A Comparison of the Noah and OSU Land Surface Models in the ECPC Seasonal Forecast Model

Abstract

The Noah land surface model (LSM) has recently been implemented into the Experimental Climate Prediction Center?s (ECPC?s) global Seasonal Forecast Model (SFM). Its performance is compared to the older ECPC SFM with the Oregon State University (OSU) LSM using two sets of 10-member 50-yr Atmospheric Model Intercomparison Project (AMIP) runs. The climatological biases of several fields tend to increase with the Noah LSM. The differences in near-surface temperature bias are traced to changes in the energy budget. In addition to climatology, the variability and skill (anomaly correlation with observations) of the two ensembles are considered. Unlike the climatology, the near-surface temperature skill of the ECPC SFM generally improves with the Noah LSM. Other climatological fields, such as precipitation, show little change in skill. While the global results are mixed, there are however significant regional improvements over Africa both in terms of climatological bias and skill. In the central African Congo River basin, the Noah LSM removed a warm-dry bias and improved upon the near-surface temperature skill of the OSU LSM. In the African Sahel, the Noah LSM greatly enhanced the climatology, variability, and skill of the ECPC SFM as well as improving the location of the African easterly jet.