar
  7. Czaja A, Frankignoul C (2002) Observed impact of Atlantic SST anomalies on the North Atlantic oscillation. J Clim 15:606–623.  https://doi.org/10.1175/1520-0442(2002)015<0606:OIOASA>2.0.CO;2 CrossRefGoogle Scholar
  8. Dirmeyer PA (2011) The terrestrial segment of soil moisture-climate coupling. Geophys Res Lett 38:L16702.  https://doi.org/10.1029/2011GL048268 CrossRefGoogle Scholar
  9. Dirmeyer PA, Cash BA, Kinter JL, Stan C, Jung T, Marx L, Towers P, Wedi N, Adams JM, Altshuler EL, Huang B, Jin EK, Manganello J (2012) Evidence for enhanced land–atmosphere feedback in a warming climate. J Hydrometeorol 13(3):981–995.  https://doi.org/10.1175/jhm-d-11-0104.1 CrossRefGoogle Scholar
  10. Dong D, Huang G, Qu X, Tao W, Fan G (2014) Temperature trend–altitude relationship in China during 1963–2012. Theor Appl Climatol 122(1–2):285–294.  https://doi.org/10.1007/s00704-014-1286-9 CrossRefGoogle Scholar
  11. 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 108(D22):8851.  https://doi.org/10.1029/2002jd003296 CrossRefGoogle Scholar
  12. Eltahir EAB (1998) A soil moisture rainfall feedback mechanism: 1.Theory and observations. Water Resour Res 34(4):777–785.  https://doi.org/10.1029/97WR03497 CrossRefGoogle Scholar
  13. Frankignoul C, Czaja A, L’Heveder B (1998) Air–sea feedback in the North Atlantic and surface boundary conditions for ocean models. J Clim 11(9):2310–2324.  https://doi.org/10.1175/1520-0442(1998)011<2310:asfitn>2.0.co;2 CrossRefGoogle Scholar
  14. Frankignoul C, Hasselmann K (1977) Stochastic climate models, Part II Application to sea-surface temperature anomalies and thermocline variability. Tellus 29(4):289–305.  https://doi.org/10.3402/tellusa.v29i4.11362 CrossRefGoogle Scholar
  15. Han B, Lü S, Li R, Wang X, Zhao L, Zhao C, Wang D, Meng X (2017) Global land surface climate analysis based on the calculation of a modified Bowen ratio. Adv Atmos Sci 34(5):663–678.  https://doi.org/10.1007/s00376-016-6175-y CrossRefGoogle Scholar
  16. Herold N, Kala J, Alexander LV (2016) The influence of soil moisture deficits on Australian heatwaves. Environ Res Lett 11:064003.  https://doi.org/10.1088/1748-9326/11/6/064003 CrossRefGoogle Scholar
  17. Koster RD, Suarez MJ (2001) Soil moisture memory on climate models. J Hydrometeorol 2:558–570.  https://doi.org/10.1175/1525-7541(2001)002<0558:SMMICM>2.0.CO;2 CrossRefGoogle Scholar
  18. Koster RD, Dirmeyer PA, Guo Z, Bonan G, Chan E, Cox P, Gordon CT, Kanae S, Kowalczyk E, Lawrence D, Liu P, Lu CH, Malyshev S, McAvaney B, Mitchell K, Mocko D, Oki T, Oleson K, Pitman A, Sud YC, Taylor CM, Verseghy D, Vasic R, Xue Y, , Yamada T (2004) Regions of strong coupling between soil moisture and precipitation. Science 305, 1138–1140, doi: https://doi.org/10.1126/science.1100217 CrossRefGoogle Scholar
  19. Koster RD, Mahanama SPP, Yamada TJ, Balsamo G, Berg AA, Boisserie M, Dirmeyer PA, Doblas-Reyes FJ, Drewitt G, Gordon CT, Guo Z, Jeong JH, Lawrence DM, Lee WS, Li Z, Luo L, Malyshev S, Merryfield WJ, Seneviratne SI, Stanelle T, van den Hurk BJJM, Vitart F, Wood EF (2010) Contribution of land surface initialization to subseasonal forecast skill: first results from a multi-model experiment. Geophys Res Lett 37(2):L02402.  https://doi.org/10.1029/2009gl041677 CrossRefGoogle Scholar
  20. Lewis JM (1995) The story behind the Bowen ratio. Bull Am Meteorol Soc 76(12):2433–2444.  https://doi.org/10.1175/1520-0477(1995)076<2433:TSBTBR>2.0.CO;2 CrossRefGoogle Scholar
  21. Li M, Ma Z, Niu GY (2011) Modeling spatial and temporal variations in soil moisture in China. Chin Sci Bull 56(17):1809–1820.  https://doi.org/10.1007/s11434-011-4493-0 CrossRefGoogle Scholar
  22. Li M, Ma Z (2013) Soil moisture-based study of the variability of dry-wet climate and climate zones in China. Chin Sci Bull 58(4–5):531–544.  https://doi.org/10.1007/s11434-012-5428-0 CrossRefGoogle Scholar
