Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties

Probabilistic estimates of climate system properties often rely on the comparison of model simulations to observed temperature records and an estimate of the internal climate variability. In this study, we investigate the sensitivity of probability distributions for climate system properties in the Massachusetts Institute of Technology Earth System Model to the internal variability estimate. In particular, we derive probability distributions using the internal variability extracted from 25 different Coupled Model Intercomparison Project Phase 5 models. We further test the sensitivity by pooling variability estimates from models with similar characteristics. We find the distributions to be highly sensitive when estimating the internal variability from a single model. When merging the variability estimates across multiple models, the distributions tend to converge to a wider distribution for all properties. This suggests that using a single model to approximate the internal climate variability produces distributions that are too narrow and do not fully represent the uncertainty in the climate system property estimates

Beyond equilibrium climate sensitivity

ISSN:1752-0908ISSN:1752-089

Baseline evaluation of the impact of updates to the MIT Earth System Model on its model parameter estimates

For over 20 years, the Massachusetts Institute of Technology Earth System Model (MESM) has been used extensively for climate change research. The model is under continuous development with components being added and updated. To provide transparency in the model development, we perform a baseline evaluation by comparing model behavior and properties in the newest version to the previous model version. In particular, changes resulting from updates to the land surface model component and the input forcings used in historical simulations of climate change are investigated. We run an 1800-member ensemble of MESM historical climate simulations where the model parameters that set climate sensitivity, the rate of ocean heat uptake, and the net anthropogenic aerosol forcing are systematically varied. By comparing model output to observed patterns of surface temperature changes and the linear trend in the increase in ocean heat content, we derive probability distributions for the three model parameters. Furthermore, we run a 372-member ensemble of transient climate simulations where all model forcings are fixed and carbon dioxide concentrations are increased at the rate of 1 % yearĝ'1. From these runs, we derive response surfaces for transient climate response and thermosteric sea level rise as a function of climate sensitivity and ocean heat uptake. We show that the probability distributions shift towards higher climate sensitivities and weaker aerosol forcing when using the new model and that the climate response surfaces are relatively unchanged between model versions. Because the response surfaces are independent of the changes to the model forcings and similar between model versions with different land surface models, we suggest that the change in land surface model has limited impact on the temperature evolution in the model. Thus, we attribute the shifts in parameter estimates to the updated model forcings

Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties

Probabilistic estimates of climate system properties often rely on the comparison of model simulations to observed temperature records and an estimate of the internal climate variability. In this study, we investigate the sensitivity of probability distributions for climate system properties in the Massachusetts Institute of Technology Earth System Model to the internal variability estimate. In particular, we derive probability distributions using the internal variability extracted from 25 different Coupled Model Intercomparison Project Phase 5 models. We further test the sensitivity by pooling variability estimates from models with similar characteristics. We find the distributions to be highly sensitive when estimating the internal variability from a single model. When merging the variability estimates across multiple models, the distributions tend to converge to a wider distribution for all properties. This suggests that using a single model to approximate the internal climate variability produces distributions that are too narrow and do not fully represent the uncertainty in the climate system property estimates

Prevalência e fatores associados com o consumo de substâncias psicoativas por acadêmicos de enfermagem da Universidade de Passo Fundo Prevalence and factors associated with psychoactives substances consumption for academics of nursing of the University of Passo Fundo

Com o objetivo de estimar a prevalência de consumo de substâncias psicoativas e seus determinantes entre acadêmicos de enfermagem da Universidade de Passo Fundo (RS), realizou-se estudo transversal com 266 alunos, maiores de dezoito anos, que responderam o questionário do Centro Brasileiro de Informações Sobre Drogas Psicotrópicas. Empregou-se estatística descritiva, qui-quadrado e regressão logística múltipla para análise de dados. A prevalência de uso na vida, no ano e no mês foi maior para álcool, tabaco, benzodiazepínicos e estimulantes. Da amostra, 94% consumiram álcool na vida, 90% no ano e 79% no mês, sendo 14% caracterizado como uso pesado. As alunas consumiram mais benzodiazepínicos e estimulantes que os alunos. Os maiores de 20 anos de idade e os do sexo feminino evidenciaram menor chance de consumo de álcool no mês e aqueles com renda familiar mensal superior a dez salários mínimos apresentaram maior chance de consumo de maconha (OR: 1,92), cocaína (OR:4,63) e inalantes (OR:7,02). O padrão de consumo de substâncias psicoativas assemelha-se ao encontrado em outros grupos de universitários, salvo os benzodiazepínicos e estimulantes, sugerindo-se uma avaliação mais aprofundada desse consumo.<br>The objective of this epidemiologic transversal cut study was to investigate the consumption of psychoactive substances and their determinants between the nursery academics of the University of Passo Fundo, Rio Grande do Sul State. 266 students, aging more than eighteen years old answered a questionnaire of the Brazilian Center of Information about Psychoactive Drugs. A descriptive statistics, qui-square and multiple logistics regression were carried out for the data analysis. Of the sample, 94% had consumed alcohol in the life, 90% in that year and 79% in that month, 14% were characterized as heavy users. The girls had consumed benzodiazepines and stimulants more than the boys. The ones aging 20 year and more and females had evidenced minor possibility of alcohol consumption in the month and those with a monthly family income lower than ten salaries presented a greater possibility of marijuana (OR: 1.92), cocaine (OR:4.63) and inhalants (OR:7.02) consumption. The standard of psychoactive substance consumption is similar than the one found in other groups of colleges student, except for the benzodiazepines and stimulants, suggesting itself a deeper evaluation of this consumption

North Atlantic observations sharpen meridional overturning projections

Atlantic Meridional Overturning Circulation (AMOC) projections are uncertain due to both model errors, as well as internal climate variability. An AMOC slowdown projected by many climate models is likely to have considerable effects on many aspects of global and North Atlantic climate. Previous studies to make probabilistic AMOC projections have broken new ground. However, they do not drift-correct or cross-validate the projections, and do not fully account for internal variability. Furthermore, they consider a limited subset of models, and ignore the skill of models at representing the temporal North Atlantic dynamics. We improve on previous work by applying Bayesian Model Averaging to weight 13 Coupled Model Intercomparison Project phase 5 models by their skill at modeling the AMOC strength, and its temporal dynamics, as approximated by the northern North-Atlantic temperature-based AMOC Index. We make drift-corrected projections accounting for structural model errors, and for the internal variability. Cross-validation experiments give approximately correct empirical coverage probabilities, which validates our method. Our results present more evidence that AMOC likely already started slowing down. While weighting considerably moderates and sharpens our projections, our results are at low end of previously published estimates. We project mean AMOC changes between periods 1960-1999 and 2060-2099 of -4.0 Sv and -6.8 Sv for RCP4.5 and RCP8.5 emissions scenarios respectively. The corresponding average 90% credible intervals for our weighted experiments are [-7.2, -1.2] and [-10.5, -3.7] Sv respectively for the two scenarios