The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals
Abstract
We propose a method for merging soil moisture retrievals from spaceborne active and passive microwave instruments based on weighted averaging taking into account the error characteristics of the individual data sets. The merging scheme is parameterized using error variance estimates obtained from using triple collocation analysis (TCA). In regions where TCA is deemed unreliable, we use correlation significance levels ($p$-values) as indicator for retrieval quality to decide whether to use active data only, passive data only, or an unweighted average. We apply the proposed merging scheme to active retrievals from advanced scatterometer and passive retrievals from the Advanced Microwave Scanning Radiometer—Earth Observing System using Global Land Data Assimilation System-Noah to complement the triplet required for TCA. The merged time series is evaluated against soil moisture estimates from ERA-Interim/Land andin situmeasurements from the International Soil Moisture Network using the European Space Agency’s (ESA’s) current Climate Change Initiative—Soil Moisture (ESA CCI SM) product version v02.3 as benchmark merging scheme. Results show that the$p$-value classification provides a robust basis for decisions regarding using either active or passive data alone, or an unweighted average in cases where relative weights cannot be estimated reliably, and that the weights estimated from TCA in almost all cases outperform the ternary decision upon which the ESA CCI SM v02.3 is based. The proposed method forms the basis for the new ESA CCI SM product version v03.x and higher.
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Cites
The Global Land Data Assimilation System
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., et al. (2004) · Bulletin of the American Meteorological Society · doi:10.1175/bams-85-3-381 · Cited by 5,614
The Soil Moisture Active Passive (SMAP) Mission
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J., et al. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2043918 · Cited by 3,754
Self-citationThe SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle
Kerr, Y. H., Waldteufel, P., Wigneron, J.-P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M.-J., Font, J., Reul, N., Gruhier, C., et al. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2043032 · Cited by 1,988
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., et al. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.07.001 · Cited by 1,521
Self-citationA Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data
Wagner, W., Lemoine, G., & Rott, H. (1999) · Remote Sensing of Environment · doi:10.1016/s0034-4257(99)00036-x · Cited by 1,254
Self-citationDorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., et al. (2011) · Hydrology and Earth System Sciences · doi:10.5194/hess-15-1675-2011 · Cited by 1,177
Self-citationMultisensor historical climatology of satellite‐derived global land surface moisture
Owe, M., de Jeu, R., & Holmes, T. (2008) · Journal of Geophysical Research: Earth Surface · doi:10.1029/2007jf000769 · Cited by 1,031
Toward the true near‐surface wind speed: Error modeling and calibration using triple collocation
Stoffelen, A. (1998) · Journal of Geophysical Research: Oceans · doi:10.1029/97jc03180 · Cited by 891
Trend-preserving blending of passive and active microwave soil moisture retrievals
Liu, Y., Dorigo, W. A., Parinussa, R., de Jeu, R., Wagner, W., McCabe, M. F., Evans, J. P., & van Dijk, A. I. J. M. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.03.014 · Cited by 727
Self-citationLiu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., & Evans, J. P. (2011) · Hydrology and Earth System Sciences · doi:10.5194/hess-15-425-2011 · Cited by 662
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Cited by
Ma, H., Zeng, J., Chen, N., Zhang, X., Cosh, M. H., & Wang, W. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111215 · Cited by 389
Beck, H. E., Pan, M., Miralles, D. G., Reichle, R. H., Dorigo, W. A., Hahn, S., Sheffield, J., Karthikeyan, L., Balsamo, G., Parinussa, R. M., et al. (2021) · Hydrology and Earth System Sciences · doi:10.5194/hess-25-17-2021 · Cited by 380
Self-citationBlunden, J., & Arndt, D. S. (2019) · Bulletin of the American Meteorological Society · doi:10.1175/2019bamsstateoftheclimate.1 · Cited by 253
The Value of SMAP for Long-Term Soil Moisture Estimation With the Help of Deep Learning
Fang, K., Pan, M., & Shen, C. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2872131 · Cited by 186
Ghajarnia, N., Kalantari, Z., & Destouni, G. (2021) · Water Resources Research · doi:10.1029/2020wr029377 · Cited by 21
Metadata
- Authors
- Gruber, A., Dorigo, W. A., Crow, W., & Wagner, W.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2017-12
- Volume
- 55
- Issue
- 12
- Pages
- 6780-6792
- ISSN
- 0196-2892 (ISSN-L)
- 1558-0644
- OpenAlex
- W2759163218
- Cited by
- 423
- References
- 39
- FWCI
- 19.88
- Type
- journal article
- Language
- en
- Open access
- closed
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