Samuel Scherrer published the article "Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe" in Copernicus' Hydrology and Earth System Sciences.
- Copernicus Global Land Service LAI retrievals were assimilated into the Noah-MP land surface model.
- Both bias-blind and bias-aware data assimilation methods were tested
- In areas with a large LAI bias, the bias-blind LAI DA leads to a reduced bias between observed and modelled LAI, an improved agreement of GPP, ET, and runoff estimates with independent products, but a worse agreement of soil moisture estimates with the European Space Agency Climate Change Initiative (ESA CCI) soil moisture product.
- The bias-aware approaches based on a priori rescaling of LAI observations to the model climatology avoid the negative effects of the bias-blind assimilation.
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