Professor Myles Allen CBE FRS

Abstract:

Key mechanisms important for the simulation and better understanding of the precipitation of the North American monsoon (NAM) were analyzed in this paper. Three experiments with the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model, the Hadley Centre Regional Model version 3P (HadRM3P), driven by different boundary conditions were carried out. After a detailed analysis of the moisture and low-level winds derived from the models, the authors conclude that the Gulf of Mexico (GoM) moisture and the Great Plains low-level jet (GPLLJ) play an important role in the northern portion of the NAM. Moreover, the realistic simulation of these features is necessary for a better simulation of precipitation in the NAM. Previous works suggest that the influence of moisture from the GoM in Arizona-New Mexico (AZNM) takes place primarily via the middle- and upper-tropospheric flow (above 700 mb). However, it is shown here that if the GoM does not supply enough moisture and the GPLLJ at lower levels (below 700 mb) does not reach the AZNM region, then a dry westerly flow dominates that area and the summer precipitation is below normal. The implications of these findings for studies of climate change are demonstrated with the analysis of two general circulation models (GCMs) commonly used for climate change prediction, which are shown not to reproduce correctly the GPLLJ intensity nor the moisture in the GoM. This implies that the precipitation in AZNM would not be correctly represented by a regional model driven by these GCMs. © 2011 American Meteorological Society.

Abstract:

Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 1766, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.3 billion (refs 5, 6). Although the flooding was deemed a 'wake-up call' to the impacts of climate change at the time, such claims are typically supported only by general thermodynamic arguments that suggest increased extreme precipitation under global warming, but fail to account fully for the complex hydrometeorology associated with flooding. Here we present a multi-step, physically based 'probabilistic event attribution' framework showing that it is very likely that global anthropogenic greenhouse gas emissions substantially increased the risk of flood occurrence in England and Wales in autumn 2000. Using publicly volunteered distributed computing, we generate several thousand seasonal-forecast-resolution climate model simulations of autumn 2000 weather, both under realistic conditions, and under conditions as they might have been had these greenhouse gas emissions and the resulting large-scale warming never occurred. Results are fed into a precipitation-runoff model that is used to simulate severe daily river runoff events in England and Wales (proxy indicators of flood events). The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.

Abstract:

A number of recent studies have found a strong link between peak human-induced global warming and cumulative carbon emissions from the start of the industrial revolution, while the link to emissions over shorter periods or in the years 2020 or 2050 is generally weaker. However, cumulative targets appear to conflict with the concept of a 'floor' in emissions caused by sectors such as food production. Here, we show that the introduction of emissions floors does not reduce the importance of cumulative emissions, but may make some warming targets unachievable. For pathways that give a most likely warming up to about 4°C, cumulative emissions from pre-industrial times to year 2200 correlate strongly with most likely resultant peak warming regardless of the shape of emissions floors used, providing a more natural long-term policy horizon than 2050 or 2100. The maximum rate of CO(2)-induced warming, which will affect the feasibility and cost of adapting to climate change, is not determined by cumulative emissions but is tightly aligned with peak rates of emissions. Hence, cumulative carbon emissions to 2200 and peak emission rates could provide a clear and simple framework for CO(2) mitigation policy.