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Impact of the soil hydrology scheme on simulated soil moisture memory

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Abstract

Soil moisture–atmosphere feedback effects play an important role in several regions of the globe. For some of these regions, soil moisture memory may contribute significantly to the state and temporal variation of the regional climate. Identifying those regions can help to improve predictability in seasonal to decadal climate forecasts. In order to accurately simulate soil moisture memory and associated soil moisture–atmosphere interactions, an adequate representation of soil hydrology is required. The present study investigates how different setups of a soil hydrology scheme affect soil moisture memory simulated by the global climate model of the Max Planck Institute for Meteorology, ECHAM6/JSBACH. First, the standard setup is applied in which soil water is represented by a single soil moisture reservoir corresponding to the root zone. Second, a new five layer soil hydrology scheme is introduced where not only the root zone is differentiated into several layers but also layers below are added. Here, three variants of the new scheme are utilized to analyse how different characteristics of the soil hydrology and the associated fluxes influence soil moisture memory. Soil moisture memory of the different setups is analysed from global ECHAM6/JSBACH simulations forced by observed SST. Areas are highlighted where the regional climate seems to be sensitive to the improved representation of soil hydrology in the new setup and its variants. Results indicate that soil moisture memory is generally enlarged in regions during the dry season where a soil moisture buffer is present below the root zone due to the 5-layer scheme. This effect is usually enhanced when this buffer is increased. Memory tends to be weakened (strengthened) where bare soil evaporation is increased (decreased), especially in semi-arid regions and wet seasons. For some areas, this effect is compensated by a decreased (increased) transpiration.

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References

  • Asharaf S, Ahrens B (2013) Soil-moisture memory in the regional climate model COSMO-CLM during the Indian summer monsoon season. J Geophys Res 118:6144–6151. doi:10.1002/jgrd.50429

    Google Scholar 

  • Beringer J, Lynch AH, Chapin FS II, Mack M, Bonan GB (2001) The representation of Arctic soils in the land surface model: the importance of mosses. J Clim 14:3324–3335

    Article  Google Scholar 

  • Brovkin V, Raddatz T, Reick CH, Claussen M, Gayler V (2009) Global biogeophysical interactions between forest and climate. Geophys Res Lett 36(L07):405. doi:10.1029/2009GL037543

    Google Scholar 

  • Caldwell MM, Dawson TE, Richards JH (1998) Hydraulic lift: consequences of water efflux from the roots of plants. Oecologia 113:151–161

    Article  Google Scholar 

  • Clapp RB, Hornberger GM (1978) Empirical equations for some soil hydraulic properties. Water Resourc Res 14:601–604

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette J-J, Park B-K, Peubey C, de Rosnay P, Tavolato C, Thépaut J-N, Vitart F (2011) The era-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. doi:10.1002/qj.828,2011

    Article  Google Scholar 

  • Delworth TL, Manabe S (1988) The influence of potential evaporation on the variabilities of simulated soil wetness and climate. J Clim 1:523–547

    Article  Google Scholar 

  • Dirmeyer P, Koster R, Guo ZAD (2006) Do global models properly represent the feedback between land and atmosphere? J Hydrometeor 7:1177–1198

    Article  Google Scholar 

  • Disse M (1995) Modellierung der Verdunstung und der Grundwasserneubildung in ebenen Einzugsgebieten. Mitteilungen des Inst. f. Hydrologie u. Wasserwirtschaft d. Universität Karlsruhe 53:95–107

    Google Scholar 

  • Dümenil Gates L, Hagemann S, Golz C (2000) Observed historical discharge data from major rivers for climate model validation. Max Planck Institute for Meteorology Rep 307 [available from MPI for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany]

  • Dümenil L, Todini E (1992) A rainfall-runoff scheme for use in the Hamburg climate model. In: Kane JP (ed) Advances in theoretical hydrology—a tribute to James Dooge. Elsevier Science Publishers, Amsterdam, pp 129–157

