Development of a Chinese land data assimilation system: Its progress and prospects

Progress in Natural Science: Materials International

Volumn 17, Issue 8, 2007, Pages 881-892

  Xin, Li ^a   Chunlin, Huang ^a   Tao, Che ^a   Rui, Jin ^a   Shugong, Wang ^a   Jiemin, Wang ^a   Feng, Gao ^a   Shuwen, Zhang ^b   Chongjian, Qiu ^b   Chenghai, Wang ^b  

^a Chinese Academy of Sciences   (China)

^b LANZHOU UNIVERSITY   (China)

Author keywords

Kalman filter; Land data assimilation; Land surface model; Passive remote sensing

Indexed keywords

BANDPASS FILTERS; IMAGE ENHANCEMENT; MICROWAVE SENSORS; MICROWAVES; MONTE CARLO METHODS; PASSIVE FILTERS; RADIATIVE TRANSFER; REMOTE SENSING; SNOW; SOIL MOISTURE; SOIL SURVEYS; SURFACE MEASUREMENT; TEMPERATURE;

BIOSPHERE MODELS; LAND DATA ASSIMILATION; LAND DATA ASSIMILATION SYSTEMS; LAND MODEL; LAND SURFACE; LAND SURFACE MODELS; LAND-SURFACE PROCESS; MULTI-SOURCES; PASSIVE REMOTE SENSING; SIMPLE++; PASSIVE MICROWAVE REMOTE SENSING;

KALMAN FILTERS;

EID: 34548177307     PISSN: 10020071     EISSN: None     Source Type: Journal    
DOI: 10.1080/10002007088537487     Document Type: Article

References (64)

