121 research outputs found
The Arctic predictability and prediction on seasonal-to-interannual timescales (APPOSITE) data set version 1
This is the final version of the article. Available from the publisher via the DOI in this record.
Discussion paper (published on 15 Oct 2015)Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi- 5 model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model 10 intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate vari15 ability on these timescales, such as the El Niño Southern Oscillation.This work was supported by the Natural Environment Research Council
(grant NE/I029447/1). Helge Goessling was supported by a fellowship of the German Research
Foundation (DFG grant GO 2464/1-1). Data storage and processing capacity was kindly provided
by the British Atmospheric Data Centre (BADC). Thanks to Yanjun Jiao (CCCma) for his
assistance with the CanCM4 simulations and to Bill Merryfield for his comments on a draft of the pape
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Have Aerosols Caused the Observed Atlantic Multidecadal Variability?
Identifying the prime drivers of the twentieth-century multidecadal variability in the Atlantic Ocean is crucial for predicting how the Atlantic will evolve in the coming decades and the resulting broad impacts on weather and precipitation patterns around the globe. Recently, Booth et al. showed that the Hadley Centre Global Environmental Model, version 2, Earth system configuration (HadGEM2-ES) closely reproduces the observed multidecadal variations of area-averaged North Atlantic sea surface temperature in the twentieth century. The multidecadal variations simulated in HadGEM2-ES are primarily driven by aerosol indirect effects that modify net surface shortwave radiation. On the basis of these results, Booth et al. concluded that aerosols are a prime driver of twentieth-century North Atlantic climate variability. However, here it is shown that there are major discrepancies between the HadGEM2-ES simulations and observations in the North Atlantic upper-ocean heat content, in the spatial pattern of multidecadal SST changes within and outside the North Atlantic, and in the subpolar North Atlantic sea surface salinity. These discrepancies may be strongly influenced by, and indeed in large part caused by, aerosol effects. It is also shown that the aerosol effects simulated in HadGEM2-ES cannot account for the observed anticorrelation between detrended multidecadal surface and subsurface temperature variations in the tropical North Atlantic. These discrepancies cast considerable doubt on the claim that aerosol forcing drives the bulk of this multidecadal variability
Just in case it rains:building a hydrophobic biofilm the <i>Bacillus subtilis</i> way
Over the millennia, diverse species of bacteria have evolved multiple independent mechanisms to structure sessile biofilm communities that confer protection and stability to the inhabitants. The Gram-positive soil bacterium Bacillus subtilis biofilm presents as an architecturally complex, highly hydrophobic community that resists wetting by water, solvents, and biocides. This remarkable property is conferred by a small secreted protein called BslA, which self-assembles into an organized lattice at an interface. In the biofilm, production of BslA is tightly regulated and the resultant protein is secreted into the extracellular environment where it forms a very effective communal barrier allowing the resident B. subtilis cells to shelter under the protection of a protein raincoat
Decadal to multi-decadal scale variability of Indian summer monsoon rainfall in the coupled ocean-atmosphere-chemistry climate model SOCOL-MPIOM
Systematic Estimates of Decadal Predictability for Six CGCMs
Initial-value predictability measures the degree to which the initial state can influence predictions. In this paper, the initial-value predictability of six atmosphere–ocean general circulation models in the North Pacific and North Atlantic is quantified and contrasted by analyzing long control integrations with time invariant external conditions. Through the application of analog and multivariate linear regression methodologies, average predictability properties are estimated for forecasts initiated from every state on the control trajectories. For basinwide measures of predictability, the influence of the initial state tends to last for roughly a decade in both basins, but this limit varies widely among the models, especially in the North Atlantic. Within each basin, predictability varies regionally by as much as a factor of 10 for a given model, and the locations of highest predictability are different for each model. Model-to-model variations in predictability are also seen in the behavior of prominent intrinsic basin modes. Predictability is primarily determined by the mean of forecast distributions rather than the spread about the mean. Horizontal propagation plays a large role in the evolution of these signals and is therefore a key factor in differentiating the predictability of the various models
High-Resolution Melting Genotyping of Enterococcus faecium Based on Multilocus Sequence Typing Derived Single Nucleotide Polymorphisms
