SEARCH

SEARCH BY CITATION

References

  • Boni, G., F. Castelli, and D. Entekhabi (2001), Sampling strategies and assimilation of ground temperature for the estimation of surface energy balance components, IEEE Trans. Geosci. Remote Sens., 39, 165172.
  • Brusdal, K., J. M. Brankart, G. Halberstadt, G. Evensen, P. Brasseur, P. J. Van Leeuwen, E. Dombrowsky, and J. Verron (2003), A demonstration of ensemble-based assimilation methods with a layered OGCM from the perspective of operational ocean forecasting systems, J. Mar. Syst., 40–41, 253289.
  • Burgers, G., P. J. Van Leeuwen, and G. Evensen (1998), Analysis scheme in the ensemble Kalman filter, Mon. Weather Rev., 126(6), 17191724.
  • Castelli, F., D. Entekhabi, and E. Caporali (1999), Estimation of surface heat flux and an index of soil moisture using adjoint-state surface energy balance, Water Resour. Res., 35, 31153125.
  • Chen, F., K. Mitchell, J. Schaake, Y. Xue, H.-L. Pan, V. Koren, Q. Duan, M. Ek, and A. Betts (1996), Modeling of land surface evaporation by four schemes and comparison with FIFE observations, J. Geophys. Res., 101(D3), 72517268.
  • Choudhury, B. J., T. Schmugge, A. Chang, and R. W. Newton (1979), Effect of surface roughness on the microwave emission from soils, J. Geophys. Res., 84(C9), 56995706.
  • Courtier, P., J. Derber, R. Errico, J.-F. Louis, and T. Vukicevic (1993), Important iterature on the use of adjoint, variational methods and the Kalman filter in meteorology, Tellus, Ser. A, 45, 342357.
  • Crosson, W. L., C. Laymon, R. Inguva, and M. Schamschula (2002), Assimilating remote sensing data in a surface flux-soil moisture model, Hydrol. Processes, 16(8), 16451662.
  • Crow, W. T. (2003), Correcting land surface model predictions for the impact of temporally sparse rainfall rate measurements using an ensemble kalman filter and surface brightness temperatures, J. Hydrometeorol., 4(5), 960973.
  • Crow, W. T., and E. F. Wood (2003), The assimilation of remotely-sensed soil brightness temperature imagery into a land surface model using ensemble Kalman filtering: A case study based on estar measurements during SGP97, Adv. Water Resour., 26(2), 137149.
  • Entekhabi, D., H. Nakamura, and E. Njoku (1994), Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations, IEEE Trans. Geosci. Remote Sens., 32, 438448.
  • Entekhabi, D., et al. (2004), The Hydrosphere State (Hydros) mission concept: An Earth system pathfinder for global mapping of soil moisture and land freeze/thaw, IEEE Trans. Geosci. Remote Sens., 42, 21842195.
  • Evensen, G. (1994), Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res., 99(C5), 10,14310,163.
  • Evensen, G. (2003), The ensemble Kalman filter: Theoretical formulation and practical implementation, Ocean Dyn., 53, 343367.
  • Evensen, G., and P. J. Van Leeuwen (1996), Assimilation of Geosat altimeter data for the Agulhas Current using the ensemble Kalman filter with a quasigeostrophic model, Mon. Weather Rev., 124(1), 8596.
  • Evensen, G., and P. J. Van Leeuwen (2000), An ensemble Kalman smoother for nonlinear dynamics, Mon. Weather Rev., 128(6), 18521867.
  • Galantowicz, J., D. Entekhabi, and E. Njoku (1999), Tests of sequential data assimilation for retrieving profile soil moisture and temperature from observed L-band radiobrightness, IEEE Trans. Geosci. Remote Sens., 37, 18601870.
  • Gelb, A. (1974), Applied Optimal Estimation, MIT Press, Cambridge, Mass.
  • Ghil, M., and P. Manalotte-Rizzoli (1991), Data assimilation in meteorology and oceanography, Adv. Geophys., 33, 141266.
  • Giering, R., and T. Kaminski (1998), Recipes for adjoint code construction, Trans. Math. Software, 24(4), 437474.
  • Gronnevik, R., and G. Evensen (2001), Application of ensemble-based techniques in fish stock assessment, Sarsia, 86, 517526.
  • Hawk, K., and P. Eagleson (1992), Climatology of station storm rainfall in the continental United States: Parameters of the Bartlett-Lewis and Poisson rectangular pulses models, Tech. Rep. 336, Mass. Inst. of Technol., Cambridge.
  • Heemink, A., M. Verlaan, and A. Segers (2001), Variance reduced ensemble Kalman filtering, Mon. Weather Rev., 129(7), 17181728.
  • Houtekamer, P., and H. Mitchell (1998), Data assimilation using an Ensemble Kalman filter technique, Mon. Weather Rev., 126(3), 796811.
  • Houtekamer, P., and H. Mitchell (2001), A sequential Kalman filter for atmospheric data assimilation, Mon. Weather Rev., 129(1), 123137.
  • Jackson, T. (1997), Soil moisture estimation using special satellite microwave/imager (SSM/I) satellite data over a grassland region, Water Resour. Res., 33, 14751484.
