Predictability of weather and climate

Abstract:

In recent years, the idea of geoengineering, artificially modifying the climate to reduce global temperatures, has received increasing attention due to the lack of progress in reducing global greenhouse gas emissions. Stratospheric sulfate injection (SSI) is a geoengineering method proposed to reduce planetary warming by reflecting a proportion of solar radiation back into space that would otherwise warm the surface and lower atmosphere. We analyze results from the HadGEM2-CCS climate model with stratospheric emissions of 10 Tg yr-1 of SO2, designed to offset global temperature rise by around 1°C. A reduction in concentrating solar power (CSP) output of 5.9% on average over land is shown under SSI compared to a baseline future climate change scenario (RCP4.5) due to a decrease in direct radiation. Solar photovoltaic (PV) energy is generally less affected as it can use diffuse radiation, which increases under SSI, at the expense of direct radiation. Our results from HadGEM2-CCS are compared to the GEOSCCM chemistry-climate model from the Geoengineering Model Intercomparison Project (GeoMIP), with 5 Tg yr-1 emission of SO2. In many regions, the differences predicted in solar energy output between the SSI and RCP4.5 simulations are robust, as the sign of the changes for both the HadGEM2-CCS and GEOSCCM models agree. Furthermore, the sign of the total and direct annual mean radiation changes evaluated by HadGEM2-CCS agree with the sign of the multi-model mean changes of an ensemble of GeoMIP models over the majority of the world.

Abstract:

The impact of the stochastic schemes Stochastically Perturbed Parametrisation Tendencies (SPPT) and Stochastic Kinetic Energy Backscatter Scheme (SKEBS) on the representation of interannual variability in the Asian summer monsoon is examined in the coupled climate model CCSM4. The Webster–Yang index, measuring anomalies of a specified wind-shear index in the monsoon region, is used as a metric for monsoon strength, and is used to analyse the output of three model integrations: one deterministic, one with SPPT, and one with SKEBS. Both schemes show improved variability, which we trace back to improvements in the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). SPPT improves the representation of ENSO and through teleconnections thereby the monsoon, supporting previous work on the benefits of this scheme on the model climate. SKEBS also improves monsoon variability by way of improving the representation of the IOD, in particular by breaking an overly strong coupling to ENSO.

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.