Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes

Hydrology and Earth System Sciences

Volumn 19, Issue 11, 2015, Pages 4463-4478

  Kumar, S V ^a,b   Peters Lidard, C D ^b   Santanello, J A ^b   Reichle, R H ^b   Draper, C S ^b,c   Koster, R D ^b   Nearing, G ^a,b   Jasinski, M F ^b  

^a SAIC FREDERICK INC   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

^c UNIVERSITIES SPACE RESEARCH ASSOCIATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BUDGET CONTROL; IRRIGATION; METEOROLOGICAL INSTRUMENTS; RADIOMETERS; REMOTE SENSING; SATELLITES; SURFACE MEASUREMENT;

ADVANCED MICROWAVE SCANNING RADIOMETER; ADVANCED MICROWAVE SCANNING RADIOMETER FOR THE EARTH OBSERVING SYSTEM; AGRICULTURAL IRRIGATION; LAND DATA ASSIMILATION; LAND DATA ASSIMILATION SYSTEMS; SATELLITE REMOTE SENSING; SATELLITE SOIL MOISTURE; SOIL MOISTURE OCEAN SALINITIES;

SOIL MOISTURE;

AMSR-E; DATA ASSIMILATION; EOS; GEOGRAPHICAL REGION; IRRIGATION SYSTEM; LAND SURFACE; REMOTE SENSING; SATELLITE DATA; SOIL MOISTURE; WATER BUDGET;

UNITED STATES;

EID: 84946922486     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-19-4463-2015     Document Type: Article

References (53)

