1,720,991 research outputs found
Evolving Bayesian Emulators for Structured Chaotic Time Series, with Application to Large Climate Models
No full textWe develop Bayesian dynamic linear model Gaussian processes for emulation of time series output for computer models that may exhibit chaotic behavior, but where this behavior retains some underlying structure. The statistical technology is particularly suited to emulating the time series output of large climate models that exhibit this feature and where we want samples from the posterior of the emulator to evolve in the same way as dynamic processes in the computer model do. The methodology combines key features of good uncertainty quantification (UQ) methods such as using complex mean functions to capture large-scale signals within parameter space, with dynamic linear models in a way that allows UQ to borrow strength from the Bayesian time series literature. We present an MCMC algorithm for sampling from the posterior of the emulator parameters when the roughness lengths of the Gaussian process are unknown. We discuss an interpretation of the results of this algorithm that allows us to use MCMC to fix the correlation lengths, making future online samples from the emulator tractable when used in practical applications where online MCMC is infeasible. We apply this methodology to emulate the Atlantic Meridional Overturning Circulation (AMOC) as a time series output of the fully coupled non--flux-adjusted atmosphere-ocean general circulation model HadCM3.
Read More: http://epubs.siam.org/doi/abs/10.1137/12090091
Corrigendum to: Sévellec, F., J. J.-M. Hirschi, and A. T. Blaker, 2013: On the near-inertial resonance of the Atlantic meriodional overturning circulation. J. Phys. Oceanogr., 43, 2661–2672, doi:10.1175/JPO-D-13-092.1.
No full textIdentifying and removing structural biases in climate models with history matching
Full text linkWe describe the method of history matching, a method currently used to help quantify parametric uncertainty in climate models, and argue for its use in identifying and removing structural biases in climate models at the model development stage. We illustrate the method using an investigation of the potential to improve upon known ocean circulation biases in a coupled non-flux-adjusted climate model (the third Hadley Centre Climate Model; HadCM3). In particular, we use history matching to investigate whether or not the behaviour of the Antarctic Circumpolar Current (ACC), which is known to be too strong in HadCM3, represents a structural bias that could be corrected using the model parameters. We find that it is possible to improve the ACC strength using the parameters and observe that doing this leads to more realistic representations of the sub-polar and sub-tropical gyres, sea surface salinities (both globally and in the North Atlantic), sea surface temperatures in the sinking regions in the North Atlantic and in the Southern Ocean, North Atlantic Deep Water flows, global precipitation, wind fields and sea level pressure. We then use history matching to locate a region of parameter space predicted not to contain structural biases for ACC and SSTs that is around 1 % of the original parameter space. We explore qualitative features of this space and show that certain key ocean and atmosphere parameters must be tuned carefully together in order to locate climates that satisfy our chosen metrics. Our study shows that attempts to tune climate model parameters that vary only a handful of parameters relevant to a given process at a time will not be as successful or as efficient as history matching
On the Near-Inertial Resonance of the Atlantic Meridional Overturning Circulation
Full text linkThe Atlantic meridional overturning circulation (AMOC) is a crucial component of the global climate system. It is responsible for around a quarter of the global northward heat transport and contributes to the mild European climate. Observations and numerical models suggest a wide range of AMOC variability. Recent results from an ocean general circulation model (OGCM) in a high-resolution configuration (¼°) suggest the existence of superinertial variability of the AMOC. In this study, the validity of this result in a theoretical framework is tested. At a low Rossby number and in the presence of Rayleigh friction, it is demonstrated that, unlike a typical forced damped oscillator (which shows subinertial resonance), the AMOC undergoes both super- and subinertial resonances (except at low latitudes and for high friction). A dimensionless number Sr, measuring the ratio of ageo- to geostrophic forcing (i.e., the zonal versus meridional pressure gradients), indicates which of these resonances dominates. If Sr ≪ 1, the AMOC variability is mainly driven by