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The global-mean climate feedback quantifies how much the climate system will warm in response to a forcing such as increased CO2 concentration. Under a constant forcing, this feedback becomes less negative (increasing) over time in comprehensive climate models, which has been attributed to increases in cloud and lapse-rate feedbacks. However, out of eight Earth system models of intermediate complexity (EMICs) not featuring interactive clouds, two also simulate such a feedback increase: Bern3D-LPX and LOVECLIM. Using these two models, we investigate the causes of the global-mean feedback increase in the absence of cloud feedbacks. In both models, the increase is predominantly driven by processes in the Southern Ocean region. In LOVECLIM, the global-mean increase is mainly due to a local longwave feedback increase in that region, which can be attributed to lapse-rate changes. It is enhanced by the slow atmospheric warming above the Southern Ocean, which is delayed due to regional ocean heat uptake. In Bern3D-LPX, this delayed regional warming is the main driver of the global-mean feedback increase. It acts on a near-constant local feedback pattern mainly determined by the sea ice–albedo feedback. The global-mean feedback increase is limited by the availability of sea ice: faster Southern Ocean sea ice melting due to either stronger forcing or higher equilibrium climate sensitivity (ECS) reduces the increase of the global mean feedback in Bern3D-LPX. In the highest-ECS simulation with 4 × CO2 forcing, the feedback even becomes more negative (decreasing) over time. This reduced ice–albedo feedback due to sea ice depletion is a plausible mechanism for a decreasing feedback also in high-forcing simulations of other models.

An intermediate-complexity moist general circulation model is used to investigate the forcing of stationary waves in the Northern Hemisphere boreal winter by land–sea contrast, horizontal heat fluxes in the ocean, and topography. The additivity of the response to these building blocks is investigated. In the Pacific sector, the stationary wave pattern is not simply the linear additive sum of the response to each forcing. In fact, over the northeast Pacific and western North America, the sum of the responses to each forcing is actually opposite to that when all three are imposed simultaneously due to nonlinear interactions among the forcings. The source of the nonlinearity is diagnosed using the zonally anomalous steady-state thermodynamic balance, and it is shown that the background-state temperature field set up by each forcing dictates the stationary wave response to the other forcings. As all three forcings considered here strongly impact the temperature field and its zonal gradients, the nonlinearity and nonadditivity in our experiments can be explained, but only in a diagnostic sense. This nonadditivity extends up to the stratosphere, and also to surface temperature, where the sum of the responses to each forcing differs from the response if all forcings are included simultaneously. Only over western Eurasia is additivity a reasonable (though not perfect) assumption; in this sector land–sea contrast is most important over Europe, while topography is most important over western Asia. In other regions, where nonadditivity is pronounced, the question of which forcing is most important is ill-posed.

Decisions on how to manage future flood risks are frequently informed by both sophisticated and computationally expensive models. This complexity often limits the representation of uncertainties and the consideration of strategies. Here we use an intermediate complexity model framework that enables us to analyze a richer set of strategies, a wider range of objectives, and greater levels of uncertainty than are typically considered by more sophisticated and computationally expensive models. We find that allowing for more combinations of risk mitigation strategies can help expand the solution set, help explain synergies and trade‐offs, and point to strategies that can improve outcomes.

Marine ecosystems, biodiversity, and fisheries are under strain worldwide due to global changes including climate warming and demographic pressure. To address this issue, many scientists and stakeholders advocate the use of an ecosystem approach for fisheries that integrates the numerous ecological and economic complexities at play rather than focusing on the management of individual target species. However, the operationalization of such an ecosystem approach remains challenging, especially from a bio-economic standpoint. Here, to address this issue, we propose a model of intermediate complexity (MICE) relying on multi-species, multi-fleet, and resource-based dynamics. Climate change effects are incorporated through an envelope model for the biological growth of fish species as a function of sea surface temperature. The model is calibrated for the small-scale fishery in French Guiana using a time series of fish landings and fishing effort from 2006 to 2018. From the calibrated model, a predictive fishing effort projection and RCP climate scenarios derived from IPCC, we explore the ecosystem dynamics and the fishery production at the horizon 2100. Our results demonstrate the long-term detrimental impact of both climate change and ecological competition on fish biodiversity. The prognosis is particularly catastrophic under the most pessimistic climate scenario, with a potential collapse of both biomass targeted species and fishing activity by 2100. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

