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.     

On Newtonian cosmology with a varying gravitational constant

In a paper with the same title as this one, J. P. Vinti studies the effects a varying gravitational constant has upon Newtonian cosmology. In this paper an alternative approach for the analysis is given which obtains and improves upon some of Vinti's major results.Supported in part by a NSF Grant.     

The sunlit lunar surface

Directional infrared emission from the sunlit lunar surface is determined for the thermal meridian and as a function of observer elevation and azimuth angles at three Sun elevation angles. A study of selected mare sites at full Moon suggests that brightness temperatures are relatively insensitive to changes in certain surface parameters, such as the photometric function, emissivity, and thermophysical properties of the soil. The observed deviations from predictions for an average surface can be accounted for by changes in surface roughness.Deceased 12 January, 1971.     

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.     

Superhyperbolic expansion,noncollision singularities and symmetry configurations

A large class of symmetry solutions of the Newtonian n-body problem cannot end in a noncollision singularity nor expand faster than any constant multiple of time.Following a suggestion from Christian Marchal, we extended the original theme of this essay to include superhyperbolic motion. The work of D. Saari was supported by NSF Grant ISI 9103180; the work of F. Diacu was supported by NSERC Grant 3-48376     

Instability and Diffusion in the Elliptic Restricted Three-body Problem

The importance of the stability characteristics of the planar elliptic restricted three-body problem is that they offer insight about the general dynamical mechanisms causing instability in celestial mechanics. To analyze these concerns, elliptic–elliptic and hyperbolic–elliptic resonance orbits (periodic solutions with lower period) are numerically discovered by use of Newton's differential correction method. We find indications of stability for the elliptic–elliptic resonance orbits because slightly perturbed orbits define a corresponding two-dimensional invariant manifold on the Poincaré surface-section. For the resonance orbit of the hyperbolic–elliptic type, we show numerically that its stable and unstable manifolds intersect transversally in phase-space to induce instability. Then, we find indications that there are orbits which jump from one resonance zone to the next before escaping to infinity. This phenomenon is related to the so-called Arnold diffusion. This revised version was published online in August 2006 with corrections to the Cover Date.     

Particulate matter dispersion and haze occurrence potential studies at a local palm oil mill

The emissions from palm oil industry through incineration and open burning are the major sources of air pollutions contribution in Malaysia. The consequence of increasing the particulate concentration, the particulate matter dissolves with vapour and grows into droplets when the humidity exceeds approximately 70% and causing opaque situation known as haze. This work focuses on the dispersion particulate matter from palm oil mill. Gaussian Plume Model from a point source, subject to various atmospheric conditions is used to calculate particulate matter concentration then display the distribution of plume dispersion using geographic information system. Atmospheric Stability, mixing height, wind direction, wind speed, natural and artificial features play an important role in dispersion process. Study on the dispersion of particulate matters and the haze potential are presented as a case study in this paper. The data obtained will be served as the purpose of modeling the transport of particulate matter for obtaining permits and prevention of significant deterioration to the environment.