Articles | Volume 14, issue 12
https://doi.org/10.5194/hess-14-2605-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-14-2605-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
16 Dec 2010
Research article |
| 16 Dec 2010
Error characterisation of global active and passive microwave soil moisture datasets
W. A. Dorigo
Vienna University of Technology, Institute of Photogrammetry and Remote Sensing, Vienna, Austria
K. Scipal
ESA, ESTEC, Noordwijk, The Netherlands
R. M. Parinussa
VU University Amsterdam, Faculty of Earth and Life Sciences, Department of Hydrology and Geo-Environmental Sciences, The Netherlands
Y. Y. Liu
VU University Amsterdam, Faculty of Earth and Life Sciences, Department of Hydrology and Geo-Environmental Sciences, The Netherlands
School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia
CSIRO Land and Water, Black Mountain Laboratories, Canberra, Australia
W. Wagner
Vienna University of Technology, Institute of Photogrammetry and Remote Sensing, Vienna, Austria
R. A. M. de Jeu
VU University Amsterdam, Faculty of Earth and Life Sciences, Department of Hydrology and Geo-Environmental Sciences, The Netherlands
V. Naeimi
Vienna University of Technology, Institute of Photogrammetry and Remote Sensing, Vienna, Austria
German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Wessling, Germany
Related subject area
Subject: Global hydrology | Techniques and Approaches: Uncertainty analysis
Information content of soil hydrology in a west Amazon watershed as informed by GRACE
Diagnostic evaluation of river discharge into the Arctic Ocean and its impact on oceanic volume transports
The 63-year changes in annual streamflow volumes across Europe with a focus on the Mediterranean basin
Multivariable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL (Institute Pierre Simon Laplace) climate model
Implications of model selection: a comparison of publicly available, conterminous US-extent hydrologic component estimates
Historical and future changes in global flood magnitude – evidence from a model–observation investigation
A global-scale evaluation of extreme event uncertainty in the eartH2Observe project
Assessment of precipitation error propagation in multi-model global water resource reanalysis
The potential of global reanalysis datasets in identifying flood events in Southern Africa
Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model
Global change in streamflow extremes under climate change over the 21st century
Have precipitation extremes and annual totals been increasing in the world's dry regions over the last 60 years?
Sensitivity of future continental United States water deficit projections to general circulation models, the evapotranspiration estimation method, and the greenhouse gas emission scenario
Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use
Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach
Flood and drought hydrologic monitoring: the role of model parameter uncertainty
Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration
Climate change impacts on runoff in West Africa: a review
Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis
Disinformative data in large-scale hydrological modelling
The impact of climate mitigation on projections of future drought
Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data
Monitoring and quantifying future climate projections of dryness and wetness extremes: SPI bias
Improving runoff estimates from regional climate models: a performance analysis in Spain
A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models
Assessment of soil moisture fields from imperfect climate models with uncertain satellite observations
Elias C. Massoud, A. Anthony Bloom, Marcos Longo, John T. Reager, Paul A. Levine, and John R. Worden
Hydrol. Earth Syst. Sci., 26, 1407–1423, https://doi.org/10.5194/hess-26-1407-2022, https://doi.org/10.5194/hess-26-1407-2022, 2022
Short summary
Short summary
The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step toward improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.
Susanna Winkelbauer, Michael Mayer, Vanessa Seitner, Ervin Zsoter, Hao Zuo, and Leopold Haimberger
Hydrol. Earth Syst. Sci., 26, 279–304, https://doi.org/10.5194/hess-26-279-2022, https://doi.org/10.5194/hess-26-279-2022, 2022
Short summary
Short summary
We evaluate Arctic river discharge using in situ observations and state-of-the-art reanalyses, inter alia the most recent Global Flood Awareness System (GloFAS) river discharge reanalysis version 3.1. Furthermore, we combine reanalysis data, in situ observations, ocean reanalyses, and satellite data and use a Lagrangian optimization scheme to close the Arctic's volume budget on annual and seasonal scales, resulting in one reliable and up-to-date estimate of every volume budget term.
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, Giorgio Vacchiano, Christian Massari, and Luca Brocca
Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, https://doi.org/10.5194/hess-25-5589-2021, 2021
Short summary
Short summary
We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.
