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Zhang X.,National Satellite Meteorological Center China Meteorological Administration | van Geffen J.,Royal Netherlands Meteorological Institute | Liao H.,CAS Institute of Atmospheric Physics | Zhang P.,National Satellite Meteorological Center China Meteorological Administration | Lou S.,CAS Institute of Atmospheric Physics
Atmospheric Environment | Year: 2012

This paper presents results of measurements of tropospheric sulphur dioxide (SO 2) from satellite over China during 2004-2009. SCIAMACHY/ENVISAT SO 2 data products have been validated by ground based remote sensing instrument MAXDOAS in China, and with predictions of the atmospheric model GEOS-Chem. The spatial and temporal distribution of tropospheric SO 2 over China is discussed in this study. The result shows that the SO 2 load over East China is decreasing since strong control for pollution emission in 2007 for preparation of 2008 Olympic Games in China, while the SO 2 load in West China is increasing all the way during 2004-2009, which might reflect that the anthropogenic activity was added to promote the economy development in west of China.Typical seasonal variation with high pollution levels in winter and low in summer is found in the northwest of China, while the inverse seasonal variation is found for the south of China. The characteristics of tropospheric SO 2 over the major cities in China were explored and found that tropospheric SO 2 was partly under control from 2007 because of the policy from China government for reduction in SO 2 emissions in 2006. And the SO 2 value shows remarkably decrease in most of the major cities after 2007 because strong control for the pollution emission for 2008 Olympic games. Guangzhou city shows high SO 2 pollution levels in summer time, since most of the coal power plants and thermal power industry are located to the south of Guangzhou city and southerly winds dominate during summer time. © 2012 Elsevier Ltd.


Guo Y.,Nanjing University of Information Science and Technology | Guo Y.,National Satellite Meteorological Center China Meteorological Administration | Lu N.-M.,National Satellite Meteorological Center China Meteorological Administration | Qi C.-L.,National Satellite Meteorological Center China Meteorological Administration | And 2 more authors.
Chinese Journal of Geophysics (Acta Geophysica Sinica) | Year: 2015

The Fengyun (FY)-3C satellites was successfully launched on 23 December 2013 and carries the Microwave humidity and temperature sounder on board which started its measurements since December 30. MWHTS observe the vertical distribution of atmospheric temperature and moisture. MWHTS is a cross-track scanning instrument which observing in 15 channels at frequencies ranging from 89 to 191 GHz. Eight temperature sounding channels have center frequency at 118.75 GHz oxygen absorption line, five humidity sounding channels have center frequency at 183.31 GHz water vapor absorption line and two window channels centered at 89 and 150 GHz.118 GHz channel is first used to detect atmosphere on current operational satellite.118GHz and 183 GHz channels can obtain fine vertical distribution structure of atmosphere humidity and temperatures. These data will be used in data assimilation and climate research. Before MWHTS observationsquantitative application, the on-orbit test was carried out. The MWHTS post-launch instrument performance was conducted with on-orbit data during a period of three months. The main parameters monitored include the radiometric counts from the cold space and warm target, the warm target temperature and instrument temperature. These calibration data through quality control were converted to brightness temperature use non-linear correction and correction of antenna spill-over effects. There are three methods to validate MWHTS measurements: 1.Use the atmospheric humidity and temperature profiles and surface temperatures which were observed by site calibration test in the radiance transfer model Mono RTM(Monochromatic Radiative Transfer Model) to simulating the MWHTS radiation. The difference between simulations and measurements are assessed. 2.When the same kind sensors observe the same target at the same time, the observed brightness temperature difference should be the small and constant bias. The ATMS on a SNPP satellite was used to be reference sensor. The MWHTS calibration results are cross compared with ATMS by the SNO. The time gap for matched data is less than 20 minutes and the ground distance is less than 3 km. The scan angle difference is less than 5 degree around nadir. Spatial subsets are extracted for 3×3 MWHTS pixels for homogeneity checking, the brightness temperature standard deviation is less than the threshold of 1.0 K are qualified. 3. The CRTM(Community Radiative Transfer Model)was used to simulate the brightness temperature at MWHTS channels. The input data for CRTM come from the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS). The difference between observations and simulations which to be referred as O-B were analyzed. The statistic characteristics of O-B were also affected by the change of channel frequency, accuracy of radiative transfer model simulation and input profiles. The inter-satellite validation is useless for the first used channels (such as 118.75 GHz channels). The O-B characteristics were partly demonstrating the calibration accuracy of sensor. The results of post launch site calibration show that brightness temperature bias for every channel except 14 is less than 1.3 K. The brightness temperature observed by MWHTS and ATMS were compared to demonstrate the mean bias for channel 14 is the biggest than other channels and the standard deviations for five humidity sounding channels is less than 1 K. Furthermore, the differences between MWHTS observations and the forward radiativetransfer model simulations, referred to as “O-B”, suggest that the standard deviations of “O-B” difference for channel 2 to 6 which is near the center of 118.75 GHz oxygen absorption line is less than 0.5 K and that for other channels is similar to that for corresponding ATMS channels. The scan-dependent biases for MWHTS indicate the temperature dependence of scan biases is noticed of channel 1, 7 to 13 and 15. ©, 2015, Science Press. All right reserved.

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