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We conduct a thorough comparison of two basic notch filters employed to mitigate the pattern effect that manifests when semiconductor optical amplifiers (SOAs) serve linear amplification purposes. The filters are implemented using as the building architecture the optical delay interferometer (ODI) and the microring resonator (MRR). We formulate and follow a rational procedure, which involves identifying and applying the appropriate conditions for the filters’ spectral response slope related to the SOA pattern effect suppression mechanism. We thus extract the values of the free spectral range and detuning of each filter, which allow one to equivocally realize the pursued comparison. We define suitable performance metrics and obtain simulation results for each filter. The quantitative comparison reveals that most employed metrics are better with the MRR than with the ODI. Although the difference in performance is small, it is sufficient to justify considering also using the MRR for the intended purpose. Finally, we concisely discuss practical implementation issues of these notch filters and further make a qualitative comparison between them in terms of their inherent advantages and disadvantages. This discussion reveals that each scheme has distinct features that render it appropriate for supporting SOA direct signal amplification applications with a suppressed pattern effect.

Atmosphere‐ocean general circulation models (AOGCMs) struggle to reproduce recently observed sea surface temperature (SST) trend patterns. Here, we quantify the relevance of this SST pattern uncertainty to global‐mean temperature projections through convolving Green's functions with SST pattern scenarios that differ from the ones AOGCMs produce by themselves. We find that future SST pattern uncertainty has a significant impact on projections, such as increasing total model uncertainty by 40% in a high‐emissions scenario by 2085. A reversal of the current cooling trend in the East Pacific over the next few decades could lead to a period of global‐mean warming with a 60% higher rate than currently projected. SST pattern uncertainty works through a destabilization of the shortwave cloud feedback to affect temperature projections. It is critical for climate change impact, adaptation, and mitigation assessments to incorporate this previously unaccounted for uncertainty until we trust the evolution of SST patterns in AOGCMs. Plain Language Summary Temperature projections from climate models guide global adaptation and mitigation efforts in response to anthropogenic climate change. However, these climate models are unable to reproduce the pattern of recently observed sea surface temperature (SST) trends in large regions. In this study, we demonstrate how this discrepancy between observations and models, which we define as SST pattern uncertainty, impacts future global‐mean temperature projections. We find that SST pattern uncertainty significantly impacts projections. In fact, when the current cooling SST trend in the East Pacific switches to a warming trend, the planet could experience a period of strong warming with a warming rate 60% greater than what current projections from climate models suggest. We recommend this uncertainty be incorporated into future climate change assessments until we thoroughly trust the pattern of SST evolution in climate models. Key Points Since climate models struggle to reproduce the recently observed sea surface temperature trend pattern, they may continue doing so in the future Accounting for this error in temperature projections increases uncertainty by as much as 40% in a high emissions scenario by 2085 A reversal of the cooling trend in the East Pacific could lead to a warming rate 60% higher than current projections

The plastid genome is highly conserved among plant species, suggesting that alterations of its structure would have dramatic impacts on plant fitness. Nevertheless, little is known about the direct consequences of plastid genome instability. Recently, it was reported that the plastid Whirly proteins WHY1 and WHY3 and a specialized type-I polymerase, POLIB< act as safeguards against plastid genome instability in Arabidopsis (Arabidopsis thaliana). In this study, we use ciprofloxacin, an organelle doublestrand break-inducing agent, and the why1why3polIb-1 variegated mutant to evaluate the impact of generalized plastid DNA instability. First, we show that in why1why3polIb-1 and ciprofloxacin-treated plants, plastid genome instability is associated with increased reactive oxygen species production. Then, using different light regimens, we show that the elevated reactive oxygen species production correlates with the appearance of a yellow-variegated phenotype in the why1why3polIb-1 population. This redox imbalance also correlates to modifications of nuclear gene expression patterns, which in turn leads to acclimation to high light. Taken together, these results indicate that plastid genome instability induces an oxidative burst that favors, through nuclear genetic reprogramming, adaptation to subsequent oxidative stresses.

The magnitude of global surface temperature change in response to unit radiative forcing depends on the type and magnitude of forcing agent—a concept known as a “forcing efficacy.” However, the mechanisms behind the forcing efficacy are still unclear. In this study, we perform a set of simulations using CESM1 to calculate the efficacy of 10 different forcing agents defined in terms of fixed‐SST effective radiative forcing, and then use a Green's function approach to show that each forcing efficacy can be largely understood in terms of the radiative feedbacks associated with the different surface temperature patterns induced by the forcing agents (a pattern effect). We also quantify how the state dependence of feedbacks on global mean surface temperature anomalies impacts forcing efficacies. The results show that the forcing efficacy can be well reconstructed with a combination of pattern effect and state dependence. Plain Language Summary The magnitude of global warming in response to unit forcing induced by carbon dioxide is different to that induced by methane or solar radiation, and the efficacy of a specific climate forcing agent depends on its type and magnitude. Our results show that the forcing efficacy can be explained with a combination of pattern effect and state dependence. When there is relatively stronger forcing over the tropical western Pacific Ocean, where feedbacks are more negative, the corresponding sea surface warming pattern favors a lower efficacy. When the forcing induces a larger global surface warming, less‐stabilizing feedbacks are induced and the corresponding efficacy tends to be higher. Key Points Forcing efficacy can be explained with a combination of pattern effect and state dependence of feedbacks Efficacy is lower when there is relatively stronger forcing over the tropical western Pacific Ocean Efficacy is higher when the forcing is more positive, inducing less‐stabilizing feedbacks at higher warming