RESUMEN Objetivo: determinar la adherencia global y por componentes a la estrategia minuto de oro en médicos que atienden recién nacidos en una entidad de mediano nivel de complejidad. Materiales y métodos: estudio de corte transversal; se incluyeron recién nacidos vivos de partos vaginales espontáneos atendidos por médicos pediatras, ginecólogos o internos en sala de partos de un hospital universitario de la ciudad de Cali, Colombia, en el 2017. Se excluyeron fetos con mal- formaciones congénitas mayores, gemelares y con menos de 34 semanas de edad gestacional. Muestreo sistemático. Tamaño muestral: 150 recién nacidos. Se evaluaron las características basales de los recién nacidos y sus madres, y la adherencia a la estrategia minuto de oro y sus componentes. Se hizo análisis descriptivo. Resultados: la adherencia al minuto de oro en médicos pediatras fue del 65,6 % (IC 95 %: 53,8-78,4), en ginecobstetras, de 33,33 % (IC 95 %: 4,3-77,7), y en médicos internos, de 75,3 % (IC 95 %: 64,8- 85,1). La menor frecuencia se dio en la colocación del gorro al recién nacido, 64,90 % (IC 95 %: 56,7- 72,4), y poner al bebé piel a piel sobre la madre, 65 % (IC 95 %: 55,9-74,4); la mayor frecuencia se presentó en cubrir al recién nacido con paños calientes, 98,6 % (IC 95 %: 95,3-99,8), y la ventilación con presión positiva en los casos en los que no había respuesta a la estimulación inicial, 100 % (IC 95 %: 30-100). Conclusiones: los resultados obtenidos sobre el grado de adherencia de los profesionales sugieren la necesidad de realizar procesos continuos de educación y evaluación sobre la aplicación de esta estrategia de reconocida efectividad en las institu- ciones que ofrecen el servicio de atención de partos. ABSTRACT Objective: To determine adherence, overall and by components, to the Helping Babies Breathe strategy by physicians caring for neonates in an intermediate complexity institution. Materials and Methods: Cross-sectional study that included live neonates born by spontaneous vaginal delivery and who received care from pediatricians, gynecologists or interns in the delivery room of a university hospital in the city of Cali, Colombia, in 2017. Fetuses with major congenital malformations, twins, and neonates with less than 34 weeks of gestational age were excluded. Sampling was systematic and the sample size was of 150 neonates. Baseline neonatal and maternal characteristics were assessed, as well as adherence to the Helping Babies Breathe strategy and its components. A descriptive analysis was performed. Results: Adherence to the Helping Babies Breathe was 65.6% (95% CI 53.8-78.4) for pediatricians, 33.33% (95% CI: 4,3-77,7) for obstetricians and gynecologists, and 75.3% (95% CI: 64,8-85,1) for interns. The lowest frequency was found for cap placement on the neonate’s head, 64.90% (95% CI: 56.7-72.4), and placement of the baby in contact with the mother’s skin, 65% (95% CI: 55.9-74.4); the highest frequency was found for covering the baby with warm blankets, 98,6% (95% CI: 95.3-99.8), and positive pressure ventilation in those cases of absent response to initial stimulation, 100% (95% CI 30-100). Conclusions: Results pertaining to the degree of adherence on the part of the practitioners suggest the need to implement continuous education and evaluation processes focused on the application of this strategy which has been shown to be effective in institutions offering childbirth care.

The National Quality Control Program in Mycology (PNCCM) of Argentina was establishedin 1996 to improve the quality of the mycological diagnosis, to help establish and to setup standardized procedures and continuous training of laboratory staff. The aim of this studywas to assess the effectiveness of the PNCCM in the 1996---2018 period. Data from the NationalMycology Laboratory Network (NMLN) and PNCCM database was used to estimate the increasein the number of controlled laboratories and jurisdictions, the percentage of participation, theimprovement in the quality of results and the adherence to the program. Satisfaction surveyswere performed to assess user satisfaction. The number of controlled laboratories increasedfrom 29 to 146; participation increased from 49% to 93% and general adherence was 72% inthe evaluated period (1996---2018). Improvement in the quality of the results was 15% for lowcomplexity samples; 7% for intermediate complexity samples and 14% for the identification ofhigh complexity strains. Up to 84% of the users consider the PNCCM to be ‘‘very good’’ and 16%‘‘satisfactory’’. These results show the importance of the PNCCM, which is widely accepted bymycological diagnostic laboratories from Argentina. Resumen En 1996 se creó el Programa Nacional de Control de Calidad en Micología (PNCCM)de Argentina con el objetivo de mejorar la calidad del diagnóstico micológico, colaborar enel establecimiento de procedimientos estandarizados en aquellos laboratorios que carecen deellos y contribuir a la capacitación continua del personal.El objetivo de este estudio fue evaluar la efectividad del PNCCM en el período 1996-2018.Se utilizaron los datos de la base de la Red Nacional de Laboratorios de Micología (RNLM) ydel PNCCM para estimar el aumento en el número de laboratorios controlados y el porcentajede participación, la mejora de la calidad de los resultados y la adhesión al programa. Paraevaluar el grado de satisfacción de los usuarios, se analizaron las encuestas de satisfacción delos participantes. En el período evaluado, el número de laboratorios controlados aumentó de 29a 146, la participación aumentó de 49% a 93% y la adherencia general de los participantes fue del72%. La mejora de la calidad de los resultados de los laboratorios fue del 15% para muestras debaja complejidad, 7% para muestras de complejidad intermedia y 14% para la identificación decepas de alta complejidad. El 84% de los usuarios considera que el PNCCM es muy bueno y el 16%que es satisfactorio. Estos resultados evidencian la importancia del PNCCM, que es ampliamenteaceptado por los laboratorios que realizan diagnóstico micológico en nuestro país.

