Abstract. Eddy covariance data are widely used for the investigation of surface-air interactions. Although numerical datasets exist in public depositories for upland ecosystems, few research groups have released eddy covariance data collected over lakes. In this paper, we describe a dataset from the Lake Taihu Eddy Flux Network, a network consisting of seven lake sites and one land site. Lake Taihu is the third largest freshwater lake (area 2,400 km2) in China, under the influence of subtropical climate. The dataset spans the period from June 2010 to December 2018. Data variables are recorded at half-hourly intervals and include micrometeorology (air temperature, humidity, wind speed, wind direction, rainfall, and water/soil temperature profile), the four components of surface radiation balance, friction velocity, and sensible and latent heat fluxes. Except for rainfall and wind direction, all other variables are gap-filled, with each datapoint marked by a quality flag. Several areas of research can potentially benefit from the publication of this dataset, including evaluation of mesoscale weather forecast models, development of lake-air flux parameterizations, investigation of climatic controls on lake evaporation, validation of remote sensing surface data products, and global synthesis on lake-air interactions. The dataset is publicly available at https://yncenter.sites.yale.edu/data-access and from Harvard Dataverse (doi: 10.7910/DVN/HEWCWM)
Referee's report on: A dataset of microclimate and radiation and energy fluxes from the Lake Taihu Eddy Flux Network
