We discuss equilibrium changes in daily extreme surface air temperature and precipitation events in response to doubled atmospheric
CO2, simulated in an ensemble of 53 versions of HadSM3, consisting of the HadAM3 atmospheric general circulation model (GCM)
coupled to a mixed layer ocean. By virtue of its size and design, the ensemble, which samples uncertainty arising from the
parameterisation of atmospheric physical processes and the effects of natural variability, provides a first opportunity to
quantify the robustness of predictions of changes in extremes obtained from GCM simulations. Changes in extremes are quantified
by calculating the frequency of exceedance of a fixed threshold in the 2 × CO2 simulation relative to the 1 × CO2 simulation. The ensemble-mean value of this relative frequency provides a best estimate of the expected change while the
range of values across the ensemble provides a measure of the associated uncertainty. For example, when the extreme threshold
is defined as the 99th percentile of the 1 × CO2 distribution, the global-mean ensemble-mean relative frequency of extremely warm days is found to be 20 in January, and 28
in July, implying that events occurring on one day per hundred under present day conditions would typically occur on 20–30 days
per hundred under 2 × CO2 conditons. However the ensemble range in the relative frequency is of similar magnitude to the ensemble-mean value, indicating
considerable uncertainty in the magnitude of the increase. The relative frequencies in response to doubled CO2 become smaller as the threshold used to define the extreme event is reduced. For one variable (July maximum daily temperature)
we investigate this simulated variation with threshold, showing that it can be quite well reproduced by assuming the response
to doubling CO2 to be characterised simply as a uniform shift of a Gaussian distribution. Nevertheless, doubling CO2 does lead to changes in the shape of the daily distributions for both temperature and precipitation, but the effect of these
changes on the relative frequency of extreme events is generally larger for precipitation. For example, around one-fifth of
the globe exhibits ensemble-mean decreases in time-averaged precipitation accompanied by increases in the frequency of extremely
wet days. The ensemble range of changes in precipitation extremes (relative to the ensemble mean of the changes) is typically
larger than for temperature extremes, indicating greater uncertainty in the precipitation changes. In the global average,
extremely wet days are predicted to become twice as common under 2 × CO2 conditions. We also consider changes in extreme seasons, finding that simulated increases in the frequency of extremely warm
or wet seasons under 2 × CO2 are almost everywhere greater than the corresponding increase in daily extremes. The smaller increases in the frequency of
daily extremes is explained by the influence of day-to-day weather variability which inflates the variance of daily distributions
compared to their seasonal counterparts. 相似文献
This is the first of two papers that describe the generation of a 25-member perturbed parameter ensemble (PPE) of high-resolution, global coupled simulations for the period 1900–2100, using CMIP5 historical and RCP8.5 emissions. Fifteen of these 25 coupled simulations now form a subset of the global projections provided for the UK Climate Projections 2018 (UKCP18). This first paper describes the selection of 25 variants (combinations of 47 parameters) using a set of cheap, coarser-resolution atmosphere-only simulations from a large sample of nearly 3000 variants. Retrospective 5-day weather forecasts run at climate resolution, and simulations of 2004–2009 with prescribed SST and sea ice are evaluated to filter out poor performance. We opted for a single design choice and sensitivity tests were done after the PPE was generated to demonstrate the effect of design choices on the filtering. Given our choice, only 38 of the parameter combinations were found to have acceptable performance at this stage. Idealised atmosphere-only simulations were then used to select the subset of 25 members that were as diverse as possible in terms of their CO2 and aerosol forcing, and their response to warmer SSTs. Using our parallel set of atmosphere-only and coupled PPEs (the latter from paper 2), we show that local biases in the atmosphere-only experiments are generally informative about the biases in the coupled PPE. Biases in radiative fluxes and cloud amounts are strongly informative for most regions, whereas this is only true for a smaller fraction of the globe for precipitation and dynamical variables. Therefore, the cheap experiments are an affordable way to search for promising parameter combinations but have limitations.
FAMOUS is an unfluxadjusted coupled atmosphere-ocean general circulation model (AOGCM) based on the Met Office Hadley Centre
AOGCM HadCM3. Its parametrisations of physical and dynamical processes are almost identical to those of HadCM3, but by virtue
of reduced horizontal and vertical resolution and increased timestep it runs about ten times faster. The speed of FAMOUS means
that parameter sensitivities can be investigated more thoroughly than in slower higher-resolution models, with the result
that it can be tuned closer to its target climatology. We demonstrate a simple method for systematic tuning of parameters,
resulting in a configuration of FAMOUS whose climatology is significantly more realistic than would be expected for a model
of its resolution and speed. FAMOUS has been tuned to reproduce the behaviour of HadCM3 as nearly as possible, in order that
experiments with each model are of maximum relevance to the physical interpretation of the other. Analysis of the control
climate and climate change simulation of FAMOUS show that it possesses sufficient skill for its intended purposes in Earth
system science as a tool for long-timescale integrations and for large ensembles of integrations, when HadCM3 cannot be afforded.