Hiroki Mizuochi, Agnès Ducharne, Frédérique Cheruy, Josefine Ghattas, Amen Al-Yaari, Jean-Pierre Wigneron, Vladislav Bastrikov, Philippe Peylin, Fabienne Maignan, and Nicolas Vuichard
Hydrol. Earth Syst. Sci., 25, 2199–2221, https://doi.org/10.5194/hess-25-2199-2021, https://doi.org/10.5194/hess-25-2199-2021, 2021
Samuel Saxe, William Farmer, Jessica Driscoll, and Terri S. Hogue
Hydrol. Earth Syst. Sci., 25, 1529–1568, https://doi.org/10.5194/hess-25-1529-2021, https://doi.org/10.5194/hess-25-1529-2021, 2021
Short summary
Short summary
We compare simulated values from 47 models estimating surface water over the USA. Results show that model uncertainty is substantial over much of the conterminous USA and especially high in the west. Applying the studied models to a simple water accounting equation shows that model selection can significantly affect research results. This paper concludes that multimodel ensembles help to best represent uncertainty in conclusions and suggest targeted research efforts in arid regions.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
Short summary
Short summary
We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Toby R. Marthews, Eleanor M. Blyth, Alberto Martínez-de la Torre, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 24, 75–92, https://doi.org/10.5194/hess-24-75-2020, https://doi.org/10.5194/hess-24-75-2020, 2020
Short summary
Short summary
Climate change impact modellers can only act on predictions of the occurrence of an extreme event in the Earth system if they know the uncertainty in that prediction and how uncertainty is attributable to different model components. Using eartH2Observe data, we quantify the balance between different sources of uncertainty in global evapotranspiration and runoff, making a crucial contribution to understanding the spatial distribution of water resources allocation deficiencies.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, https://doi.org/10.5194/hess-23-1973-2019, 2019
Short summary
Short summary
This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
Gaby J. Gründemann, Micha Werner, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 22, 4667–4683, https://doi.org/10.5194/hess-22-4667-2018, https://doi.org/10.5194/hess-22-4667-2018, 2018
Short summary
Short summary
Flooding in vulnerable and data-sparse regions such as the Limpopo basin in Southern Africa is a key concern. Data available to local flood managers are often limited, inconsistent or asymmetrically distributed. We demonstrate that freely available global datasets are well suited to provide essential information. Despite the poor performance of simulated discharges, these datasets hold potential in identifying damaging flood events, particularly for higher-resolution datasets and larger basins.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
Short summary
Short summary
We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Behzad Asadieh and Nir Y. Krakauer
Hydrol. Earth Syst. Sci., 21, 5863–5874, https://doi.org/10.5194/hess-21-5863-2017, https://doi.org/10.5194/hess-21-5863-2017, 2017
Short summary
Short summary
Multi-model analysis of global streamflow extremes for the 20th and 21st centuries under two warming scenarios is performed. About 37 and 43 % of global land areas show potential for increases in flood and drought events. Nearly 10 % of global land areas, holding around 30 % of world’s population, reflect a potentially worsening hazard of flood and drought. A significant increase in streamflow of the regions near and above the Arctic Circle, and decrease in subtropical arid areas, is projected.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
Short summary
Short summary
The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Seungwoo Chang, Wendy D. Graham, Syewoon Hwang, and Rafael Muñoz-Carpena
Hydrol. Earth Syst. Sci., 20, 3245–3261, https://doi.org/10.5194/hess-20-3245-2016, https://doi.org/10.5194/hess-20-3245-2016, 2016
Short summary
Short summary
Projecting water deficit depends on how researchers combine possible future climate scenarios such as general circulation models (GCMs), evapotranspiration estimation method (ET), and greenhouse gas emission scenarios. Using global sensitivity analysis, we found the relative contribution of each of these factors to projecting future water deficit and the choice of ET estimation method are as important as the choice of GCM, and greenhouse gas emission scenario is less influential than the others.
