A Synthetic Experiment to Investigate the Potential of Assimilating LAI through Direct Insertion in a Land Data Assimilation System
Abstract
This study evaluates the potential of assimilating phenology observations in a land data assimilation system by constraining the modeled terrestrial carbon dynamics with remotely sensed observations of vegetation condition. Specifically, observations of Leaf Area Index (LAI) are assimilated in the Noah-Multi Parameterization (Noah-MP) within a Land Data Assimilation System, forced with the NASA NLDAS-2 dataset across the contiguous United States (CONUS). An Observing System Simulation Experiment (OSSE) has been developed to understand and quantify the model response to assimilating LAI information. Firstly, NOAH-MP has been spun up for 30 years (from 1981-2010) to initialize the deterministic run (DE) for year 2011. States from the DE run are considered as "truth" in the OSSE. Secondly, a 10-member open-loop (OL) ensemble simulation has been run by perturbing some forcings (shortwave/longwave radiation and precipitation) and initial conditions (soil moisture content and soil carbon). Thirdly, a direct insertion data assimilation (DA) run aims to improve the model state by assimilating every 8 days LAI values extracted from the DE run and perturbed to represent hypothetical satellite, like MODIS LAI. Model states (e.g., soil moisture, skin temperature) from the OL and DA runs are then compared to the corresponding "true" states from the DE run. The seasonal variability of LAI and surface soil moisture has also been investigated. Although the seasonality of LAI was evident, the relationship between soil moisture and LAI is not as trivial. Further investigation is undergoing to verify whether there is any regional and/or seasonal dependency of the DA performance.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H31I2022R
- Keywords:
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- 1655 Water cycles;
- GLOBAL CHANGEDE: 1847 Modeling;
- HYDROLOGYDE: 1855 Remote sensing;
- HYDROLOGYDE: 1910 Data assimilation;
- integration and fusion;
- INFORMATICS