Precipitation Sensitivity to Surface Heat Fluxes over North America in Reanalysis and Model Data

Alexis Berg Rutgers, The State University of New Jersey, New Brunswick, and Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Kirsten Findell Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Benjamin R. Lintner Rutgers, The State University of New Jersey, New Brunswick, New Jersey

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Pierre Gentine Columbia University, New York, New York

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Christopher Kerr University Corporation for Atmospheric Research/GFDL, Princeton, New Jersey

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Abstract

A new methodology for assessing the impact of surface heat fluxes on precipitation is applied to data from the North American Regional Reanalysis (NARR) and to output from the Geophysical Fluid Dynamics Laboratory’s Atmospheric Model 2.1 (AM2.1). The method assesses the sensitivity of afternoon convective rainfall frequency and intensity to the late-morning partitioning of latent and sensible heating, quantified in terms of evaporative fraction (EF). Over North America, both NARR and AM2.1 indicate sensitivity of convective rainfall triggering to EF but no appreciable influence of EF on convective rainfall amounts. Functional relationships between the triggering feedback strength (TFS) metric and mean EF demonstrate the occurrence of stronger coupling for mean EF in the range of 0.6 to 0.8. To leading order, AM2.1 exhibits spatial distributions and seasonality of the EF impact on triggering resembling those seen in NARR: rainfall probability increases with higher EF over the eastern United States and Mexico and peaks in Northern Hemisphere summer. Over those regions, the impact of EF variability on afternoon rainfall triggering in summer can explain up to 50% of seasonal rainfall variability. However, the AM2.1 metrics also exhibit some features not present in NARR, for example, strong coupling extending northwestward from the central Great Plains into Canada. Sources of disagreement may include model hydroclimatic biases that affect the mean patterns and variability of surface flux partitioning, with EF variability typically much lower in NARR. Finally, the authors also discuss the consistency of their results with other assessments of land–precipitation coupling obtained from different methodologies.

Corresponding author address: Alexis Berg, Department of Environmental Sciences, Rutgers, The State University of New Jersey, 14 College Farm Rd., New Brunswick, NJ 08901-8551. E-mail: alexis.berg@noaa.gov

Abstract

A new methodology for assessing the impact of surface heat fluxes on precipitation is applied to data from the North American Regional Reanalysis (NARR) and to output from the Geophysical Fluid Dynamics Laboratory’s Atmospheric Model 2.1 (AM2.1). The method assesses the sensitivity of afternoon convective rainfall frequency and intensity to the late-morning partitioning of latent and sensible heating, quantified in terms of evaporative fraction (EF). Over North America, both NARR and AM2.1 indicate sensitivity of convective rainfall triggering to EF but no appreciable influence of EF on convective rainfall amounts. Functional relationships between the triggering feedback strength (TFS) metric and mean EF demonstrate the occurrence of stronger coupling for mean EF in the range of 0.6 to 0.8. To leading order, AM2.1 exhibits spatial distributions and seasonality of the EF impact on triggering resembling those seen in NARR: rainfall probability increases with higher EF over the eastern United States and Mexico and peaks in Northern Hemisphere summer. Over those regions, the impact of EF variability on afternoon rainfall triggering in summer can explain up to 50% of seasonal rainfall variability. However, the AM2.1 metrics also exhibit some features not present in NARR, for example, strong coupling extending northwestward from the central Great Plains into Canada. Sources of disagreement may include model hydroclimatic biases that affect the mean patterns and variability of surface flux partitioning, with EF variability typically much lower in NARR. Finally, the authors also discuss the consistency of their results with other assessments of land–precipitation coupling obtained from different methodologies.

Corresponding author address: Alexis Berg, Department of Environmental Sciences, Rutgers, The State University of New Jersey, 14 College Farm Rd., New Brunswick, NJ 08901-8551. E-mail: alexis.berg@noaa.gov
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  • Alfieri, L., Claps P. , D’Odorico P. , Laio F. , and Over T. M. , 2008: An analysis of the soil moisture feedback on convective and stratiformprecipitation. J. Hydrometeor., 9, 280291.

