[1] Albergel, C., P. de Rosnay, C. Gruhier, et al., 2012: Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sens. Environ., 118, 215–226. doi: 10.1016/j.rse.2011.11.017
[2] Cao, B. J., F. P. Mao, S. W. Zhang, et al., 2019: Assessing the performance of separate bias Kalman filter in correcting the model bias for estimation of soil moisture profiles. J. Meteor. Res., 33, 519–527. doi: 10.1007/s13351-019-8057-6
[3] Choudhury, B. J., T. J. Schmugge, and T. Mo, 1982: A parameterization of effective soil temperature for microwave emission. J. Geophys. Res. Oceans, 87, 1301–1304. doi: 10.1029/JC087iC02p01301
[4] Du, J. Y., J. S. Kimball, L. A. Jones, et al., 2017: A global satellite environmental data record derived from AMSR-E and AMSR2 microwave Earth observations. Earth Syst. Sci. Data, 9, 791–808. doi: 10.5194/essd-9-791-2017
[5] Green, J. K., S. I. Seneviratne, A. M. Berg, et al., 2019: Large influence of soil moisture on long-term terrestrial carbon uptake. Nature, 565, 476–479. doi: 10.1038/s41586-018-0848-x
[6] Jackson, T. J., and T. J. Schmugge, 1991: Vegetation effects on the microwave emission of soils. Remote Sens. Environ., 36, 203–212. doi: 10.1016/0034-4257(91)90057-D
[7] Kerr, Y. H., 2007: Soil moisture from space: Where are we? Hydrogeol. J., 15, 117–120. doi: 10.1007/s10040-006-0095-3
[8] Kerr, Y. H., P. Waldteufel, J.-P. Wigneron, et al., 2001: Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission. IEEE Trans. Geosci. Remote Sens., 39, 1729–1735. doi: 10.1109/36.942551
[9] Li, L., E. G. Njoku, E. Im, et al., 2004: A preliminary survey of radio-frequency interference over the U.S. in Aqua AMSR-E data. IEEE Trans. Geosci. Remote Sens., 42, 380–390. doi: 10.1109/TGRS.2003.817195
[10] Liao, W. L., D. G. Wang, G. L. Wang, et al., 2019: Quality control and evaluation of the observed daily data in the North American Soil Moisture Database. J. Meteor. Res., 33, 501–518. doi: 10.1007/s13351-019-8121-2
[11] Liaw, A., and M. Wiener, 2002: Classification and regression by randomForest. R News, 2, 18–22.
[12] Liu, J. C., X. W. Zhan, C. Hain, et al., 2016: NOAA Soil Moisture Operational Product System (SMOPS) and its validations. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Beijing, China, 3477–3480, doi: 10.1109/IGARSS.2016.7729899.
[13] Njoku, E. G., and D. Entekhabi, 1996: Passive microwave remote sensing of soil moisture. J. Hydrol., 184, 101–129. doi: 10.1016/0022-1694(95)02970-2
[14] Njoku, E. G., T. J. Jackson, V. Lakshmi, et al., 2003: Soil moisture retrieval from AMSR-E. IEEE Trans. Geosci. Remote Sens., 41, 215–229. doi: 10.1109/TGRS.2002.808243
[15] 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
[16] Paloscia, S., G. Macelloni, E. Santi, et al., 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
[17] Pangaluru, K., I. Velicogna, G. A, et al., 2019: Soil moisture variability in India: Relationship of land surface–atmosphere fields using maximum covariance analysis. Remote Sens., 11, 335. doi: 10.3390/rs11030335
[18] Parinussa, R. M., G. Wang, T. R. H. Holmes, et al., 2014: Global surface soil moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite. Int. J. Remote Sens., 35, 7007–7029. doi: 10.1080/01431161.2014.960622
[19] Parrens, M., J.-C. Calvet, P. de Rosnay, et al., 2014: Benchmarking of L-band soil microwave emission models. Remote Sens. Environ., 140, 407–419. doi: 10.1016/j.rse.2013.09.017
[20] Rudd, A. C., A. L. Kay, and V. A. Bell, 2019: National-scale analysis of future river flow and soil moisture droughts: Potential changes in drought characteristics. Climatic Change, 156, 323–340. doi: 10.1007/s10584-019-02528-0
[21] Ruosteenoja, K., T. Markkanen, A. Venäläinen, et al., 2018: Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century. Climate Dyn., 50, 1177–1192. doi: 10.1007/s00382-017-3671-4
[22] Schaefer, G. L., and R. F. Paetzold, 2000: SNOTEL (SNOwpack TELemetry) and SCAN (Soil Climate Analysis Network). Presented at the Automated Weather Stations for Applications in Agriculture and Water Resources Management: Current Use and Future Perspectives, USDA-NRCS, Lincoln, NE.
