Contrasting responses of mean and extreme snowfall to climate change

Snowfall is an important element of the climate system, and one that is expected to change in a warming climate. Both mean snowfall and the intensity distribution of snowfall are important, with heavy snowfall events having particularly large economic and human impacts. Simulations with climate models indicate that annual mean snowfall declines with warming in most regions but increases in regions with very low surface temperatures. The response of heavy snowfall events to a changing climate, however, is unclear. Here I show that in simulations with climate models under a scenario of high emissions of greenhouse gases, by the late twenty-first century there are smaller fractional changes in the intensities of daily snowfall extremes than in mean snowfall over many Northern Hemisphere land regions. For example, for monthly climatological temperatures just below freezing and surface elevations below 1,000 metres, the 99.99th percentile of daily snowfall decreases by 8% in the multimodel median, compared to a 65% reduction in mean snowfall. Both mean and extreme snowfall must decrease for a sufficiently large warming, but the climatological temperature above which snowfall extremes decrease with warming in the simulations is as high as −9 °C, compared to −14 °C for mean snowfall. These results are supported by a physically based theory that is consistent with the observed rain–snow transition. According to the theory, snowfall extremes occur near an optimal temperature that is insensitive to climate warming, and this results in smaller fractional changes for higher percentiles of daily snowfall. The simulated changes in snowfall that I find would influence surface snow and its hazards; these changes also suggest that it may be difficult to detect a regional climate-change signal in snowfall extremes.National Science Foundation (U.S.) (Grant AGS-1148594)United States. National Aeronautics and Space Administration (ROSES Grant 09-IDS09-0049

Frequency of extreme Sahelian storms tripled since 1982 in satellite observations

The hydrological cycle is expected to intensify under global warming, with studies reporting more frequent extreme rain events in many regions of the world, and predicting increases in future flood frequency. Such early, predominantly mid-latitude observations are essential because of shortcomings within climate models in their depiction of convective rainfall. A globally important group of intense storms—mesoscale convective systems (MCSs)—poses a particular challenge, because they organize dynamically on spatial scales that cannot be resolved by conventional climate models. Here, we use 35 years of satellite observations from the West African Sahel to reveal a persistent increase in the frequency of the most intense MCSs. Sahelian storms are some of the most powerful on the planet, and rain gauges in this region have recorded a rise in ‘extreme’ daily rainfall totals. We find that intense MCS frequency is only weakly related to the multidecadal recovery of Sahel annual rainfall, but is highly correlated with global land temperatures. Analysis of trends across Africa reveals that MCS intensification is limited to a narrow band south of the Sahara desert. During this period, wet-season Sahelian temperatures have not risen, ruling out the possibility that rainfall has intensified in response to locally warmer conditions. On the other hand, the meridional temperature gradient spanning the Sahel has increased in recent decades, consistent with anthropogenic forcing driving enhanced Saharan warming. We argue that Saharan warming intensifies convection within Sahelian MCSs through increased wind shear and changes to the Saharan air layer. The meridional gradient is projected to strengthen throughout the twenty-first century, suggesting that the Sahel will experience particularly marked increases in extreme rain. The remarkably rapid intensification of Sahelian MCSs since the 1980s sheds new light on the response of organized tropical convection to global warming, and challenges conventional projections made by general circulation models

Single-Batch Production of Recombinant Human Polyclonal Antibodies

We have previously described the development and implementation of a strategy for production of recombinant polyclonal antibodies (rpAb) in single batches employing CHO cells generated by site-specific integration, the SympressTM I technology. The SympressTM I technology is implemented at industrial scale, supporting a phase II clinical development program. Production of recombinant proteins by site-specific integration, which is based on incorporation of a single copy of the gene of interest, makes the SympressTM I technology best suited to support niche indications. To improve titers while maintaining a cost-efficient, highly reproducible single-batch manufacturing mode, we have evaluated a number of different approaches. The most successful results were obtained using random integration in a new producer cell termed ECHO, a CHO DG44 cell derivative engineered for improved productivity at Symphogen. This new expression process is termed the SympressTM II technology. Here we describe proof-of-principle data demonstrating the feasibility of the SympressTM II technology for single-batch rpAb manufacturing using two model systems each composed of six target-specific antibodies. The compositional stability and the batch-to-batch reproducibility of rpAb produced by the ECHO cells were at least as good as observed previously using site-specific integration technology. Furthermore, the new process had a significant titer increase

Assessing variations of extreme indices inducing weather-hazards on critical infrastructures over Europe?the INTACT framework

Extreme weather events are projected to be more frequent and severe across the globe because of global warming. This poses challenging problems for critical infrastructures, which could be dramatically affected (or disrupted), and may require adaptation plans to the changing climate conditions. The INTACT FP7-European project evaluated the resilience and vulnerability of critical infrastructures to extreme weather events in a climate change scenario. To identify changes in the hazard induced by climate change, appropriate extreme weather indicators (EWIs), as proxies of the main atmospheric features triggering events with high impact on the infrastructures, were defined for a number of case studies and different approaches were analyzed to obtain local climate projections. We considered the influence of weighting and bias correction schemes on the delta approach followed to obtain the resulting projections, considering data from the Euro-CORDEX ensemble of regional future climate scenarios over Europe. The aim is to provide practitioners, decision-makers, and administrators with appropriate methods to obtain actionable and plausible results on local/regional future climate scenarios. Our results show a small sensitivity to the weighting approach and a large sensitivity to bias correcting the future projections.This work has been carried out within the activities of INTACT project, receiving funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° FP7-SEC-2013-1-606799. The information and views set out in this paper are those of the authors and do not necessarily reflect the opinion of the European Union. We acknowledge the World Climate Research Programme's Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5

