Intensification of precipitation extremes in the world's humid and water-limited regions

Changes in precipitation totals and extremes are among the most relevant consequences of climate change, but in particular regional changes remain uncertain. While aggregating over larger regions reduces the noise in time series and typically shows increases in the intensity of precipitation extremes, it has been argued that this may not be the case in water-limited regions. Here we investigate long-term changes in annual precipitation totals and extremes aggregated over the world's humid, transitional, and dry regions as defined by their climatological water availability. We use the globally most complete observational datasets suitable for the analysis of daily precipitation extremes, and data from global climate model simulations. We show that precipitation totals and extremes have increased in the humid regions since the mid-20th century. Conversely, despite showing tendencies to increase, no robust changes can be detected in the drier regions, in part due to the large variability of precipitation and sparse observational coverage particularly in the driest regions. Future climate simulations under increased radiative forcing indicate total precipitation increases in more humid regions but no clear changes in the more arid regions, while precipitation extremes are more likely to increase than to decrease on average over both the humid and arid regions of the world. These results highlight the increasing risk of heavy precipitation in most regions of the world, including water-limited regions, with implications for related impacts through flooding risk or soil erosion.This study was funded by the Australian Research Council (ARC) grant DE150100456. MGD acknowledges additional funding by the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 grant reference RYC-2017-22964; AMU acknowledges funding from the ARC Centre of Excellence for Climate Extremes (CE170100023)

Multi-model forecast quality assessment of CMIP6 decadal predictions

Decadal climate predictions are a new source of climate information for inter-annual to decadal time scales (filling the gap between seasonal predictions and climate projections), which is of increasing interest to users. The external forcings (natural and anthropogenic) and the internal climate variability (natural slow variations of the climate system) provide predictability on these time scales. However, due to chaotic characteristics of the climate system, it is not possible to predict its exact evolution. Thus, decadal forecasting provides large ensembles of predictions that, besides predicting the average anomalies based on the ensemble mean, are also used to obtain probabilistic information about the likelihood of certain event types. Forecast quality assessment is essential to identify windows of opportunity (e.g., variables, regions, and lead times) with skill that can be used to develop a climate service and inform users in specific sectors. Besides, it can help to monitor improvements in current forecast systems. The forecast quality assessment needs to be carried out over a long enough period in the past (when observations are available to compare against) to achieve robust results that can be used as an estimate of how well the forecast system may perform in simulating future climatic anomalies. Thus, retrospective decadal forecasts (also known as hindcasts) are performed with the same forecast systems used to predict future climate variations. For this, the forecast systems are utilized to simulate the evolution of the climate system from our best estimate of the observed initial state, which is referred to as forecast system initialization and the predictions also incorporate information about the external forcings. The hindcasts are also used to apply calibration techniques to partially correct systematic biases of the predictions. The Decadal Climate Prediction Project (DCPP [1]) of the Coupled Model Intercom-parison Project Phase 6 (CMIP6 [2]) now provides the most comprehensive set of retrospective decadal predictions from multiple forecast systems. The increasing availability of these simulations leads to the question of how to best post-process the raw output from the forecast systems so that the most useful and reliable information is provided to users

Bid participates in genotoxic drug-induced apoptosis of HeLa cells and is essential for death receptor ligands' apoptotic and synergistic effects

Background: The BH3-only protein Bid is an important component of death receptor-mediated caspase activation. Bid is cleaved by caspase-8 or -10 into t-Bid, which translocates to mitochondria and triggers the release of caspase-activating factors. Bid has also been reported to be cleaved by other proteases. Methodology/Principal Findings: To test the hypothesis that Bid is a central mediator of stress-induced apoptosis, we investigated the effects of a small molecule Bid inhibitor on stress-induced apoptosis, and generated HeLa cells deficient for Bid. Stable knockdown of bid lead to a pronounced resistance to Fas/CD95- and TRAIL-induced caspase activation and apoptosis, and significantly increased clonogenic survival. While Bid-deficient cells were equally sensitive to ER stress-induced apoptosis, they showed moderate, but significantly reduced levels of apoptosis, as well as increased clonogenic survival in response to the genotoxic drugs Etoposide, Oxaliplatin, and Doxorubicin. Similar effects were observed using the Bid inhibitor BI6C9. Interestingly, Bid-deficient cells were dramatically protected from apoptosis when subtoxic concentrations of ER stressors, Etoposide or Oxaliplatin were combined with subtoxic TRAIL concentrations. Conclusions/Significance: Our data demonstrate that Bid is central for death receptor-induced cell death and participates in anti-cancer drug-induced apoptosis in human cervical cancer HeLa cells. They also show that the synergistic effects of TRAIL in combination with either ER stressors or genotoxic anti-cancer drugs are nearly exclusively mediated via an increased activation of Bid-induced apoptosis signalling

