Two Ultraviolet Radiation Datasets that Cover China

Ultraviolet（UV） radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization＇s measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes.

Modeling methane dynamics in three wetlands in Northeastern China by using the CLM-Microbe model

Wetlands account for up to 70%of the natural source of methane(CH_(4))in terrestrial ecosystems on a global scale.Soil microbes are the ultimate producers and biological consumers of CH_(4)in wetlands.Therefore,simulating microbial mechanisms of CH_(4)production and consumptionwould improve the predictability of CH_(4)flux in wetland ecosystems.In this study,we applied a microbial-explicit model,the CLM-Microbe,to simulate CH_(4)flux in three major natural wetlands in northeastern China.The CLM-Microbe model was able to capture the seasonal variation of gross primary productivity(GPP),dissolved organic carbon(DOC),and CH_(4)flux.The CLM-Microbe model explained more than 40%of the variation in GPP and CH_(4)flux across sites.Marsh wetlands had higher CH_(4)flux than mountain peatlands.Ebullition dominated the CH_(4)transport pathway in all three wetlands.The methanogenesis dominates while methanotroph makes a minor contribution to the CH_(4)flux,making all wetlands a CH_(4)source.Sensitivity analysis indicated that microbial growth and death rates are the key factors governing CH_(4)emission and vegetation physiological properties(flnr)and maintenance respiration predominate GPP variation.Explicitly simulating microbial processes allows genomic information to be incorporated,laying a foundation for better predicting CH_(4)dynamics under the changing environment.