2026-10-13T16:24:00Z https://www.scidb.cn/oai

10.57760/sciencedb.o00119.00048 2023-06-02T10:23:27Z

2023-06-02 A dataset of carbon and water fluxes observation in subtropical evergreen broad-leaved forest in Jinfo Mountain from 2020 to 2021 doi:10.57760/sciencedb.o00119.00048 en Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station was officially approved for construction in late 2021 by China’s Ministry of Science and Technology. As the main observation field, based on the eddy covariance technique, long-term and continuous measurements of carbon and water fluxes of the subtropical evergreen broad-leaved forest ecosystem has been operational since three years ago. Based on the flux data processing system of ChinaFLUX, this work produced the standard dataset of the subtropical evergreen broad-leaved forest ecosystem including carbon and water fluxes, as well as the key meteorological data at the Jinfo station from 2020 to 2021. This dataset can provide significant data support to analyze the carbon source/sink of typical forest ecosystem, the coupling relationship between carbon and water cycles, as well as their response mechanisms to global climate change.This dataset consists of 4 EXCEL data files, which are divided into 2 categories, namely flux data and meteorological data. The dataset is comprised of net ecosystem carbon exchange, gross primary productivity, ecosystem respiration, latent heat, sensible heat, as well as air temperature/humidity, wind speed/direction, soil temperature/humidity, precipitation, total radiation, net radiation and photosynthetically active radiation. The meteorological data are divided into 10 min, 30 min, daily, monthly and annual scales, and flux data are divided into 30 min, daily, monthly and annual scales. eddy covariance system; carbon and water cycles; flux observation; Jinfo Mountain; evergreen broad-leaved forest tang xu guang Debing Kong Yanan Chen Yuanqing Li Feng Qian Zhi Ding Mingguo Ma PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.11922/11-6035.csd.2023.0103.zh Science Data Bank