    • Search Google Scholar
    • Export Citation
  • Arakawa, A., and Schubert W. , 1974: Interaction of a cumulus cloud ensemble with the large-scale environment, Part I. J. Atmos. Sci., 31, 674701.

    • Search Google Scholar
    • Export Citation
  • Becker, E. J., Berbery E. H. , and Higgins R. W. , 2009: Understanding the characteristics of daily precipitation over the United States using the North American Regional Reanalysis. J. Climate, 22, 62686286.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., 1973: Non-precipitating cumulus convection and its parameterization. Quart. J. Roy. Meteor. Soc., 99, 178196.

  • Betts, A. K., 1992: FIFE atmospheric boundary layer budget methods. J. Geophys. Res., 97, 18 52318 531.

  • Betts, A. K., and Jakob C. , 2002: Evaluation of the diurnal cycle of precipitation, surface thermodynamics, and surface fluxes in the ECMWF model using LBA data. J. Geophys. Res., 107, 8045, doi:10.1029/2001JD000427.

    • Search Google Scholar
    • Export Citation
  • Bouttier, F., Mahfouf J. , and Noilhan J. , 1993: Sequential assimilation of soil-moisture from atmospheric low-level parameters. Part I: Sensitivity and calibration studies. J. Appl. Meteor., 32, 13351351.

    • Search Google Scholar
    • Export Citation
  • Brubaker, K., Entekhabi D. , and Eagleson P. , 1993: Estimation of Continental precipitation recycling. J. Climate, 6, 10771089.

  • Bukovsky, M., and Karoly D. , 2007: A brief evaluation of precipitation from the North American Regional Reanalysis. J. Hydrometeor., 8, 837846.

    • Search Google Scholar
    • Export Citation
  • Carleton, A. M., Travis D. J. , Adegoke J. O. , Arnold D. L. , and Curran S. , 2008: Synoptic circulation and land surface influences on convection in the Midwest U.S. “Corn Belt” during the summers of 1999 and 2000. Part II: Role of vegetation boundaries. J. Climate, 21, 36173641.

    • Search Google Scholar
    • Export Citation
  • Conil, S., Douville H. , and Tyteca S. , 2009: Contribution of realistic soil moisture initial conditions to boreal summer predictability. Climate Dyn., 32, 7593.

    • Search Google Scholar
    • Export Citation
  • Cook, B. I., Bonan G. B. , and Levis S. , 2006: Soil moisture feedbacks to precipitation in South Africa. J. Climate, 19, 41984206.

  • Dai, A., 2006: Precipitation characteristics in eighteen coupled climate models. J. Climate, 19, 46054630.

  • Dai, A., Giorgi F. , and Trenberth K. E. , 1999: Observed and model-simulated diurnal cycles of precipitation over the contiguous United States. J. Geophys. Res., 104, 63776402.

    • Search Google Scholar
    • Export Citation
  • Davin, E. L., de Noblet-Ducoudré N. , and Friedlingstein P. , 2007: Impact of land cover change on surface climate: Relevance of the radiative forcing concept. Geophys. Res. Lett., 34, L13702, doi:10.1029/2007GL029678.

    • Search Google Scholar
    • Export Citation
  • Delworth, T. L., and Coauthors, 2006: GFDL’s CM2 global coupled climate models. Part I: Formulation and simulation characteristics. J. Climate, 19, 643674.

    • Search Google Scholar
    • Export Citation
  • De Ridder, K., 1997: Land surface processes and the potential for convective precipitation. J. Geophys. Res., 102, 30 08530 090.

  • Dirmeyer, P. A., 2003: The role of the land surface background state in climate predictability. J. Hydrometeor., 4, 599610.