The three-dimensional (3D) multicellular tumor spheroids (MCTs) model is becoming an essential tool in cancer research as it expresses an intermediate complexity between 2D monolayer models and in vivo solid tumors. MCTs closely resemble in vivo solid tumors in many aspects, such as the heterogeneous architecture, internal gradients of signaling factors, nutrients, and oxygenation. MCTs have growth kinetics similar to those of in vivo tumors, and the cells in spheroid mimic the physical interaction of the tumors, such as cell-to-cell and cell-to-extracellular matrix interactions. These similarities provide great potential for studying the biological properties of tumors and a promising platform for drug screening and therapeutic efficacy evaluation. However, MCTs are not well adopted as preclinical tools for studying tumor behavior and therapeutic efficacy up to now. In this review, we addressed the challenges with MCTs application and discussed various efforts to overcome the challenges.

Hysteresis diagrams of the Atlantic meridional overturning circulation (AMOC) under freshwater forcing from climate models of intermediate complexity are fitted to a simple model based on the Langevin equation. A total of six parameters are sufficient to quantitatively describe the collapses seen in these simulations. Reversing the freshwater forcing results in asymmetric behaviour that is less well captured and appears to require a more complicated model. The Langevin model allows for comparison between models that display an AMOC collapse. Differences between the climate models studied here are mainly due to the strength of the stable AMOC and the strength of the response to a freshwater forcing.

We apply two independent data analysis methodologies to locate stable climate states in an intermediate complexity climate model and analyze their interplay. First, drawing from the theory of quasipotentials, and viewing the state space as an energy landscape with valleys and mountain ridges, we infer the relative likelihood of the identified multistable climate states, and investigate the most likely transition trajectories as well as the expected transition times between them. Second, harnessing techniques from data science, specifically manifold learning, we characterize the data landscape of the simulation output to find climate states and basin boundaries within a fully agnostic and unsupervised framework. Both approaches show remarkable agreement, and reveal, apart from the well known warm and snowball earth states, a third intermediate stable state in one of the two climate models we consider. The combination of our approaches allows to identify how the negative feedback of ocean heat transport and entropy production via the hydrological cycle drastically change the topography of the dynamical landscape of Earth's climate., 28 pages, 12 figures plus Supplementary Material. Revised version

Using a machine learning technique, collapse trajectories of the Atlantic Meridional Overturning Circulation from climate models of intermediate complexity are fitted to a simple model based on the Langevin equation. A total of six parameters are sufficient to quantitatively describe the collapses seen in these simulations under a freshwater forcing. Reversing the freshwater forcing results in asymmetric behaviour that is less well captured and would require a more complicated model.

Excessive river erosion and sedimentation threatens critical infrastructure, degrades aquatic habitat, and impairs water quality. Tools for predicting the magnitude of erosion, sedimentation, and channel evolution processes are needed for effective mitigation and management. We present a new numerical model that simulates coupled river bed and bank erosion at the watershed scale. The model uses modified versions of Bagnold’s sediment transport equation to simulate bed erosion and aggradation, as well as a simplified Bank Stability and Toe Erosion Model (BSTEM) to simulate bank erosion processes. The model is mechanistic and intermediate complexity, accounting for the dominant channel evolution processes while limiting data requirements. We apply the model to a generic test case of channel network response following a disturbance and the results match physical understanding of channel evolution. The model was also tested on two field data sets: below Parker Dam on the lower Colorado River and the North Fork Toutle River (NFTR) which responded dramatically to the 1980 eruption of Mount St. Helens. It accurately predicts observed channel incision and bed material coarsening on the Colorado River, as well as observations for the upstream 18 km of the NFTR watershed. The model does not include algorithms for extensive lateral migration and avulsions and therefore did not perform well in the lower NFTR where the channel migrated across a wide valley bottom. REM is parsimonious and useful for simulating network scale channel change in single thread systems responding to disturbance.

