A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature

Journal of Geophysical Research Atmospheres

Volumn 114, Issue 16, 2009, Pages

  Tian, Xiangjun ^a   Xie, Zhenghui ^a   Dai, Aiguo ^b   Shi, Chunxiang ^c   Jia, Binghao ^a   Chen, Feng ^a   Yang, Kun ^d  

^a INSTITUTE OF ATMOSPHERIC PHYSICS   (China)

^b NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^c NATIONAL SATELLITE METEOROLOGICAL CENTER   (China)

^d INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC RADIATION; CALIBRATION; DATA PROCESSING; DESIGN; GEOLOGIC MODELS; GROUNDWATER; MATHEMATICAL OPERATORS; MICROWAVES; MOISTURE DETERMINATION; PARAMETER ESTIMATION; PERMITTIVITY; RADIATIVE TRANSFER; SIMULATORS; SOIL MOISTURE; STRUCTURAL OPTIMIZATION; TEMPERATURE;

ADVANCED MICROWAVE SCANNING RADIOMETER- EOS; BRIGHTNESS TEMPERATURES; IN-SITU OBSERVATIONS; LAND DATA ASSIMILATION SYSTEMS; LAND SURFACE MODELS; MICROWAVE BRIGHTNESS TEMPERATURE; MODEL PARAMETERS; MODEL STATE; OPTIMAL PARAMETER; OPTIMIZATION TECHNIQUES; PARAMETER CALIBRATION; PARAMETER OPTIMIZATION; RADIATIVE TRANSFER MODEL; SHUFFLED COMPLEX EVOLUTION; SOIL MOISTURE PROFILES; SURFACE SOIL MOISTURE; SURFACE TEMPERATURES; TIME WINDOWS; TWO PHASIS; VARIATIONAL ASSIMILATION; VARIATIONAL DATA ASSIMILATION; VOLUMETRIC SOIL MOISTURE CONTENTS;

SOIL SURVEYS;

ALGORITHM; DATA ASSIMILATION; MICROWAVE IMAGERY; MOISTURE CONTENT; RADIATIVE TRANSFER; SATELLITE IMAGERY; SIMULATION; SOIL MOISTURE; SURFACE TEMPERATURE;

EID: 71949107809     PISSN: 01480227     EISSN: None     Source Type: Journal    
DOI: 10.1029/2008JD011600     Document Type: Article

References (54)