  • Dirmeyer, P. A., 2005: The land surface contribution to the potential predictability of boreal summer season climate. J. Hydrometeor., 6, 618632.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., and Brubaker K. L. , 2007: Characterization of the global hydrologic cycle from a back-trajectory analysis of atmospheric water vapor. J. Hydrometeor., 8, 2037.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., Brubaker K. L. , and DelSole T. , 2009a: Import and export of atmospheric water vapor between nations. J. Hydrol., 365, 1122, doi:10.1016/j.jhydrol.2008.11.016.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., Schlosser C. A. , and Brubaker K. L. , 2009b: Precipitation, recycling, and land memory: An integrated analysis. J. Hydrometeor., 10, 278288.

    • Search Google Scholar
    • Export Citation
  • Dominguez, F., and Kumar P. , 2008: Precipitation recycling variability and ecoclimatological stability—A study using NARR data. Part I: Central U.S. Plains ecoregion. J. Climate, 21, 51655186.

    • Search Google Scholar
    • Export Citation
  • Dominguez, F., Kumar P. , Liang X. , and Ting M. , 2006: Impact of atmospheric moisture storage on precipitation recycling. J. Climate, 19, 15131530.

    • Search Google Scholar
    • Export Citation
  • Douville, H., 2004: Relevance of soil moisture for seasonal atmospheric predictions: Is it an initial value problem? Climate Dyn., 22, 429446.

    • Search Google Scholar
    • Export Citation
  • Ek, M., and Holtslag A. , 2004: Influence of soil moisture on boundary layer cloud development. J. Hydrometeor., 5, 8699.

  • Eltahir, E. A. B., and Bras R. L. , 1996: Precipitation recycling. Rev. Geophys., 34, 367378.

  • Entekhabi, D., and Brubaker K. , 1995: An analytic approach to modeling land atmosphere interaction: 2. Stochastic formulation. Water Resour. Res., 31, 633643.

    • Search Google Scholar
    • Export Citation
  • Findell, K. L., and Eltahir E. A. B. , 2003a: Atmospheric controls on soil moisture–boundary layer interactions. Part I: Framework development. J. Hydrometeor., 4, 552569.

    • Search Google Scholar
    • Export Citation
  • Findell, K. L., and Eltahir E. A. B. , 2003b: Atmospheric controls on soil moisture–boundary layer interactions. Part II: Feedbacks within the continental United States. J. Hydrometeor., 4, 570583.

    • Search Google Scholar
    • Export Citation
  • Findell, K. L., Shevliakova E. , Milly P. C. D. , and Stouffer R. J. , 2007: Modeled impact of anthropogenic land cover change on climate. J. Climate, 20, 36213634.

    • Search Google Scholar
    • Export Citation
  • Findell, K. L., Gentine P. , Lintner B. R. , and Kerr C. , 2011: Probability of afternoon precipitation in eastern United States and Mexico enhanced by high evaporation. Nat. Geosci., 4, 434439.

    • Search Google Scholar
    • Export Citation
  • Fischer, E. M., Seneviratne S. I. , Lüthi D. , and Schär C. , 2007: The contribution of land-atmosphere coupling to recent European summer heatwaves. Geophys. Res. Lett., 34, L06707, doi:10.1029/2006GL029068.

    • Search Google Scholar
    • Export Citation
  • Gentine, P., Entekhabi D. , Chehbouni A. , Boulet G. , and Duchemin B. , 2007: Analysis of evaporative fraction diurnal behaviour. Agric. For. Meteor., 143, 1329, doi:10.1016/j.agrformet.2006.11.002.

    • Search Google Scholar
    • Export Citation
  • Gentine, P., Entekhabi D. , and Polcher J. , 2010: Spectral behaviour of a coupled land-surface and boundary-layer system. Bound.-Layer Meteor., 134, 157180, doi:10.1007/s10546-009-9433-z.

    • Search Google Scholar
    • Export Citation
  • Gentine, P., Entekhabi D. , and Polcher J. , 2011a: The diurnal behavior of evaporative fraction in the soil–vegetation–atmospheric boundary layer continuum. J. Hydrometeor., 12, 15301546.

