Terrestrial amplification of past, present, and future climate change.

Terrestrial amplification (TA) of land warming relative to oceans is apparent in recent climatic observations. TA results from land-sea coupling of moisture and heat and is therefore important for predicting future warming and water availability. However, the theoretical basis for TA has never been tested outside the short instrumental period, and the spatial pattern and amplitude of TA remain uncertain. Here, we investigate TA during the Last Glacial Maximum (LGM; ~20 thousand years) in the low latitudes, where the theory is most applicable. We find remarkable consistency between paleotemperature proxies, theory, and climate model simulations of both LGM and future climates. Paleoclimate data thus provide crucial new support for TA, refining the range of future low-latitude, low-elevation TA to [Formula: see text] (95% confidence interval), i.e., land warming ~40% more than oceans. The observed data model theory agreement helps reconcile LGM marine and terrestrial paleotemperature proxies, with implications for equilibrium climate sensitivity.

Intensification of subhourly heavy rainfall.

Short-duration rainfall extremes can cause flash flooding with associated impacts. Previous studies of climate impacts on extreme precipitation have focused mainly on daily rain totals. Subdaily extremes are often generated in small areas that can be missed by gauge networks or satellites and are not resolved by climate models. Here, we show a robust positive trend of at least 20% per decade in subhourly extreme rainfall near Sydney, Australia, over 20 years, despite no evidence of trends at hourly or daily scales. This trend is seen consistently in storms tracked using multiple independent ground radars, is consistent with rain-gauge data, and does not appear to be associated with known natural variations. This finding suggests that subhourly rainfall extremes may be increasing substantially faster than those on more widely reported time scales.

Correction to: Changes in relative fit of human heat stress indices to cardiovascular, respiratory, and renal hospitalizations across five Australian urban populations.

The authors of the article would like to bring the following correction/corrigendum to attention: When recently investigating future changes in heat stress indices, we discovered an error in the use of the heatwave indices we compared in Goldie et al. (2017).

Changes in relative fit of human heat stress indices to cardiovascular, respiratory, and renal hospitalizations across five Australian urban populations.

Various human heat stress indices have been developed to relate atmospheric measures of extreme heat to human health impacts, but the usefulness of different indices across various health impacts and in different populations is poorly understood. This paper determines which heat stress indices best fit hospital admissions for sets of cardiovascular, respiratory, and renal diseases across five Australian cities. We hypothesized that the best indices would be largely dependent on location. We fit parent models to these counts in the summers (November-March) between 2001 and 2013 using negative binomial regression. We then added 15 heat stress indices to these models, ranking their goodness of fit using the Akaike information criterion. Admissions for each health outcome were nearly always higher in hot or humid conditions. Contrary to our hypothesis that location would determine the best-fitting heat stress index, we found that the best indices were related largely by health outcome of interest, rather than location as hypothesized. In particular, heatwave and temperature indices had the best fit to cardiovascular admissions, humidity indices had the best fit to respiratory admissions, and combined heat-humidity indices had the best fit to renal admissions. With a few exceptions, the results were similar across all five cities. The best-fitting heat stress indices appear to be useful across several Australian cities with differing climates, but they may have varying usefulness depending on the outcome of interest. These findings suggest that future research on heat and health impacts, and in particular hospital demand modeling, could better reflect reality if it avoided "all-cause" health outcomes and used heat stress indices appropriate to specific diseases and disease groups.

Comparative evaluation of human heat stress indices on selected hospital admissions in Sydney, Australia.

OBJECTIVE: To find appropriate regression model specifications for counts of the daily hospital admissions of a Sydney cohort and determine which human heat stress indices best improve the models' fit. METHODS: We built parent models of eight daily counts of admission records using weather station observations, census population estimates and public holiday data. We added heat stress indices; models with lower Akaike Information Criterion scores were judged a better fit. RESULTS: Five of the eight parent models demonstrated adequate fit. Daily maximum Simplified Wet Bulb Globe Temperature (sWBGT) consistently improved fit more than most other indices; temperature and heatwave indices also modelled some health outcomes well. Humidity and heat-humidity indices better fit counts of patients who died following admission. CONCLUSIONS: Maximum sWBGT is an ideal measure of heat stress for these types of Sydney hospital admissions. Simple temperature indices are a good fallback where a narrower range of conditions is investigated. Implications for public health: This study confirms the importance of selecting appropriate heat stress indices for modelling. Epidemiologists projecting Sydney hospital admissions should use maximum sWBGT as a common measure of heat stress. Health organisations interested in short-range forecasting may prefer simple temperature indices.

Prospects for narrowing bounds on Earth's equilibrium climate sensitivity.

The concept of Earth's Equilibrium Climate Sensitivity (ECS) is reviewed. A particular problem in quantifying plausible bounds for ECS has been how to account for all of the diverse lines of relevant scientific evidence. It is argued that developing and refuting physical storylines (hypotheses) for values outside any proposed range has the potential to better constrain these bounds and to help articulate the science needed to narrow the range further. A careful reassessment of all important lines of evidence supporting these storylines, their limitations, and the assumptions required to combine them is therefore required urgently.

Temperature and Humidity Effects on Hospital Morbidity in Darwin, Australia.