1. Beezley, J. D., and J. Mandel (2008), Morphing ensemble Kalman filters, Tellus, Ser. A, 60, 131-140.
2. Chahine, T. M. (1992), The hydrological cycle and its influence on climate, Nature, 359, 373-380, doi:10.1038/359373a0.
3. 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, 137-149, doi:10.1016/S0309-1708 (02) 00088-X.
4. Darcy, H. (1856), Les Fontaines Publiques de la Ville de Dijon, Dalmont, Paris.
5. Dickinson, R. E., K: W. Oleson, G. B. Bonan, F. Hoffman, P. Thornton, M. Vertenstein, Z. L. Yang, and X. Zeng (2006), The Community Land Model and its climate statistics as a component of the Community Climate System Model, J. Clim., 19, 2302-2324, doi:10.1175/JCLI3742.1. (Pubitemid 43881284)
6. Dirmeyer, P. A., A. J. Dolman, and N. Sato (1999), The pilot phase of the Global Soil Wetness Project, Bull. Am. Meteorol. Soc., 80, 851-878, doi:10.1175/1520-0477 (1999) 080<0851:TPPOTG>2.0. CO;2.
7. Dobson, M. C., F. T. Ulaby, M. T. Halikainen, and M. A. El-Rayes (1985), Microwave dielectric behavior of wet soil-part II: Dielectric mixing models, IEEE Trans. Geosci. Remote Sens., GE- 23, 35-46, doi:10.1109/TGRS.1985.289498.
8. Duan, Q., V. K. Gupta, and S. Sorooshian (1993), A shuffled complex evolution approach for effective and efficient global minimization, J. Optim. Theory Appl., 76, 501-521, doi:10.1007/BF00939380.
9. Entekhabi, D., J. F. Galantowicz, and E. G. Njoku (1994), Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observation, IEEE Trans. Geosci. Remote Sens., 32, 438-448, doi:10.1109/36.295058.
10. Evensen, G. (1994), Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res., 99, 10, 143-10, 162.
11. Evensen, G. (2003), The ensemble Kalman filter: Theoretical formulation and practical implementation, Ocean Dyn., 53, 343-367, doi:10.1007 /S10236-003-0036-9.
12. Fujii, H. (2005), Development of a microwave radiative transfer model for vegetated land surface based on comprehensive in-situ observations, PhD diss., Univ. of Tokyo.
13. Houser, P. R., W. J. Shuttleworth, J. S. Famiglietti, H. V. Gupta, K. H. Syed, and D. C. Goodrich (1998), Integration of soil moisture remote sensing and hydrologic modeling using data assimilation, Water Resour. Res., 34, 3405-3420, doi:10.1029/1998WR900001.
14. Jackson, T. J. (1993), Measuring surface soil moisture using passive microwave remote sensing, Hydrol. Process., 7, 139-152, doi:10.1002 /hyp. 3360070205.
15. Jackson, T. J., and T. J. Schmuge (1991), Vegetation effects on the microwave emission of soils, Remote Sens. Environ., 36, 203-212, doi:10.1016/0034-4257 (91) 90057-D.
16. Kalnay, E., H. Li, T. Miyoshi, S. C. Yang, and J. Ballabrera-Poy (2007), 4-D-Var or ensemble Kalman filter?, Tellus, Ser. A, 59, 758-773, doi:10.1111/j.1600-0870.2007.00261.x. (Pubitemid 47434011)
17. Ly, H. V., and H. T. Tran (2001), Modeling and control of physical processes using proper orthogonal decomposition, Math. Comput. Model., 33, 223-236, doi:10.1016/S0895-7177 (00) 00240-5.
18. Ly, H. V., and H. T. Tran (2002), Proper orthogonal decomposition for flow calculations and optimal control in a horizontal CVD reactor, Q. Appl. Math., 60, 631-656.
19. Mitchell, K. E., et al. (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.
20. Moradkhani, H., K.-L. Hsu, H. Gupta, and S. Sorooshian (2005a), Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter, Water Resour. Res., 41, W05012, doi:10.1029/2004WR003604. (Pubitemid 40856462)
21. Moradkhani, H. S., S. Sorooshian, H. V. Gupta, and P. Houser (2005b), Dual state-parameter estimation of hydrologic model using ensemble Kalman filter, Adv. Water Resour., 28, 135-147, doi:10.1016/j.advwatres. 2004.09.002.