geostrophic forcing and shows subinertial resonance. Alternatively and consistent with the recently published ¼° OGCM experiments, if Sr ≫ 1, the AMOC variability is mainly driven by the ageostrophic forcing and shows superinertial resonance. In both regimes, a forcing of ±1 K induces an AMOC variability of ±10 Sv (1 Sv ≡ 106 m3 s−1) through these near-inertial resonance phenomena. It is also shown that, as expected from numerical simulations, the spatial structure of the near-inertial AMOC variability corresponds to equatorward-propagating waves equivalent to baroclinic Poincaré waves. The long-time average of this resonance phenomenon, raising and depressing the pycnocline, could contribute to the mixing of the ocean stratification
Tuning without over-tuning: parametric uncertainty quantification for the NEMO ocean model
No full textIn this paper we discuss climate model tuning and present an iterative automatic tuning method from the statistical science literature. The method, which we refer to here as iterative refocussing (though also known as history matching), avoids many of the common pitfalls of automatic tuning procedures that are based on optimisation of a cost function, principally the over-tuning of a climate model due to using only partial observations. This avoidance comes by seeking to rule out parameter choices that we are confident could not reproduce the observations, rather than seeking the model that is closest to them (a procedure that risks over-tuning). We comment on the state of climate model tuning and illustrate our approach through three waves of iterative refocussing of the NEMO (Nucleus for European Modelling of the Ocean) ORCA2 global ocean model run at 2° resolution. We show how at certain depths the anomalies of global mean temperature and salinity in a standard configuration of the model exceeds 10 standard deviations away from observations and show the extent to which this can be alleviated by iterative refocussing without compromising model performance spatially. We show how model improvements can be achieved by simultaneously perturbing multiple parameters, and illustrate the potential of using low-resolution ensembles to tune NEMO ORCA configurations at higher resolutions
North Atlantic SST anomalies and the cold North European weather events of winter 2009/10 and December 2010
Full text linkNorthern Europe experienced consecutive periods of extreme cold weather in the winter of 2009/2010 and in late 2010. These periods were characterised by a tripole pattern in North Atlantic sea surface temperature (SST) anomalies and exceptionally negative phases of the North Atlantic Oscillation (NAO). A global Ocean-Atmosphere General Circulation Model (OAGCM) is used to investigate the ocean’s role in influencing North Atlantic and European climate. Observed SST anomalies are used to force the atmospheric model and the resultant changes in atmospheric conditions over Northern Europe are examined. We observe differences between the atmospheric responses in the winter of 2009/2010 and the early winter of 2010. Our experiments suggest that North Atlantic SST anomalies did not significantly affect the development of the negative NAO phase in the cold winter of 2009/2010. However, in November and December 2010 the large-scale North Atlantic SST anomaly pattern leads to significant shift in the atmospheric circulation over the North Atlantic towards a NAO negative phase. Therefore, our results indicate that SST anomalies in November/December 2010 were particularly conducive to the development of a negative NAO phase which culminated in the extreme cold weather conditions experienced over Northern Europe in December 2010
The Surface-Forced Overturning of the North Atlantic: Estimates from Modern Era Atmospheric Reanalysis Datasets
Full text linkEstimates of the recent mean and time varying water mass transformation rates associated with North Atlantic surface-forced overturning are presented. The estimates are derived from heat and freshwater surface fluxes and sea surface temperature fields from six atmospheric reanalyses (JRA, NCEP-1, NCEP-2, ERA-I, CFSR and MERRA) together with sea surface salinity fields from two globally gridded data sets (World Ocean Atlas and EN3). The resulting twelve estimates of the 1979-2007 mean surface-forced streamfunction all depict a subpolar cell, with maxima north of 45°N, near σ =27.5 kg m-3, and a subtropical cell between 20°N and 40°N, near σ =26.1 kg m-3. The mean magnitude of the subpolar cell varies between 12-18 Sv, consistent with estimates of the overturning circulation from subsurface observations. Analysis of the thermal and haline components of the surface density fluxes indicates that large differences in the inferred low latitude circulation are largely due to the biases in reanalysis net heat flux fields, which range in the global mean from -13 W m-2 to 19 W m-2. The different estimates of temporal variability in the subpolar cell are well correlated with each other. This suggests the uncertainty associated with the choice of reanalysis product does not critically limit the ability of the method to infer the variability in the subpolar overturning. In contrast, the different estimates of subtropical variability are poorly correlated with each other, and only a subset of them capture a significant fraction of the variability in independently estimated North Atlantic Subtropical Mode Water volume
