Evaluation of 10 Methods for Initializing a Land Surface Model

Abstract

Improper initialization of numerical models can cause spurious trends in the output, inviting erroneous interpretations of the earth system processes that one wishes to study. In particular, soil moisture memory is considerable, so that accurate initialization of this variable in land surface models (LSMs) is critical. The most commonly employed method for initializing an LSM is to spin up by looping through a single year repeatedly until a predefined equilibrium is achieved. The downside to this technique, when applied to continental- to global-scale simulations, is that regional annual anomalies in the meteorological forcing accumulate as artificial anomalies in the land surface states, including soil moisture. Nine alternative approaches were tested and compared using the Mosaic LSM and 15 yr of global meteorological forcing. Results indicate that the most efficient way to initialize an LSM, if possible and given that multiple years of preceding forcing are not available, is to use climatological average states from the same model for the precise time of year of initialization. Three other approaches were also determined to be preferable to the single-year spinup method. In addition, low-resolution spinup scenarios were devised and tested, and based on the results, an effective yet computationally economical technique is proposed.