Quanliang Chen

Characteristics of Water Vapor in the UTLS over the Tibetan Plateau Based on AURA/MLS Observations

Water vapor (WV) has a vital effect on global climate change. Using satellite data observed by AURA/MLS and ERA-Interim reanalysis datasets, the spatial distributions and temporal variations of WV were analyzed. It was found that high WV content in the UTLS over the southern Tibetan Plateau is more apparent in summer, due to monsoon-induced strong upward motions. The WV content showed the opposite distribution at 100 hPa, though, during spring and winter. And a different distribution at 121 hPa indicated that the difference in WV content between the northern and southern plateau occurs between 121 and 100 hPa in spring and between 147 and 121 hPa in winter. In the UTLS, it diminishes rapidly with increase in altitude in these two seasons, and it shows a “V” structure in winter. There has been a weak increasing trend in WV at 100 hPa, but a downtrend at 147 and 215 hPa, during the past 12 years. At the latter two heights, the WV content in summer has been much higher than in other seasons. Furthermore, WV variation showed a rough wave structure in spring and autumn at 215 hPa. The variation of WV over the Tibetan Plateau is helpful in understanding the stratosphere-troposphere exchange (STE) and climate change.

Spatial and temporal distribution of the cloud optical depth over China based on MODIS satellite data during 2003–2016

The cloud optical depth (COD) is one of the important parameters used to characterize atmospheric clouds. We analyzed the seasonal variations in the COD over East Asia in 2011 using cloud mode data from the AERONET (Aerosol Robotic Network) ground-based observational network. The applicability of the MODIS (Moderate Resolution Imaging Spectroradiometer) COD product was verified and compared with the AERONET cloud mode dataset. There was a good correlation between the AERONET and the MODIS. The spatial and temporal distribution and trends in the COD over China were then analyzed using MODIS satellite data from 2003 to 2016. The seasonal changes in the AERONET data and the time sequence variation of the satellite data suggest that the seasonal variations in the COD are significant. The result shows that the COD first decreases and then increases with the season in northern China, and reaches the maximum in summer and minimum in winter. However, the spatial distribution change is just the opposite in southern China. The spatial variation trend shows the COD in China decreases first with time and gradually increases after 2014. And the trend of COD in the western and central China is consistent with that in China. While the trend of COD shows a continuously increasing over time in northeast China and the Pearl River Delta.

Spatial and Temporal Features of the Frequency of Cloud Occurrence over China Based on CALIOP

Spatial and temporal distribution of cloud vertical structure are key components of global climate change. The occurrence of clouds over China and its surrounding areas has been calculated based on cloud layer products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) at 1 km resolution. Results show significant regional differences in the frequency of cloud occurrence. Fewer clouds are found over the Mongolian Plateau and northern Indian Peninsula, with more clouds apparent over tropical seas and southern China. Cloud cover at night is slightly higher than during the day. Single-layer clouds are more common than multilayer clouds in most areas. In most areas, high-level cloud accounts for the largest proportion of single-layer clouds. The occurrence of clouds in summer and autumn is generally greater than in spring and winter. Single-layer clouds over the Mongolian Plateau and northern Indian Peninsula occur less frequently than multilayer clouds, especially in winter. Furthermore, single-layer clouds are common over the eastern part of southwest China all year round. Over parts of the Tibetan Plateau in summer, high clouds account for the largest proportion (>35%) of annual single-layer clouds, as a result of topography and enhanced summer convection.