Abstract. Eddy covariance data are widely used for the investigation of surface–air
interactions. Although numerous datasets exist in public depositories for
land 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 of 2400 km2) in China, under the influence of subtropical climate. The dataset
spans the period from June 2010 to December 2018. Data variables are saved
as half-hourly averages and include micrometeorology (air temperature,
humidity, wind speed, wind direction, rainfall, and water or 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 data point 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 (last access: 24 October 2020) and from the Harvard Dataverse
(https://doi.org/10.7910/DVN/HEWCWM; Zhang et al., 2020).