A GCM assessment of atmospheric seasonal predictability associated with soil moisture anomalies over North America

Abstract

The impact of soil moisture anomalies on the seasonal mean atmospheric predictability over North America is investigated on the basis of a 100‐year simulation by an atmospheric general circulation model (AGCM). It is shown that soil moisture anomalies have the smallest persistence during the late spring and summer months, yet the associated near‐surface atmospheric climate anomalies are the largest. The causes for this seasonality are traced to the seasonal variation of the surface evaporation and the modulating control of the atmospheric dynamic variability. It is also shown that the dominant spatial modes of interannual soil moisture variability in late spring can have different degrees of interaction with the surface climate. To what extent do initial soil moisture anomalies and their subsequent evolution impact the atmospheric variability? This question is of relevance if the soil moisture anomalies are to be observed and are used as one of the initial conditions in seasonal climate forecast. To investigate this, we carried out additional AGCM experiments for which soil moisture anomalies are initialized as the extreme states from the control simulation. It is found that the relationship between the soil moisture and the near‐surface atmospheric anomalies in these additional experiments is similar to those obtained in the control simulation. This leads us to the conclusions that (1) there is a certain potential for seasonal predictability of the atmospheric surface climate anomalies due to interannual variations in the soil moisture, and (2) the effect of the soil moisture anomalies, however, is mostly confined to the near‐surface climate variability with little impact on the dynamic variability in the atmosphere, for example, in the upper troposphere. We conclude that atmospheric potential predictability associated with soil moisture anomalies is modest and confined to summer months. Any realization of this predictability depends on correctly observing and initializing large‐scale soil moisture anomalies. These conclusions are based on a particular AGCM and its land surface parameterization scheme. More thorough investigations with more sophisticated land surface schemes are certainly warranted.