The Massachusetts Institute of Technology Integrated Global System Model (IGSM) is designed for analyzing the global environmental changes that may result from anthropogenic causes, quantifying the uncertainties associated with the projected changes, and assessing the costs and environmental effectiveness of proposed policies to mitigate climate risk. The IGSM consists of the Massachusetts Institute of Technology Earth System Model (MESM) of intermediate complexity and the Economic Projections and Policy Analysis model. This paper documents the current version of the MESM, which includes a two-dimensional (zonally averaged) atmospheric model with interactive chemistry coupled to the zonally averaged version of Global Land System model and an anomaly-diffusing ocean model., United States. Department of Energy. Office of Science (DE-FG02-94ER61937)

An intermediate-complexity model for four-dimensional variational data assimilation including moist processes

A pilot coupled climate sensitivity study is presented based on the newly developed adjoint coupled climate model, Centrum für Erdsystemforschung und Nachhaltigkeit (CEN) Earth System Assimilation Model (CESAM). To this end the components of the coupled forward model are summarized, and the generation of the adjoint code out of the model forward code through the application of the Transformation of Algorithms in FORTRAN (TAF) adjoint compiler is discussed. It is shown that simulations of the intermediate-complexity CESAM are comparable in quality to CMIP-type coupled climate models, justifying the usage of the model to compute adjoint sensitivities of the northern Europe near-surface temperature to anomalies in surface temperature, sea surface salinity, and sea ice over the North Atlantic and the Arctic on time scales of up to one month. Results confirm that on a time scale of up to a few days surface temperatures over northern Europe are influenced by Atlantic temperature anomalies just upstream of the target location. With increasingly longer time lapse, however, it is the influence of SSTs over the central and western North Atlantic on the overlying atmosphere and the associated changes in storm-track pattern that dominate the evolution of the surface European temperature. Influences of surface salinity and sea ice on the northern European temperature appear to have similar sensitivity mechanisms, invoked indirectly through their influence on near-surface temperature anomalies. The adjoint study thus confirms that the SST’s impact on the atmospheric dynamics, notably storm tracks, is the primary cause for the influence of northern European temperature changes.

This work evaluated the National Research Council (NRC) dairy model (2001) predictions of rumen undegradable (RUP) and degradable (RDP) protein compared with measured postruminal non-ammonia, nonmicrobial (NANMN) and microbial N flows. Models were evaluated using the root mean squared prediction error (RMSPE) as a percent of the observed mean; mean and slope biases as percentages of mean squared prediction error (MSPE), and concordance correlation coefficient, (CCC). The NRC (2001) over-estimated NANMN by 18% and under-estimated microbial N by 14%. Both responses had large mean biases (19% and 20% of MSPE, respectively); and NANMN had a slope Dias (22% of MSPE). The NRC NANMN estimate had high RMSPE (46% of observed mean) and low CCC (0.37); updating feed library A, B, and C protein fractions and degradation rate (K-d) estimates with newer literature only marginally improved fit. The re-fit NRC models for NANMN and microbial N had CCC of 0.89 and 0.94, respectively. When compared with a prediction of NANMN as a static mean fraction of N intake; the re-derived NRC approach did not have improved fit. A protein system of intermediate complexity was derived in an attempt to estimate NANMN with improved fit compared with the static mean NANMN model. In this system, postruminal appearance of A, B, and C protein fractions were predicted in a feed-type specific mariner rather than from estimated passage and degradation rates. In a comparison to independent data. achieved through cross-validation; the new protein system improved RMSPE (34 vs. 36% of observed mean) and CCC (0.42 vs. 0.30) compared with the static mean NANMN model. When the NRC microbial N equation was re-derived, the RDP term dropped from the model. Consequently, 2 new microbial protein equations were formulated, both used a saturating (increasing at a decreasing rate) form: one saturated with respect to TDN and the other saturated over increasing intakes of rumen degraded starch and NDF. Both equations expressed maximal microbial N production as a linear function of RDP intake. The function relating microbial N to intake of rumen degradable carbohydrate improved RMSPE (24 vs. 28% of the observed mean) and CCC (0.63 vs 0.30) compared with the re-derived NRC model. The newly derived equations showed modest improvements in model fit and improved capacity to account for known biological effects; however, substantial variability in NANMN and microbial N estimates remained unexplained. Agricultural and Food Research Initiative Competitive Grant [2011-68004-30340]; USDA National Institute of Food and Agriculture (Washington, DC) [2015-03656]; Papillon (Easton, MD) In addition to the funding sources listed in the title page footnote, funding for this project was provided by Agricultural and Food Research Initiative Competitive Grant no. 2011-68004-30340 and no. 2015-03656 from the USDA National Institute of Food and Agriculture (Washington, DC) and by Papillon (Easton, MD). The authors acknowledge the contributions of the late L. F. Reutzel (Laud O'Lakes/Purina Mills) to portions of the initial code used in the project and the late Gale Bateman (Akey, Lewisburg, OH) for help in assembling and collating the dietary ingredient data.

