Real-time factor model forecasting and the effects of instability

Factor forecasting models are shown to deliver real-time gains over autoregressive models for US real activity variables during the recent period, but are less successful for nominal variables. The gains are largely due to the Financial Crisis period, and are primarily at the shortest (one quarter ahead) horizon. Excluding the pre-Great Moderation years from the factor forecasting model estimation period (but not from the data used to extract factors) results in a marked fillip in factor model forecast accuracy, but does the same for the AR model forecasts. The relative performance of the factor models compared to the AR models is largely unaffected by whether the exercise is in real time or is pseudo out-of-sample.

A novel transport assimilation method for the Atlantic meridional overturning circulation at 26°N

One of the prerequisites for achieving skill in decadal climate prediction is to initialize and predict the circulation in the Atlantic Ocean successfully. The RAPID array measures the Atlantic Meridional Overturning Circulation (MOC) at 26°N. Here we develop a method to include these observations in the Met Office Decadal Prediction System (DePreSys). The proposed method uses covariances of overturning transport anomalies at 26°N with ocean temperature and salinity anomalies throughout the ocean to create the density structure necessary to reproduce the observed transport anomaly. Assimilating transport alone in this way effectively reproduces the observed transport anomalies at 26°N and is better than using basin-wide temperature and salinity observations alone. However, when the transport observations are combined with in situ temperature and salinity observations in the analysis, the transport is not currently reproduced so well. The reasons for this are investigated using pseudo-observations in a twin experiment framework. Sensitivity experiments show that the MOC on monthly time-scales, at least in the HadCM3 model, is modulated by a mechanism where non-local density anomalies appear to be more important for transport variability at 26°N than local density gradients.

Importance of allelopathy as peudo-mixotrophy for the dynamics and diversity of phytoplankton

Understanding the dynamics and diversity of marine phytoplankton is essential for predicting oceanic primary production, oxygen generation and carbon sequestration. Several top-down and bottom-up factors lead to complex phytoplankton dynamics. Complexities further arise from inter-species interactions within phytoplankton communities. Consequently, some of the basic questions on phytoplankton diversity, identified long ago, still puzzle the ecologists: for example, what regulates the diversity in simple systems where species compete for limiting resources? In this context, allelopathic interaction among phytoplankton species has been identified as a potential driver of their dynamics and regulator of their diversity. This chapter deals with the importance of allelopathy in regulating the outcome of nutrient competition among phytoplankton species, through analysis of a resource-competition model. It demonstrates that, through the mechanism of pseudo-mixotrophy - proposed earlier by the author - allelopathy provides essential growth advantage to weaker competitors, and stabilizes resource competition, which ensures the coexistence of two phytoplankton on a single nutrient. In simple nutrient-phytoplankton interactions where higher-trophic influences are negligible, this mechanism theoretically promotes phytoplankton diversity, and can potentially support high diversity in natural phytoplankton communities.