We have developed a single nucleotide polymorphism (SNP) nucleated high-resolution melting (HRM) technique to genotype Enterococcus faecium. Eight SNPs were derived from the E. faecium multilocus sequence typing (MLST) database and amplified fragments containing these SNPs were interrogated by HRM. We tested the HRM genotyping scheme on 85 E. faecium bloodstream isolates and compared the results with MLST, pulsed-field gel electrophoresis (PFGE) and an allele specific real-time PCR (AS kinetic PCR) SNP typing method. In silico analysis based on predicted HRM curves according to the G+C content of each fragment for all 567 sequence types (STs) in the MLST database together with empiric data from the 85 isolates demonstrated that HRM analysis resolves E. faecium into 231 “melting types” (MelTs) and provides a Simpson's Index of Diversity (D) of 0.991 with respect to MLST. This is a significant improvement on the AS kinetic PCR SNP typing scheme that resolves 61 SNP types with D of 0.95. The MelTs were concordant with the known ST of the isolates. For the 85 isolates, there were 13 PFGE patterns, 17 STs, 14 MelTs and eight SNP types. There was excellent concordance between PFGE, MLST and MelTs with Adjusted Rand Indices of PFGE to MelT 0.936 and ST to MelT 0.973. In conclusion, this HRM based method appears rapid and reproducible. The results are concordant with MLST and the MLST based population structure
Phosphorylated DegU Manipulates Cell Fate Differentiation in the <i>Bacillus subtilis</i> Biofilm<em/>
Cell differentiation is ubiquitous and facilitates division of labor and development. Bacteria are capable of multicellular behaviors that benefit the bacterial community as a whole. A striking example of bacterial differentiation occurs throughout the formation of a biofilm. During Bacillus subtilis biofilm formation, a subpopulation of cells differentiates into a specialized population that synthesizes the exopolysaccharide and the TasA amyloid components of the extracellular matrix. The differentiation process is indirectly controlled by the transcription factor Spo0A that facilitates transcription of the eps and tapA (tasA) operons. DegU is a transcription factor involved in regulating biofilm formation. Here, using a combination of genetics and live single-cell cytological techniques, we define the mechanism of biofilm inhibition at high levels of phosphorylated DegU (DegU∼P) by showing that transcription from the eps and tapA promoter regions is inhibited. Data demonstrating that this is not a direct regulatory event are presented. We demonstrate that DegU∼P controls the frequency with which cells activate transcription from the operons needed for matrix biosynthesis in favor of an off state. Subsequent experimental analysis led us to conclude that DegU∼P functions to increase the level of Spo0A∼P, driving cell fate differentiation toward the terminal developmental process of sporulation
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Irreducible uncertainty in near-term climate projections
Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional climate. Here we use large idealised initial condition ensembles of the FAMOUS global climate model with a 1 %/year compound increase in CO2 levels to quantify the range of future temperatures in model-based projections. These simulations explore the role of both atmospheric and oceanic initial conditions and are the largest such ensembles to date. Short-term simulated trends in global temperature are diverse, and cooling periods are more likely to be followed by larger warming rates. The spatial pattern of near-term temperature change varies considerably, but the proportion of the surface showing a warming is more consistent. In addition, ensemble spread in inter-annual temperature declines as the climate warms, especially in the North Atlantic. Over Europe, atmospheric initial condition uncertainty can, for certain ocean initial conditions, lead to 20 year trends in winter and summer in which every location can exhibit either strong cooling or rapid warming. However, the details of the distribution are highly sensitive to the ocean initial condition chosen and particularly the state of the Atlantic meridional overturning circulation. On longer timescales, the warming signal becomes more clear and consistent amongst different initial condition ensembles. An ensemble using a range of different oceanic initial conditions produces a larger spread in temperature trends than ensembles using a single ocean initial condition for all lead times. This highlights the potential benefits from initialising climate predictions from ocean states informed by observations. These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the uncertainty in near-term regional climate is to be adequately quantified
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A verification framework for interannual-to-decadal predictions experiments
Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty
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Decadal prediction of the North Atlantic subpolar gyre in the HiGEM high-resolution climate model
This paper presents an analysis of initialised decadal hindcasts of the North Atlantic subpolar gyre (SPG) using the HiGEM model, which has a nominal grid-spacing of 90 km in the atmosphere, and 1/3 ∘∘ in the ocean. HiGEM decadal predictions (HiGEM-DP) exhibit significant skill at capturing 0–500 m ocean heat content in the SPG, and outperform historically forced transient integrations and persistence for up to a decade ahead. An analysis of case-studies of North Atlantic decadal change, including the 1960s cooling, the mid-1990s warming, and the post-2005 cooling, show that changes in ocean circulation and heat transport dominate the predictions of the SPG. However, different processes are found to dominate heat content changes in different regions of the SPG. Specifically, ocean advection dominates in the east, but surface fluxes dominate in the west. Furthermore, compared to previous studies, we find a smaller role for ocean heat transport changes due to ocean circulation anomalies at the latitudes of the SPG, and, for the 1960s cooling, a greater role for surface fluxes. Finally, HiGEM-DP predicts the observed positive state of the North Atlantic Oscillation in the early 1990s. These results support an important role for the ocean in driving past changes in the North Atlantic region, and suggest that these changes were predictable
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