Hannes Müller Schmied, Linda Adam, Stephanie Eisner, Gabriel Fink, Martina Flörke, Hyungjun Kim, Taikan Oki, Felix Theodor Portmann, Robert Reinecke, Claudia Riedel, Qi Song, Jing Zhang, and Petra Döll
Hydrol. Earth Syst. Sci., 20, 2877–2898, https://doi.org/10.5194/hess-20-2877-2016, https://doi.org/10.5194/hess-20-2877-2016, 2016
Short summary
Short summary
The assessment of water balance components of the global land surface by means of hydrological models is affected by large uncertainties, in particular related to meteorological forcing. We analyze the effect of five state-of-the-art forcings on water balance components at different spatial and temporal scales modeled with WaterGAP. Furthermore, the dominant effect (precipitation/human alteration) for long-term changes in river discharge is assessed.
Dave MacLeod, Hannah Cloke, Florian Pappenberger, and Antje Weisheimer
Hydrol. Earth Syst. Sci., 20, 2737–2743, https://doi.org/10.5194/hess-20-2737-2016, https://doi.org/10.5194/hess-20-2737-2016, 2016
Short summary
Short summary
Soil moisture memory is a key aspect of seasonal climate predictions, through feedback between the land surface and the atmosphere. Estimates have been made of the length of soil moisture memory; however, we show here how estimates of memory show large variation with uncertain model parameters. Explicit representation of model uncertainty may then improve the realism of simulations and seasonal climate forecasts.
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
Short summary
Short summary
Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
H. Müller Schmied, S. Eisner, D. Franz, M. Wattenbach, F. T. Portmann, M. Flörke, and P. Döll
Hydrol. Earth Syst. Sci., 18, 3511–3538, https://doi.org/10.5194/hess-18-3511-2014, https://doi.org/10.5194/hess-18-3511-2014, 2014
P. Roudier, A. Ducharne, and L. Feyen
Hydrol. Earth Syst. Sci., 18, 2789–2801, https://doi.org/10.5194/hess-18-2789-2014, https://doi.org/10.5194/hess-18-2789-2014, 2014
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
A. Kauffeldt, S. Halldin, A. Rodhe, C.-Y. Xu, and I. K. Westerberg
Hydrol. Earth Syst. Sci., 17, 2845–2857, https://doi.org/10.5194/hess-17-2845-2013, https://doi.org/10.5194/hess-17-2845-2013, 2013
I. H. Taylor, E. Burke, L. McColl, P. D. Falloon, G. R. Harris, and D. McNeall
Hydrol. Earth Syst. Sci., 17, 2339–2358, https://doi.org/10.5194/hess-17-2339-2013, https://doi.org/10.5194/hess-17-2339-2013, 2013
H. Xie, L. Longuevergne, C. Ringler, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 16, 3083–3099, https://doi.org/10.5194/hess-16-3083-2012, https://doi.org/10.5194/hess-16-3083-2012, 2012
F. Sienz, O. Bothe, and K. Fraedrich
Hydrol. Earth Syst. Sci., 16, 2143–2157, https://doi.org/10.5194/hess-16-2143-2012, https://doi.org/10.5194/hess-16-2143-2012, 2012
D. González-Zeas, L. Garrote, A. Iglesias, and A. Sordo-Ward
Hydrol. Earth Syst. Sci., 16, 1709–1723, https://doi.org/10.5194/hess-16-1709-2012, https://doi.org/10.5194/hess-16-1709-2012, 2012
S. N. Gosling, R. G. Taylor, N. W. Arnell, and M. C. Todd
Hydrol. Earth Syst. Sci., 15, 279–294, https://doi.org/10.5194/hess-15-279-2011, https://doi.org/10.5194/hess-15-279-2011, 2011
G. Schumann, D. J. Lunt, P. J. Valdes, R. A. M. de Jeu, K. Scipal, and P. D. Bates
Hydrol. Earth Syst. Sci., 13, 1545–1553, https://doi.org/10.5194/hess-13-1545-2009, https://doi.org/10.5194/hess-13-1545-2009, 2009
Cited articles
Balsamo, G., Viterbo, P., Beijaars, A., van den Hurk, B., Hirschi, M., Betts, A. K., and Scipal, K.: A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the integrated forecast system, J. Hydrometeorol., 10, 623–643, 2009.
Bartalis, Z., Scipal, K., and Wagner, W.: Azimuthal anisotropy of scatterometer measurements over land, IEEE T. Geosci. Remote., 44, 2083–2092, 2006.
Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., and Hasenauer, S.: Improving runoff prediction through the assimilation of the ASCAT soil moisture product, Hydrol. Earth Syst. Sci., 14, 1881–1893, https://doi.org/10.5194/hess-14-1881-2010, 2010.