22. Nijssen, B., R. Schnur, and D. P. Lettenmaier (2001), Global retrospective estimation of soil moisture using the variable infiltration capacity land surface model, 1980-93, J. Clim., 14, 1790-1808, doi:10.1175/1520-0442 (2001) 014<1790:GREOSM>2.0. CO;2.
23. Njoku, E. G., and D. Entekhabi (1996), Passive microwave remote sensing of soil moisture, J. Hydrol. Amsterdam, 184, 101-129, doi:10.1016 /0022-1694 (95) 02970-2.
24. Njoku, E. G., T. J. Jackson, V. Lakshmi, T. K. Chan, and S. V. Nghiem (2003), Soil moisture retrieval from AMSR-E, IEEE Trans. Geosci. Remote Sens., 41, 215-229, doi:10.1109/TGRS.2002.808243. (Pubitemid 350178126)
25. Oleson, K. W., et al. (2004), Technical description of the community land model (CLM), Rep. NCAR/TN-461+STR, 186 pp., Natl. Cent. for Atmos. Res., Boulder, Colo.
26. Owe, M., R. de Jeu, and J. Walker (2001), A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index, IEEE Trans. Geosci. Remote Sens., 39, 1643-1654, doi: 10.1109/36.942542. (Pubitemid 32933003)
27. Paloscia, S., and P. Pampaloni (1988), Microwave polarization index for monitoring vegetation growth, IEEE Trans. Geosci. Remote Sens., 26, 617-621, doi:10.1109/36.7687.
28. Paloscia, S., G. Macelloni, E. Santi, and T. Koike (2001), A multifrequency algorithm for the retrieval of soil moisture on a large scale using microwave data from SMMR and SSM/I satellites, IEEE Trans. Geosci. Remote Sens., 39, 1655-1661, doi:10.1109/36.942543. (Pubitemid 32933004)
29. Qian, T., A. Dai, K. E. Trenberth, and K. W. Oleson (2006), Simulation of global land surface conditions from 1948 to 2004. Part I: Forcing data and evaluations, J. Hydrometeorol., 7, 953-975, doi:10.1175/JHM540.1. (Pubitemid 44734307)
30. Reichle, R. H., and D. Entekhabi (2001), Downscaling of radio brightness measurements for soil moisture estimation: A four-dimensional variational data assimilation approach, Water Resour. Res., 37, 2353-2364.
31. Reichle, R. H., D. Entekhabi, and D. B. McLaughlin (2001), Downscaling of radio brightness measurements for soil moisture estimation: A fourdimensional variational data assimilation approach, Water Resour. Res., 37, 2353-2364, doi:10.1029/2001WR000475. (Pubitemid 32808505)
32. Reichle, R. H., D. B. McLaughlin, and D. Entekhabi (2002a), Hydrologic data assimilation with the ensemble Kalman filter, Mon. Weather Rev., 130, 103-114, doi:10.1175/1520-0493 (2002) 130<0103:HDAWTE>2.0. CO;2.
33. Reichle, R. H., J. P. Walker, R. D. Koster, and P. R. Houser (2002b), Extended versus ensemble Kalman filtering for land data assimilation, J. Hydrometeorol., 3, 728-740, doi:10.1175/1525-7541 (2002) 003<0728: EVEKFF>2.0. CO;2.
34. Sellers, P. J., D. A. Randall, G. J. Collatz, J. A. Berry, C. B. Field, D. A. Dazlich, C. Zhang, G. D. Collelo, and L. Bounoua (1996), A revised land surface parameterization (SIB2) for atmospheric GCMs. Part I: Model formulation, J. Clim., 9, 676-705, doi:10.1175/1520-0442 (1996) 009<0676:ARLSPF>2.0. CO;2. (Pubitemid 126544330)
35. Seuffert, G., H. Wilker, P. Viterbo, J. F. Mahfouf, M. Drusch, and J. C. Calvet (2003), Soil moisture analysis combining screen-level parameters and microwave brightness temperature: A test with field data, Geophys. Res. Lett., 30 (10), 1498, doi:10.1029/2003GL017128.
36. Seufrert, G., H. Wilker, P. Viterbo, M. Drusch, and J. F. Mahfouf (2004), The usage of screen-level parameters and microwave brightness temperature for soil moisture analysis, J. Hydrometeorol., 5, 516-531, doi: 10.1175/1525-7541 (2004) 005<0516:TUOSPA>2.0. CO;2.
37. Sheffield, J., and E. F. Wood (2008), Global trends and variability in soil moisture and drought characteristics, 1950-2000, from observation-driven simulations of the terrestrial hydrologic cycle, J. Clim., 21, 432-458, doi: 10.1175/2007JCLI1822.1.