We use the Bern3D model of intermediate complexity to examine the marine cycle of isotopes 231Pa and 230Th and the relationship between the particle-bound ratio Pa p / Th p and changes in the formation of the North Atlantic Deep Water (NADW). Model parameters describing reversible scavenging of isotopes by organic particles, opal, calcite and resuspended sediments were systematically varied and alternative sink parametrisations explored. It proves difficult to simultaneously achieve a good agreement with observations of dissolved and particle-associated concentrations of 231Pa and 230Th ( Pa d , Th d , Pa p , Th p ) as well as the particle-bound ratio Pa p / Th p within the classical concept of reversible scavenging alone. Agreement between simulated and observed Pa d , Th d and estimates of mean ocean residence times is improved by taking into account simplified representations of additional sinks at the sea floor (bottom scavenging) and at continental boundaries (boundary scavenging). We also find improved agreement between model and data by increasing lateral advection, in particular for Pa d . These results point to the importance of sink processes that act in addition to reversible scavenging to shape the steady state distribution of 231Pa and, to a lesser degree, of 230Th. In transient experiments in which the strength of the Atlantic meridional overturning circulation (AMOC) is periodically turned on and off, we find a strong statistical relationship between variations in AMOC strength and Pa p / Th p at great depths in the Northwest Atlantic region. These conclusions are robust across the range of sink parametrisations, that are consistent with estimates in the mean ocean residence time of 231Pa and 230Th. Our results indicate that the relationship between Pa p / Th p and AMOC-strength may not be fundamentally affected by uncertainties in sink processes, at least on the large spatial and temporal scale considered here, and support the idea that changes in Pa p / Th p in sediments of the Northwest Atlantic are indicative of changes in AMOC strength. Taking into account our simplified approach, our results indicate that the relationship between Pa p / Th p and AMOC-strength in the deep Northwest Atlantic is not affected by boundary scavenging or bottom scavenging. Our results thus support the idea that changes in Pa p / Th p in sediments of the Northwest Atlantic are indicative of changes in AMOC strength.

Although past decades have witnessed significant reductions in mortality of heart failure together with advances in our understanding of its cellular, molecular, and whole-heart features, a lot of basic cardiac research still fails to translate into clinical practice. In this review we examine myocardial slices, a novel model in the translational arena. Myocardial slices are living ultra-thin sections of heart tissue. Slices maintain the myocardium’s native function (contractility, electrophysiology) and structure (multicellularity, extracellular matrix) and can be prepared from animal and human tissue. The discussion begins with the history and current advances in the model, the different interlaboratory methods of preparation and their potential impact on results. We then contextualize slices’ advantages and limitations by comparing it with other cardiac models. Recently, sophisticated methods have enabled slices to be cultured chronically in vitro while preserving the functional and structural phenotype. This is more timely now than ever where chronic physiologically relevant in vitro platforms for assessment of therapeutic strategies are urgently needed. We interrogate the technological developments that have permitted this, their limitations, and future directions. Finally, we look into the general obstacles faced by the translational field, and how implementation of research systems utilizing slices could help in resolving these., Graphical Abstract Graphical Abstract

Myocardial slices, also known as “cardiac tissue slices” or “organotypic heart slices,” are ultrathin (100–400 μm) slices of living adult ventricular myocardium prepared using a high-precision vibratome. They are a model of intermediate complexity as they retain the native multicellularity, architecture, and physiology of the heart, while their thinness ensures adequate oxygen and metabolic substrate diffusion in vitro. Myocardial slices can be produced from a variety of animal models and human biopsies, thus providing a representative human in vitro platform for translational cardiovascular research. In this review, we compare myocardial slices to other in vitro models and highlight some of the unique advantages provided by this platform. Additionally, we discuss the work performed in our laboratory to optimize myocardial slice preparation methodology, which resulted in highly viable myocardial slices from both large and small mammalian hearts with only 2–3% cardiomyocyte damage and preserved structure and function. Applications of myocardial slices span both basic and translational cardiovascular science. Our laboratory has utilized myocardial slices for the investigation of cardiac multicellularity, visualizing 3D collagen distribution and micro/macrovascular networks using tissue clearing protocols and investigating the effects of novel conductive biomaterials on cardiac physiology. Myocardial slices have been widely used for pharmacological testing. Finally, the current challenges and future directions for the technology are discussed.

The uncertainty in a climate data records (CDRs) derived from Earth observations in part derives from the propagated uncertainty in the radiance record (the fundamental climate data record, FCDR) from which the geophysical estimates in the CDR are derived. A common barrier to providing uncertainty-quantified CDRs is the inaccessibility to CDR creators of appropriate radiance uncertainty information in the FCDR. Here, we propose radiance uncertainty information designed directly to facilitate estimation of propagated uncertainty in derived CDRs at full resolution and in gridded products. Errors in Earth observations are typically highly structured and complex, and the uncertainty information we propose is of intermediate complexity, sufficient to capture the main variability in propagated uncertainty in a CDR, while avoiding unfeasible complexity or data volume. The uncertainty and error correlation characteristics of uncertainty are quantified for three classes of error with different propagation properties: independent, structured and common radiance errors. The meaning, mathematical derivations, practical evaluation and example applications of this set of uncertainty information are presented.