[23] Schmugge, T., and T. J. Jackson, 1994: Mapping surface soil moisture with microwave radiometers. Meteor. Atmos. Phys., 54, 213–223. doi: 10.1007/BF01030061
[24] Seager, R., J. Nakamura, and M. F. Ting, 2019: Mechanisms of seasonal soil moisture drought onset and termination in the southern Great Plains. J. Hydrometeor., 20, 751–771. doi: 10.1175/JHM-D-18-0191.1
[25] Shi, J., L. Jiang, L. Zhang, et al., 2006: Physically based estimation of bare-surface soil moisture with the passive radiometers. IEEE Trans. Geosci. Remote Sens., 44, 3145–3153. doi: 10.1109/TGRS.2006.876706
[26] Ulaby, F. T., and E. A. Wilson, 1985: Microwave attenuation properties of vegetation canopies. IEEE Trans. Geosci. Remote Sens., GE-23, 746–753. doi: 10.1109/TGRS.1985.289393
[27] Wagner, W., G. Blöschl, P. Pampaloni, et al., 2007: Operational readiness of microwave remote sensing of soil moisture for hydrologic applications. Hydrol. Res., 38, 1–20. doi: 10.2166/nh.2007.029
[28] Wang, J. R., 1983: Passive microwave sensing of soil moisture content: The effects of soil bulk density and surface roughness. Remote Sens. Environ., 13, 329–344. doi: 10.1016/0034-4257(83)90034-2
[29] Wang, J. R., and B. J. Choudhury, 1981: Remote sensing of soil moisture content, over bare field at 1.4 GHz frequency. J. Geophys. Res. Oceans, 86, 5277–5282. doi: 10.1029/JC086iC06p05277
[30] Wang, J. S., J. S. Zhang, and Y. Q. Tang, 2010: Fengyun satellites: Achievements and future. Chinese J. Space Sci., 30, 468–473.
[31] Wigneron, J.-P., J.-C. Calvet, T. Pellarin, et al., 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
[32] Xu, J. W., W. C. Zhang, Z. Y. Zheng, et al., 2012: Establishment of a hybrid rainfall-runoff model for use in the Noah LSM. Acta Meteor. Sinica, 26, 85–92. doi: 10.1007/s13351-012-0108-1
[33] Yang, H., F. Z. Weng, L. Q. Lv, et al., 2011: The FengYun-3 Microwave Radiation Imager on-orbit verification. IEEE Trans. Geosci. Remote Sens., 49, 4552–4560. doi: 10.1109/TGRS.2011.2148200
[34] Yang, J., P. Zhang, N. M. Lu, et al., 2012: Improvements on global meteorological observations from the current Fengyun 3 satellites and beyond. Int. J. Digit. Earth, 5, 251–265. doi: 10.1080/17538947.2012.658666
[35] Yang, Z. D., N. M. Lu, J. M. Shi, et al., 2012: Overview of FY-3 payload and ground application system. IEEE Trans. Geosci. Remote Sens., 50, 4846–4853. doi: 10.1109/TGRS.2012.2197826
[36] Zhang, F. M., Z. X. Pu, and C. H. Wang, 2019: Impacts of soil moisture on the numerical simulation of a post-landfall storm. J. Meteor. Res., 33, 206–218. doi: 10.1007/s13351-019-8002-8
[37] Zhang, S. W., Y. H. Liu, and W. D. Zhang, 2013: Ensemble square root filter assimilation of near-surface soil moisture and reference-level observations into a coupled land surface-boundary layer model. Acta Meteor. Sinica, 27, 541–555. doi: 10.1007/s13351-013-0402-6