The first observational experiment under the Indian Climate Research Programme, called the Bay of Bengal Monsoon Experiment (BOBMEX), was carried out during July-August 1999. BOBMEX was aimed at measurements of important variables of the atmosphere, ocean, and their interface to gain deeper insight into some of the processes that govern the variability of organized convection over the bay. Simultaneous time series observations were carried out in the northern and southern Bay of Bengal from ships and moored buoys. About 80 scientists from 15 different institutions in India collaborated during BOBMEX to make observations in most-hostile conditions of the raging monsoon. In this paper, the objectives and the design of BOBMEX are described and some initial results presented. During the BOBMEX field phase there were several active spells of convection over the bay, separated by weak spells. Observation with high-resolution radiosondes, launched for the first time over the northern bay, showed that the magnitudes of the convective available potential energy (CAPE) and the convective inhibition energy were comparable to those for the atmosphere over the west Pacific warm pool. CAPE decreased by 2-3 kJ kg-1 following con-vection, and recovered in a time period of 1-2 days. The surface wind speed was generally higher than 8 ms-1. The thermohaline structure as well as its time evolution during the BOBMEX field phase were found to be different in the northern bay than in the southern bay. Over both the regions, the SST decreased during rain events and increased in cloud-free conditions. Over the season as a whole, the upper-layer salinity decreased for the north bay and increased for the south bay. The variation in SST during 1999 was found to be of smaller amplitude than in 1998. Further analysis of the surface fluxes and currents is expected to give insight into the nature of coupling.

People in central-eastern China are suffering from severe air pollution of nitrogen oxides. Top-down approaches have been widely applied to estimate the ground concentrations of NO 2 based on satellite data. In this paper, a one-year dataset of tropospheric NO 2 columns from the Ozone Monitoring Instrument (OMI) together with ambient monitoring station measurements and meteorological data from May 2013 to April 2014, are used to estimate the ground level NO 2 . The mean values of OMI tropospheric NO 2 columns show significant geographical and seasonal variation when the ambient monitoring stations record a certain range. Hence, a geographically and temporally weighted regression (GTWR) model is introduced to treat the spatio-temporal non-stationarities between tropospheric-columnar and ground level NO 2 . Cross-validations demonstrate that the GTWR model outperforms the ordinary least squares (OLS), the geographically weighted regression (GWR), and the temporally weighted regression (TWR), produces the highest R 2 (0.60) and the lowest values of root mean square error mean (RMSE), absolute difference (MAD), and mean absolute percentage error (MAPE). Our method is better than or comparable to the chemistry transport model method. The satellite-estimated spatial distribution of ground NO 2 shows a reasonable spatial pattern, with high annual mean values (>40 µg/m 3 ), mainly over southern Hebei, northern Henan, central Shandong, and southern Shaanxi. The values of population-weight NO 2 distinguish densely populated areas with high levels of human exposure from others.

No abstract

No abstract

No abstract