  • Jackson, T., and T. Schmugge (1991), Vegetation effects on the microwave emission of soils, Remote Sens. Environ., 36(3), 203212.
  • Jackson, T., D. L. Vine, C. Swift, T. Schmugge, and F. Schiebe (1995), Large area mapping of soil moisture using the ESTAR passive microwave radiometer in Washita'92, Remote Sens. Environ., 54(1), 2737.
  • Jackson, T., D. LeVine, A. Hsu, A. Oldak, P. Starks, C. Swift, J. Isham, and M. Haken (1999), Soil moisture mapping at regional scales using microwave radiometry: The Southern Great Plains Hydrology Experiment, IEEE Trans. Geosci. Remote. Sens., 37, 21362151.
  • Jazwinski, A. H. (1970), Stochastic Processes and Filtering Theory, Elsevier, New York.
  • Ljung, L. (1979), Asymptotic behaviour of the extended Kalman filter as a parameter estimator for linear systems, IEEE Trans. Autom. Control, 24, 3650.
  • Lohmann, D., et al. (2004), Streamflow and water balance intercomparisons of four land surface models in the North America land data assimilation system project, J. Geophys. Res., 109, D07S91, doi:10.1029/2003JD003517.
  • Lorenc, A. C. (1986), Analysis methods for numerical weather prediction, Q. J. R. Meteorol. Soc., 112(474), 11771194.
  • Margulis, S. A. (2002), Variational sensitivity analysis and data assimilation studies of the coupled land surface-atmospheric boundary layer system, Ph.D. thesis, Mass. Inst. of Technol., Cambridge.
  • Margulis, S. A., and D. Entekhabi (2001), Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface, Hydrol. Earth Syst. Sci., 5(1), 2738.
  • Margulis, S. A., D. McLaughlin, D. Entekhabi, and S. Dunne (2002), Land data assimilation and estimation of soil moisture using measurements from the Southern Great Plains 1997 Field Experiment, Water Resour. Res., 38(12), 1299, doi:10.1029/2001WR001114.
  • Nakamura, H., D. Entekhabi, and E. Njoku (1994), Soil moisture profile retrieval by assimilation by multispectral remote sensing and surface observations, paper presented at Geosciences and Remote Sensing Annual Conference, Inst. of Electr. and Electron. Eng., Pasadena, Calif.
  • Reichle, R. (2000), Variational assimilation of remote sensing data for land surface hydrologic applications, Ph.D. thesis, Massachusetts Institute of Technology.
  • Reichle, R., D. Entekhabi, and D. McLaughlin (2001a), Downscaling of radiobrightness measurements for soil moisture estimation: A four-dimensional variational data assimilation approach, Water Resour. Res., 37, 23532364.
  • Reichle, R., D. B. McLaughlin, and D. Entekhabi (2001b), Variational data assimilation of microwave radiobrightness observations for land surface hydrology applications, IEEE Trans. Geosci. Remote Sens., 39, 17081718.
  • Reichle, R., D. McLaughlin, and D. Entekhabi (2002), Hydrologic data assimilation with the ensemble Kalman filter, Mon. Weather Rev., 130(1), 103114.
  • Rodriguez-Iturbe, I., V. K. Gupta, and E. Waymire (1984), Scale considerations in the modeling of temporal rainfall, Water Resour. Res., 20, 16111619.
  • Segers, A., A. Heemink, M. Verlaan, and M. VanLoon (2000), A modified RRSQRT-filter for assimilating data in atmospheric chemistry models, Environ. Modell. Software, 15, 663671.
  • Ulaby, F., R. Moore, and A. Fung (1986), Microwave Remote Sensing, Artech House, Norwood, Mass.
  • Van Leeuwen, P. J. (2001), An ensemble smoother with error estimates, Mon. Weather Rev., 129(4), 709728.
  • Van Leeuwen, P. J., and G. Evensen (1996), Data assimilation and inverse methods in terms of a probabilistic formulation, Mon. Weather Rev., 124(12), 28982913.
  • Verlaan, M. (1998), Efficient Kalman filtering algorithms for hydrodynamic models, Ph.D. thesis, Technische Univ. Delft, Delft, Netherlands.
  • Verlaan, M., and A. Heemink (2001), Nonlinearity in data assimilation applications: A practical method for analysis, Mon. Weather Rev., 129(6), 15781589.
  • Walker, J. P., and P. R. Houser (2001), A methodology for initializing soil moisture in a global climate model: Assimilation of near-surface soil moisture observations, J. Geophys. Res., 106(D11), 11,76111,774.
  • Walker, J. P., G. R. Willgoose, and J. D. Kalma (2001), One-dimensional soil moisture profile retrieval by assimilation of near-surface observations: A comparison of retrieval algorithms, Adv. Water Resour., 24, 631650.
  • Wang, J., and T. Schmugge (1980), An empirical model for the complex dielectric permittivity of soils as a function of water content, IEEE Trans. Geosci. Remote Sens., 18, 288295.
  • Wunsch, C. (1996), The Ocean Circulation Inverse Problem, Cambridge Univ. Press, New York.