Exploring Controlling Factors of Water and Heat Exchanges over Zoige Wetland
The Qinghai-Tibet Plateau (QTP) is composed of complex and diverse underlying surface characteristics, as well as many significant differences in water, heat and momentum flux exchanges under different underlying surfaces.
High-elevation wetland is one of the typical underlying surfaces of the Qinghai-Tibet Plateau, which is very sensitive to temperature and precipitation.
Now, a joint research team from the Northwest Institute of Eco-Environment and Resources (NIERR) of the Chinese Academy of Sciences (CAS) and Chengdu University of Information Technology investigated the characteristics of hydrometeorological factors of high-elevation wetland in warm season (June-August) and cold season (December-February) through field observation in Zoige wetland, to examine water and heat exchange mechanisms within the nearby wetland.
This study was published in Advances in Atmospheric Sciences on Dec. 10.
The researchers evaluated the region's atmospheric contributions and new surface parameters using the Community Land Model (CLM) 5. The CLM5 model is capable of determining water and heat transfers among soil, alpine wetland surface, and the atmosphere, using in situ observations as its input data.
They found that the depth of frozen soil averaged between 20 cm and 40 cm throughout the alpine wetland. The sensible heat flux before 16:00 (BJT) was greater in cold season than in warm season, while the diurnal latent heat flux was greater in warm season.
Compared with other atmospheric factors, longwave radiation had a greater influence on heat fluxes at night, as heat radiates away from the surface. Both temperature and longwave radiation are controlling factors for sensible heat flux during the daytime. Temperature and air pressure control the latent heat flux, but the atmospheric influence is negligible in cold season.
Furthermore, the research team also investigated control factors and influencing parameters for water and heat exchanges, with results showing that controlling factors vary amongst different underlying surfaces. The accuracy of the results is still limited by the quality of the observation data and CLM5 model.