BACKGROUND: Many studies have explored the relationship between temperature and health in the context of a changing climate, but few have considered the effects of humidity, particularly in tropical locations, on human health and well-being. To investigate this potential relationship, this study assessed the main and interacting effects of daily temperature and humidity on hospital admission rates for selected heat-relevant diagnoses in Darwin, Australia. METHODS: Univariate and bivariate Poisson generalized linear models were used to find statistically significant predictors and the admission rates within bins of predictors were compared to explore nonlinear effects. FINDINGS: The analysis indicated that nighttime humidity was the most statistically significant predictor (P < 0.001), followed by daytime temperature and average daily humidity (P < 0.05). There was no evidence of a significant interaction between them or other predictors. The nighttime humidity effect appeared to be strongly nonlinear: Hot days appeared to have higher admission rates when they were preceded by high nighttime humidity. CONCLUSIONS: From this analysis, we suggest that heat-health policies in tropical regions similar to Darwin need to accommodate the effects of temperature and humidity at different times of day.

The impact of parametrized convection on cloud feedback.

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that 'ConvOff' models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.

Spread in model climate sensitivity traced to atmospheric convective mixing.

Equilibrium climate sensitivity refers to the ultimate change in global mean temperature in response to a change in external forcing. Despite decades of research attempting to narrow uncertainties, equilibrium climate sensitivity estimates from climate models still span roughly 1.5 to 5 degrees Celsius for a doubling of atmospheric carbon dioxide concentration, precluding accurate projections of future climate. The spread arises largely from differences in the feedback from low clouds, for reasons not yet understood. Here we show that differences in the simulated strength of convective mixing between the lower and middle tropical troposphere explain about half of the variance in climate sensitivity estimated by 43 climate models. The apparent mechanism is that such mixing dehydrates the low-cloud layer at a rate that increases as the climate warms, and this rate of increase depends on the initial mixing strength, linking the mixing to cloud feedback. The mixing inferred from observations appears to be sufficiently strong to imply a climate sensitivity of more than 3 degrees for a doubling of carbon dioxide. This is significantly higher than the currently accepted lower bound of 1.5 degrees, thereby constraining model projections towards relatively severe future warming.

Recent Northern Hemisphere tropical expansion primarily driven by black carbon and tropospheric ozone.

Observational analyses have shown the width of the tropical belt increasing in recent decades as the world has warmed. This expansion is important because it is associated with shifts in large-scale atmospheric circulation and major climate zones. Although recent studies have attributed tropical expansion in the Southern Hemisphere to ozone depletion, the drivers of Northern Hemisphere expansion are not well known and the expansion has not so far been reproduced by climate models. Here we use a climate model with detailed aerosol physics to show that increases in heterogeneous warming agents--including black carbon aerosols and tropospheric ozone--are noticeably better than greenhouse gases at driving expansion, and can account for the observed summertime maximum in tropical expansion. Mechanistically, atmospheric heating from black carbon and tropospheric ozone has occurred at the mid-latitudes, generating a poleward shift of the tropospheric jet, thereby relocating the main division between tropical and temperate air masses. Although we still underestimate tropical expansion, the true aerosol forcing is poorly known and could also be underestimated. Thus, although the insensitivity of models needs further investigation, black carbon and tropospheric ozone, both of which are strongly influenced by human activities, are the most likely causes of observed Northern Hemisphere tropical expansion.

An afucosylated anti-CD20 monoclonal antibody with greater antibody-dependent cellular cytotoxicity and B-cell depletion and lower complement-dependent cytotoxicity than rituximab.

The objective of this study was to characterize the in vitro and in vivo activity of a novel afucosylated rituximab (BLX-300) expressed in a Lemna aquatic plant-based system free of zoonotic pathogens. The glycosylation of BLX-300 was shown to be homogeneous, composed of a single major N-glycan species without detectable fucose or xylose. Target cell binding and induction of apoptosis were similar for BLX-300 and rituximab. Antibody-dependent cellular cytotoxicity (ADCC) was increased by BLX-300 versus rituximab in phenylalanine/phenylalanine (F/F), phenylalanine/valine (F/V) and valine/valine (V/V) genotype donors, as indicated by respective log reductions of 0.82, 1.07 and 0.92 in EC(50). BLX-300 also showed greater B-cell depletion than rituximab in whole blood from donors of F/F, F/V and V/V genotype in vitro and cynomolgus monkeys in vivo. Temporal changes in circulating levels of BLX-300 and rituximab were similar in cynomolgus monkeys. Complement-dependent cytotoxicity (CDC) was attenuated by BLX-300 relative to rituximab, as judged by a log increase of 0.51 in EC(50). The higher ADCC and B-cell depletion suggest a potential improvement in effectiveness and potency, while lower CDC may mitigate infusion toxicity.

An adaptability limit to climate change due to heat stress.

Despite the uncertainty in future climate-change impacts, it is often assumed that humans would be able to adapt to any possible warming. Here we argue that heat stress imposes a robust upper limit to such adaptation. Peak heat stress, quantified by the wet-bulb temperature T(W), is surprisingly similar across diverse climates today. T(W) never exceeds 31 degrees C. Any exceedence of 35 degrees C for extended periods should induce hyperthermia in humans and other mammals, as dissipation of metabolic heat becomes impossible. While this never happens now, it would begin to occur with global-mean warming of about 7 degrees C, calling the habitability of some regions into question. With 11-12 degrees C warming, such regions would spread to encompass the majority of the human population as currently distributed. Eventual warmings of 12 degrees C are possible from fossil fuel burning. One implication is that recent estimates of the costs of unmitigated climate change are too low unless the range of possible warming can somehow be narrowed. Heat stress also may help explain trends in the mammalian fossil record.