The Pacific Walker circulation (PWC) weakens under global warming in climate change projections, supported by a global hydrological constraint. However, the PWC has strengthened over the past decades despite ongoing global warming, and the cause has been a puzzle. Because PWC is coupled with the pattern of sea surface temperature (SST) in the tropical Pacific, quantifying the relative impact of SST pattern change and global warming on the past PWC trend is important. We show, using an atmosphere model driven by observed boundary conditions for 1979–2013 and a hypothetical uniform surface warming trend with varying magnitude, that the PWC scales with warming and weakens by 8% per °C, but this effect cannot overcome the SST pattern effect that intensifies the circulation. Further attribution experiments show that the past strengthening of PWC is explained directly by the SST warming pattern in the narrow equatorial band, about 30% of which is induced by the Indian Ocean. Plain Language Summary The large‐scale overturning circulation in the tropical Pacific known as the Pacific Walker circulation is the heart of the general circulation of the atmosphere. Most of the future climate projections by climate models suggest that the Walker circulation weakens with surface warming. However, observations show that the circulation has strengthened over the past decades despite ongoing global warming. We show, using atmosphere model simulations for 1979–2013 that the Walker circulation strengthening is well reproduced and it weakens when a hypothetical uniform surface warming trend was imposed on the sea surface temperature (SST) data that force the model. The weakening of the Walker circulation occurs at a rate of about 8% per degree warming, but this effect cannot overcome the SST pattern effect that intensifies the circulation. Further attribution simulations show that the past strengthening is explained directly by the SST warming pattern in the narrow equatorial band, about one‐third of which is induced by the warming of the Indian Ocean. Key Points The past strengthening trend of the Pacific Walker circulation (PWC) is well reproduced in the AMIP simulations PWC weakens with surface warming consistent with global energy constraints, but the effect cannot overcome the pattern effect on circulation The pattern effect originates directly from the SST trend in the equatorial band, to which Indian Ocean warming contributes by about 30%

Understanding the relationships between internal variability and forced climate feedbacks is key for using observations to constrain future climate change. Here we probe and interpret the differences in these relationships between the climate change projections provided by the CMIP5 and CMIP6 experiment ensembles. We find that internal variability feedbacks better predict forced feedbacks in CMIP6 relative to CMIP5 by over 50%, and that the increased predictability derives primarily from the slow (>20 years) response to climate change. A key novel result is that the increased predictability is consistent with the higher resemblance between the patterns of internal and forced temperature changes in CMIP6, which suggests temperature pattern effects play a key role in predicting forced climate feedbacks. Despite the increased predictability, emergent constraints provided by observed internal variability are weak and largely unchanged from CMIP5 to CMIP6 due to the shortness of the observational record. Plain Language Summary A key goal in climate change research is to use observed, internal climate feedbacks to constrain the forced feedbacks that govern climate change. Here the authors explore the differences in the relationships between internal and forced climate feedbacks in simulations run under the auspices of the two recent IPCC reports: The CMIP5 and CMIP6 simulations. They find notable increases in the relationships between internal and forced feedbacks between CMIP5 and CMIP6, and attribute these increases at least partially to the patterns of temperature variability associated with internal climate variability and forced climate change. However, they argue that the increases do not lead to improvements in our ability to constrain future climate change based on observations due to the uncertainty in the observed, internal climate feedbacks. Key Points Internal variability feedbacks better predict forced feedbacks in CMIP6 relative to CMIP5 by over 50% The improved prediction derives in part from the greater similarity between the patterns of internal and forced temperature changes in CMIP6 The improved prediction does not significantly improve the emergent constraint associated with internal variability feedbacks

The dependence of climate response on the vertical structure of radiative forcing is studied using a set of idealized experiments, with horizontally uniform and vertically confined forcings. We find for a given effective forcing magnitude, higher‐altitude forcing causes a smaller global warming, owing to more negative cloud feedback. We present novel evidence relating this altitude dependence to sea‐surface temperature patterns and tropospheric static stability. The imposed instantaneous forcings are horizontally uniform, but higher‐altitude forcings more effectively suppress convection in the tropical warm pool, producing a more positive effective (adjusted) surface forcing in that region. This gives rise, during the subsequent climate change, to greater warming contrast between the warm pool and rest of the globe, and hence to increase in low cloud amount. Our results show that to achieve accurate climate projections under anthropogenic forcings, it is important to correctly represent the vertical structures of the applied radiative forcing.

