3D noise mapping in urban areas

Noise mapping is the process of determining and visualizing noise impact on the environment in order to support environmental policies. Currently most noise impact studies are based on a 2D approach. The 3D output of noise simulation software is processed and visualized in 2D and combined with 2D topographical and other data, such as population distribution, to quantify the effects. The research described in this paper aims at improving visualization and assessment of noise impact on the environment by generating a 3D noise map in cases where 3D effects are relevant. Based on the specific demand, an approach is presented to generate a 3D noise map as a basis for noise impact studies. The proposed concept is proofed by applying it to a sample noise impact study. From experiences with the sample, it can be concluded that the 3D noise map offers significant insight in situations where 3D noise effects are relevant, i.e. in urban areas. Here, current 2D noise maps have limitations. In addition, more accurate assessment of noise impact is possible in particular when different floors of a building close to the noise source and/or behind noise barriers are considered. This paper also elaborates on accuracy aspects in all phases of noise modelling, including a presentation of initial experiments of 3D noise interpolation.     

The association of surface wind stresses over Indian Ocean with monsoon rainfall

Summary Variability of Indian summer monsoon rainfall is examined with respect to variability of surface wind stresses over Indian Ocean. The Indian Ocean region extending from 40°–120° E, and 30° S–25° N, has been divided into 8 homogeneous subregions, viz (1) Arabian Sea (AS), (2) Bay of Bengal (BB), (3) West-equatorial Indian Ocean (WEIO), (4) Central-equatorial Indian Ocean (CEIO), (5) East-equatorial Indian Ocean (EEIO), (6) South-west Indian Ocean (SWIO), (7) South-central Indian Ocean (SCIO), and (8) South-east Indian Ocean (SEIO). The period of study extends for 13 years from 1982–1994. Monthly NCEP surface wind stress data of five months – May through September, have been used in the study. The spatial variability of seasonal and monthly surface wind stresses shows very low values over CEIO and EEIO and very high values over AS, SWIO, and SEIO regions. On the seasonal scale, all India summer monsoon rainfall (AISMR) shows concurrent positive relationships with the surface wind stresses over AS, BB, WEIO, SWIO and SCIO and negative relationships with the surface wind stresses over EEIO and SEIO. The relationships of AISMR with the surface wind stresses over AS and WEIO are significant at 5% level. The concurrent relationships between monthly surface wind stresses over these 8 oceanic sub-regions and monthly subdivisional rainfalls over 29 sub-divisions have been studied. The rainfalls over the subdivisions in the central India and on the west coast of India are found to be significantly related with surface wind stresses over AS, SWIO, SCIO. Monthly subdivisional rainfalls of four subdivisions in the peninsular India show negative relationship with BB surface wind stresses. May surface wind stresses over AS, BB, WEIO, CEIO and SWIO have been found to be positively related with ensuing AISMR. The relationship with AS wind stresses is significant at 5% level and hence may be considered as a potential predictor of AISMR. Received May 21, 2001 Revised October 8, 2001