  23. Liu L, Zhang R, Zuo Z (2014) Intercomparison of spring soil moisture among multiple reanalysis data sets over eastern China. J Geophys Res Atmos 119(1):54–64.  https://doi.org/10.1002/2013jd020940 CrossRefGoogle Scholar
  24. Liu Z, Notaro M, Kutzbach J, Liu N (2006) Assessing global vegetation-climate feedbacks from observations. J Clim 19(5):787–814.  https://doi.org/10.1175/JCLI3658.1 CrossRefGoogle Scholar
  25. Lu R, Chen R (2016) A review of recent studies on extreme heat in China. Atmospheric Oceanic Sci Lett 9(2):114–121.  https://doi.org/10.1080/16742834.2016.1133071 CrossRefGoogle Scholar
  26. Nie S, Luo Y, Zhu J (2008) Trends and scales of observed soil moisture variations in China. Adv Atmos Sci 25:43–58.  https://doi.org/10.1007/s00376-008-0043-3 CrossRefGoogle Scholar
  27. Notaro M, Liu Z, Williams JW (2006) Observed vegetation–climate feedbacks in the United States. J Clim 19(5):763–786.  https://doi.org/10.1175/JCLI3657.1 CrossRefGoogle Scholar
  28. Orlowsky B, Seneviratne SI (2010) Statistical analyses of land–atmosphere feedbacks and their possible pitfalls. J Clim 23(14):3918–3932.  https://doi.org/10.1175/2010jcli3366.1 CrossRefGoogle Scholar
  29. Rodell M, Houser PR, Jambor U, Gottschalck J, Mitchell K, Meng CJ, Arsenault K, Cosgrove B, Radakovich J, Bosilovich M, Entin JK, Walker JP, Lohmann D, Toll D (2004) The global land data assimilation system. Bull Am Meteorol Soc 85(3):381–394.  https://doi.org/10.1175/bams-85-3-381 CrossRefGoogle Scholar
  30. Seneviratne SI, Koster RD, Guo Z, Dirmeyer PA, Kowalczyk E, Lawrence D, Liu P, Lu CH, Mocko D, Oleson KW, Verseghy D (2006) Soil moisture memory in AGCM simulations: analysis of Global Land-Atmosphere Coupling Experiment (GLACE) data. J Hydrometeorol 7:1090–1112.  https://doi.org/10.1175/JHM533.1 CrossRefGoogle Scholar
  31. Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture-climate interaction in a changing climate: a review. Earth Sci Rev 99:125–161.  https://doi.org/10.1016/j.earscirev.2010.02.004 CrossRefGoogle Scholar
  32. Sheffield J, Goteti G, Wood EF (2006) Delelopment of a 50-year-high-resolution global dataset of meteorological forcing for land surface modeling. J Clim 19(13):3088–3111.  https://doi.org/10.1175/JCLI3790.1 CrossRefGoogle Scholar
  33. Shi P, Sun S, Wang M, Li N, Wang JA, Jin Y, Gu X, Yin W (2014) Climate change regionalization in China (1961–2010). Sci China Earth Sci 57(11):2676–2689.  https://doi.org/10.1007/s11430-014-4889-1 CrossRefGoogle Scholar
  34. Spennemann PC, Saulo AC (2015) An estimation of the land-atmosphere coupling strength in South America using the Global Land Data Assimilation System. Int J Climatol 35(14):4151–4166.  https://doi.org/10.1002/joc.4274 CrossRefGoogle Scholar
  35. Sun S, Wang G (2012) The complexity of using a feedback parameter to quantify the soil moisture-precipitation relationship. J Geophys Res Atmos 117:D11113.  https://doi.org/10.1029/2011jd017173 CrossRefGoogle Scholar
  36. Sun S, Chen H, Sun G, Ju W, Wang G, Li X, Yan G, Gao C, Huang J, Zhang F, Zhu S, Hua W (2017) Attributing the changes in reference evapotranspiration in southwestern China using a new separation method. J Hydrometeorol 18(3):777–798.  https://doi.org/10.1175/jhm-d-16-0118.1 CrossRefGoogle Scholar
  37. Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23:1696–1718.  https://doi.org/10.1175/2009jcli2909.1 CrossRefGoogle Scholar
  38. Wei J, Jin Q, Yang ZL, Dirmeyer PA (2016) Role of ocean evaporation in California droughts and floods. Geophys Res Lett 43(12):6554–6562.  https://doi.org/10.1002/2016gl069386 CrossRefGoogle Scholar
  39. Wen QH, Zhang X, Xu Y, Wang B (2013) Detecting human influence on extreme temperatures in China. Geophys Res Lett 40(6):1171–1176.  https://doi.org/10.1002/grl.50285 CrossRefGoogle Scholar
  40. Wu L, Zhang J (2013) Asymmetric effects of soil moisture on mean daily maximum and minimum temperatures over eastern China. Meteorog Atmos Phys 122(3–4):199–213.  https://doi.org/10.1007/s00703-013-0284-2 CrossRefGoogle Scholar
