How are emergent constraints quantifying uncertainty and what do they leave behind?

The use of emergent constraints to quantify uncertainty for key policy relevant quantities such as Equilibrium Climate Sensitivity (ECS) has become increasingly widespread in recent years. Many researchers, however, claim that emergent constraints are inappropriate or even under-report uncertainty. In this paper we contribute to this discussion by examining the emergent constraints methodology in terms of its underpinning statistical assumptions. We argue that the existing frameworks are based on indefensible assumptions, then show how weakening them leads to a more transparent Bayesian framework wherein hitherto ignored sources of uncertainty, such as how reality might differ from models, can be quantified. We present a guided framework for the quantification of additional uncertainties that is linked to the confidence we can have in the underpinning physical arguments for using linear constraints. We provide a software tool for implementing our general framework for emergent constraints and use it to illustrate the framework on a number of recent emergent constraints for ECS. We find that the robustness of any constraint to additional uncertainties depends strongly on the confidence we can have in the underpinning physics, allowing a future framing of the debate over the validity of a particular constraint around the underlying physical arguments, rather than statistical assumptions

Is the subtropical jet shifting poleward?

The tropics are expanding poleward at about 0.5∘ per decade in observations. This poleward expansion of the circulation is consistently reported using Hadley cell edge metrics and lower-atmospheric tropical edge metrics. However, some upper-atmospheric tropical metrics report smaller trends that are often not significant. One such upper-atmospheric metric is the subtropical jet latitude, which has smaller trends compared to the Hadley cell edge. In this study we investigate the robustness of the weak trends in the subtropical jet position by introducing a new method for locating the subtropical jet, and examining the trends and variability of the subtropical jet latitude. We introduce the tropopause gradient method based on the peak gradient in potential temperature along the dynamic tropopause. Using this method we find the trends in the subtropical jet latitude are indeed much smaller than 0.5∘ per decade, consistent with previous studies. We also find that natural variability within the subtropical jet latitude would not prevent trends from being detected if they were similar to the Hadley cell edge, as trends greater than 0.24∘ per decade could reliably be detected using monthly data or 0.09∘ per decade using daily data. Despite the poleward expansion of the tropics, there is no robust evidence to suggest the subtropical jet is shifting poleward in either hemisphere. Neither the current diagnostic methods nor natural variability can account for the small subtropical jet trends. The most likely explanation, which requires further investigation, is that the subtropical jet position is not tied dynamically to the Hadley cell edge

A Bayesian framework for verification and recalibration of ensemble forecasts: How uncertain is NAO predictability?

Predictability estimates of ensemble prediction systems are uncertain due to limited numbers of past forecasts and observations. To account for such uncertainty, this paper proposes a Bayesian inferential framework that provides a simple 6-parameter representation of ensemble forecasting systems and the corresponding observations. The framework is probabilistic, and thus allows for quantifying uncertainty in predictability measures such as correlation skill and signal-to-noise ratios. It also provides a natural way to produce recalibrated probabilistic predictions from uncalibrated ensembles forecasts. The framework is used to address important questions concerning the skill of winter hindcasts of the North Atlantic Oscillation for 1992-2011 issued by the Met Office GloSea5 climate prediction system. Although there is much uncertainty in the correlation between ensemble mean and observations, there is strong evidence of skill: the 95% credible interval of the correlation coefficient of [0.19,0.68] does not overlap zero. There is also strong evidence that the forecasts are not exchangeable with the observations: With over 99% certainty, the signal-to-noise ratio of the forecasts is smaller than the signal-to-noise ratio of the observations, which suggests that raw forecasts should not be taken as representative scenarios of the observations. Forecast recalibration is thus required, which can be coherently addressed within the proposed framework.Comment: 36 pages, 10 figure

Simple uncertainty frameworks for selecting weighting schemes and interpreting multimodel ensemble climate change experiments

Future climate change projections are often derived from ensembles of simulations from multiple global circulation models using heuristic weighting schemes. This study provides a more rigorous justification for this by introducing a nested family of three simple analysis of variance frameworks. Statistical frameworks are essential in order to quantify the uncertainty associated with the estimate of the mean climate change response. The most general framework yields the “one model, one vote” weighting scheme often used in climate projection. However, a simpler additive framework is found to be preferable when the climate change response is not strongly model dependent. In such situations, the weighted multimodel mean may be interpreted as an estimate of the actual climate response, even in the presence of shared model biases. Statistical significance tests are derived to choose the most appropriate framework for specific multimodel ensemble data. The framework assumptions are explicit and can be checked using simple tests and graphical techniques. The frameworks can be used to test for evidence of nonzero climate response and to construct confidence intervals for the size of the response. The methodology is illustrated by application to North Atlantic storm track data from the Coupled Model Intercomparison Project phase 5 (CMIP5) multimodel ensemble. Despite large variations in the historical storm tracks, the cyclone frequency climate change response is not found to be model dependent over most of the region. This gives high confidence in the response estimates. Statistically significant decreases in cyclone frequency are found on the flanks of the North Atlantic storm track and in the Mediterranean basin

Free backbone carbonyls mediate rhodopsin activation

Conserved prolines in the transmembrane helices of G-protein-coupled receptors (GPCRs) are often considered to function as hinges that divide the helix into two segments capable of independent motion. Depending on their potential to hydrogen-bond, the free C=O groups associated with these prolines can facilitate conformational flexibility, conformational switching or stabilization of the receptor structure. To address the role of conserved prolines in family A GPCRs through solid-state NMR spectroscopy, we focus on bovine rhodopsin, a GPCR in the visual receptor subfamily. The free backbone C=O groups on helices H5 and H7 stabilize the inactive rhodopsin structure through hydrogen-bonds to residues on adjacent helices. In response to light-induced isomerization of the retinal chromophore, hydrogen-bonding interactions involving these C=O groups are released, thus facilitating repacking of H5 and H7 onto the transmembrane core of the receptor. These results provide insights into the multiple structural and functional roles of prolines in membrane proteins

A single cell atlas of frozen shoulder capsule identifies features associated with inflammatory fibrosis resolution

Frozen shoulder is a spontaneously self-resolving chronic inflammatory fibrotic human disease, which distinguishes the condition from most fibrotic diseases that are progressive and irreversible. Using single-cell analysis, we identify pro-inflammatory MERTKlowCD48+ macrophages and MERTK + LYVE1 + MRC1+ macrophages enriched for negative regulators of inflammation which co-exist in frozen shoulder capsule tissues. Micro-cultures of patient-derived cells identify integrin-mediated cell-matrix interactions between MERTK+ macrophages and pro-resolving DKK3+ and POSTN+ fibroblasts, suggesting that matrix remodelling plays a role in frozen shoulder resolution. Cross-tissue analysis reveals a shared gene expression cassette between shoulder capsule MERTK+ macrophages and a respective population enriched in synovial tissues of rheumatoid arthritis patients in disease remission, supporting the concept that MERTK+ macrophages mediate resolution of inflammation and fibrosis. Single-cell transcriptomic profiling and spatial analysis of human foetal shoulder tissues identify MERTK + LYVE1 + MRC1+ macrophages and DKK3+ and POSTN+ fibroblast populations analogous to those in frozen shoulder, suggesting that the template to resolve fibrosis is established during shoulder development. Crosstalk between MerTK+ macrophages and pro-resolving DKK3+ and POSTN+ fibroblasts could facilitate resolution of frozen shoulder, providing a basis for potential therapeutic resolution of persistent fibrotic diseases