A realistic representation of top‐of‐the‐atmosphere (TOA) radiation response to surface warming is key for trusting climate model projections. We show that coupled models with freely evolving ocean‐atmosphere interactions systematically underestimate the observed global TOA radiation trend during 2001–2022 in 552 simulations. Locally, even if a simulation spontaneously reproduces observed surface temperature trends, TOA radiation trends are more likely under‐ than overestimated. This response bias stems from the models' inability to reproduce the observed large‐scale surface warming pattern and from errors in the atmospheric physics affecting short‐ and longwave radiation. Models with a better representation of the TOA radiation response to local surface warming have a relatively low equilibrium climate sensitivity. Our bias metric is a novel process‐based approach which links a model's current response to climate change to its behavior in the future. Plain Language Summary A realistic representation of the radiation balance at the top of the Earth’s atmosphere (TOA) by coupled climate models is essential for trust in future climate projections. Despite that relevance, it is still not clear whether the models correctly simulate the coupling between surface warming and TOA radiation because of the short observational record. We show that climate models systematically underestimate the observed increase in global TOA radiation during 2001–2022 in 552 simulations. Locally, even if a simulation reproduces observed changes in surface temperature, changes in TOA radiation are more likely under‐ than overestimated. This response bias stems from the models' inability to reproduce the observed large‐scale patterns of surface warming and from errors in the atmospheric physics which suppress the communication of the surface information to the TOA. Models that better represent the TOA radiation response to local surface warming have a relatively low equilibrium climate sensitivity, that is, a weak global‐mean surface warming in response to a doubling of the atmospheric CO2 concentration above pre‐industrial levels. Our new bias metric links a model’s current response to climate change to its behavior in the future. Key Points Climate models underestimate the observed global TOA radiation trend during 2001–2022 Surface warming patterns and atmospheric physics matter for the observation‐model discrepancy Models with a small bias in the coupling between surface warming and TOA radiation trends have a relatively low climate sensitivity

Glutamatergic neurotransmission mediated by N -methyl- d -aspartate (NMDA) receptors is vital for the cortical computations underlying cognition and might be disrupted in severe neuropsychiatric illnesses such as schizophrenia. Studies on this topic have been limited to processes in local circuits; however, cognition involves large-scale brain systems with multiple interacting regions. A prominent feature of the human brain’s global architecture is the anticorrelation of default-mode vs. task-positive systems. Here, we show that administration of an NMDA glutamate receptor antagonist, ketamine, disrupted the reciprocal relationship between these systems in terms of task-dependent activation and connectivity during performance of delayed working memory. Furthermore, the degree of this disruption predicted task performance and transiently evoked symptoms characteristic of schizophrenia. We offer a parsimonious hypothesis for this disruption via biophysically realistic computational modeling, namely cortical disinhibition. Together, the present findings establish links between glutamate’s role in the organization of large-scale anticorrelated neural systems, cognition, and symptoms associated with schizophrenia in humans.

Climate models predict a slowing of the atmospheric overturning circulation with warming. In models, this slowing manifests primarily as a weakening of the Walker Circulation (WC). However, observational studies indicate a strengthened Pacific WC over the past several decades, raising questions about the models' ability to represent critical energetic and hydrologic constraints responsible for the predicted weakening. This discrepancy is closely tied to differences in the warming pattern over the Pacific during this period. We show that model simulations with either observed or model‐projected warming patterns predict a robust weakening of atmospheric overturning circulation, despite having opposing changes in the Pacific WC strength. This weakening occurs in the zonally asymmetric circulation, rather than in the zonal‐mean Hadley cell. Weakening inferred from satellite observations is reproduced in coupled models only when anthropogenic forcing is included, suggesting that a human‐induced weakening of the global atmospheric circulation is already detectable in observations. Plain Language Summary The atmospheric circulation transfers moisture and energy from the tropics to the polar regions and regulates the distribution of rainfall in the tropics which is home to around 40% of the world's population. In recent years, observations show a strengthening of the Pacific Walker Circulation (WC), a regional‐level circulation, which contrasts the weakening of the circulation predicted by climate models. This discrepancy questions the climate models' ability to predict future changes in overturning circulations. Using various strength indices, we find a consistent “weakening with warming” of the global overturning circulation in both observations and climate models for the common period, regardless of the behavior of regional‐level circulations. Moreover, we find that it is highly unlikely that this observed weakening is due to natural variations in the climate. Key Points The global atmospheric overturning circulation has weakened in recent decades despite a strengthening of the Walker Circulation Climate models predict a circulation weakening consistent with observations, manifested primarily as a weakening of the zonally asymmetric overturning circulation The observed weakening is reproduced in coupled climate models only when anthropogenic forcing is included