A Critical review of theoretical models of negatively polarized light scattered by atmosphereless solar system bodies

About a dozen physical mechanisms and models aspire to explain the negative polarization of light scattered by atmosphereless celestial bodies. This is too large a number for the reliable interpretation of observational data. Through a comparative analysis of the models, our main goal is to answer the question: Does any one model have an advantage over the others? Our analysis is based on new laboratory polarimetric and photometric data as well as on theoretical results. We show that the widely used models due to Hopfield and Wolff cannot realistically explain the phase-angle dependence of the degree of polarization observed at small phase angles. The so-called interference or coherent backscattering mechanism is the most promising model. Models based on that mechanism use well-defined physical parameters to explain both negative polarization and the opposition effect. They are supported by laboratory experiments, particularly those showing enhancement of negative polarization with decreasing particle size down to the wavelength of light. According to the interference mechanism, pronounced negative branches of polarization, like those of C-class asteroids, may indicate a high degree of optical inhomogeneity of light-scattering surfaces at small scales. The mechanism also seems appropriate for treating the negative polarization and opposition effects of cometary dust comae, planetary rings, and the zodiacal light.     

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.     

Projections of daily mean temperature variability in the future: cross-validation tests with ENSEMBLES regional climate simulations

Because of model biases, projections of future climate need to combine model simulations of recent and future climate with information on observed climate. Here, 10 methods for projecting the distribution of daily mean temperatures are compared, using six regional climate change simulations for Europe. Cross validation between the models is used to assess the potential performance of the methods in projecting future climate. Delta change and bias correction type methods show similar cross-validation performance, with methods based on the quantile mapping approach doing best in both groups due to their apparent ability to reduce the errors in the projected time mean temperature change. However, as no single method performs best under all circumstances, the optimal approach might be to use several well-behaving methods in parallel. When applying the various methods to real-world temperature projection for the late 21st century, the largest intermethod differences are found in the tails of the temperature distribution. Although the intermethod variation of the projections is generally smaller than their intermodel variation, it is not negligible. Therefore, it should be preferably included in uncertainty analysis of temperature projections, particularly in applications where the extremes of the distribution are important.     

Weighting of model results for improving best estimates of climate change

Climate projections from multi-model ensembles are commonly represented by the multi-model mean (MMM) climate change. As an alternative, various subjectively formulated schemes for performance-based weighting of models have been proposed. Here, a more objective framework for model weighting is developed. A key ingredient of this scheme is a calibration step quantifying the relationship between intermodel similarity in observable climate and intermodel similarity in simulated climate change. Models that simulate the observable climate better are only given higher weight where and when such an intermodel relationship is found, and the difference in weight between better and worse performing models increases with the strength of this relationship. The method is applied to projections of temperature change from the Third Coupled Model Intercomparison Project. First, cross-validation is used to estimate the potential of the method to improve the accuracy of climate change estimates and to search for suitable predictor variables. The decrease in cross-validation error allowed by the weighting is relatively modest but not negligible, and it could potentially be increased if better predictor variables were found. Second, observations are used to weight the models, to study the differences between the weighted mean and MMM estimates of twenty-first century temperature change and the sensitivity of these differences to the predictor variables and observational data sets used.     

Interpretation of the surface brightness of Phobos

Analysis of disk resolved images of Phobos obtained by the Phobos 2 spacecraft allows us to study the surface scattering law and albedo variations. From low phase angle images we find variations in local geometric albedo approximately 10%, with a correlation length approximately 1km. The scattering law is reasonably well matched by the recent proposed LPI (Lumme et al. 1990a) model, which allows us to deduce a small scale (approximately 1 mm) surface roughness (approximately 0.5), defined here as the rms. tangent of the local surface normal relative to the mean surface normal in the Duxbury (1991) model of Phobos. This value is very close to what has been found for Mercury and the Moon.     