Response of the North Atlantic storm track to climate change shaped by ocean–atmosphere coupling

A poleward shift of the mid-latitude storm tracks in response to anthropogenic greenhouse-gas forcing has been diagnosed in climate model simulations1, 2. Explanations of this effect have focused on atmospheric dynamics3, 4, 5, 6, 7. However, in contrast to storm tracks in other regions, the North Atlantic storm track responds by strengthening and extending farther east, in particular on its southern flank8. These adjustments are associated with an intensification and extension of the eddy-driven jet towards western Europe9 and are expected to have considerable societal impacts related to a rise in storminess in Europe10, 11, 12. Here, we apply a regression analysis to an ensemble of coupled climate model simulations to show that the coupling between ocean and atmosphere shapes the distinct storm-track response to greenhouse-gas forcing in the North Atlantic region. In the ensemble of simulations we analyse, at least half of the differences between the storm-track responses of different models are associated with uncertainties in ocean circulation changes. We compare the fully coupled simulations with both the associated slab model simulations and an ocean-forced experiment with one climate model to establish causality. We conclude that uncertainties in the response of the North Atlantic storm track to anthropogenic emissions could be reduced through tighter constraints on the future ocean circulation

Sensible heat has significantly affected the global hydrological cycle over the historical period

Globally, latent heating associated with a change in precipitation is balanced by changes to atmospheric radiative cooling and sensible heat fluxes. Both components can be altered by climate forcing mechanisms and through climate feedbacks, but the impacts of climate forcing and feedbacks on sensible heat fluxes have received much less attention. Here we show, using a range of climate modelling results, that changes in sensible heat are the dominant contributor to the present global-mean precipitation change since preindustrial time, because the radiative impact of forcings and feedbacks approximately compensate. The model results show a dissimilar influence on sensible heat and precipitation from various drivers of climate change. Due to its strong atmospheric absorption, black carbon is found to influence the sensible heat very differently compared to other aerosols and greenhouse gases. Our results indicate that this is likely caused by differences in the impact on the lower tropospheric stability

Extreme rainfall events alter the trophic structure in bromeliad tanks across the Neotropics

Changes in global and regional precipitation regimes are among the most pervasive components of climate change. Intensification of rainfall cycles, ranging from frequent downpours to severe droughts, could cause widespread, but largely unknown, alterations to trophic structure and ecosystem function. We conducted multi-site coordinated experiments to show how variation in the quantity and evenness of rainfall modulates trophic structure in 210 natural freshwater microcosms (tank bromeliads) across Central and South America (18°N to 29°S). The biomass of smaller organisms (detritivores) was higher under more stable hydrological conditions. Conversely, the biomass of predators was highest when rainfall was uneven, resulting in top-heavy biomass pyramids. These results illustrate how extremes of precipitation, resulting in localized droughts or flooding, can erode the base of freshwater food webs, with negative implications for the stability of trophic dynamics

The role of horizontal resolution in simulating drivers of the global hydrological cycle

The role of atmospheric general circulation model (AGCM) horizontal resolution in representing the global energy budget and hydrological cycle is assessed, with the aim of improving the understanding of model uncertainties in simulating the hydrological cycle. We use two AGCMs from the UK Met Office Hadley Centre: HadGEM1-A at resolutions ranging from 270 to 60 km, and HadGEM3-A ranging from 135 to 25 km. The models exhibit a stable hydrological cycle, although too intense compared to reanalyses and observations. This over-intensity is explained by excess surface shortwave radiation, a common error in general circulation models (GCMs). This result is insensitive to resolution. However, as resolution is increased, precipitation decreases over the ocean and increases over the land. This is associated with an increase in atmospheric moisture transport from ocean to land, which changes the partitioning of moisture fluxes that contribute to precipitation over land from less local to more non-local moisture sources. The results start to converge at 60-km resolution, which underlines the excessive reliance of the mean hydrological cycle on physical parametrization (local unresolved processes) versus model dynamics (large-scale resolved processes) in coarser HadGEM1 and HadGEM3 GCMs. This finding may be valid for other GCMs, showing the necessity to analyze other chains of GCMs that may become available in the future with such a range of horizontal resolutions. Our finding supports the hypothesis that heterogeneity in model parametrization is one of the underlying causes of model disagreement in the Coupled Model Intercomparison Project (CMIP) exercises

Predicting climate change using response theory: global averages and spatial patterns

The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O(105105) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting—at any lead time and in an ensemble sense—the change in climate properties resulting from increase in the concentration of CO22 using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as in their spatial patterns. The quality of the predictions obtained for the surface temperature fields is rather good, while in the case of precipitation a good skill is observed only for the global average. We also show how it is possible to define accurately concepts like the inertia of the climate system or to predict when climate change is detectable given a scenario of forcing. Our analysis can be extended for dealing with more complex portfolios of forcings and can be adapted to treat, in principle, any climate observable. Our conclusion is that climate change is indeed a problem that can be effectively seen through a statistical mechanical lens, and that there is great potential for optimizing the current coordinated modelling exercises run for the preparation of the subsequent reports of the Intergovernmental Panel for Climate Change