Professor Myles Allen CBE FRS

Abstract:

The North Atlantic Oscillation (NAO) and eddy-driven jet contain a forced component arising from sea surface temperature (SST) variations. Due to large amounts of internal variability, it is not trivial to determine where and to what extent SSTs force the NAO and jet. A linear statistical-dynamic method is employed with a large climate ensemble to compute the sensitivities of the winter and summer NAO and jet speed and latitude to the SSTs. Key regions of sensitivity are identified in the Indian and Pacific basins, and the North Atlantic tripole. Using the sensitivity maps and a long observational SST dataset, skilful reconstructions of the NAO and jet time series are made. The ability to skilfully forecast both the winter and summer NAO using only SST anomalies is also demonstrated. The linear approach used here allows precise attribution of model forecast signals to SSTs in particular regions. Skill comes from the Atlantic and Pacific basins on short lead times, whilst the Indian Ocean SSTs may contribute to the longer term NAO trend. However, despite the region of high sensitivity in the Indian Ocean, SSTs here do not provide significant skill on interannual timescales which highlights the limitations of the imposed SST approach. Given the impact of the NAO and jet on Northern Hemisphere weather and climate, these results provide useful information that could be used for improved attribution and forecasting.

Abstract:

We investigate the opposing effects of direct radiative forcing and sea surface warming on the atmospheric circulation using a hierarchy of models. In large ensembles of three general circulation models, direct CO2 forcing produces a wavenumber 5 stationary wave over the Northern Hemisphere in summer. Sea surface warming produces a similar wave, but with the opposite sign. The waves are also present in the Coupled Model Intercomparison Project phase 5 ensemble with opposite signs due to direct CO2 and sea surface warming. Analyses of tropical precipitation changes and equivalent potential temperature changes and the results from a simple barotropic model show that the wave is forced from the tropics. Key forcing locations are the Western Atlantic, Eastern Atlantic and in the Indian Ocean just off the east coast of Africa. The stationary wave has a significant impact on regional temperature anomalies in the Northern Hemisphere summer, explaining some of the direct effect that CO2 concentration has on temperature extremes. Ultimately, the climate sensitivity and future changes in the land–sea temperature contrast will dictate the balance between the opposing effects on regional changes in mean and extreme temperature and precipitation under climate change.

Abstract:

A severe drought hit the Greater Horn of Africa (GHA) in 2014, but it remains unclear whether this extreme event was attributable to anthropogenic climate change or part of longer‐term natural cycles. Precipitation patterns are known to be changing across the GHA, but trajectories in land surface variables are much less well known. We simulated the GHA land surface environment to assess the balance between natural cycles and human‐induced climate change. Using a new form of event attribution study where we focused on both climate variables and also directly simulated land surface variables, we combined publicly volunteered distributed computing with land surface simulations to quantify land surface responses. Uncertainty was quantified both for climate model and land surface model outputs. We identified two distinct “drought trajectories” in the GHA bimodal seasonality area during the March–May (Long Rains season) of 2014. Human‐induced climate change may have resulted in regions from Lake Nalubaale (Lake Victoria) to Northern Kenya receiving less precipitation in this season and having up to 20% higher probability of drought‐level evapotranspiration rates (increasing drought). In contrast, the simulated anthropogenic climate change signal for this season induced somewhat wetter conditions and up to 20% lower probability of drought‐level evapotranspiration in Eastern Ethiopia, Southern Somalia, and coastal Kenya (decreasing drought). Uncertainties in our modeling system varied by region and variable of focus, but broadly we found that land surface simulation uncertainty neither added significantly to climate model uncertainty nor significantly reduced it.

Abstract:

In June 2013, Uttarakhand experienced a hydro-meteorological disaster due to a 4 d extreme precipitation event of return period more than 100 years, claiming thousands of lives and causing enormous damage to infrastructure. Using the weather@home climate modelling system and its Half a degree Additional warming, Prognosis and Projected Impacts simulations, this study investigates the change in the return period of similar events in a 1.5 °C and 2 °C warmer world, compared to current and pre-industrial levels. We find that the likelihood of such extreme precipitation events will significantly increase under both future scenarios. We also estimate the change in extreme river flow at the Ganges; finding a considerable increase in the risk of flood events. Our results also suggest that until now, anthropogenic aerosols may have effectively counterbalanced the otherwise increased meteorological flood risk due to greenhouse gas (GHG) induced warming. Disentangling the response due to GHGs and aerosols is required to analyses the changes in future rainfall in the South Asia monsoon region. More research with other climate models is also necessary to make sure these results are robust.