Predictability of weather and climate

Abstract:

Uncertainties in parametrized processes in general circulation models can be represented as stochastic perturbations to the model formulation. The European Centre for Medium-Range Weather Forecasts (ECMWF) has pioneered approaches to represent these model errors in forecasting systems. In particular, the stochastically perturbed physical tendency (SPPT) scheme for the atmosphere is used in their operational ensemble system for medium- and long-range predictions. Recent studies have shown that these stochastic approaches can both increase the reliability of the probabilistic forecasts and reduce long-term mean biases of the model climate. Towards developing a seamless prediction system in the future, these benefits of stochastic parametrization for both short-term and long-term forecasts make it an essential component of the next generation Earth System models. We present results of the impact of different configurations of the SPPT scheme in ECMWF's seasonal forecasting System 4 on the mean and variability in tropical precipitation. Small-scale perturbations in the SPPT scheme play a significant role in reducing the mean biases in tropical precipitation. The stochastic physics also nonlinearly rectify the convection and precipitation during different phases of El Niño Southern Oscillation events and improve the reliability of the ensemble forecasts for the Madden–Julian Oscillation (MJO). They impact the MJO dynamics by modulating the convective and suppressed phases of the MJO. Finally, we discuss some of the caveats to this analysis and some future prospects.

Abstract:

Predictability of Atlantic Ocean sea surface temperatures (SST) on seasonal and decadal timescales is investigated using a suite of statistical linear inverse models (LIM). Observed monthly SST anomalies in the Atlantic sector (between 22(Formula presented.)S and 66(Formula presented.)N) are used to construct the LIMs for seasonal and decadal prediction. The forecast skills of the LIMs are then compared to that from two current operational forecast systems. Results indicate that the LIM has good forecast skill for time periods of 3–4 months on the seasonal timescale with enhanced predictability in the spring season. On decadal timescales, the impact of inter-annual and intra-annual variability on the predictability is also investigated. The results show that the suite of LIMs have forecast skill for about 3–4 years over most of the domain when we use only the decadal variability for the construction of the LIM. Including higher frequency variability helps improve the forecast skill and maintains the correlation of LIM predictions with the observed SST anomalies for longer periods. These results indicate the importance of temporal scale interactions in improving predictability on decadal timescales. Hence, LIMs can not only be used as benchmarks for estimates of statistical skill but also to isolate contributions to the forecast skills from different timescales, spatial scales or even model components.

Abstract:

© 2015, The Author(s). The winter 2009/2010 was remarkably cold and snowy over North America and across Eurasia, from Europe to the Far East, coinciding with a pronounced negative phase of the North Atlantic Oscillation (NAO). While previous studies have investigated the origin and persistence of this anomalously negative NAO phase, we have re-assessed the role that the Eurasian snowpack could have played in contributing to its maintenance. Many observational and model studies have indicated that the autumn Eurasian snow cover influences circulation patterns over high northern latitudes. To investigate that role, we have performed a suite of forecasts with the coupled ocean–atmosphere ensemble prediction system from the European Centre for Medium-Range Weather Forecasts. Pairs of 2-month ensemble forecasts with either realistic or else randomized snow initial conditions are used to demonstrate how an anomalously thick snowpack leads to an initial cooling over the continental land masses of Eurasia and, within 2 weeks, to the anomalies that are characteristic of a negative NAO. It is also associated with enhanced vertical wave propagation into the stratosphere and deceleration of the polar night jet. The latter then exerts a downward influence into the troposphere maximizing in the North Atlantic region, which establishes itself within 2 weeks. We compare the forecasted NAO index in our simulations with those from several operational forecasts of the winter 2009/2010 made at the ECWMF, and highlight the importance of relatively high horizontal resolution.