    • Search Google Scholar
    • Export Citation
  • Gentine, P., Polcher J. , and Entekhabi D. , 2011b: Harmonic propagation of variability in surface energy balance within a coupled soil-vegetation-atmosphere system, Water Resour. Res., 47, W05525, doi:10.1029/2010WR009268.

    • Search Google Scholar
    • Export Citation
  • Gentine, P., Betts A. , Findell K. , Lintner B. , Tzella A. , and D’Andrea F. , 2013a: A probabilistic-bulk model of coupled mixed layer and convection. Part I: Clear-sky case. J. Atmos. Sci., in press.

    • Search Google Scholar
    • Export Citation
  • Gentine, P., Betts A. , Findell K. , Lintner B. , and D’Andrea F. , 2013b: A probabilistic-bulk model of coupled mixed layer and convection. Part II: Shallow convection case. J. Atmos. Sci., in press.

    • Search Google Scholar
    • Export Citation
  • Gentine, P., Holtslag A. A. M. , D’Andrea F. , and Ek M. , 2013c: Surface and atmospheric controls on moist convection onset over land. J. Hydrometeor., in press.

    • Search Google Scholar
    • Export Citation
  • GFDL Global Atmospheric Model Development Team, 2004: The new GFDL global atmosphere and land model AM2–LM2: Evaluation with prescribed SST simulations. J. Climate, 17, 46414673.

    • Search Google Scholar
    • Export Citation
  • Goessling, H. F., and Reick C. H. , 2011: What do moisture recycling estimates tell us? Exploring the extreme case of non-evaporating continents. Hydrol. Earth Syst. Sci., 15, 32173235, doi:10.5194/hess-15-3217-2011.

    • Search Google Scholar
    • Export Citation
  • Guo, Z. C., and Coauthors, 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part II: Analysis. J. Hydrometeor., 7, 611625.

    • Search Google Scholar
    • Export Citation
  • Hohenegger, C., Brockhaus P. , Bretherton C. S. , and Schär C. , 2009: The soil moisture–precipitation feedback in simulations with explicit and parameterized convection. J. Climate, 22, 50035020.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J., Hack J. , Shea D. , Caron J. , and Rosinski J. , 2008: A new sea surface temperature and sea ice boundary data set for the Community Atmosphere Model. J. Climate, 21, 51455153.

    • Search Google Scholar
    • Export Citation
  • Klein, S. A., Jiang X. , Boyle J. S. , Malyshev S. , and Xie S. , 2006: Diagnosis of the summertime warm and dry bias over the U.S. Southern Great Plains in the GFDL climate model using a weather forecasting approach. Geophys. Res. Lett., 33, L18805, doi:10.1029/2006GL027567.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., 2011: Climate science: Storm instigation from below. Nat. Geosci., 4, 427428.

  • Koster, R. D., and Suarez M. , 2003: Impact of land surface initialization on seasonal precipitation and temperature prediction. J. Hydrometeor., 4, 408423.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 11381140.

  • Koster, R. D., and Coauthors, 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview. J. Hydrometeor., 7, 590610.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2011: The second phase of the Global Land–Atmosphere Coupling Experiment: Soil moisture contributions to subseasonal forecast skill. J. Hydrometeor., 12, 805822.

    • Search Google Scholar
    • Export Citation
  • Lawrence, D. M., and Slingo J. M. , 2005: Weak land–atmosphere coupling strength in HadAM3: The role of soil moisture variability. J. Hydrometeor., 6, 670680.

    • Search Google Scholar
    • Export Citation
  • Lee, J.-E., Lintner B. R. , Boyce C. K. , and Lawrence P. J. , 2011: Land use change exacerbates tropical South American drought by sea surface temperature variability. Geophys. Res. Lett., 38, L19706, doi:10.1029/2011GL049066.