Thus, it can help to bridge the gap between models of intermediate complexity and the higher-resolution AOGCMs used for policy-relevant
climate prediction. 相似文献
Ensembles of climate model simulations are required for input into probabilistic assessments of the risk of future climate change in which uncertainties are quantified. Here we document and compare aspects of climate model ensembles from the multi-model archive and from perturbed physics ensembles generated using the third version of the Hadley Centre climate model (HadCM3). Model-error characteristics derived from time-averaged two-dimensional fields of observed climate variables indicate that the perturbed physics approach is capable of sampling a relatively wide range of different mean climate states, consistent with simple estimates of observational uncertainty and comparable to the range of mean states sampled by the multi-model ensemble. The perturbed physics approach is also capable of sampling a relatively wide range of climate forcings and climate feedbacks under enhanced levels of greenhouse gases, again comparable with the multi-model ensemble. By examining correlations between global time-averaged measures of model error and global measures of climate change feedback strengths, we conclude that there are no simple emergent relationships between climate model errors and the magnitude of future global temperature change. Algorithms for quantifying uncertainty require the use of complex multivariate metrics for constraining projections. 相似文献
Analytical vibro-replacement design approaches typically quantify the settlement reduction using a dimensionless settlement improvement factor, defined as the ratio of the settlements without and with treatment. Most approaches do not explicitly consider the improvement to creep settlement. This is unfortunate because the ‘stone column’ technique is being increasingly used to reduce settlement and improve bearing capacity in soft normally consolidated and lightly overconsolidated cohesive soils (in which creep settlement tends to account for a significant proportion of the total settlement). Analytical design approaches typically consider primary settlement only. In this study, two-dimensional axisymmetric analyses have been carried out using PLAXIS 2D to establish the variation of improvement factor with time using different soil models, one of which incorporates creep behaviour. Two different approaches have been used to establish the influence of creep on predicted settlement improvement factors. The first approach is based on a direct comparison of two different soil models (one of which incorporates creep) whereas the second approach is based solely on the model incorporating creep. The settlement improvement factors have been evaluated for different area-replacement ratios, modular ratios and column lengths. The primary settlement improvement factors are in good agreement with some of the more popular analytical design methods while the creep settlement improvement factors are either equivalent or lower (depending on the approach used). The primary settlement improvement factors show a dependence on the modular ratio whereas it appears that the corresponding creep settlement improvement factors are relatively independent of it. 相似文献
Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO2 doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%. 相似文献
This paper provides a quantitative assessment of large-scale features in a perturbed parameter ensemble (PPE) of Met Office Unified Model HadGEM-GC3.05 in coupled global historical and future simulations. The main motivation for the simulations is to provide a major component of the UK Climate Projections 2018 (UKCP18), but they will also be used to make worldwide projections and inform future model development. Initially, a 25-member PPE, with 25 different parameter combinations, was simulated. Five members were subsequently dropped because either their simulated climate was unrealistically cool by 1970 or they suffered from numerical instabilities. The remaining 20 members were evaluated after completing the historical phase (1900–2005) against 13 separately selected Climate Model Intercomparison Project Phase 5 (CMIP5) models, and five more members were dropped. The final product is a combined projection system of 15 PPE members and 13 CMIP5 models, which has a number of benefits. In particular, the range of outcomes available from the combined set of 28 is often larger than from either of the two constituent ensembles, thus providing users with a more complete picture of plausible impacts. Here we mainly describe the evaluation process of the 20 PPE members. We evaluate biases in a number of important properties of the global coupled system, including assessment of climatological averages, coupled modes of internal variability and historical and future changes. The parameter combinations yielded plausible yet diverse atmosphere and ocean model behaviours. The range of global temperature changes is narrow, largely driven by use of different CO2 pathways. The range of global warming is seemingly not linked to range of feedbacks estimated from atmosphere-only runs, though we caution that the range of the latter is narrow relative to CMIP5, and therefore this result is not unexpected. This is the second of two papers describing the generation of the PPE for UKCP18 projections. Part 1 (Sexton et al. 2021) describes the selection of 25 parameter combinations of 47 atmosphere and land surface parameters, using a set of cheap atmosphere-only runs at a coarser resolution from nearly 3000 samples of parameter space.
Although finite element packages facilitating coupled consolidation analyses are increasingly in use, many practitioners still favour linear uncoupled analysis out of familiarity with the use of coefficients of consolidation. However, coefficients of consolidation measured by any single means tend to exhibit significant variation, with mean results from different laboratory and field tests also varying widely, leaving uncertainty over the correct values to apply to field problems. In this paper, a finite difference approach is used to back-calculate operational coefficients of consolidation from pore pressure measurements pertinent to a pile group driven in clay–silt. The research shows that this method is capable of successfully capturing the process of pore pressure dissipation, and that the operational coefficient of consolidation around the pile group is higher than that derived from piezocone dissipation tests in the same material. 相似文献
We examine the global mean surface temperature and carbon cycle responses to the A1B emissions scenario for a new 57 member perturbed-parameter ensemble of simulations generated using the fully coupled atmosphere-ocean-carbon cycle climate model HadCM3C. The model variants feature simultaneous perturbation to parameters that control atmosphere, ocean, land carbon cycle and sulphur cycle processes in this Earth system model, and is the first experiment of its kind. The experimental design, based on four earlier ensembles with parameters varied within each individual Earth system component, allows the effects of interactions between uncertainties in the different components to be explored. A large spread in response is obtained, with atmospheric CO2 at the end of the twenty-first century ranging from 615 to 1,100 ppm. On average though, the mean effect of the parameter perturbations is to significantly reduce the amount of atmospheric CO2 compared to that seen in the standard HadCM3C model. Global temperature change for 2090–2099 relative to the pre-industrial period ranges from 2.2 to 7.5 °C, with large temperature responses occurring when atmospheric model versions with high climate sensitivities are combined with carbon cycle components that emit large amounts of CO2 to the atmosphere under warming. A simple climate model, tuned to reproduce the responses of the separate Earth system component ensembles, is used to demonstrate that interactions between uncertainties in the different components play a significant role in determining the spread of responses in global mean surface temperature. This ensemble explores a wide range of interactions and response, and therefore provides a useful resource for the provision of regional climate projections and associated uncertainties. 相似文献