Numerical modelling of airborne electromagnetic anomalies originating from low-conductivity 3D bodies1

Responses of a multifrequency, multicoil airborne electromagnetic (AEM) system were modelled numerically for 3D electrical conductors embedded in a resistive bedrock and overlain by an overburden of low to moderate conductivity. The results cover a horizontal coplanar coil configuration and two frequencies, 7837 Hz and 51 250 Hz. The models studied are single or multiple, poor conductors (conductance lower than 0.1 S) embedded in a host rock of high but finite resistivity (5000 Ωm) and overlain by a layer of overburden with finite thickness and low to moderate conductivity (conductance up to 2 S). On the basis of the modelling results, limits of detectability for poor conductors have been studied for the various model structures. The results indicate that the anomaly from a steeply dipping, plate-like conductor will decrease significantly when the conductor is embedded in a weakly conductive host rock and is overlain by a conductive overburden. However, an anomaly is obtained, and its magnitude can even increase with increasing overburden conductivity or frequency. The plate anomaly remains practically constant when only the overburden thickness is varied. Changes in overburden conductivity will cause the plate-anomaly values to change markedly. If the plate conductance is less than that of the overburden, a local anomaly opposite in sign to the normal type of anomaly will be recorded. Another major consequence is that conductors interpreted with free-space models will be heavily overestimated in depth or underestimated in conductance, if in reality induction and current channelling in the host rock and overburden make even a slight contribution to the anomalous EM field. The lateral resolution for the horizontal coplanar coil system was found to be about 1.7 times the sensor altitude. Similarly, the lateral extension of a horizontal conductive ribbon, required to reach the semi-infinite (half-space) behaviour, is more than three times the sensor altitude. Finally, screening of a steeply dipping plate, caused by a small, conductive horizontal ribbon, is much more severe than screening of the same plate by an extensive horizontal layer.     

Uncertainty of forest carbon stock changes – implications to the total uncertainty of GHG inventory of Finland

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of the efforts needed for development of the inventory. This paper presents an uncertainty analysis of GHG emissions of all Kyoto sectors and gases for Finland consolidated with estimates of emissions/removals from LULUCF categories. In Finland, net GHG emissions in 2003 were around 69 Tg (±15 Tg) CO₂ equivalents. The uncertainties in forest carbon sink estimates in 2003 were larger than in most other emission categories, but of the same order of magnitude as in carbon stock change estimates in other land use, land-use change and forestry (LULUCF) categories, and in N₂O emissions from agricultural soils. Uncertainties in sink estimates of 1990 were lower, due to better availability of data. Results of this study indicate that inclusion of the forest carbon sink to GHG inventories reported to the UNFCCC increases uncertainties in net emissions notably. However, the decrease in precision is accompanied by an increase in the accuracy of the overall net GHG emissions due to improved completeness of the inventory. The results of this study can be utilised when planning future GHG mitigation protocols and emission trading schemes and when analysing environmental benefits of climate conventions.     

Young people’s voiceless politics in the struggle over urban space

This article discusses the particularity of young people’s politics as it unfolds in the practice of everyday life. By exploring a conflict concerning the use of a public park in the City of Oulu, Finland, we discuss how young people may participate in struggles over urban space trough politics that is not based on voice but voicelessness. This political engagement can be understood as a form of nonparticipatory politics that is easily left unnoticed—politics that shirks civic involvement, customary participatory practices and articulated resistance. We deem it important to acknowledge such action as political for two reasons. First, voiceless politics is a weapon of the weak: It is used when other political agencies are not feasible e. Viewing non-participation as apolitical will only further marginalize those who practice politics in such ways. Second, it is important to find ways of acknowledging nonparticipatory action because, while not commonly understood as politics, it is not easily bypassed in political struggles either. By distinguishing political aspects from young people’s urban behaviors, instead of hearing their presence as mere noise, provides tools for bringing their politics to the public agenda and thus developing more democratic urban spaces.     

Evaluation of delta change and bias correction methods for future daily precipitation: intermodel cross-validation using ENSEMBLES simulations

Due to inherent limitations in climate models, their output is biased in relation to observed climate and as such does not provide reliable climate projections. In this study, nine methods used to account for biases in daily precipitation are tested. First, cross-validation tests were made using a set of ENSEMBLES regional model simulations to gain insights in the potential performance of the methods in the future climate. The results show that quantile mapping type methods, being able to modify the shape of the precipitation distribution, often outperform other types of methods. Yet, as the performance depends on time of the year, location and part of the distribution considered, it is not possible to distinguish one universally best performing method. In addition, the improvement relative to the projections that would have been obtained assuming unchanged climate is relatively modest, particularly in the early twentyfirst century conditions. Further tests with different method combinations show that the projections could be potentially improved by using several well performing methods in parallel. In the second part of the study, contributions of method and model differences to the overall variation of precipitation projections are assessed. It is shown that although intermodel differences play an important role, uncertainties related to intermethod differences are substantial, particularly in the tails of the distribution. This suggests that method uncertainty should be taken into account when constructing daily precipitation projections, possibly by using several methods in parallel.