Makale detayı · 2013
The Optimality of Potential Rescaling Approaches in Land Data Assimilation
- Yıl
- 2013
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı Journal of Hydrometeorology
- Katalog eşleşmesi (ISSN) Journal of Hydrometeorology
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
Abstract It is well known that systematic differences exist between modeled and observed realizations of hydrological variables like soil moisture. Prior to data assimilation, these differences must be removed in order to obtain an optimal analysis. A number of rescaling approaches have been proposed for this purpose. These methods include rescaling techniques based on matching sampled temporal statistics, minimizing the least squares distance between observations and models, and the application of triple collocation. Here, the authors evaluate the optimality and relative performances of these rescaling methods both analytically and numerically and find that a triple collocation–based rescaling method results in an optimal solution, whereas variance matching and linear least squares regression approaches result in only approximations to this optimal solution.
Konular
Atıflar
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144 atıf
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Yerel katalogda bu makaleye atıf yapan 14 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
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- The Auto Tuned Land Data Assimilation System ATLAS 2014
- Optimal averaging of soil moisture predictions from ensemble land surface model simulations 2015
- Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey 2019
- Impact of Rescaling Approaches in Simple Fusion of Soil Moisture Products 2019