Subfilter-scale Fluxes over a Surface Roughness Transition. Part I: Measured Fluxes and Energy Transfer Rates

A wind-tunnel experiment was designed and carried out to study the effect of a surface roughness transition on subfilter-scale (SFS) physics in a turbulent boundary layer. Specifically, subfilter-scale stresses are evaluated that require parameterizations and are key to improving the accuracy of large-eddy simulations of the atmospheric boundary layer. The surface transition considered in this study consists of a sharp change from a rough, wire-mesh covered surface to a smooth surface. The resulting magnitude jump in aerodynamic roughnesses, M = ln(z ₀₁/z ₀₂), where z ₀₁ and z ₀₂ are the upwind and downwind aerodynamic surface roughnesses respectively, is similar to that of past experimental studies in the atmospheric boundary layer. The two-dimensional velocity fields used in this study are measured using particle image velocimetry and are acquired at several positions downwind of the roughness transition as well as over a homogeneous smooth surface. Results show that the SFS stress, resolved strain rate and SFS transfer rate of resolved kinetic energy are dependent on the position within the boundary layer relative to the surface roughness transition. A mismatch is found in the downwind trend of the SFS stress and resolved strain rate with distance from the transition. This difference of behaviour may not be captured by some eddy-viscosity type models that parameterize the SFS stress tensor as proportional to the resolved strain rate tensor. These results can be used as a benchmark to test the ability of existing and new SFS models to capture the spatial variability SFS physics associated with surface roughness heterogeneities.     

Global comparison of the regional rainfall results of enhanced greenhouse coupled and mixed layer ocean experiments: Implications for climate change scenario development

The extent of agreement amongst current global climate models (GCMs) on the global pattern of rainfall change simulated under enhanced greenhouse conditions is assessed. We consider the results of five experiments which use a simple mixed layer ocean formulation and five which use a fully dynamic ocean model (coupled experiments). For many regions of the northern hemisphere there is strong agreement amongst both mixed layer and coupled experiments on the sign of simulated rainfall change. However, in the southern hemisphere there are large, and apparently systematic, differences between the coupled and mixed layer experiments. In particular, whereas the mixed layer experiments agree on simulated rainfall increase in summer in the tropics and subtropics of the Australian sector, the coupled experiments agree (although more weakly) on rainfall decreases. These differences appear to relate to the much reduced warming simulated by the coupled experiments in the high latitudes of the southern hemisphere. However, recent oceanographie evidence suggests that this suppressed warming may be considerably overestimated. We conclude therefore that despite the in-principle advantages of coupled models, it may be too soon to base some regionally specific climate change scenarios solely on the results of coupled experiments.     

Assessing vulnerability due to sea-level rise in Maui, Hawai‘i using LiDAR remote sensing and GIS

Sea-level rise (SLR) threatens islands and coastal communities due to vulnerable infrastructure and populations concentrated in low-lying areas. LiDAR (Light Detection and Ranging) data were used to produce high-resolution DEMs (Digital Elevation Model) for Kahului and Lahaina, Maui, to assess the potential impacts of future SLR. Two existing LiDAR datasets from USACE (U.S. Army Corps of Engineers) and NOAA (National Oceanic and Atmospheric Administration) were compared and calibrated using the Kahului Harbor tide station. Using tidal benchmarks is a valuable approach for referencing LiDAR in areas lacking an established vertical datum, such as in Hawai‘i and other Pacific Islands. Exploratory analysis of the USACE LiDAR ground returns (point data classified as ground after the removal of vegetation and buildings) indicated that another round of filtering could reduce commission errors. Two SLR scenarios of 0.75 (best-case) to 1.9 m (worst-case) (Vermeer and Rahmstorf Proc Natl Acad Sci 106:21527–21532, 2009) were considered, and the DEMs were used to identify areas vulnerable to flooding. Our results indicate that if no adaptive strategies are taken, a loss ranging from $18.7 million under the best-case SLR scenario to $296 million under the worst-case SLR scenario for Hydrologically Connected (HC; marine inundation) and Hydrologically Disconnected (HD; drainage problems due to a higher water table) areas combined is possible for Kahului; a loss ranging from $57.5 million under the best-case SLR scenario to $394 million under the worst-case SLR scenario for HC and HD areas combined is possible for Lahaina towards the end of the century. This loss would be attributable to inundation between 0.55 km² to 2.13 km² of area for Kahului, and 0.04 km² to 0.37 km² of area for Lahaina.     

Downscaling reveals diverse effects of anthropogenic climate warming on the potential for local environments to support malaria transmission

The potential impact of climate warming on patterns of malaria transmission has been the subject of keen scientific and policy debate. Standard climate models (GCMs) characterize climate change at relatively coarse spatial and temporal scales. However, malaria parasites and the mosquito vectors respond to diurnal variations in conditions at very local scales. Here we bridge this gap by downscaling a series of GCMs to provide high-resolution temperature data for four different sites and show that although outputs from both the GCM and the downscaled models predict diverse but qualitatively similar effects of warming on the potential for adult mosquitoes to transmit malaria, the predicted magnitude of change differs markedly between the different model approaches. Raw GCM model outputs underestimate the effects of climate warming at both hot (3-fold) and cold (8–12 fold) extremes, and overestimate (3-fold) the change under intermediate conditions. Thus, downscaling could add important insights to the standard application of coarse-scale GCMs for biophysical processes driven strongly by local microclimatic conditions.     

Tropical and extratropical cyclone damages under climate change

This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone damages under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 478 estimates of the temperature-damage relationship from nineteen studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5 °C increase in global surface air temperature would cause hurricane damages to increase by 63 %. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are +28 % and +23 %, respectively. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.     

Is public awareness and perceived threat of climate change associated with governmental mitigation targets?

Social scientists and science communicators are concerned about the apparent discrepancy between the scientific consensus on climate change (Anderegg et al. Proc Natl Acad Sci 107:12107–12109, 2010; Doran and Zimmerman EOS Trans Am Geophys Union 90:22–3, 2009) and the general public’s views (Knight Environ Sociol 2:101–113, 2016; Lee et al. Nat Clim Chang 5:1014–1020, 2015). It is reasoned that increased public awareness and perceived threat of climate change may pressure governments to enact policy to counteract climate change (e.g. setting stringent carbon emissions targets). Despite a logical link between public awareness and government-set emissions targets, this relationship remains untested. We examined the relationship between public awareness about and perceived threat of climate change and governmental emissions targets across 71 countries and 1 region. We found a positive association between the proportions of a country’s population that are aware of climate change and the unconditional emissions reduction targets set by that country in the Paris Agreement (Rogelj et al. Nature 534:631–639, 2016). However, the proportion of people in a country who perceive climate change as a personal threat was not associated with higher emissions reduction targets. Our results suggest that public awareness may be an important part of garnering the public support required for policies designed to mitigate climate change to succeed.