How Does the Partitioning of Evapotranspiration and Runoff between Different Processes Affect the Variability and Predictability of Soil Moisture and Precipitation?

Water stored as part of the land surface is lost to evapotranspiration and runoff on different time scales, and the partitioning between these time scales is important for modeling soil water in a climate model. Different time scales are imposed on evapotranspiration primarily because it is derived from different reservoirs with different storage capacities, from the very rapid evaporation of canopy stores to the slow removal by transpiration of rooting zone soil moisture. Runoff likewise ranges in time scale from rapid surface terms to the slower base-flow. The longest time scale losses of water determine the slow variation of soil moisture and hence the longer time scale effects of soil moisture on precipitation. This paper shows with a simple analysis how shifting the partitioning of evapotranspiration between the different reservoirs affects the variability of soil moisture and precipitation. In particular, it is concluded that a shift to shorter time scale reservoirs shifts the variance of precipitation from that which is potentially predictable to unpredictable.

Evaluating Common Land Model Energy Fluxes Using FLUXNET Data

Given the crucial role of land surface processes in global and regional climates, there is a pressing need to test and verify the performance of land surface models via comparisons to observations. In this study, the eddy covariance measurements from 20 FLUXNET sites spanning more than 100 site-years were utilized to evaluate the performance of the Common Land Model （CoLM） over different vegetation types in various climate zones. A decomposition method was employed to separate both the observed and simulated energy fluxes, i.e., the sensible heat flux, latent heat flux, net radiation, and ground heat flux, at three timescales ranging from stepwise （30 rain） to monthly. A comparison between the simulations and observations indicated that CoLM produced satisfactory simulations of all four energy fluxes, although the different indexes did not exhibit consistent results among the different fluxes, A strong agreement between the simulations and observations was found for the seasonal cycles at the 20 sites, whereas CoLM underestimated the latent heat flux at the sites with distinct dry and wet seasons, which might be associated with its weakness in simulating soil water during the dry season. CoLM cannot explicitly simulate the midday depression of leaf gas exchange, which may explain why CoLM also has a maximum diurnal bias at noon in the summer. Of the eight selected vegetation types analyzed, CoLM performs best for evergreen broadleaf forests and worst for croplands and wetlands.