This paper investigates the role played by cooperation for the sustainable harvesting of an ecosystem. To achieve this, a bio-economic model based on a multi-species dynamics with interspecific relationships and multi-agent catches is considered. A comparison between the non-cooperative and cooperative optimal strategies is carried out. Revisiting the Tragedy of Open Access and over-exploitation issues, it is first proved analytically how harvesting pressure is larger in the non-cooperative case for every species. Then it is examined to what extent gains from cooperation can also be derived for the state of the ecosystem. It turns out that cooperation clearly promotes the conservation of every species when the number of agents is high. When the number of agents remains limited, results are more complicated, especially if a species-by-species viewpoint is adopted. However, we identify two metrics involving the state of every species and accounting for their ecological interactions which exhibit gains from cooperation at the ecosystem scale in the general case. Numerical examples illustrate the mathematical findings.

With limited computational resources, there is a need for computationally frugal models. This is particularly the case for atmospheric sciences, which have long relied on either simplistic analytical solutions or computationally expensive numerical models. The simpler solutions are inadequate for many problems, while the cost of numerical models makes their use impossible for many problems, most notably high-resolution climate downscaling applications spanning large areas, long time periods, and many global climate projections. Here the Intermediate Complexity Atmospheric Research model (ICAR) is presented to provide a new step along the modeling complexity continuum. ICAR leverages an analytical solution for high-resolution perturbations to wind velocities, in conjunction with numerical physics schemes, that is, advection and cloud microphysics, to simulate the atmosphere. The focus of the initial development of ICAR is for predictions of precipitation, and eventually temperature, humidity, and radiation at the land surface. Comparisons between ICAR and the Weather Research and Forecasting (WRF) Model for simulations over an idealized mountain are presented, as well as among ICAR, WRF, and the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) observation-based product for a year-long simulation over the Colorado Rockies. In the ideal simulations, ICAR matches WRF precipitation predictions across a range of environmental conditions with a coefficient of determination r2 of 0.92. In the Colorado Rockies, ICAR, WRF, and PRISM show very good agreement, with differences between ICAR and WRF comparable to the differences between WRF and PRISM in the cool season. For these simulations, WRF required 140–800 times more computational resources than ICAR.

The local ensemble transform Kalman filter (LETKF) is used to develop a strongly coupled data assimilation (DA) system for an intermediate complexity ocean-atmosphere coupled model. Strongly coupled DA uses the cross-domain error covariance from a coupled-model background ensemble to allow observations in one domain to directly impact the state of the other domain during the analysis update. This method is compared to weakly coupled DA in which the coupled model is used for the background, but the cross-domain error covariance is not utilized. We perform an observing system simulation experiment with atmospheric observations only. Strongly coupled DA reduces the ocean analysis errors compared to weakly coupled DA, and the higher accuracy of the ocean also improves the atmosphere. The LETKF system design presented should allow for easy implementation of strongly coupled DA with other types of coupled models.

We present a computationally efficient modelling system, IMOGEN, designed to undertake global and regional assessment of climate change impacts on the physical and biogeochemical behaviour of the land surface. A pattern-scaling approach to climate change drives a gridded land surface and vegetation model MOSES/TRIFFID. The structure allows extrapolation of General Circulation Model (GCM) simulations to different future pathways of greenhouse gases, including rapid first-order assessments of how the land surface and associated biogeochemical cycles might change. Evaluation of how new terrestrial process understanding influences such predictions can also be made with relative ease.

A new framework is proposed for the evaluation of stochastic subgrid-scale parameterizations in the context of MAOOAM, a coupled ocean-atmosphere model of intermediate complexity. Two physically-based parameterizations are investigated, the first one based on the singular perturbation of Markov operator, also known as homogenization. The second one is a recently proposed parameterization based on the Ruelle's response theory. The two parameterization are implemented in a rigorous way, assuming however that the unresolved scale relevant statistics are Gaussian. They are extensively tested for a low-order version known to exhibit low-frequency variability, and some preliminary results are obtained for an intermediate-order version. Several different configurations of the resolved-unresolved scale separations are then considered. Both parameterizations show remarkable performances in correcting the impact of model errors, being even able to change the modality of the probability distributions. Their respective limitations are also discussed., Comment: 44 pages, 12 figures, 4 tables

The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000-19,000 y ago (27-19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30-13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, therewere almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe.