38. Shi, C. X. (2008), A study on soil moisture remote sensing data assimilation based on ensemble Kalman filter (EnKF) (in Chinese), Ph. D. diss., 177 pp., Inst. of Atmos. Phys., Chin. Acad. of Sci., Beijing.
39. Shi, J. C., J. Wang, A. Y. Hsu, P. E. O'Neill, and E. T. Engman (1997), Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data, IEEE Trans. Geosci. Remote Sens., 35, 1254-1266, doi:10.1109/36.628792.
40. Shi, J. C., L. Jiang, L. Zhang, K. S. Chen, J. P. Wigeron, and A. Chanzy (2005), A parameterized multifrequency-polarization surface emission model, IEEE Trans. Geosci. Remote Sens., 43, 2831-2841, doi:10.1109 /TGRS.2005.857902.
41. Tian, X., and Z. Xie (2008), A land surface soil moisture data assimilation framework in consideration of the model subgrid-scale heterogeneity and soil water thawing and freezing, Sci. China, 51, 992-1000, doi:10.1007 /s11430-008-0069-5.
42. Tian, X., A. Dai, D. Yang, and Z. Xie (2007), Effects of precipitation-bias corrections on surface hydrology over northern latitudes, J. Geophys. Res., 112, D14101, doi:10.1029/2007JD008420. (Pubitemid 47433797)
43. Tian, X., Z. Xie, and A. Dai (2008a), An ensemble-based explicit fourdimensional variational assimilation method, J. Geophys. Res., 113, D21124, doi:10.1029/2008JD010358.
44. Tian, X., Z. Xie, and A. Dai (2008b), A land surface soil moisture data assimilation system based on the dual-UKF method and the Community Land Model, J. Geophys. Res., 113, D14121, doi:11.1029/2007JD009650.
45. Ulaby, F. T., R. K. Moore, and A. K. Fung (1986), Microwave Remote Sensing: Active and Passive, vol. 3, From Theory to Applications, Artech House, Norwood, Mass.
46. Vrugt, J. A., C. G. H. Diks, H. V. Gupta, W. Bouten, and J. M. Verstraten (2005), Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation, Water Resour. Res., 41, W01017, doi:10.1029/2004WR003059. (Pubitemid 40359297)
47. Walker, J. P., G. R. Willgoose, and J. D. Kalma (2001), One-dimensional soil moisture profile retrieval by assimilation near-surface observations: A comparison of retrieval algorithms, Adv. Water Resour., 24, 631-650, doi:10.1016/S0309-1708 (00) 00043-9.
48. Wang, J. R., and B. J. Choudhury (1981), Remote sensing of soil moisture content cover bare fields at 1.4GHz frequency, J. Geophys. Res., 86, 5277-5282, doi:10.1029/JC086iC06p05277.
49. Wegmuller, U., and C. Matzler (1999), Rough bare soil reflectivity model, IEEE Trans. Geosci. Remote Sens., 37, 1391-1395, doi:10.1109 /36.763303.
50. Wen, J., Z. Su, and Y. Ma (2003), Determination of land surface temperature and soil moisture from Tropic Rainfall Measuring Mission/Microwave Imager remote sensing data, J. Geophys. Res., 108 (D2), 4038, doi:10.1029/2002JD002176.
51. Wigneron, J. P., J. C. Calvet, T. Pellarin, A. A. Van de Griend, M. Berger, and P. Ferrazzoli (2003), Retrieving near-surface soil moisture from microwave radiometric observations: Current status and future plans, Remote Sens. Environ., 85, 489-506, doi:10.1016/S0034-4257 (03) 00051-8.
52. Yang, K., T. Watanabe, T. Koike, X. Li, H. Fujii, K. Tamagam, Y. Ma, and H. Ishikawa (2007a), An auto-calibration system to assimilate AMSR-E data into a land surface model for estimating soil moisture and surface energy budget, J. Meteorol. Soc. Jpn., 85 A, 229-242, doi:10.2151 /jmsj.85A.229.
53. Yang, K., T. Watanabe, T. Koike, X. Li, H. Fujii, K. Tamagam, Y. Ma, and H. Ishikawa (2007b), Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget, J. Meteorol. Soc. Jpn., 85 A, 229-242, doi:10.2151/jmsj.85A.229.
54. Zhang, S. W., H. R. Li, W. D. Zhang, C. J. Qiu, and X. Li (2006), Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kalman filter (EnKF), Adv. Atmos. Sci., 20, 845-848.