Response of the Denmark Strait overflow to Nordic Seas heat loss
No full textThe impact of extreme Nordic Seas heat loss on Denmark Strait (DS) dense water transport is examined in (1) control runs of the Hadley Centre HadCM3 and HadGEM1 coupled climate models and (2) perturbation experiments with the fast coupled model FORTE that allow heat flux effects to be isolated from wind stress. All three models show an approximately linear increase in southward DS transport of cold dense water with increasing Nordic Seas winter heat loss in the range ?80 to ?250 Wm?2. The propagation of the cold anomaly from the Nordic Seas source along a trajectory through the DS and into the Irminger Basin is also examined. A common response time is found with the strongest decrease in DS temperature occurring within 8–12 months of the heat loss signal. Our results show that Nordic Seas heat loss must be considered in addition to other processes in understanding DS variability. <br/
Improved estimates of water cycle change from ocean salinity: the key role of ocean warming
Full text linkChanges in the global water cycle critically impact environmental, agricultural, and energy systems relied upon by humanity (Jiménez Cisneros et al 2014 Climate Change 2014: Impacts, Adaptation, and Vulnerability (Cambridge: Cambridge University Press)). Understanding recent water cycle change is essential in constraining future projections. Warming-induced water cycle change is expected to amplify the pattern of sea surface salinity (Durack et al 2012 Science 336 455–8). A puzzle has, however, emerged. The surface salinity pattern has amplified by 5%–8% since the 1950s (Durack et al 2012 Science 336 455–8, Skliris et al 2014 Clim. Dyn. 43 709–36) while the water cycle is thought to have amplified at close to half that rate (Durack et al 2012 Science 336 455–8, Skliris et al 2016 Sci. Rep. 6 752). This discrepancy is also replicated in climate projections of the 21st century (Durack et al 2012 Science 336 455–8). Using targeted numerical ocean model experiments we find that, while surface water fluxes due to water cycle change and ice mass loss amplify the surface salinity pattern, ocean warming exerts a substantial influence. Warming increases near-surface stratification, inhibiting the decay of existing salinity contrasts and further amplifying surface salinity patterns. Observed ocean warming can explain approximately half of observed surface salinity pattern changes from 1957–2016 with ice mass loss playing a minor role. Water cycle change of 3.6% ± 2.1% per degree Celsius of surface air temperature change is sufficient to explain the remaining observed salinity pattern change
The North Atlantic subpolar circulation in an eddy-resolving global ocean model
Full text linkThe subpolar North Atlantic represents a key region for global climate, but most numerical models still have well-described limitations in correctly simulating the local circulation patterns. Here, we present the analysis of a 30-year run with a global eddy-resolving (1/12°) version of the NEMO ocean model. Compared to the 1° and 1/4° equivalent versions, this simulation more realistically represents the shape of the Subpolar Gyre, the position of the North Atlantic Current, and the Gulf Stream separation. Other key improvements are found in the representation of boundary currents, multi-year variability of temperature and depth of winter mixing in the Labrador Sea, and the transport of overflows at the Greenland–Scotland Ridge. However, the salinity, stratification and mean depth of winter mixing in the Labrador Sea, and the density and depth of overflow water south of the sill, still present challenges to the model. This simulation also provides further insight into the spatio-temporal development of the warming event observed in the Subpolar Gyre in the mid 1990s, which appears to coincide with a phase of increased eddy activity in the southernmost part of the gyre. This may have provided a gateway through which heat would have propagated into the gyre's interior
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