Temperature and precipitation extremes in century-long gridded observations, reanalyses, and atmospheric model simulations

Knowledge about long-term changes in climate extremes is vital to better understand multidecadal climate variability and long-term changes and to place today’s extreme events in a historical context. While global changes in temperature and precipitation extremes since the midtwentieth century are well studied, knowledge about century-scale changes is limited. This paper analyses a range of largely independent observations-based data sets covering 1901–2010 for long-term changes and interannual variability in daily scale temperature and precipitation extremes. We compare across data sets for consistency to ascertain our confidence in century-scale changes in extremes. We find consistent warming trends in temperature extremes globally and in most land areas over the past century. For precipitation extremes we find global tendencies toward more intense rainfall throughout much of the twentieth century; however, local changes are spatially more variable. While global time series of the different data sets agree well after about 1950, they often show different changes during the first half of the twentieth century. In regions with good observational coverage, gridded observations and reanalyses agree well throughout the entire past century. Simulations with an atmospheric model suggest that ocean temperatures and sea ice may explain up to about 50% of interannual variability in the global average of temperature extremes, and about 15% in the global average of moderate precipitation extremes, but local correlations are mostly significant only in low latitudes

Extreme precipitation on consecutive days occurs more often in a warming climate

Extreme precipitation occurring on consecutive days may substantially increase the risk of related impacts, but changes in such events have not been studied at a global scale. Here we use a unique global dataset based on in situ observations and multimodel historical and future simulations to analyze the changes in the frequency of extreme precipitation on consecutive days (EPCD). We further disentangle the relative contributions of variations in precipitation intensity and temporal correlation of extreme precipitation to understand the processes that drive the changes in EPCD. Observations and climate model simulations show that the frequency of EPCD is increasing in most land regions, in particular, in North America, Europe, and the Northern Hemisphere high latitudes. These increases are primarily a consequence of increasing precipitation intensity, but changes in the temporal correlation of extreme precipitation regionally amplify or reduce the effects of intensity changes. Changes are larger in simulations with a stronger warming signal, suggesting that further increases in EPCD are expected for the future under continued climate warming.We acknowledge support from the National Key R&D Program of China (2019YFC0409101), Science and Technology Development Plan of Jilin Province (20190201291JC), the Joint Fund of National Natural Science Foundation of China (U19A2023), the Fundamental Research Funds for the Central Universities (2412020FZ002), and 2236 Co-Funded Brain Circulation Scheme2 (CoCirculation2) of TÜBİTAK (121C054). M.G.D. acknowledges support by the Horizon 2020 EUCP project under Grant Agreement 776613 and by the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 Grant Reference RYC-2017-22964.Peer Reviewed"Article signat per 28 autors/es: Haibo Du, Markus G. Donat, Shengwei Zong, Lisa V. Alexander, Rodrigo Manzanas, Andries Kruger, Gwangyong Choi, Jim Salinger, Hong S. He, Mai-He Li, Fumiaki Fujibe, Banzragch Nandintsetseg, Shafiqur Rehman, Farhat Abbas, Matilde Rusticucci, Arvind Srivastava, Panmao Zhai, Tanya Lippmann, Ibouraïma Yabi, Michael C. Stambaugh, Shengzhong Wang, Altangerel Batbold, Priscilla Teles de Oliveira, Muhammad Adrees, Wei Hou, Claudio Moises Santos e Silva, Paulo Sergio Lucio, and Zhengfang Wu "Postprint (published version