  41. Wu L, Zhang J (2015) The relationship between spring soil moisture and summer hot extremes over North China. Adv Atmos Sci 32(12):1660–1668.  https://doi.org/10.1007/s00376-015-5003-0 CrossRefGoogle Scholar
  42. Wu S, Yin Y, Zheng D, Yang Q (2006) Moisture conditions and climate trends in China during the period 1971–2000. Int J Climatol 26(2):193–206.  https://doi.org/10.1002/joc.1245 CrossRefGoogle Scholar
  43. Wu W, Dickinson RE (2004) Time scales of layered soil moisture memory in the context of land-atmosphere interaction. J Clim 17:2752–2764.  https://doi.org/10.1175/1520-0442(2004)017<2752:TSOLSM>2.0.CO;2 CrossRefGoogle Scholar
  44. Xu X, Du Y, Tang J, Wang Y (2011) Variations of temperature and precipitation extremes in recent two decades over China. Atmos Res 101(1–2):143–154.  https://doi.org/10.1016/j.atmosres.2011.02.003 CrossRefGoogle Scholar
  45. Zhang C, Liao Y, Duan J, Song Y, Huang D, Wang S (2016) The progresses of dry-wet climate divisional research in China. Clim Change Res 12(4):261–267.  https://doi.org/10.12006/j.issn.1763-1719.2015.191 (in Chinese with English Abstract)CrossRefGoogle Scholar
  46. Zhang J, Wu L (2011) Land-atmosphere coupling amplifies hot extremes over China. Chin Sci Bull 56(31):3328–3332.  https://doi.org/10.1007/s11434-011-4628-3 CrossRefGoogle Scholar
  47. Zhang J, Wu L, Dong W (2011a) Land-atmosphere coupling and summer climate variability over East Asia. J Geophys Res 116:D05117.  https://doi.org/10.1029/2010jd014714 CrossRefGoogle Scholar
  48. Zhang J, Wang WC, Wei J (2008) Assessing land-atmosphere coupling using soil moisture from the Global Land Data Assimilation System and observational precipitation. J Geophys Res 113:D17119.  https://doi.org/10.1029/2008jd009807 CrossRefGoogle Scholar
  49. Zhang R, Zuo Z (2011) Impact of spring soil moisture on surface energy balance and summer monsoon circulation over East Asia and precipitation in East China. J Clim 24(13):3309–3322.  https://doi.org/10.1175/2011jcli4084.1 CrossRefGoogle Scholar
  50. Zhang Y (2012) Projections of 2.0°C warming over the globe and China under RCP4.5. Atmospheric Oceanic Sci Lett 5(6):514–520.  https://doi.org/10.1080/16742834.2012.11447047 CrossRefGoogle Scholar
  51. Zhang Y, Gao Z, Pan Z, Li D, Huang X (2017) Spatiotemporal variability of extreme temperature frequency and amplitude in China. Atmos Res 185:131–141.  https://doi.org/10.1016/j.atmosres.2016.10.018 CrossRefGoogle Scholar
  52. Zhang Y, Wu K, Yu J, Xia J (2011b) Characteristics of precipitation and air temperature variation during 1951-2009 in North China. J Nat Resour 26(11):1930–1941.  https://doi.org/10.11849/zrzyxb.2011.11.012 (in Chinese with English Abstract)CrossRefGoogle Scholar
  53. Zuo Z, Zhang R (2007) The spring soil moisture and the summer rainfall in eastern China. Chin Sci Bull 52(23):3310–3312.  https://doi.org/10.1007/s11434-007-0442-3 CrossRefGoogle Scholar
  54. Zuo Z, Zhang R (2009) Temporal and spatial features of the soil moisture in boreal spring in eastern China. Sci China Ser D Earth Sci 52(2):269–278.  https://doi.org/10.1007/s11430-009-0011-5 CrossRefGoogle Scholar
  55. Zuo Z, Zhang R (2016) Influence of soil moisture in eastern China on the East Asian summer monsoon. Adv Atmos Sci 33(2):151–163.  https://doi.org/10.1007/s00376-015-5024-8 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Meteorological Disaster, Ministry of Education (KLME) / International Joint Research Laboratory of Climate and Environment Change (ILCEC) / Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science & Technology (NUIST)NanjingChina
  2. 2.College of Atmospheric ScienceNUISTNanjingChina
  3. 3.College of OceanographyHohai UniversityNanjingChina
  4. 4.State Key Laboratory of Loess and Quaternary Geology, Institute of Earth EnvironmentChinese Academy of SciencesXi’anChina
  5. 5.Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy RainChina Meteorological AdministrationWuhanChina

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