  • Dunne KA, Wilmott CJ (1996) Global distribution of plant-extractable water capacity of soil. Int J Climatol 16:841–859

    Article  Google Scholar 

  • Ekici A, Beer C, Hagemann S, Hauck C (2013) Improved soil physics for simulating high latitude permafrost regions by the JSBACH terrestrial ecosystem model. Geosci Model Dev Discuss 6:2655–2698. doi:10.5194/gmdd-6-2655-2013

    Article  Google Scholar 

  • FAO/UNESCO (1971–1981) Soil map of the world, vols 1–10, UNESCO, Paris

  • Hagemann S (2002) An improved land surface parameter dataset for global and regional climate models. Max Planck Institute for Meteorology Rep 336, Max Planck Institute for Meteorology, Hamburg, Germany [Report available electronically from: http://www.mpimet.mpg.de/en/wissenschaft/publikationen.html]

  • Hagemann S, Dümenil L (1998) A parameterization of the lateral waterflow for the global scale. Clim Dyn 14:17–31

    Article  Google Scholar 

  • Hagemann S, Loew A, Andersson A (2013) Combined evaluation of MPI-ESM land surface water and energy fluxes. J Adv Model Earth Syst 5. doi:10.1029/2012MS000173

  • Hirschi M, Seneviratne SI, Alexandrov V, Boberg F, Boroneant C, Christensen OB, Formayer H, Orlowsky B, Stepanek P (2011) Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nature Geosci 4:17–21. doi:10.1038/ngeo1032

    Article  Google Scholar 

  • Jackson RB, Sperry JS, Dawson TE (2000) Root water uptake and transport: using physiological processes in global predictions. Trend Plant Sci 5:482–488

    Article  Google Scholar 

  • Jiménez C, Prigent C, Mueller B, Seneviratne SI, McCabe M, Wood E, Rossow W, Balsamo G, Betts A, Dirmeyer P, Fisher J, Jung M, Kanamitsu M, Reichle R, Reichstein M, Rodell M, Sheffield J, Tu K, Wang K (2011) Global inter-comparison of 12 land surface heat flux estimates. J Geophys Res. doi:10.1029/2010JD014545

    Google Scholar 

  • Kato S, Loeb NG, Rose FG, Doelling DR, Rutan DA, Caldwell TE, Yu L, Weller RA (2013) Surface irradiances consistent with ceres-derived top-of-atmosphere shortwave and longwave irradiances. J Clim 26:2719–2740. doi:10.1175/JCLI-D-12-00436.1

    Article  Google Scholar 

  • Kleidon A (2004) Global datasets and rooting zone depth inferred from inverse methods. J Climate 17:2714–2722

    Article  Google Scholar 

  • Koster RD, Suarez MJ (2001) Soil moisture memory in climate models. J Hydrometeor 2:558–570

    Article  Google Scholar 

  • 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 (2004a) Regions of strong coupling between soil moisture and precipitation. Science 305(5687):1138–1140

    Article  Google Scholar 

  • Koster RD, Suarez MJ, Liu P, Jambor U, Berg A, Kistler M, Reichle R, Rodell M, Famiglietti J (2004b) Realistic initialization of land surface states: impacts on subseasonal forecast skill. J Hydrometeor 5:1049–1063

    Article  Google Scholar 

  • Koster RD, Mahanama S, Yamada TJ, Balsamo G, Boisserie M, Dirmeyer P, Doblas-Reyes F, Gordon CT, Guo Z, Jeong J-H, Lawrence DM, Lee W-S, Li Z, Luo L, Malyshev S, Merryfield W, Seneviratne SI, Stanelle T, van den Hurk B, Vitart F, Wood EF (2010) The contribution of land initialization to subseasonal forecast skill: first results from the GLACE-2 Project. Geophys Res Lett 37:L02402. doi:10.1029/2009GL041677

    Article  Google Scholar 

  • Letts MG, Roulet NT, Corner NT, Skapura MR, Verseghy DL (2000) Parametrization of peatland hydraulic properties for the Canadian land surface scheme. Atmos Ocean 38(1):141–160

