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Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of sulfur dioxide (SO2) have been performed at the Xianghe station (39.75° N, 116.96° E) located at ~50 km southeast of Beijing from March 2010 to February 2013. Tropospheric SO2 vertical profiles and corresponding vertical column densities (VCDs), retrieved by applying the Optimal Estimation Method to the MAX-DOAS observations, have been used to study the seasonal and diurnal cycles of SO2, in combination to correlative measurements from in situ instruments, as well as meteorological data. A marked seasonality was observed in both SO2 VCD and surface concentration, with a maximum in winter (February) and a minimum in summer (July). This can be explained by the larger emissions in winter due to the domestic heating and more favorable meteorological conditions for the accumulation of SO2 close to the ground during this period. Wind speed and direction are also found to be two key factors in controlling the level of the SO2-related pollution at Xianghe. In the case of east or southwest wind, the SO2 concentration rises with the increase of the wind speed, since heavy polluting industries are located to the east and southwest of the station. In contrast, when wind comes from other directions, the stronger the wind, the less SO2 is observed. Regarding the diurnal cycle, the SO2 amount is larger in the early morning and late evening and lower at noon, in line with the diurnal variation of pollutant emissions and atmospheric stability. The observed diurnal cycles of MAX-DOAS SO2 surface concentration are also in very good agreement (correlation coefficient close to 0.9) with those from collocated in-situ data, demonstrating the reliability and robustness of our retrieval. [ABSTRACT FROM AUTHOR]

The Mediterranean hydrometeorological observatory Cévennes-Vivarais (OHM-CV) coordinates hydrometeorological observations (radars, rain gauges, water level stations) on a regional scale in South-Eastern France. In the framework of OHM-CV, temporary GPS measurements have been carried out for 2 months in autumn 2002, when the heaviest rainfall are expected. These measurements increase the spatial density of the existing permanent GPS network, by adding three more receivers between the Mediterranean coast and the Cévennes-Vivarais range to monitor maritime source of water vapour flow feeding the precipitating systems over the Cévennes-Vivarais region. In addition, a local network of 18 receivers covered an area of 30 by 30 km within the field of view of the meteorological radar. These regional and local networks of permanent and temporary stations are used to monitor the precipitable water vapour (PWV) with high temporal resolution (15 min). Also, the dense local network provided data which have been inversed using tomographic techniques to obtain the 3-D field of tro15 pospheric water vapour content. This study presents methodological tests for retrieving GPS tropospheric observations from dense networks, with the aim of assessing the uncertainties of GPS retrievals. Using the optimal tropospheric GPS retrieval methods, high resolution measurements of PWV on a local scale (a few kilometres) are discussed for rain events. Finally, the results of 3-D fields of water vapour densities from GPS tomography are analysed with respect to precipitation fields derived from a meteorological radar, showing a good correlation between precipitation and water vapour depletion areas. [ABSTRACT FROM AUTHOR]

Sulphur dioxide (SO2) fluxes of active degassing volcanoes are routinely measured with ground-based equipment to characterize and monitor volcanic activity. SO2 of un-monitored volcanoes or from explosive volcanic eruptions, can be measured with satellites. However, remote-sensing methods based on absorption spectroscopy generally provide integrated amounts of already dispersed plumes of SO2 and satellite derived flux estimates are rarely reported. Here we review a number of different techniques to derive volcanic SO2 fluxes using satellite measurements of dispersed and large-scale plumes of SO2 and investigate the temporal evolution of the total emissions of SO2 for three very different volcanic events in 2011: Puyehue-Cordón Caulle (Chile), Nyamulagira (DR Congo) and Nabro (Eritrea). High spectral resolution satellite instruments operating both in the UV-visible (OMI/Aura and GOME-2/MetOp-A) and thermal infrared (IASI/MetOp-A) spectral ranges, and mul-tispectral satellite instruments operating in the thermal infrared (MODIS/Terra-Aqua) are used. We show that satellite data can provide fluxes with a sampling of a day or less (few hours in the best case). Generally the flux results from the different methods are consistent, and we discuss the advantages and weaknesses of each technique. Although the primary objective of this study is the calculation of SO2 fluxes, it also enables to assess the consistency of the SO2 products from the different sensors used. [ABSTRACT FROM AUTHOR]

This study reports on the exploitation of GNSS for weather forecasts, especially for nowcasting. We focus on GPS observations (post-processing with a time resolution of 15 min) and try to establish typical configurations of the humidity field which characterise convective systems and particularly which supply forerunners of their initiation associated with deep convection. We show the critical role of GNSS horizontal gradients of humidity to detect small scale structures of the troposphere (i.e. convective cells), and then we present our strategy to obtain typical water vapour configurations by GNSS, called "H2O alert". These alerts are based on a dry/wet contrast taking place during a 30 min window before initiation of a convective system. GNSS observations have been assessed for the rainfall event of the 28-29 June 2005 using data from the Belgian dense network (baseline from 5 to 30 km). To validate our GNSS H2O alert, we use the detection of precipitation by C-band weather radar and thermal infrared radiance of the 10.8-µm channel [Ch09] of SEVIRI instrument on METEOSAT Second Generation. Our H2O alert obtains a score of about 80%. [ABSTRACT FROM AUTHOR]