Uncertainty Characterisation in Remotely Sensed Soil Moisture

Dolman, A.J. [Promotor]Jeu, R.A.M. de [Copromotor

The impact of land surface temperature on soil moisture anomaly detection from passive microwave observations

For several years passive microwave observations have been used to retrieve soil moisture from the Earth's surface. Low frequency observations have the most sensitivity to soil moisture, therefore the current Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) satellite missions observe the Earth's surface in the L-band frequency. In the past, several satellite sensors such as the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and WindSat have been used to retrieve surface soil moisture using multi-channel observations obtained at higher microwave frequencies. While AMSR-E and WindSat lack an L-band channel, they are able to leverage multi-channel microwave observations to estimate additional land surface parameters. In particular, the availability of Ka-band observations allows AMSR-E and WindSat to obtain coincident surface temperature estimates required for the retrieval of surface soil moisture. In contrast, SMOS and SMAP carry only a single frequency radiometer and therefore lack an instrument suited to estimate the physical temperature of the Earth. Instead, soil moisture algorithms from these new generation satellites rely on ancillary sources of surface temperature (e.g. re-analysis or near real time data from weather prediction centres). A consequence of relying on such ancillary data is the need for temporal and spatial interpolation, which may introduce uncertainties. Here, two newly-developed, large-scale soil moisture evaluation techniques, the triple collocation (TC) approach and the <i>R</i><sub>value</sub> data assimilation approach, are applied to quantify the global-scale impact of replacing Ka-band based surface temperature retrievals with Modern Era Retrospective-analysis for Research and Applications (MERRA) surface temperature output on the accuracy of WindSat and AMSR-E based surface soil moisture retrievals. Results demonstrate that under sparsely vegetated conditions, the use of MERRA land surface temperature instead of Ka-band radiometric land surface temperature leads to a relative decrease in skill (on average 9.7%) of soil moisture anomaly estimates. However the situation is reversed for highly vegetated conditions where soil moisture anomaly estimates show a relative increase in skill (on average 13.7%) when using MERRA land surface temperature. In addition, a pre-processing technique to shift phase of the modelled surface temperature is shown to generally enhance the value of MERRA surface temperature estimates for soil moisture retrieval. Finally, a very high correlation (<i>R</i><sup>2</sup> = 0.95) and consistency between the two evaluation techniques lends further credibility to the obtained results

Error characterisation of global active and passive microwave soil moisture data sets

Understanding the error structures of remotely sensed soil moisture products is essential for correctly interpreting observed variations and trends in the data or assimilating them in hydrological or numerical weather prediction models. Nevertheless, a spatially coherent assessment of the quality of the various globally available data sets is often hampered by the limited availability over space and time of reliable in-situ measurements. This study explores the triple collocation error estimation technique for assessing the relative quality of several globally available soil moisture products from active (ASCAT) and passive (AMSR-E and SSM/I) microwave sensors. The triple collocation technique is a powerful tool to estimate the root mean square error while simultaneously solving for systematic differences in the climatologies of a set of three independent data sources. In addition to the scatterometer and radiometer data sets, we used the ERA-Interim and GLDAS-NOAH reanalysis soil moisture data sets as a third, independent reference. The prime objective is to reveal trends in uncertainty related to different observation principles (passive versus active), the use of different frequencies (C-, X-, and Ku-band) for passive microwave observations, and the choice of the independent reference data set (ERA-Interim versus GLDAS-NOAH). <br><br> The results suggest that the triple collocation method provides realistic error estimates. Observed spatial trends agree well with the existing theory and studies on the performance of different observation principles and frequencies with respect to land cover and vegetation density. In addition, if all theoretical prerequisites are fulfilled (e.g. a sufficiently large number of common observations is available and errors of the different data sets are uncorrelated) the errors estimated for the remote sensing products are hardly influenced by the choice of the third independent data set. The results obtained in this study can help us in developing adequate strategies for the combined use of various scatterometer and radiometer-based soil moisture data sets, e.g. for improved flood forecast modelling or the generation of superior multi-mission long-term soil moisture data sets

Управління як соціальна дія

У статті аналізується необхідність системного розгляду управління як різновиду соціальної дії, наголошується на необхідності методологічного забезпечення управлінської діяльності, для чого мають залучатися новітні парадигми останнього часу, такі як системологія і синергетика. Управління постає як цілепокладальна, цілераціональна галузь буття соціуму.В статье анализируется необходимость системного рассмотрения управления как вида социального действия, акцентируется внимание на необходимости методологического обеспечения управленческой деятельности, для чего должны привлекаться новейшие парадигмы современности, такие как системология и синергетика. Управление предстает как целеполагающая, целерациональная отрасть бытия социума.This article describes the need of systemology consideration of the management as social action, attention is directed on the need of metodological supply of manage action where newest last time paradigm, such as systemology and synergetics are involved. Management becomes as object rational and object related branch of society being

Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

Combining information derived from satellitebased passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E) and active (ASCAT) microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3) from AMSR-E and degree of saturation (%) from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 (“transitional regions”), merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied Correspondence to: Y. Y. Liu ([email protected]) to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles

Soil Moisture retrievals from the WindSat spaceborne polarimetric microwave radiometer

An existing methodology to derive surface soil moisture from passive microwave satellite observations is applied to the WindSat multifrequency polarimetric microwave radiometer. The methodology is a radiative-transfer-based model that has successfully been applied to a series of (historical) satellite sensors, including the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Brightness temperature observations from the WindSat and AMSR-E radiometers were compared, and the WindSat observations were adjusted to overcome small sensor differences (e.g., frequency, bandwidth, incidence angle, and original sensor calibration procedure). The method to relate Ka-band brightness temperature observations to land surface temperature was adapted to the overpass times of WindSat. Statistical analysis with both satellite-observed and in situ soil moistures indicates that the quality of the newly derived WindSat soil moisture product is similar to that obtained with AMSR-E after the adjustment of the WindSat brightness temperature observations. The average correlation coefficients (R) between satellite soil moisture and in situ observations are similar for the two satellites with average values of R = 0.60 for WindSat and R = 0.62 for AMSR-E as calculated from 33 sites. On a global scale, the average correlation coefficient between the two satellite soil moisture products is high with a value of R = 0.83. The results of this study demonstrate that soil moisture from WindSat is consistent with existing soil moisture products derived from AMSR-E using the land parameter retrieval model. Therefore, the soil moisture retrievals from these two satellites could easily be combined to increase the temporal resolution of satellite-derived soil moisture observations. © 2011 IEEE

A spatial Coherent Global Soil Moisture Product with Improved Temporal Resolution

Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11. km. These products are based on internal modules of the Land Parameter Retrieval Model (LPRM), an algorithm that uses the radiative transfer equation to link soil moisture, vegetation optical depth and land surface temperature to observed brightness temperatures.The soil moisture product that is independent of any type of ancillary data uses the internally calculated dielectric constant as a soil moisture proxy. This data product is not influenced by errors associated with coarse-scale global soil property maps or by any other type of forcing (e.g. re-analysis) data and is therefore solely based on satellite microwave observations. The second step builds upon recent developments to increase the spatial resolution of the LPRM retrievals using a smoothing filter downscaling method. With this method we can attain a spatial resolution that can be more useful at the scale of local and regional hydrological studies as well. The steps presented in this paper were applied to observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). The newly derived data sets were validated using ground-based observations from the International Soil Moisture Network (ISMN).The internally calculated dielectric constant product results in significantly more days with valid retrievals than the original soil moisture data products, in particular over arid regions. The dielectric constant product resulted in similar correlations with in situ data as the original soil moisture data product. Together, these findings demonstrate the usefulness of this new dielectric constant product for the hydrological modeling community and climate studies. A case study on the Australian Fitzroy catchment demonstrated that the downscaled data product has a more detailed spatial description of soil moisture, especially during wet and dry conditions with more pronounced dry and wet regions within the catchment. The increased resolution data products could therefore improve runoff predictions and this study demonstrated the potential added value of a transitioning from a spatial resolution of 56. km toward a higher resolution of 11. km. The hydrological implications of these newly developed data records are not only linked to AMSR-E satellite data, but also to the next generation Soil Moisture Active and Passive (SMAP) mission where a 9. km spatial resolution is the target resolution for satellite soil moisture products. The new data products will not replace the current LPRM products, but will be added to the existing array of data products and will become publicly available through our data portals

Comparison of Microwave and Infrared Land Surface Temperature products over the NAFE’06 Research Sites

Two different remotely sensed land surface temperature (

A Preliminary Study toward Consistent Soil Moisture from AMSR2

A preliminary study toward consistent soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2) is presented. Its predecessor, the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), has providedEarth scientists with a consistent and continuous global soil moisture dataset. A major challenge remains to achieve synergy between these soil moisture datasets, which is hampered by the lack of an overlapping observation period of the sensors. Here, observations of the multifrequency microwave radiometer on board the Tropical RainfallMeasuringMission (TRMM) satellite were used to improve consistency between AMSR-E and AMSR2. Several scenarios to achieve synergy between the AMSR-E and AMSR2 soil moisture products were evaluated. The novel soil moisture retrievals from C-band observations, a frequency band that is lacking on board the TRMM satellite, are also presented. A global comparison of soil moisture retrievals against ERA-Interim soil moisture demonstrates the need for an intercalibration procedure. Several different scenarios based on filtering were tested, and the impact on the soil moisture retrievals was evaluated against two independent reference soil moisture datasets (reanalysis and in situ soil moisture) that cover both individual observation periods of the AMSR-E and AMSR2 sensors. Results show a high degree of consistency between both satellite products and two independent reference products for the soil moisture products retrieved from X-band observations. Care should be taken in the interpretation of the presented soil moisture products, and future research is needed to further align theAMSR2 and AMSR-E sensor calibrations