Data from: Model-data assimilation of multiple phenological observations to constrain and predict leaf area index

Toni Viskari, Brady Hardiman, Ankur R. Desai & Michael C. Dietze
Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002–2005 at Willow Creek, Wisconsin, USA, a...
1 citation reported since publication in 2015.
150 views reported since publication in 2015.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
What does this mean?
28 downloads reported since publication in 2015.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
What does this mean?