Crow, W. T., Miralles, D. G., and Cosh, M. H.: A quasi-global evaluation system for satellite-based surface soil moisture retrievals, IEEE T. Geosci. Remote., 48, 2516–2527, 2010a.
Crow, W. T., Wagner, W., and Naeimi, V.: The impact of radar incidence angle on soil-moisture-retrieval skill, IEEE Geosci. Remote. S., 7, 501–505, 2010b.
Dorigo, W., Liu, Y., Parinussa, R., Wagner, W., De Jeu, R., Hasenauer, S., and Su, Z.: Merging active and passive microwave soil moisture data to contruct long-term time series in support of climate studies, ESA Living Planet Symposium, Bergen, Norway, 2010.
Drusch, M., Wood, E. F., and Gao, H.: Observation operators for the direct assimilation of TRMM microwave imager retrieved soil moisture, Geophys. Res. Lett., 32, L15403, https://doi.org/10.1029/2005GL023623, 2005.
Drusch, M.: Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's integrated forecast system and the TMI soil moisture data set, J. Geophys. Res.-Atmos., 112, D03102 https://doi.org/10.1029/2006JD007478, 2007.
Gruhier, C., de Rosnay, P., Hasenauer, S., Holmes, T., de Jeu, R., Kerr, Y., Mougin, E., Njoku, E., Timouk, F., Wagner, W., and Zribi, M.: Soil moisture active and passive microwave products: intercomparison and evaluation over a Sahelian site, Hydrol. Earth Syst. Sci., 14, 141–156, https://doi.org/10.5194/hess-14-141-2010, 2010.
Jackson, T. J., Schmugge, T. J., and Wang, J. R.: Passive microwave sensing of soil moisture under vegetation canopies, Water Resour. Res., 18, 1137–1142, 1982.
Jackson, T. J.: III. Measuring surface soil moisture using passive microwave remote sensing, Hydrol. Process., 7, 139–152, 1993.
Jackson, T. J., Cosh, M. H., Bindlish, R., Starks, P. J., Bosch, D. D., Seyfried, M., Goodrich, D. C., Moran, M. S., and Du, J.: Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products, IEEE T. Geosci. Remote., 1–17, 2010.
Jeu, R. A. M., Wagner, W., Holmes, T. R. H., Dolman, A. J., Giesen, N. C., and Friesen, J.: Global soil moisture patterns observed by space borne microwave radiometers and scatterometers, Surv. Geophys., 29, 399–420, 2008.
Kirdyashev, K. P., Chukhlantsev, A. A., and Shutko, A. M.: Microwave radiation of the Earth's surface in the presence of a vegetation cover, Radio Eng. Electron. P., 24, 37–44, 1979.
Koike, T., Nakamura, Y., Kaihotsu, I., Davva, N., Matsuura, N., Tamagawa, K., and Fujii, H.: Development of an Advanced Microwave Scanning Radiometer (AMSR-E) Algorithm of Soil Moisture and Vegetation Water Content, Annual Journal of Hydraulic Engineering, JSCE, 48, 217–222, 2004.
Li, L., Gaiser, P. W., Gao, B. C., Bevilacqua, R. M., Jackson, T. J., Njoku, E. G., Rüdiger, C., Calvet, J. C., and Bindlish, R.: WindSat global soil moisture retrieval and validation, IEEE T. Geosci. Remote., 48, 2224–2241, 2010.
Liu, Y. Y., Van Dijk, A. I. J. M., De Jeu, R. A. M., and Holmes, T. R. H.: An analysis of spatiotemporal variations of soil and vegetation moisture from a 29-year satellite-derived data set over mainland Australia, Water Resour. Res., 45, W07405, https://doi.org/10.1029/2008wr007187, 2009.
Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., de Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.: Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals, Hydrol. Earth Syst. Sci. Discuss., 7, 6699–6724, https://doi.org/10.5194/hessd-7-6699-2010, 2010.
Mahfouf, J. F.: Assimilation of satellite-derived soil moisture from ASCAT in a limited-area NWP model, Q. J. Roy. Meteor. Soc., 136, 784–798, 2010.
Martínez-Fernández, J. and Ceballos, A.: Mean soil moisture estimation using temporal stability analysis, J. Hydrol., 312, 28–38, 2005.
