We present an augmented version of the reliability ensemble averaging (REA) method designed to generate probabilistic climate-change information from ensembles of climate model simulations. Compared to the original version, the augmented method includes consideration of multiple variables and statistics in the calculation of performance-based weighting. In addition, the model convergence criterion previously employed has been removed. The method is applied to the calculation of changes in mean values and the variability of temperature and precipitation over different sub-regions of East Asia, based on the recently completed CMIP3 multi-model ensemble.Comparison of the new and old REA methods, along with the simple averaging procedure, and the use of different combinations of performance metrics shows that at fine sub-regional scales the choice of weighting is relevant. This is mostly because the models show a substantial spread in performance for the simulation of precipitation statistics, a result that supports the use of model weighting as a useful option to account for wide ranges in the quality of models. The REA method and, in particular, the upgraded method provide a simple and flexible framework for assessing the uncertainty related to the aggregation of results from ensembles of models in order to produce climate-change information at a regional scale.KEY WORDS: Reliability ensemble averaging method · REA · Climate change · CMIP3Resale or republication not permitted without written consent of the publisher OPEN PEN
At the United Nations Framework Convention on Climate Change Conference in Cancun, in November 2010, the Heads of State reached an agreement on the aim of limiting the global temperature rise to 2°C relative to preindustrial levels. They recognized that long-term future warming is primarily constrained by cumulative anthropogenic greenhouse gas emissions, that deep cuts in global emissions are required, and that action based on equity must be taken to meet this objective. However, negotiations on emission reduction among countries are increasingly fraught with difficulty, partly because of arguments about the responsibility for the ongoing temperature rise. Simulations with two earth-system models (NCAR/CESM and BNU-ESM) demonstrate that developed countries had contributed about 60-80%, developing countries about 20-40%, to the global temperature rise, upper ocean warming, and sea-ice reduction by 2005. Enacting pledges made at Cancun with continuation to 2100 leads to a reduction in global temperature rise relative to business as usual with a 1/3-2/3 (CESM 33-67%, BNU-ESM 35-65%) contribution from developed and developing countries, respectively. To prevent a temperature rise by 2°C or more in 2100, it is necessary to fill the gap with more ambitious mitigation efforts.climate modeling | Coupled Model Intercomparison Project phase 5 | Cancun pledge | climate ethics | geoengineering T he impact of human activities on climate change at global and regional scales, including surface temperature (1), sea-level pressure (2), tropopause height (3), precipitation (4), and ocean heat content (5), has been explored and assessed. Greenhouse gas emissions, mostly CO 2 , are the most important anthropogenic forcing on climate (6). The contribution of greenhouse gas emissions varies widely among nations in both the past and the future. As a result, the United Nations Framework Convention on Climate Change (UNFCCC) reached an agreement that each nation should accept its "common but differentiated responsibilities." This ethical construct demands attribution studies of the historical contribution of emissions to climate change (7). To date, research has tracked the causal chain of climate change from human activities to greenhouse gas emissions, to radiative forcing, and finally to climate change. However, this conventional methodological flow does not consider the reverse process or include feedbacks from climate change to greenhouse-gas concentrations via biogeochemistry or decision-making processes (8). More than 100 countries have adopted a global warming limit of 2°C or below (relative to preindustrial levels) as a guiding principle for mitigation efforts to reduce climate-change risks, impacts, and damage (9, 10). The relationship between the climate policy making and the 2°C target by an appropriate emission pathway has been studied in simple climate models and probabilistic analysis (11, 12). However, climate projection experiments under many emission scenarios, even the latest representative concentration pathways (RC...
We have achieved the selective monitoring of H2O2 fluctuation in vivo free from O2 interference by a single-atom Cu–N2 electrocatalyst.
Elevated expression of Copine 1 (CPNE1) has been observed in multiple cancers; however, the underlying mechanisms by which it affects cancer cells are unclear. We aimed to study the effect of CPNE1 on the tumorigenesis and radioresistance of triple‐negative breast cancer (TNBC). Quantitative real‐time polymerase chain reaction was used to detect the expression of CPNE1 in TNBC tissues and cell lines. Western blot, immunohistochemistry, and immunofluorescence were used to investigate the levels of CPNE1, p‐AKT, AKT, cleaved caspase‐3, cleaved PARP1, and γ‐H2AX. Cell viability and apoptosis were measured by CCK‐8 and flow cytometry, respectively. CPNE1 was overexpressed in TNBC tissues and cell lines and was associated with tumor size, distant metastases, and survival rates of patients with TNBC. Moreover, function study shows that CPNE1 promoted cell viability and inhibited cell apoptosis in vitro and inhibited the radiosensitivity of TNBC. Importantly, inactivation of AKT signaling inhibited the tumorigenesis and radioresistance mediated by CPNE1 in TNBC cells. In vivo xenograft study also shows that CPNE1 knockdown inhibited tumor growth and promoted cell apoptosis. Overall, our findings suggest that CPNE1 promotes tumorigenesis and radioresistance in TNBC by regulating AKT activation and targeted CPNE1 expression may be a strategy to sensitize TNBC cells toward radiation therapy.
Global climate change is known to affect the assembly of ecological communities by altering species' spatial distribution patterns, but little is known about how climate change may affect community assembly by changing species' temporal co-occurrence patterns, which is highly likely given the widely observed phenological shifts associated with climate change. Here, we analyzed a 29-year phenological data set comprising community-level information on the timing and span of temporal occurrence in 11 seasonally occurring animal taxon groups from 329 local meteorological observatories across China. We show that widespread shifts in phenology have resulted in community-wide changes in the temporal overlap between taxa that are dominated by extensions, and that these changes are largely due to taxa's altered span of temporal occurrence rather than the degree of synchrony in phenological shifts. Importantly, our findings also suggest that climate change may have led to less phenological mismatch than generally presumed, and that the context under which to discuss the ecological consequences of phenological shifts should be expanded beyond asynchronous shifts.
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