    • Search Google Scholar
    • Export Citation
  • Liang, X.-Z., Li L. , Dai A. , and Kunkel K. E. , 2004: Regional climate model simulation of summer precipitation diurnal cycle over the United States. Geophys. Res. Lett., 31, L24208, doi:10.1029/2004GL021054.

    • Search Google Scholar
    • Export Citation
  • Lin, S.-J., 2004: A “vertically Lagrangian” finite-volume dynamical core for global models. Mon. Wea. Rev., 132, 22932307.

  • Mahfouf, J. F., 1991: Analysis of soil moisture from near-surface parameters: A feasibility study. J. Appl. Meteor., 30, 15341547.

  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360.

  • Milly, P. C. D., and Shmakin A. B. , 2002: Global modeling of land water and energy balances. Part I: The Land Dynamics (LaD) model. J. Hydrometeor., 3, 283299.

    • Search Google Scholar
    • Export Citation
  • Moorthi, S., and Suarez M. J. , 1992: Relaxed Arakawa–Schubert: A parameterization of moist convection for general circulation models. Mon. Wea. Rev., 120, 9781002.

    • Search Google Scholar
    • Export Citation
  • Orlowsky, B., and Seneviratne S. I. , 2010: Statistical analyses of land–atmosphere feedbacks and their possible pitfalls. J. Climate, 23, 39183932.

    • Search Google Scholar
    • Export Citation
  • Paegle, J., Mo K. C. , and Nogues-Paegle J. , 1996: Dependence of simulated precipitation on surface evaporation during the 1993 United States summer floods. Mon. Wea. Rev., 124, 345361.

    • Search Google Scholar
    • Export Citation
  • Pal, J. S., and Eltahir E. A. B. , 2003: A feedback mechanism between soil moisture distribution and storm tracks. Quart. J. Roy. Meteor. Soc., 129, 22792297.

    • Search Google Scholar
    • Export Citation
  • Pielke, R. A. Sr., 2001: Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev. Geophys., 39, 151177.

    • Search Google Scholar
    • Export Citation
  • Pitman, A. J., and Coauthors, 2009: Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study. Geophys. Res. Lett., 36, L14814, doi:10.1029/2009GL039076.

    • Search Google Scholar
    • Export Citation
  • Polcher, J., 1995: Sensitivity of tropical convection to land surface processes. J. Atmos. Sci., 52, 31433161.

  • Pongratz, J., Reick C. , Raddatz T. , and Claussen M. , 2010: Biogeophysical versus biogeochemical climate response to historical anthropogenic land cover change. Geophys. Res. Lett., 37, L08702, doi:10.1029/2010GL043010.

    • Search Google Scholar
    • Export Citation
  • Rio, C., Hourdin F. , Grandpeix J.-Y. , and Lafore J.-P. , 2009: Shifting the diurnal cycle of parameterized deep convection over land. Geophys. Res. Lett., 36, L07809, doi:10.1029/2008GL036779.

    • Search Google Scholar
    • Export Citation
  • Rodriguez-Iturbe, I., Entekhabi D. , and Bras R. L. , 1991a: Nonlinear dynamics of soil moisture at climate scales: 1. Stochastic analysis. Water Resour. Res., 27, 18991906.

    • Search Google Scholar
    • Export Citation
  • Rodriguez-Iturbe, I., Entekhabi D. , Lee J. , and Bras R. L. , 1991b: Nonlinear dynamics of soil moisture at climate scales: 2. Chaotic analysis. Water Resour. Res., 27, 19071915.

    • Search Google Scholar
    • Export Citation
  • Ruane, A. C., 2010: NARR’s atmospheric water cycle components. Part II: Summertime mean and diurnal interactions. J. Hydrometeor., 11, 12201233.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., and Koster R. D. , 2012: A revised framework for analyzing soil moisture memory in climate data: Derivation and interpretation. J. Hydrometeor., 13, 404412.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., Corti T. , Davin E. L. , Hirschi M. , Jaeger E. B. , Lehner I. , Orlowsky B. , and Teuling A. J. , 2010: Investigating soil moisture climate interactions in a changing climate: A review. Earth Sci. Rev., 99, 125161.