Amplified warming of seasonal cold extremes relative to the mean in the Northern Hemisphere extratropics

Cold extremes are anticipated to warm at a faster rate than both hot extremes and average temperatures for much of the Northern Hemisphere. Anomalously warm cold extremes can affect numerous sectors, including human health, tourism and various ecosystems that are sensitive to cold temperatures. Using a selection of global climate models, this paper explores the accelerated warming of seasonal cold extremes relative to seasonal mean temperatures in the Northern Hemisphere extratropics. The potential driving physical mechanisms are investigated by assessing conditions on or prior to the day when the cold extreme occurs to understand how the different environmental fields are related. During winter, North America, Europe and much of Eurasia show amplified warming of cold extremes projected for the late 21st century, compared to the mid-20th century. This is shown to be largely driven by reductions in cold air temperature advection, suggested as a likely consequence of Arctic amplification. In spring and autumn, cold extremes are expected to warm faster than average temperatures for most of the Northern Hemisphere mid-latitudes to high latitudes, particularly Alaska, northern Canada and northern Eurasia. In the shoulder seasons, projected decreases in snow cover and associated reductions in surface albedo are suggested as the largest contributor affecting the accelerated rates of warming in cold extremes. The key findings of this study improve our understanding of the environmental conditions that contribute to the accelerated warming of cold extremes relative to mean temperatures.This study was supported by the Australian Research Council (ARC) Centre of Excellence for Climate Extremes (grant CE170100023). Markus G. Donat received funding from the ARC (grant DE150100456) and the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 grant reference RYC-2017-22964. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in Table 1 of this paper) for producing and making their model output available.Peer ReviewedPostprint (published version

Constraining decadal variability regionally improves near-term projections of hot, cold and dry extremes

Hot, cold and dry meteorological extremes are often linked with severe impacts on the public health, agricultural, energy and environmental sectors. Skillful predictions of such extremes could therefore enable stakeholders to better plan and adapt to future impacts of these events. The intensity, duration and frequency of such extremes are affected by anthropogenic climate change and modulated by different modes of climate variability. Here we use a large multi-model ensemble from the Coupled Model Intercomparison Project Phase 6 and constrain these simulations by sub-selecting those members whose global SST anomaly patterns are most similar to observations at a given point in time, thereby phasing in the decadal climate variability with observations. Hot and cold extremes are skillfully predicted over most of the globe, with also a widespread added value from using the constrained ensemble compared to the unconstrained full CMIP6 ensemble. On the other hand, dry extremes show skill only in some regions with results sensitive to the index used. Still, we find skillful predictions and added skill for dry extremes in some regions such as western north America, southern central and eastern Europe, southeastern Australia, southern Africa and the Arabian peninsula. We also find that the added skill in the constrained ensemble is due to a combination of improved multi-decadal variations in phase with observed climate extremes and improved representation of long-term changes. Our results demonstrate that constraining decadal variability in climate projections can provide improved estimates of temperature extremes and drought in the next twenty years, which can inform targeted adaptation strategies to near-term climate change.This research has been partly supported by the Horizon2020 LANDMARC project (grant agreement No. 869367) and the Horizon Europe ASPECT project (grant number 101081460). PDL has received funding from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement No 101059659. CDT acknowledges financial support from the Spanish Ministry for Science and Innovation (FPI PRE2019-509 08864 financed by MCIN/AEI/10.13039/501100011033 and by FSE invierte en tu futuro). MGD is grateful for support by the AXA Research Fund. The authors are further grateful for the support by the Department of Research and Universities of the Government of Catalonia to the Climate Variability and Change Research Group (Code: 2021 SGR 00786).Peer ReviewedPostprint (author's final draft

Effects of Selective Dry Cow Treatment on Intramammary Infection Risk after Calving, Cure Risk during the Dry Period, and Antibiotic Use at Drying-Off: A Systematic Review and Meta-Analysis of Current Literature (2000–2021)