1. EntinJK, Robock A, VinnikovKY, et al. Evaluation of global soil wetness project soil moisture simulation. Journal of the Meteorological Society of Japan, 1999, 77(1B): 183-198
2. Koike T. Coordinated Enhanced Observing Period (CEOP)-an initial step for integrated global water cycle observation. World Meteorological Organization Bulletin, 2004, 53(2): 115-121
3. Daley R. Atmospheric Data Analysis. New York: Cambridge University Press, 1991, 457
4. Talagrand O. Assimilation of observations, an introduction. Journal of the Meteorological Society of Japan, 1997, 75(1B): 191- 209
5. McLaughlin D. Recent development in hydrologic data assimila tion. Reviews of Geophysics, 1995, 33 (supplement): 977-984
6. Entekhabi D, Galantowicz JF and Njoku EG. Solving the inverse problem for soil moisture and temperature profiles by sequential as similation of multifrequency remotely sensed observations. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(2): 438-448
7. Galantowicz JF, Entekhabi D and Njoku EG. Tests of sequential data assimilation for retrieving profile soil moisture and temperature from observed L-band radiobrightness. IEEE Transactions on Geo science and Remote Sensing, 1999, 37(4): 1860-1870
8. Houser PR, Shuttleworth WJ, Famiglietti JS, et al. Integration of soil moisture remote sensing and hydrologic modeling using data as similation Water Resources Research, 1998, 34(12): 3405- 3420
9. Walker JP and Houser PR. A methodology for initializing soil moisture in a global climate model: Assimilation of near-surface soil moisture observations. Journal of Geophysical Research, 2001, 106(D11): 11761-11774
10. Crow WT and Wood EF. The assimilation of remotely sensed soil brightness temperature imagery into a land surface model using En semble Kalman filtering: A case study based on ESTAR measurements during SGP97. Advances in Water Resources, 2003, 26 (2): 137-149
11. Margulis SA, McLaughlin D, Entekhabi D, et al. Land data as similation and estimation of soil moisture using measurements from the Southern Great Plains 1997 Field Experiment. Water Re sources Research, 2002, 38: 35-1-35-18
12. Reichle RH, McLaughlin DB and Entekhabi D. Variational data assimilation of microwave radiobrightness observations for land surface hydrology applications. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(8): 1708-1718
13. Reichle RH, Koster RD, Dong JR, et al. Global soil moisture from satellite observations, land surf ace models, and ground data: Implications for data assimilation. Journal of Hydrometeorology, 2004, 5(3): 430-442
14. Sun C, Walker JP and Houser PR. A methodology for snow data assimilation in a land surface model. Journal of Geophysical Re search, 2004, 109: D08108
15. Mitchell KE, LohmannD, HouserPR, et al. The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. Journal of Geophysical Research, 2004, 109: D07S90
16. Rodell M, Houser PR, Jambor U, et al. The global land data as similation system. Bulletin of the American Meteorological Society, 2004, 85(3): 381-394
17. van den Hurk B. ELDAS Final Report. KNMI, ECMWF, 2005
18. Li X and Huang CL. Data assimilation: A new means for multi-source geospatial data integration. Science and Technology Review (in Chinese), 2004, (12): 13-16
19. Huang CL and Li X. A review of land data assimilation system. Remote Sensing Technology and Application (in Chinese), 2004, 19(5): 424-430
20. Evensen G. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte-Carlo methods to forecast error statistics. Journal of Geophysical Research, 1994, 99 (C5): 10143-10162
21. Burgers G, van Leeuwen PJ and Evensen G. Analysis scheme in the ensemble Kalman filter. Monthly Weather Review, 1998, 126 (6): 1719-1724
22. Houtekamer PL and Mitchell HL. Data assimilation using an en semble Kalman filter technique. Monthly Weather Review, 1998, 126(3): 796-811
23. Evcnsen G. The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dynamics, 2003, 53: 343- 367
24. Evensen G. Sampling strategies and square root analysis schemes fortheEnKF. Ocean Dynamics, 2004, 54(6): 539-560
25. Reichle RH, McLaughlin DB and Entekhabi D. Hydrologic data assimilation with the ensemble Kalman filter. Monthly Weather Review, 2002, 130(1): 103-114
26. Zhang SW, Li HR, Zhang WD, et al. Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kalman filter (EnKF). Advances in Atmospheric Sciences, 2005, 22(6): 936-945
27. Huang CL and Li X. Experiments of soil moisture data assimilation system based on ensemble Kalman filter. Plateau Meteorology (in Chinese), 2006, 25(4): 665-671
28. Huang CL and Li X. Sensitive analysis on land data assimilation scheme of soil moisture. Advances in Water Science (in Chinese), 2006, 17(4): 457-465
29. Huang CL and Li X. Experiments of soil moisture data assimilation system based on ensemble Kalman filter. In: The 9th International Symposium on Physical Measurements and Signatures in Remote Sensing. Beijing, 2005, 386-389
30. Li X. Development of a land data assimilation system: System implementation and numerical experiments at the CEOP reference sites. CAREERI/CAS, 2006, 65
31. Li X, Koike T and Mahadevan P. A very fast simulated re-annealing (VFSA) approach for land data assimilation. Computers and Geosciences, 2004, 30(3): 239-248
32. Li X, Koike T and Cheng GD. An algorithm for land data assimilation by using simulated annealing method. Advances in Earth Sciences (in Chinese), 2003, 18(4): 632-636
33. Pathmathevan M, Koike T, Li X, et al. A simplified land data as similation scheme and its application to soil moisture experiments in 2002 (SMEX02). Water Resources Research, 2003, 39(12): SWC6-1