Miralles, D. G., Crow, W. T., and Cosh, M. H.: Estimating spatial sampling errors in coarse-scale soil moisture estimates derived from point-scale observations, J. Hydrometeorol., https://doi.org/10.1175/2010JHM1285.1, in print, 2010.
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations, IEEE T. Geosci. Remote., 47, 1999–2013, https://doi.org/10.1109/Tgrs.2009.2011617, 2009.
Njoku, E. G., Jackson, T. J., Lakshmi, V., Chan, T. K., and Nghiem, S. V.: Soil moisture retrieval from AMSR-E, IEEE Transactions on Geoscience and Remote Sensing, 41, 215–229, https://doi.org/10.1109/tgrs.2002.808243, 2003.
Owe, M., De Jeu, R., and Walker, J.: A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index, IEEE T. Geosci. Remote., 39, 1643–1654, 2001.
Owe, M., de Jeu, R., and Holmes, T.: Multisensor historical climatology of satellite-derived global land surface moisture, J Geophys. Res.-Earth, 113, F01002, https://doi.org/10.1029/2007jf000769, 2008.
Parinussa, R., Meesters, A. G. C. A., Liu, Y. Y., Dorigo, W., Wagner, W., and De Jeu, R. A. M.: An analytical solution to estimate the error structure of a global soil moisture data set, IEEE Geosci. Remote. S., in review, 2010.
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.
Scipal, K., Wagner, W., Trommler, M., and Naumann, K.: The global soil moisture archive 1992–2000 from ERS scatterometer data: first results, Igarss 2002: IEEE International Geoscience and Remote Sensing Symposium and 24th Canadian Symposium on Remote Sensing, Vols I-VI, Proceedings, 1399–1401, 2002.
Scipal, K., Drusch, M., and Wagner, W.: Assimilation of a ERS scatterometer derived soil moisture index in the ECMWF numerical weather prediction system, Adv. Water Resour., 31, 1101–1112, 2008a.
Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., and Wagner, W.: A possible solution for the problem of estimating the error structure of global soil moisture data sets, Geophys. Res. Lett., 35, L24403, https://doi.org/10.1029/2008gl035599, 2008b.
Simmons, A., Uppala, S., Dee, D., and Kobayashi, S.: ERA-Interim: New ECMWF reanalysis products from 1989 onwards, ECMWF Newsletter, 110, 25–35, 2007.
Stoffelen, A.: Toward the true near-surface wind speed: Error modeling and calibration using triple collocation, J. Geophys. Res., 103, 7755–7766, https://doi.org/10.1029/97jc03180, 1998.
Ulaby, F. T., Moore, M. K., and Fung, A. K.: Microwave Remote Sensing, Active and Passive: Radar Remote Sensing and Surface Scattering and Emission Theory, Vol. 2, Artech House, Norwood, MA, 1982.
Viterbo, P. and Beljaars, A. C. M.: An Improved Land-Surface Parameterization Scheme in the ECMWF Model and Its Validation, J. Climate, 8, 2716–2748, 1995.
Wagner, W., Lemoine, G., and Rott, H.: A method for estimating soil moisture from ERS scatterometer and soil data, Remote Sens. Environ., 70, 191–207, 1999.
Wagner, W., Naeimi, V., Scipal, K., de Jeu, R., and Martinez-Fernandez, J.: Soil moisture from operational meteorological satellites, Hydrogeol. J., 15, 121–131, https://doi.org/10.1007/s10040-006-0104-6, 2007.
Wigneron, J. P., Kerr, Y., Waldteufel, P., Saleh, K., Escorihuela, M. J., Richaume, P., Ferrazzoli, P., de Rosnay, P., Gurney, R., Calvet, J. C., Grant, J. P., Guglielmetti, M., Hornbuckle, B., Mätzler, C., Pellarin, T., and Schwank, M.: L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields, Remote Sens. Environ., 107, 639–655, 2007.
Zribi, M., Le Hégarat-Mascle, S., Ottlé, C., Kammoun, B., and Guerin, C.: Surface soil moisture estimation from the synergistic use of the (multi-incidence and multi-resolution) active microwave ERS Wind Scatterometer and SAR data, Remote Sens. Environ., 86, 30–41, 2003.
Special issue