The objectives of this paper were (i) to perform a systematic review of the literature over the last 21 yr and (ii) to evaluate the efficacy of selective dry cow treatment (SDCT) vs. blanket dry cow treatment (BDCT) in dairy cows regarding the risk of intramammary infection (IMI) after calving, new IMI risk after calving, cure risk during the dry period, and a reduction in antibiotic use at drying-off by meta-analysis. The systematic search was carried out using the databases PubMed, CAB Direct, and ScienceDirect. A meta-analytical assessment was performed for each outcome of interest using random-effects models, and the relative risk (RR) for IMI and cure or the pooled proportion for antibiotic use was calculated. The final number of included studies was n = 3 for IMI risk after calving and n = 5 for new IMI risk after calving, cure risk during the dry period, and antibiotic use. The RR levels for IMI (RR, 95% confidence interval [CI]: 1.02, 0.94–1.11; p = 0.592), new IMI (RR, 95% CI: 1.06, 0.94–1.20; p = 0.994), and cure (RR, 95% CI: 1.00, 0.97–1.02; p = 0.661) did not differ significantly between SDCT and BDCT. Substantial heterogeneity was observed between the trials regarding the pooled proportion of antibiotic use within the SDCT groups (I2 = 97.7%; p < 0.001). This meta-analysis provides evidence that SDCT seems to be an adequate alternative to BDCT regarding udder health with a simultaneous reduction in antibiotic use. Limitations might arise because of the small number of studies included

A multiregion model evaluation and attribution study of historical changes in the area affected by temperature and precipitation extremes

The skill of eight climate models in simulating the variability and trends in the observed areal extent of daily temperature and precipitation extremes is evaluated across five large-scale regions, using the climate extremes index (CEI) framework. Focusing on Europe, North America, Asia, Australia, and the Northern Hemisphere, results show that overall the models are generally able to simulate the decadal variability and trends of the observed temperature and precipitation components over the period 1951–2005. Climate models are able to reproduce observed increasing trends in the area experiencing warm maximum and minimum temperature extremes, as well as, to a lesser extent, increasing trends in the areas experiencing an extreme contribution of heavy precipitation to total annual precipitation for the Northern Hemisphere regions. Using simulations performed under different radiative forcing scenarios, the causes of simulated and observed trends are investigated. A clear anthropogenic signal is found in the trends in the maximum and minimum temperature components for all regions. In North America, a strong anthropogenically forced trend in the maximum temperature component is simulated despite no significant trend in the gridded observations, although a trend is detected in a reanalysis product. A distinct anthropogenic influence is also found for trends in the area affected by a much-above-average contribution of heavy precipitation to annual precipitation totals for Europe in a majority of models and to varying degrees in other Northern Hemisphere regions. However, observed trends in the area experiencing extreme total annual precipitation and extreme number of wet and dry days are not reproduced by climate models under any forcing scenario

Understanding the role of sea surface temperature-forcing for variability in global temperature and precipitation extremes

The oceans are a well-known source of natural variability in the climate system, although their ability to account for inter-annual variations of temperature and precipitation extremes over land remains unclear. In this study, the role of sea-surface temperature (SST)-forcing is investigated for variability and trends in a range of commonly used temperature and precipitation extreme indices over the period 1959 to 2013. Using atmospheric simulations forced by observed SST and sea-ice concentrations (SIC) from three models participating in the Climate of the Twentieth Century Plus (C20C+) Project, results show that oceanic boundary conditions drive a substantial fraction of inter-annual variability in global average temperature extreme indices, as well as, to a lower extent, for precipitation extremes. The observed trends in temperature extremes are generally well captured by the SST-forced simulations although some regional features such as the lack of warming in daytime warm temperature extremes over South America are not reproduced in the model simulations. Furthermore, the models simulate too strong increases in warm day frequency compared to observations over North America. For extreme precipitation trends, the accuracy of the simulated trend pattern is regionally variable, and a thorough assessment is difficult due to the lack of locally significant trends in the observations. This study shows that prescribing SST and SIC holds potential predictability for extremes in some (mainly tropical) regions at the inter-annual time-scale