34. Zhang SW, Qiu CJ and Xu Q. Estimating soil water contents from soil temperature measurements by using an adaptive Kalman filter. Journal of Applied Meteorology, 2004, 43(2): 379-389
35. Zhang SW, Qiu CJ and Zhang WD. Estimating heat fluxes by merging profile formulae and the energy budget with a variational technique. Advances in Atmospheric Sciences, 2004, 21(4): 627-636
36. Ren H, Wang CH, Qiu CJ, et al. Study of calculating surface flux in the typical arid regions of northwest China by variational method. Chinese Journal of Atmospheric Sciences, 2004, 28(3): 285-294
37. Dai Y, Zeng X, Dickinson RE, et al. The common land model. Bulletin of American Meteorological Society, 2003, 84: 101-1023
38. Dai Y, Dickinson RE and Wang YP. A two-big-leaf model for canopy temperature, photosynthesis and stomatal conductance. Journal of Climate, 2004, 17(12): 2281-2299
39. Sellers PJ, Randall DA, Collatz GJ, et al. A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model formulation. Journal of Climate, 1996, 9(4): 676-705
40. Li X and Koike T. Frozen soil parameterization in SiB2 and its validation with GAME-Tibet observations. Cold Regions Science and Technology, 2003, 36(1-3): 165-182
41. Wang CH, Dong WJ and Wei ZG. Study on relationship between freezing-thawing processes of the Qinghai-Tibet Plateau and the atmospheric circulation over east Asia. Chinese Journal of Geo physics, 2003, 46(3): 438-448
42. Wang SG, Li X and Liang X. Application of three parameter esti mation methods of hydrologic model: Uncertainty in the parameter calibration. In: International Symposium on Sustainable Water Re sources Management and Oasis-hydrosphere-desert Interaction in Arid Regions. Beijing: Tsinghua University Press, 2005, 97-116
43. Fung AK, Li ZQ and Chen KS. Backscattering from a randomly rough dielectric surface. IEEE Transactions on Geoscience and Re mote Sensing, 1992, 30(2): 356-369
44. Fung AK. Microwave Scattering and Emission Models and Their Applications. Norwood: Artech House, 1994, 573
45. Chen KS, Wu TD, Tsang L, et al. Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method simulations. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(1): 90-101
46. Wang JR and Choudhury BJ. Remote sensing of soil moisture con tent over bare field at 1. 4GHz frequency. Journal of Geophysical Research-oceans and Atmospheres, 1981, 86(NC6): 5277-5282
47. Njoku EG, Jackson TJ, Lakshmi V, et al. Soil moisture retrieval from AMSR-E. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(2): 215-229
48. Jin YQ. Remote Sensing Theory of Electromagnetic Scattering and Thermal Emission (in Chinese). Beijing: Science Press, 1993, 292
49. Liou YA and England AW. A land-surface process/radiobrightness model with coupled heat and moisture transport for freezing soil. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36 (2): 669-677
50. Wiesmann A and Matzler C. Microwave emission model of layered snowpacks. Remote Sensing of Environment, 1999, 70: 307- 316
51. Matzler C and Wiesmann A. Extension of the microwave emission model of layered snowpacks to coarse-grained snow. Remote Sensing of Environment, 1999, 70: 317-325
52. Che T and Li X. Retrieval of snow depth in China by passive microwave remote sensing data and its accuracy assessment. Remote Sensing Technology and Application (in Chinese), 2004, 19(5): 301-306
53. Che T, Li X and Gao F. Estimation of snow water equivalent in the Tibetan Plateau using passive microwave remote sensing data (SSM/1). Journal of Glaciology and Geocryology (in Chinese), 2004, 26(3): 363-368
54. Che T and Li X. Spatial distribution and temporal variation of snow water resources in China during 1993-2002. Journal of Glaciology and Geocryology (in Chinese), 2005, 27(1): 64-67
55. Reichle RH, Entekhabi D and McLaughlin DB. Downscaling of radio brightness measurements for soil moisture estimation: A four-dimensional variational data assimilation approach. Water Resources Research, 2001, 37(9): 2353-2364
56. Moradkhani H, Sorooshian S, Gupta HV, et al. Dual state-parameter estimation of hydrological models using ensemble Kalman filter. Advances in Water Resources, 2005, 28(2): 135-147
57. Qiu C and Chou J. Four-dimensional data assimilation method based on SVD: Theoretical aspect. Theoretical and Applied Climatology, 2006, 83(1-4): 51-57
58. Entekhabi D, Njoku EJ, Houser P, et al. The hydrosphere state (Hydros) satellite mission: An Earth system pathfinder for global mapping of soil moisture and land freeze/thaw. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(10): 2184-2195
59. Kerr YH, Waldteufel P, Wigneron JP, et al. Soil moisture retrieval from space: The soil moisture and ocean salinity (SMOS) mission. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(8): 1729-1735
60. Walker JP and Houser PR. Requirements of a global near-surface soil moisture satellite mission: accuracy, repeat time, and spatial resolution. Advances in Water Resources, 2004, 27(8): 785- 801
61. Jin YQ and Liang Z. An approach of three-dimensional vector radiative transfer (3-D-VRT) equation for inhomogeneous scatter media IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(2): 355-360
62. Jin YQ. Theory and Method for Data Validation of Space-Borne Microwave Remote Sensing. Beijing: Science Press, 2005, 250
63. Jin YQ. Theory and Approach of Information Retrievals From Electromagnetic Scattering and Remote Sensing. Netherlands: Springer, 2005, 384
64. McLaughlin D. An integrated approach to hydrologic data assimilation: Interpolation, smoothing, and filtering. Advances in Water Resources, 2002, 25: 1275-1286