Variability in seasonal forecast skill of Northern Hemisphere winters over the twentieth century
Geophysical Research Letters American Geophysical Union (AGU) (2017)
Abstract:
©2017. American Geophysical Union. All Rights Reserved. Seasonal hindcast experiments, using prescribed sea surface temperatures (SSTs), are analyzed for Northern Hemisphere winters from 1900 to 2010. Ensemble mean Pacific/North American index (PNA) skill varies dramatically, dropping toward zero during the mid-twentieth century, with similar variability in North Atlantic Oscillation (NAO) hindcast skill. The PNA skill closely follows the correlation between the observed PNA index and tropical Pacific SST anomalies. During the mid-century period the PNA and NAO hindcast errors are closely related. The drop in PNA predictability is due to mid-century negative PNA events, which were not forced in a predictable manner by tropical Pacific SST anomalies. Overall, negative PNA events are less predictable and seem likely to arise more from internal atmospheric variability than positive PNA events. Our results suggest that seasonal forecasting systems assessed over the recent 30 year period may be less skillful in periods, such as the mid-twentieth century, with relatively weak forcing from tropical Pacific SST anomalies.The impact of stochastic physics on tropical rainfall variability in global climate models on daily to weekly time scales
Journal of Geophysical Research: Atmospheres American Geophysical Union 122:11 (2017) 5738-5762
Abstract:
Many global atmospheric models have too little precipitation variability in the tropics on daily to weekly time scales, and also poor representation of tropical precipitation extremes associated with intense convection. Stochastic parameterisations have the potential to mitigate this problem by representing unpredictable subgrid variability that is left out of deterministic models. We evaluate the impact on the statistics of tropical rainfall of two stochastic schemes, the stochastically perturbed parameterization tendency scheme (SPPT) and stochastic kinetic energy backscatter scheme (SKEBS), in three climate models: EC-Earth, the Met Office Unified Model and the Community Atmosphere Model, version 4 (CAM4). The schemes generally improve the statistics of simulated tropical rainfall variability, particularly by increasing the frequency of heavy rainfall events, reducing its persistence and increasing the high-frequency component of its variability. There is a large range in the size of the impact between models, with EC-Earth showing the largest improvements. The improvements are greater than those obtained by increasing horizontal resolution to ∼20km. Stochastic physics also strongly affects projections of future changes in the frequency of extreme tropical rainfall in EC-Earth. This indicates that small-scale variability that is unresolved and unpredictable in these models has an important role in determining tropical climate variability statistics. Using these schemes, and improved schemes currently under development, is therefore likely to be important for producing good simulations of tropical variability and extremes in the present day and future.Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 9:2 (2017) 1231-1250
Introducing independent patterns into the Stochastically Perturbed Parametrisation Tendencies (SPPT) scheme
Quarterly Journal of the Royal Meteorological Society Wiley 143:706 (2017) 2168-2181
Abstract:
The Stochastically Perturbed Parametrisation Tendencies (SPPT) scheme is used at weather and climate forecasting centres worldwide to represent model uncertainty that arises from simplifications involved in the parametrisation process. It uses spatio-temporally correlated multiplicative noise to perturb the sum of the parametrised tendencies. However, SPPT does not distinguish between different parametrisation schemes, which do not necessarily have the same error characteristics. A generalisation to SPPT is proposed, whereby the tendency from each parametrisation scheme can be perturbed using an independent stochastic pattern. This acknowledges that the forecast errors arising from different parametrisations are not perfectly correlated. Two variations of this ‘independent SPPT’ (iSPPT) approach are tested in the Integrated Forecasting System (IFS). The first perturbs all parametrised tendencies independently while the second groups tendencies before perturbation. The iSPPT schemes lead to statistically significant improvements in forecast reliability in the tropics in medium range weather forecasts. This improvement can be attributed to a large, beneficial increase in ensemble spread in regions with significant convective activity. The iSPPT schemes also lead to improved forecast skill in the extra tropics for a set of cases in which the synoptic initial conditions were more likely to result in European ‘forecast busts’. Longer 13-month simulations are also considered to indicate the effect of iSPPT on the mean climate of the IFS.The primacy of doubt: Evolution of numerical weather prediction from determinism to probability
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 9:2 (2017) 730-734