1. Anagnostou, E., Negri, A., and Adler, R.: Statistical adjustment of satellite microwave monthly rainfall estimates over Amazonia, J. Appl. Meteorol., 38, 1590-1598, 1999.
2. Atlas, D., Rosenfield, D., and Wolff, D.: Climatologically tuned reflectivity-rain rate relations and links to area-time integrals, J. Appl. Meteorol., 29, 1120-1135, 1990.
3. Calheiros, R. and Zawadzki, I.: Reflectivity-rain rate relationships for radar hydrology in Brazil, J. Clim. Appl. Meteorol., 118, 118-132, 1987.
4. Cao, Y., Yang, X., and Zhu, X.: Retrieval snow depth by artificial neural network methodology from integrated AMSR-E and insitu data-A case study in QInghai-Tibet plateau, Chin. Geogra. Sci., 18, 356-360, 2008.
5. Chakravarti, I., Laha, R., and Roy, J.: Handbook methods of applied statistics, John Wiley and Sons, New York, 392-394, 1967.
6. Crow, W. T. and Reichle, R.: Comparison of adaptive filtering techniques for land surfacce data assimilation, Water Resour. Res., 44, W08423, doi:10.1029/2008WR006883, 2008.
7. Crow, W. T. and Van Loon, E.: Impact of Incorrect Model Error Assumptions on the Sequential Assimilation of Remotely Sensed Surface Soil Moisture, J. Hydrometeorol., 7, 421-432, 2006.
8. Crow, W. T., Koster, R., Reichle, R., and Sharif, H.: Relevance of time-varying and time-invariant retrieval error sources on the utility of spaceborne soil moisture products, Geophys. Res. Lett., 32, L24405, doi:10.1029/2005GL024889, 2005.
9. Dee, D.: Bias and data assimilation, Q. J. Roy. Meteorol. Soc., 131, 3323-3343, 2005.
10. Dee, D. and da Silva, A.: Data assimilation in the presence of forecast bias, Q. J. Roy. Meteorol. Soc., 124, 269-295, 1998.
11. De Lannoy, G., Reichle, R., Houser, P., Pauwels, V., and Verhoest, N.: Correcting for forecast bias in soil moisture assimilation with the ensemble kalman filter, Water Resour. Res., 43, W09410, doi:10.1029/2006WR005449, 2007.
12. De Lannoy, G., Reichle, R., and Pauwels, V.: Global calibration of GEOS-5 L-band microwave radiative transfer model over nonfrozen land using SMOS observations, J. Hydrometeorol., 14, 765-785, doi:10.1175/JHM-D-12-092.1, 2013.
13. de Rosnay, P., Polcher, J., Laval, K., and Sabre, M.: Integrated parameterization of irrigation in the land surface model ORCHIDEE. Validation over Indian Peninsula, Geophys. Res. Lett., 30, 1986, doi:10.1029/2003GL018024, 2003.
14. Douglas, E., Beltran-Przekurat, A., Niyogi, D., Pielke Sr., R., and Vorosmarty, C.: The impact of agricultural intensification and irrigation on land-atmosphere interactions and Indian monsoon precipitation-A mesoscale modeling perspective, Global Planet. Change, 67, 117-128, doi:10.1016/j.gloplacha.2008.12.007, 2009.
15. Draper, C., Mahfouf, J., and Walker, J.: Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture, J. Geophys. Res.-Atmos., 116, D02127, doi:10.1029/2010JD013829, 2011.
16. Draper, C. S., Reichle, R. H., De Lannoy, G. J. M., and Liu, Q.: Assimilation of passive and active microwave soil moisture retrievals, Geophys. Res. Lett., 39, L04401, doi:10.1029/2011GL050655, 2012.
17. Draper, C., Reichle, R., De Lannoy, G., and Scarino, B.: A Dynamic Approach to Addressing Observation-Minus-Forecast Mean Differences in a Land Surface Skin Temperature Data Assimilation System, J. Hydrometeorol., 16, 449-464, doi:10.1175/JHM-D-14-0087.1, 2015.
18. Drusch, M., Wood, E., and Gao, H.: Observation operators for the direct assimilation of TRMM microwave imager retrieved soil moisture, Geophys. Res. Lett., 32, L15403, doi:10.1029/2005GL023623, 2005.
19. Ek, M., Mitchell, K., Yin, L., Rogers, P., Grunmann, P., Koren, V., Gayno, G., and Tarpley, J.: Implementation of Noah land-surface model advances in the NCEP operational mesoscale Eta model, J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296, 2003.
20. Entekhabi, D., Reichle, R., Koster, R., and Crow, W.: Performance metrics for soil moisture retrievals and applications requirements, J. Hydrometeorol., 11, 832-840, doi:10.1175/2010JHM1223.1, 2010.
21. EORC: Status of AMSR2 Level-3 products (Algorithms Version 1.00), Japan Aerospace Research Centre and GCOM-W1 Algorithm Development, Saitama, Japan, 2013.
22. Forman, B., Reichle, R., and Derksen, C.: Estimating passive microwave brightness temperature over snow covered land in North America using a land surface model and an artificial neural network, IEEE T. Geosci. Remote, 52, 235-248, doi:10.1109/TGRS.2013.2237913, 2014.
23. Friedl, M., McIver, D., Hodges, J., Zhang, X., Muchoney, D., Strahler, A., Woodcock, C., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS: algorithms and early results, Remote Sens. Environ., 83, 287-302, doi:10.1016/S0034-4257(02)00078-0, 2002.
24. Gelb, A.: Applied Optimal Estimation, MIT Press, Cambridge, MA, 301-365, 1974.
25. Gordon, L., Steffen, W., Jonsson, B., Folke, C., Falkenmark, M., and Johannesen, A.: Human modification of global water vapor flows from the land surface, P. Natl. Acad. Sci., 102, 7612-7617, doi:10.1073/pnas.0500208102, 2005.
26. Hain, C., Crow, W., Anderson, M., and Mecikalski, J.: An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land surface model, Water Resour. Res., 48, W11517, doi:10.1029/2011WR011268, 2012.
27. Hooke, R., Martin-Duque, J., and Pedraza, J.: Land transformation by humans: a review, GSA Today, 22, 4-10, 2012.
28. Jackson, T. J.: Measuring surface soil moisture using passive microwave remote sensing, Hydrol. Process., 7, 139-152, 1993.