    • Search Google Scholar
    • Export Citation
  • Sutton, C., Hamill T. M. , and Warner T. T. , 2006: Will perturbing soil moisture improve warm-season ensemble forecasts? A proof of concept. Mon. Wea. Rev., 134, 31743189.

    • Search Google Scholar
    • Export Citation
  • Taylor, C. M., Gounou A. , Guichard F. , Harris P. P. , Ellis R. J. , Couvreux F. , and de Kauwe M. , 2011: Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns. Nat. Geosci., 4, 430433.

    • Search Google Scholar
    • Export Citation
  • Taylor, C. M., De Jeu R. A. M. , Guichard F. , Harris P. P. , and Dorigo W. A. , 2012: Afternoon rain more likely over drier soils. Nature, 489, 423426.

    • Search Google Scholar
    • Export Citation
  • Teuling, A. J., and Coauthors, 2010: Contrasting response of European forest and grassland energy exchange to heatwaves. Nat. Geosci., 3, 722727, doi:10.1038/ngeo950.

    • Search Google Scholar
    • Export Citation
  • van der Ent, R. J., and Savenije H. H. G. , 2011: Length and time scales of atmospheric moisture recycling. Atmos. Chem. Phys., 11, 18531863, doi:10.5194/acp-11-1853-2011.

    • Search Google Scholar
    • Export Citation
  • van der Ent, R. J., Savenije H. H. G. , Schaefli B. , and Steele-Dunne S. C. , 2010: Origin and fate of atmospheric moisture over continents. Water Resour. Res., 46, W09525, doi:10.1029/2010WR009127.

    • Search Google Scholar
    • Export Citation
  • Vautard, R., and Coauthors, 2007: Summertime European heat and drought waves induced by wintertime Mediterranean rainfall deficit. Geophys. Res. Lett., 34, L07711, doi:10.1029/2006GL028001.

    • Search Google Scholar
    • Export Citation
  • Wang, J. F., and Coauthors, 2009: Impact of deforestation in the Amazon basin on cloud climatology. Proc. Natl. Acad. Sci. USA, 106, 36703674.

    • Search Google Scholar
    • Export Citation
  • Wei, J., Dickinson R. E. , and Chen H. , 2008: A negative soil moisture–precipitation relationship and its causes. J. Hydrometeor., 9, 13641376.

    • Search Google Scholar
    • Export Citation
  • Weisheimer, A., Doblas-Reyes F. J. , Jung T. , and Palmer T. N. , 2011: On the predictability of the extreme summer 2003 over Europe. Geophys. Res. Lett., 38, L05704, doi:10.1029/2010GL046455.

    • Search Google Scholar
    • Export Citation
  • Westra, D., Steeneveld G. J. , and Holtslag A. A. M. , 2012: Some observational evidence for dry soils supporting enhanced relative humidity at the convective boundary layer top. J. Hydrometeor., 13, 13471358.

    • Search Google Scholar
    • Export Citation
  • Xue, Y., Zeng F. , Mitchell K. , Janjic Z. , and Rogers E. , 2001: The impact of land surface processes on simulations of the U.S. hydrological cycle: A case study of the 1993 flood using the SSiB land surface model in the NCEP Eta regional model. Mon. Wea. Rev., 129, 28332860.

    • Search Google Scholar
    • Export Citation
  • Zeng, N., and Neelin J. D. , 1999: A land–atmosphere interaction theory for the tropical deforestation problem. J. Climate, 12, 857872.

    • Search Google Scholar
    • Export Citation
  • Zeng, X., Barlage M. , Castro C. , and Fling K. , 2010: Comparison of land–precipitation coupling strength using observations and models. J. Hydrometeor., 11, 979994.

    • Search Google Scholar
    • Export Citation
  • Zhang, J., Wang W.-C. , and 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, doi:10.1029/2008JD009807.

    • Search Google Scholar
    • Export Citation
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