    Article  Google Scholar 

  • Liu YY, Parinussa RM, Dorigo W, De Jeu R, Wagner W, van Dijk IJM, McCabe MF, Evans JP (2011) Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrol Earth Syst Sci 15:425–436. doi:10.5194/hess-15-425-2011

    Article  Google Scholar 

  • Loew A, Stacke T, Dorigo W, de Jeu R, Hagemann S (2013) Potential and limitations of multidecadal satellite soil moisture observations for climate model evaluation studies. Hydrol Earth Syst Sci 17:3523–3542. doi:10.5194/hess-17-3523-2013

    Article  Google Scholar 

  • Lorenz R, Jaeger EB, Seneviratne SI (2010) Persistence of heat waves and its link to soil moisture memory. Geophys Res Lett 37:L09703. doi:10.1029/2010GL042764

    Article  Google Scholar 

  • Mitchell KE, Lohmann D, Houser PR, Wood EF, Schaake JC, Robock A, Cosgrove BA, Sheffield J, Duan Q, Luo L, Higgins RW, Pinker RT, Tarpley JD, Lettenmaier DP, Marshall CH, Entin JK, Pan M, Shi W, Koren V, Meng J, Ramsay BH, Bailey AA (2004) The multi-institution North American land data assimilation system (NLDAS): utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J Geophys Res 109:D07S90. doi:10.1029/2003JD003823

  • Mueller B, Seneviratne SI, Jimenez C, Corti T, Hirschi M, Balsamo G, Ciais P, Dirmeyer P, Fisher JB, Guo Z, Jung M, Maignan F, McCabe MF, Reichle R, Reichstein M, Rodell M, Sheffield J, Teuling AJ, Wang K, Wood EF, Zhang Y (2011) Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations. Geophys Res Lett 38. doi:10.1029/2010GL046230

  • O’Geen AT (2012) Soil water dynamics. Nature Educ Knowl 3(6):12

    Google Scholar 

  • Patterson KA (1990) Global distributions of total and total-avaiable soil water-holding capacities. University of Delaware, Delaware

  • Raddatz TJ, Reick C, Knorr W, Kattge J, Roeckner E, Schnur R, Schnitzler K-G, Wetzel P, Jungclaus JH (2007) Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty-first century? Clim Dyn. doi:10.1007/s00382-007-0247-8

    Google Scholar 

  • Richards LA (1931) Capillary conduction of liquids through porous mediums. Physics 1(5):318–333. doi:10.1063/1.1745010

    Article  Google Scholar 

  • Richtmyer RD, Morton KW (1967) Difference methods for initial-value problems. Wiley-Interscience, New York

    Google Scholar 

  • Rodell M, Houser PR, Jambor U, Gottschalck J, Mitchell K, Meng C-J, 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):381394

    Article  Google Scholar 

  • Roeckner E, Arpe K, Bengtsson L, Christoph M, Claussen M, Dümenil L, Esch M, Giorgetta M, Schlese U, Schulzweida U (1996) The atmospheric general circulation model ECHAM-4: model description and simulation of the present day climate. Max Planck Institute for Meteorology Rep 218. Available from MPI for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany

  • Roesch A, Wild M, Gilgen H, Ohmura A (2001) A new snow cover fraction parameterization for the ECHAM4 GCM. Clim Dyn 17:933–946

    Article  Google Scholar 

  • Rowntree PR (1991) Atmospheric parameterization schemes for evaporation over land: basic concepts and climate modelling aspects, In: Schmugge TJ, Andre J (eds) Land surface evaporation—measurement and parameterization. Springer, Berlin, pp 5–29

  • Schlosser CA, Milly PCD (2002) A model-based investigation of soil moisture predictability and associated climate predictability. J Hydrometeor 3:483–501

    Article  Google Scholar 

  • Sellers PY, Mintz Y, Sud YC, Dalcher A (1986) A simple biosphere model (Sib) for use within general circulation models. J Atm Sci 43:505–531