At present, most models forecasting the El Niño–Southern Oscillation (ENSO) use data assimilation, which constrains models physics using available observations. In this article, an ENSO model of intermediate complexity is constrained by sea level observations: sea level from the Simple Ocean Data Assimilation (SODA) reanalysis is assimilated in the model forced by SODA winds, using an ensemble Kalman filter. In addition, retrospective ENSO forecasts over the period 1958–2007 are computed. The assimilation of sea level observations slightly improves the model’s predictive skill, which is due to the correction of the recharge–discharge process simulated by the model. To assess this, two indices relevant to the ENSO recharge–discharge theory are considered: the zonal tilt and zonal mean of sea level in the equatorial Pacific. The assimilation of those two observed indices alone leads to results that are qualitatively similar to the assimilation of full maps of sea level observations. This partly results from the fact that the leading statistical modes of the model errors on sea level have a zonal tilt and zonal mean structure. The data assimilation corrects in particular a too weak amplitude of the zonal mean sea level and its associated subsurface variability in the model. The authors suggest that insight on the role of the recharge–discharge process in other models could be gained by comparing the assimilation of full maps of sea level observations with the assimilation of the two indices of sea level.

Objetivo: describir los conocimientos que tienen las pacientes acerca del uso de la citología, y las emociones y el comportamiento que genera en estas un resultado positivo en la citología vaginal con atipias escamosas de significado indeterminado (ASCUS) o lesión escamosa intraepitelial de bajo grado (LEI-BG).Materiales y métodos: investigación cualitativa fenomenológica, que busca establecer las experiencias vividas por mujeres entre 18 y 69 años que consultaron por primera vez, por el hallazgo en la citología cérvico-vaginal de ASCUS o LEI-BG, a la unidad de patología cervical de dos instituciones de nivel medio de complejidad en Bogotá (Colombia), una institución pública y otra un centro de atención ambulatorio privado. El tamaño de la muestra se determinó por saturación teórica y muestreo consecutivo. Se realizaron grupos focales y entrevistas, la información fue grabada y transcrita posteriormente, creando categorías para evaluar las experiencias: caracterización sociodemográfica, cognición, características afectivas y comportamiento. Se empleó el estilo de análisis mediante edición, presentado como material narrativo, a fin de ordenar la información recolectada para su síntesis e interpretación.Resultados: se incluyeron 27 mujeres. El resultado anormal de la citología cérvico-vaginal despierta sentimientos de culpa, angustia y preocupación pues lo relacionan con el cáncer de cuello uterino, dado que no es claro para ellas que este es un examen de tamización. La principal conducta posterior a recibir el resultado de la citología fue priorizar la cita médica. Hay alteraciones en las relaciones de pareja basadas en la percepción de infidelidad secundaria a la infección de VPH.Conclusiones: la toma de la citología cérvico-vaginal es considerada por las pacientes como importantísima y obligatoria en el marco de la necesidad de prevenir y tratar el cáncer de cuello uterino.

This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon-Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect and imperfect model data are comparable., Comment: monthly weather review (in press)

A new optimization strategy is proposed to identify the sensitivities of simulations of atmospheric and oceanic models to uncertain parameters. The strategy is based on a nonlinear optimization method that is able to estimate the maximum values of specific parameter sensitivity measures; meanwhile, it takes into account interactions among uncertain parameters. It is tested using the Lorenz’63 model and an intermediate complexity 2.5-layer shallow-water model of the North Pacific Ocean. For the Lorenz’63 model, it is shown that the parameter sensitivities of the model results depend on the initial conditions. For the 2.5-layer shallow-water model used to simulate the Kuroshio large meander (KLM) south of Japan, the optimization strategy reveals that the prediction of the KLM path is insensitive to the uncertainties in the bottom friction coefficient, the interfacial friction coefficient, and the lateral friction coefficient. Rather, the KLM prediction is relatively sensitive to the uncertainties of the reduced gravity representing ocean stratification and the wind stress coefficient.

Modeling is an important tool in the food industry since it is able to simplify explanation of phenomena and optimize processes that cover a broad field from manufacture to byproducts treatment. The goal of the current article is to explore the development of enzyme kinetic models and their evolution over the last decades. For this reason, corresponding simulations were classified in deterministic, empirical, and stochastic models, prior investigating limitations, corrections, and industrial applications in each case. The ultimate goal is to provide an answer to a major problem: how can we develop an intermediate complexity model that achieves satisfactorily representation of the main phenomena with a limited number of parameters?

SummaryPrevious studies have shown that neurons in area V4 are involved in the processing of shapes of intermediate complexity and are sensitive to curvature. These studies also suggest that curvature-tuned neurons are position invariant. We sought to examine the mechanisms that endow V4 neurons with these properties. Consistent with previous studies, we found that response rank order to the most- and least-preferred stimuli was preserved throughout the receptive field. However, a fine-grained analysis of shape tuning revealed a surprising result: V4 neurons tuned to highly curved shapes exhibit very limited translation invariance. At a fine spatial scale, these neurons exhibit local variation in orientation. In contrast, neurons that prefer straight contours exhibit spatially invariant orientation-tuning and homogenous fine-scale orientation maps. Both of these patterns are consistent with a simple orientation-pooling model, with tuning for straight or curved shapes resulting, respectively, from pooling of homogenous or heterogeneous orientation signals inherited from early visual areas.

