[1] We provide a new view of global and regional monsoonal rainfall, and their changes in the 21st century under RCP4.5 and RCP8.5 scenarios as projected by 29 climate models that participated in the Coupled Model Intercomparison Project phase 5. The model results show that the global monsoon area defined by the annual range in precipitation is projected to expand mainly over the central to eastern tropical Pacific, the southern Indian Ocean, and eastern Asia. The global monsoon precipitation intensity and the global monsoon total precipitation are also projected to increase. Indices of heavy precipitation are projected to increase much more than those for mean precipitation. Over the Asian monsoon domain, projected changes in extreme precipitation indices are larger than over other monsoon domains, indicating the strong sensitivity of Asian monsoon to global warming. Over the American and African monsoon regions, projected future changes in mean precipitation are rather modest, but those in precipitation extremes are large. Models project that monsoon retreat dates will delay, while onset dates will either advance or show no change, resulting in lengthening of the monsoon season. However, models' limited ability to reproduce the present monsoon climate and the large scatter among the model projections limit the confidence in the results. The projected increase of the global monsoon precipitation can be attributed to an increase of moisture convergence due to increased surface evaporation and water vapor in the air column although offset to a certain extent by the weakening of the monsoon circulation.

Projections of climate change are emerging to play major roles in many applications. However, assessing reliability of climate change projections, especially at regional scales, remains a major challenge. An important question is the degree of progress made since the earlier IPCC simulations (CMIP3) to the latest, recently completed CMIP5. We consider the continental Indian monsoon as an example and apply a hierarchical approach for assessing reliability, using the accuracy in simulating the historical trend as the primary criterion. While the scope has increased in CMIP5, there is essentially no improvement in skill in projections since CMIP3 in terms of reliability (confidence). Thus, it may be necessary to consider acceptable models for specific assessment rather than simple ensemble. Analysis of climate indices shows that in both CMIP5 and CMIP3 certain common processes at large and regional scales as well as slow timescales are associated with successful simulation of trend and mean.

Short-term traffic forecasting is becoming more important in intelligent transportation systems. The k-nearest neighbours (kNN) method is widely used for short-term traffic forecasting. However, the self-adjustment of kNN parameters has been a problem due to dynamic traffic characteristics. This paper proposes a fully automatic dynamic procedure kNN (DP-kNN) that makes the kNN parameters self-adjustable and robust without predefined models or training for the parameters. A real-world dataset with more than one year traffic records is used to conduct experiments. The results show that DP-kNN can perform better than manually adjusted kNN and other benchmarking methods in terms of accuracy on average. This study also discusses the difference between holiday and workday traffic prediction as well as the usage of neighbour distance measurement.

Figure 1: A large reciprocal frame (RF) AbstractA reciprocal frame (RF) is a self-supported three-dimensional structure made up of three or more sloping rods, which form a closed circuit, namely an RF-unit. Large RF-structures built as complex grillages of one or a few similar RF-units have an intrinsic beauty derived from their inherent self-similar and highly symmetric patterns. Designing RF-structures that span over large domains is an intricate and complex task. In this paper, we present an interactive computational tool for designing RF-structures over a 3D guiding surface, focusing on the aesthetic aspect of the design.There are three key contributions in this work. First, we draw an analogy between RF-structures and plane tiling with regular polygons, and develop a computational scheme to generate coherent RF-tessellations from simple grammar rules. Second, we employ a conformal mapping to lift the 2D tessellation over a 3D guiding surface, allowing a real-time preview and efficient exploration of wide ranges of RF design parameters. Third, we devise an optimization method to guarantee the collinearity of contact joints along each rod, while preserving the geometric properties of the RF-structure. Our tool not only supports the design of wide variety of RF pattern classes and their variations, but also allows preview and refinement through interactive controls.

[1] In the backdrop of a changing climate, we investigate whether the Indian summer monsoon is changing either in terms of duration or spatial coverage. Such an analysis specifically for the continental Indian region has both conceptual and societal implications, and has been lacking. We show here, based on an analysis of daily gridded observed rainfall data for the period 1951 -2003, that there are decreasing trends in both early and late monsoon rainfall and number of rainy days, implying a shorter monsoon over India. Similarly, there is a sharp decrease in the area that receives a certain amount of rainfall and number of rainy days during the season. These trends are consistent with other variables like OLR and rainfall from independent datasets; in particular, the land-ocean temperature contrast has a decreasing trend, consistent with a weakening monsoon. The results emphasize need for careful regional analysis in drawing conclusions regarding agro-ecological sustainability in a changing climate. Citation: Ramesh, K. V., and P. Goswami (2007), Reduction in temporal and spatial extent of the Indian summer monsoon, Geophys. Res. Lett., 34, L23704,