    Article  Google Scholar 

  • Seneviratne SI, Stöckli R (2008) The role of land-atmosphere interactions for climate variability in Europe. In: Brönnimann et al (eds) Climate variability and extremes during the past 100 years. Adv Global Change Res 33. Springer, Berlin (Book chapter)

  • Seneviratne SI, Koster RD, Guo Z, Dirmeyer PA, Kowalczyk E, Lawrence D, Liu P, Lu C-H, Mocko D, Oleson KW, Verseghy D (2006a) Soil moisture memory in AGCM simulations: analysis of global land–atmosphere coupling experiment (GLACE) data. J Hydrometeor 7:1090–1112

    Article  Google Scholar 

  • Seneviratne SI, Lüthi D, Litschi M, Schär C (2006b) Land–atmosphere coupling and climate change in Europe. Nature 443:205–209

    Article  Google Scholar 

  • Seneviratne SI, Corti T, Davin E, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture–climate interactions in a changing climate: a review. Earth-Sci Rev 99:125–161. doi:10.1016/j.earscirev.2010.02.004

    Article  Google Scholar 

  • Stevens B, Giorgetta M, Esch M, Mauritsen T, Crueger T, Rast S, Salzmann M, Schmidt H, Bader J, Block K, Brokopf R, Fast I, Kinne S, Kornblueh L, Lohmann U, Pincus R, Reichler T, Roeckner E (2013) The atmospheric component of the MPI-M earth system model: ECHAM6. J Adv Model Earth Syst 5:146–172. doi:10.1002/jame.20015

    Article  Google Scholar 

  • Taylor CM, Ellis RJ (2006) Satellite detection of soil moisture impacts on convection at the mesoscale. Geophys Res Lett 33:L03404. doi:10.1029/2005GL025252

    Article  Google Scholar 

  • Taylor KE, Williamson D, Zwiers F (2000) The sea surface temperature and sea-ice concentration boundary conditions for AMIP II simulations. PCMDI Report, 60, program for climate model diagnosis and intercomparison. Lawrence Livermore National Laboratory, Livermore, California, 25 pp

  • Van Genuchten MT (1980) A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J 44:892–898

    Article  Google Scholar 

  • Warrilow DA, Sangster AB, Slingo A (1986) Modelling of land surface processes and their influence on European climate. UK Met Office Tech Note DCTN 38, 92 pp

  • Weedon GP, Gomes S, Viterbo P, Shuttleworth WJ, Blyth E, Österle H, Adam JC, Bellouin N, Boucher O, Best M (2011) Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J Hydrometeor 12:823–848. doi:10.1175/2011JHM1369.1

    Article  Google Scholar 

  • Williams RD, Ahuja LR (2003) Scaling and estimating the soil water characteristic using a one-parameter model. In: Pachepsky Y, Radcliffe DE, Selim HM (eds) Scaling methods in soil physics. CRC Press, Boca Raton, pp 35–48

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Acknowledgments

The present work was supported by funding for Stefan Hagemann from the European Commission’s 7th Framework Programme, under Grant Agreement number 282672, within the EMBRACE project. Tobias Stacke acknowledges funding from the Federal Ministry of Education and Research in Germany (BMBF) through the research programme MiKlip (FKZ: 01LP1108A). Moreover, we would like to thank Veronika Gayler, Thomas Raddatz, Christian Reick, Reiner Schnur and Stiig Wilkenskjeld from MPI-M for helpful advice during the technical implementation of the 5-layer scheme into the JSBACH model.

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  1. Max Planck Institute for Meteorology, Bundesstr. 53, 20146, Hamburg, Germany

    Stefan Hagemann & Tobias Stacke

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Correspondence to Stefan Hagemann.

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Hagemann, S., Stacke, T. Impact of the soil hydrology scheme on simulated soil moisture memory. Clim Dyn 44, 1731–1750 (2015). https://doi.org/10.1007/s00382-014-2221-6

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