The dominant source of inter-model differences in comprehensive global climate models (GCMs) are cloud radiative effects on Earth's energy budget. Intermediate complexity models, while able to run more efficiently, often lack cloud feedbacks. Here, we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4xCO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.

Artificial ocean alkalinization (AOA) is investigated as a method to mitigate local ocean acidification and protect tropical coral ecosystems during a 21st century high CO2 emission scenario. Employing an Earth system model of intermediate complexity, our implementation of AOA in the Great Barrier Reef, Caribbean Sea and South China Sea regions, shows that alkalinization has the potential to counteract expected 21st century local acidification in regard to both oceanic surface aragonite saturation Omega and surface pCO(2). Beyond preventing local acidification, regional AOA, however, results in locally elevated aragonite oversaturation and pCO(2) decline. A notable consequence of stopping regional AOA is a rapid shift back to the acidified conditions of the target regions. We conclude that AOA may be a method that could help to keep regional coral ecosystems within saturation states and pCO(2) values close to present-day values even in a high-emission scenario and thereby might 'buy some time' against the ocean acidification threat, even though regional AOA does not significantly mitigate the warming threat.

State-of-the-science global climate models show that global warming is likely to weaken the Atlantic Meridional Overturning Circulation (AMOC). While such models are arguably the best tools to perform AMOC projections, they do not allow a comprehensive uncertainty assessment because of limited computational resources. Here we present an AMOC-emulator, a box model with a number of free parameters that can be tuned to mimic the sensitivity of the AMOC to climate change of a specific global climate model. The AMOC-emulator (M-AMOC1.0) is applied to simulations of global warming and melting of the Greenland Ice Sheet, performed with an intermediate complexity model. Predictive power of the AMOC-emulator is shown by comparison with a number of additional warming and Greenland Ice Sheet melt scenario that have not been used in the tuning of the AMOC-emulator, highlighting the potential of the AMOC-emulator to assess the uncertainty in AMOC projections.

Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO₂ and 4×CO₂ forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.

Foram realizadas simulacoes climaticas a partir de 2 experimentos de sensibilidade numerica conduzidos com um modelo acoplado de complexidade intermediaria, LOVECLIM , estendendo-se para um periodo de 300 anos. Sendo que, neste experimento foi realizada a reducao em 50% da topografia geral do hemisferio norte, um com modelo acoplado (oceano-atmosfera) e outro desacoplado (somente atmosfera). Nos resultados obtidos, foram observadas alteracoes no padrao de clima global e local, em especial a regiao da Asia, relacionadas com aumento de temperatura do ar a superficie e intensidade do vento. Maiores alteracoes foram observados em regioes continentais no hemisferio norte. Isto mostra o maior impacto local causado pela forcante topografica com o a reducao da pela metade da topografia boreal. Palavras-chave : Topografia, Mudancas Climaticas, Modelos Climaticos, Forcante Climatica Modelling the Impact of Topography on Global Climate Boreal ABSTRACT Simulations were conducted from two numerical sensitivity experiments conducted with a coupled model with intermediate complexity, LOVECLIM, extending for a period of 300 years. Since this experiment was carried out 50% reduction in the general topography of the northern hemisphere, with a coupled model (ocean-atmosphere) and the other uncoupled (atmosphere only). Their results have been observed changes in the pattern of global and local climate, particularly in Asia, linked to increase of air temperature and wind intensity. The biggest impacts were observed in continental regions in the north hemisphere. This shows the greater local impact caused by topographic forcing Keywords : Topography, Climate Change, Climate Models, Topographic Forcing

Here we developed a composite pollen-based record of altitudinal vegetation changes from Lake Fúquene (5° N) in Colombia at 2540 m elevation. We quantitatively calibrated Arboreal Pollen percentages (AP%) into mean annual temperature (MAT) changes with an unprecedented ~60-year resolution over the past 284 000 years. An age model for the AP% record was constructed using frequency analysis in the depth domain and tuning of the distinct obliquity-related variations to the latest marine oxygen isotope stacked record. The reconstructed MAT record largely concurs with the ~100 and 41-kyr (obliquity) paced glacial cycles and is superimposed by extreme changes of up to 7 to 10° Celsius within a few hundred years at the major glacial terminations and during marine isotope stage 3, suggesting an unprecedented North Atlantic – equatorial link. Using intermediate complexity transient climate modelling experiments, we demonstrate that ice volume and greenhouse gasses are the major forcing agents causing the orbital-related MAT changes, while direct precession-induced insolation changes had no significant impact on the high mountain vegetation during the last two glacial cycles.