Decadal wintertime variability in the North Pacific climate system observed over the last few decades is documented. The decadal sea surface temperature (SST) variability is found to be concentrated around two major oceanic fronts. The variability around the subtropical front, accompanied by the anomalous subtropical high, exhibits strong negative simultaneous correlation with the tropical SST variability, but that around the subarctic front does not. In fact, cooling around the subarctic front in the mid-1970s cannot be attributed to the influence through the atmosphere of tropical warming that occurred about two years later. During the coolest period around the subarctic front in the mid-1980s, the enhanced surface westerlies associated with the intensified Aleutian low seemed to reinforce the underlying SST anomalies. The westerlies tended to be substantially weaker during the warmest period around 1970. These findings are suggestive of self-maintaining mechanisms inherent to the northern North Pacific climate system for the decadal variability.

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Abstract. The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors.The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraftand entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some exten...

The tail of the Xenopus tadpole will regenerate completely after transection. Much of the mass of the regenerate is composed of skeletal muscle, but there has been some uncertainty about the source of the new myofibres. Here, we show that the growing tail contains many muscle satellite cells. They are active in DNA replication, whereas the myonuclei are not. As in mammals, the satellite cells express pax7. We show that a domain-swapped construct, pax7EnR, can antagonize pax7 function. Transgenic tadpoles were prepared containing pax7EnR driven by a heat-inducible promoter. When induced, this reduces the proportion of satellite cells formed in the regenerate. A second amputation of the resulting tails yielded second regenerates containing notochord and spinal cord but little or no muscle. This shows that inhibition of pax7 action does not prevent differentiation of satellite cells to myofibres, but it does prevent their maintenance as a stem cell population.

We have investigated the requirement for the FGF and Wnt/beta-catenin pathways for Xenopus tadpole tail regeneration. Pathways were modified either by treatment with small molecules or by induction of transgene expression with heat shocks. Regeneration is inhibited by treatment with the FGF inhibitor SU5402, or by activation of a dominant negative FGF receptor, or by activation of expression of the Wnt inhibitor Dkk1. Agents promoting Wnt activity: the small molecule BIO, or a constitutively active form of beta-catenin, led to an increased growth rate. Combination of a Wnt activator with FGF inhibitor suppressed regeneration, while combination of a Wnt inhibitor with a FGF activator allowed regeneration. This suggests that the Wnt activity lies upstream of the FGF activity. Expression of both Wnt and FGF components was inhibited by activation of noggin, suggesting that BMP signalling lies upstream of both Wnt and FGF. The results show that the molecular mechanism of Xenopus tadpole tail regeneration is surprisingly similar to that of the Xenopus limb bud and the zebrafish caudal fin, despite the difference of anatomy.

The atmospheric component of Energy Exascale Earth System Model version 1 has included many new features in the physics parameterizations compared to its predecessors. Potential complex nonlinear interactions among the new features create a significant challenge for understanding the model behaviors and parameter tuning. Using the one-at-a-time method, the benefit of tuning one parameter may offset the benefit of tuning another parameter, or improvement in one target variable may lead to degradation in another target variable. To better understand the Energy Exascale Earth System Model version 1 model behaviors and physics, we conducted a large number of short simulations (three days) in which 18 parameters carefully selected from parameterizations of deep convection, shallow convection, and cloud macrophysics and microphysics were perturbed simultaneously using the Latin hypercube sampling method. From the perturbed parameter ensemble simulations and use of different skill score functions, we identified the most sensitive parameters, quantified how the model responds to changes of the parameters for both global mean and spatial distribution, and estimated the maximum likelihood of model parameter space for a number of important fidelity metrics. Comparison of the parametric sensitivity using simulations of two different lengths suggests that perturbed parameter ensemble using short simulations has some bearing on understanding parametric sensitivity of longer simulations. Results from this analysis provide a more comprehensive picture of the Energy Exascale Earth System Model version 1 behavior. The difficulty in reducing biases in multiple variables simultaneously highlights the need of characterizing model structural uncertainty (so-called embedded errors) to inform future development efforts.

Atmospheric aerosols from anthropogenic and natural sources reach the polar regions through long-range transport and affect the local radiation balance. Such transport is, however, poorly constrained in present-day global climate models, and few multi-model evaluations of polar anthropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD) at 550 nm from simulations with 16 global aerosol models from the AeroCom Phase II model intercomparison project with available observations at both poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the intermodel spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species: black carbon (BC) from fossil fuel and biomass burning, sulfate, organic aerosols (OAs), dust, and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOAs), we document the role of these aerosols at high latitudes. The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in winter (sea-salt) and spring (dust), whereas AOD from anthropogenic aerosols peaks in late spring and summer. The models produce a median annual mean AOD of 0.07 in the Arctic (defined here as north of 60 degrees N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70 degrees S) with a resulting AOD varying between 0.01 and 0.02. The models have estimated the shortwave anthropogenic radiative forcing contributions to the direct aerosol effect (DAE) associated with BC and OA from fossil fuel and biofuel (FF), sulfate, SOAs, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modelled annual mean DAE is slightly negative ( -0.12Wm(-2)), dominated by a positive BC FF DAE in spring and a negative sulfate DAE in summer. The Antarctic DAE is governed by BC FF. We perform sensitivity experiments with one of the AeroCom models (GISS modelE) to investigate how regional emissions of BC and sulfate and the lifetime of BC influence the Arctic and Antarctic AOD. A doubling of emissions in eastern Asia results in a 33% increase in Arctic AOD of BC. A doubling of the BC lifetime results in a 39% increase in Arctic AOD of BC. However, these radical changes still fall within the AeroCom model range

-neural region). Together, the local and long-range bioelectric signals create a binary control system capable of fine-tuning apoptosis and proliferation with the brain and spinal cord to achieve correct pattern and size control. Our data suggest a roadmap for utilizing bioelectric state as a diagnostic modality and convenient intervention parameter for birth defects and degenerative disease states of the CNS.