29. Kerr, Y., Waldteufel, P., Richaume, P., Davenport, I., Ferrazzoli, P., and Wigneron, J.: SMOS level 2 processor soil moisture algorithm theoretical basis document (ATBD), Tech. Rep. SO-TNESL-SM-GS-0001, V5. a, 15/03, SM-ESL (CBSA), CESBIO, Toulouse, 2006.
30. Koster, R.D., Guo, Z., Yang, R., Dirmeyer, P. A., Mitchell, K., and Puma, M. J.: On the Nature of Soil Moisture in Land Surface Models, J. Climate, 22, 4322-4335, doi:10.1175/2009JCLI2832.1, 2009.
31. Kumar, S., Reichle, R., Peters-Lidard, C., Koster, R., Zhan, X., Crow, W., Eylander, J., and Houser, P.: A land surface data assimilation framework using the Land Information System: Description and Applications, Adv. Water Res., 31, 1419-1432, doi:10.1016/j.advwatres.2008.01.013, 2008.
32. Kumar, S., Reichle, R., Koster, R., Crow, W., and Peters-Lidard, C.: Role of subsurface physics in the assimilation of surface soil moisture observations, J. Hydrometeorol., 10, 1534-1547, doi:10.1175/2009JHM1134.1, 2009.
33. Kumar, S., Reichle, R., Harrison, K., Peters-Lidard, C., Yatheendradas, S., and Santanello, J.: A comparison of methods for a priori bias correction in soil moisture data assimilation, Water Resour. Res., 48, doi:10.1029/2010WR010261, 2012.
34. Kumar, S., Peters-Lidard, C., Mocko, D., Reichle, R., Liu, Y., Arsenault, K., Xia, Y., Ek, M., Riggs, G., Livneh, B., and Cosh, M.: Assimilation of remotely sensed soil moisture and snow depth retrievals for drought estimation, J. Hydrometeorol., 15, 2446-2469, doi:10.1175/JHM-D-13-0132.1, 2014.
35. Lawston, P. M., Santanello, J. A., Zaitchik, B. F., and Rodell, M.: Impact of Irrigation Methods on Land Surface Model Spinup and Initialization of WRF Forecasts, J. Hydrometeorol., 16, 1135-1154, doi:10.1175/JHM-D-14-0203.1, 2015.
36. Leng, G., Huang, M., Tang, Q., Sacks, W., Lei, H., and Leung, R.: Modeling the effects of irrigation on land surface fluxes and states over the conterminous United States: Sensitivity to input data and model parameters, J. Geophys. Res. Atmos., 118, 9789-9803, doi:10.1002/jgrd.50792, 2013.
37. Li, H., Sheffield, J., and Wood, E.: Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel of Climate Change AR4 models using equidistant quantile matching, J. Geophys. Res., 115, D10101, doi:10.1029/2009JD012882, 2010.
38. Liu, J., Zhan, X., Zhao, L., Jensen, K., and Wang, X.: NOAA Soil Moisture Operational Product System (SMOPS) and its soil moisture retrieval from AMSR-E and WindSat, in: 92nd American Meteorological Society Annual Meeting, New Orleans, LA, 2012a.
39. Liu, Y., Dorigo, W., Parinussa, R., de Jeu, R., Wagner, W., McCabe, M., Evans, J., and van Dijk, A.: Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sens. Environ., 123, 280-297, 2012b.
40. Liu, Q., Reichle, R., Bindlish, R., Cosh, M., Crow, W., de Jeu, R., De Lannoy, G. J. M., Huffman, G., and Jackson, T.: The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system, J. Hydrometeorol., 12, 750-765, doi:10.1175/JHM-D-10-05000, 2011.
41. Njoku, E. G. and Entekhabi, D.: Passive microwave remote sensing of soil moisture, J. Hydrol., 184, 101-130, 1995.
42. Owe, M., de Jeu, R., and Holmes, T.: Multisensor historical climatology of satellite-derived global land surface soil moisture, J. Geophys. Res., 113, F01002, doi:10.1029/2007JF000769, 2008.
43. Ozdogan, M. and Gutman, G.: A new methodology to map irrigated areas using multi-temporal MODIS and ancillary data: An application example in the continental U.S., Remote Sens. Environ., 112, 3520-3537, 2008.
44. Ozdogan, M., Rodell, M., Beudoing, H., and Toll, D.: Simulating the effects of irrigation over the United States in a land surface model based on satellite-derived agricultural data, J. Hydrometeorol., 11, 171-184, doi:10.1175/2009JHM1116.1, 2010.
45. Reichle, R. and Koster, R.: Bias reduction in short records of satellite soil moisture, Geophys. Res. Lett., 31, L19501, doi:10.1029/2004GL020938, 2004.
46. Reichle, R., McLaughlin, D., and Entekhabi, D.: Hydrologic data assimilation with the ensemble Kalman Filter, Mon. Weather Rev., 130, 103-114, 2002a.
47. Reichle, R., Walker, J., Koster, R., and Houser, P.: Extended versus Ensemble Kalman Filtering for Land Data Assimilation, J. Hydrometeorol., 3, 728-740, 2002b.
48. Reichle, R., Koster, R., Liu, P., Mahanama, S., Njoku, E., and Owe, M.: Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Scanning Multichannel Microwave Radiometer (SMMR), J. Geophys. Res.-Atmos., 112, D09108, doi:10.1029/2006JD008033, 2007.
49. Reichle, R., Crow, W., and Keppenne, C.: An adaptive ensemble Kalman filter for soil moisture data assimilation, Water Resour. Res., 44, W03423, doi:10.1029/2007WR006357, 2008.
50. Reichle, R., Kumar, S. V., Mahanama, S., Koster, R. D. and Liu, Q.: Assimilation of satellite-derived skin temperature observations into land surface models, J. Hydrometeorol., 11, 1103-1122, doi:10.1175/2010JHM1262.1, 2010.
51. Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K., Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data Assimilation System, B. Am. Meteorol. Soc., 85, 381-394, 2004.
52. Salathe Jr., E., Mote, P., andWiley, M.: Review of scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United States pacific northwest, Int. J. Climatol., 27, 1611-1621, 2007.
53. Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L., Alonge, C., Wei, H., Meng, J., Livneh, B., Lettenmaier, D., Koren, V., Duan, Q. K. M., Fan, Y., and Mocko, D.: Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System Project Phase 2 (NLDAS-2), Part 1: Comparison Analysis and Application of Model Products, J. Geophys. Res.-Atmos., 117, D03109, doi:10.1029/2011JD016048, 2012.