Evaluation of ECMWF's soil moisture analyses using observations on the Tibetan Plateau

Su, Zhongbo; Rosnay, Patricia de; Wen, Jianguang; Wang, Lichun; Zeng, Yijian

doi:10.1002/jgrd.50468

Cited by 138 publications

(141 citation statements)

References 49 publications

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“…The ERA-Interim SM product will be adopted as the reanalysis data for this study [12]. The 12-month in situ data is deemed appropriate to capture the seasonal statistical moments, by using CDF matching technique [39,42].…”

Section: Flowchartmentioning

confidence: 99%

“…A detailed quantification can facilitate identifying imperfections in the current numerical weather prediction models and may serve as a reference to which climate scenarios can be compared. Soil moisture (hereafter as SM) is a crucial land surface state that modulates land-atmosphere interactions [5][6][7][8][9][10] and imperative for quantifying trends and variability of feedbacks between climate and the water cycle of TP [11,12].…”

Section: Introductionmentioning

confidence: 99%

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Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau

Zeng

Velde

et al. 2016

Remote Sensing

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Abstract:The inter-comparison of different soil moisture (SM) products over the Tibetan Plateau (TP) reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with the in situ measured data climatology. In this study, the in situ soil moisture networks, combined with the classification of climate zones over the TP, were used to produce the in situ measured SM climatology at the plateau scale. The generated TP scale in situ SM climatology was then used to scale the model-simulated SM data, which was subsequently used to scale the SM satellite observations. The climatology-scaled satellite and model-simulated SM were then blended objectively, by applying the triple collocation and least squares method. The final blended SM can replicate the SM dynamics across different climatic zones, from sub-humid regions to semi-arid and arid regions over the TP. This demonstrates the need to constrain the model-simulated SM estimates with the in situ measurements before their further applications in scaling climatology of SM satellite products.

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Section: Flowchartmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau

Zeng

Velde

et al. 2016

Remote Sensing

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“…Soil moisture is one of the essential climate variables (ECVs) [1][2][3][4]. On land, soil moisture is one of the few variables depicting the storage of water and heat that can be released several months later, as vegetation cover and snow do [5][6][7].…”

Section: Motivationmentioning

confidence: 99%

“…T B " εT e f f (1) where T B is the radiation intensity received by the passive microwave sensor fixed near the soil surface or on the satellite platforms while neglecting the attenuation of atmosphere. ε is the emissivity that is strongly related to soil moisture.…”

Section: Introductionmentioning

confidence: 99%

Determination of the Optimal Mounting Depth for Calculating Effective Soil Temperature at L-Band: Maqu Case

Zeng

Wen

et al. 2016

Remote Sensing

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Effective soil temperature T e f f is one of the basic parameters in passive microwave remote sensing of soil moisture. At present, dedicated satellite soil moisture monitoring missions use the L-band as the operating frequency. However, T e f f at the L-band is strongly affected by soil moisture and temperature profiles. Recently, a two-layer scheme and a corresponding multilayer form have been developed to accommodate such influences. In this study, the soil moisture/temperature data collected and simulated by the Noah land surface model across the Maqu Network are used to verify the newly developed schemes. There are two key findings. Firstly, the new two-layer scheme is able to assess which site provides relatively higher accuracy when estimating T e f f . It is found that, on average, nearly 20% of the T e f f signal cannot be captured by the Maqu Network, in the currently assumed common installation configuration. This knowledge is important, since the spatial averaged brightness temperature (a function of T e f f ) is used to determine soil moisture. Secondly, the developed method has made it possible to identify that the optimal mounting depths for the observation pair are 5 cm and 20 cm for calculating T e f f at the center station in the Maqu Network. It has been suggested that the newly developed method can provide an objective way to configure an optimal soil moisture/temperature network and improve the representativeness of the existing networks regarding the calculation of T e f f .

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“…The use of TERA leads to a general underestimation of the brightness temperature throughout the entire season. Indeed, Su et al (2013) found that in the Maqu area, as well as other parts of the Tibetan Plateau, ECMWF model underestimates the soil temperature.…”

Section: Final Remarks and Recommendationsmentioning

confidence: 99%

Microwave remote sensing for soil moisture monitoring: synergy of active and passive observations and validation of retrieved products

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Evaluation of ECMWF's soil moisture analyses using observations on the Tibetan Plateau

Cited by 138 publications

References 49 publications

Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau

Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau

Determination of the Optimal Mounting Depth for Calculating Effective Soil Temperature at L-Band: Maqu Case

Microwave remote sensing for soil moisture monitoring: synergy of active and passive observations and validation of retrieved products

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