2017-2022年福建三明站森林生态系统日尺度气象数据集OA

Meteorological parameters constitute fundamental data for understanding the multidimensional impacts of ongoing global climate change on both ecological systems and anthropogenic activities.The rigorous quantification and analysis of atmospheric data play a critical role in advancing comprehensive understanding and responding to climate change,as it not only facilitates interdisciplinary research across multiple spatial and temporal scales,but also enables early identification of extreme meteorological events.Furthermore,this rigorous data foundation provides critical evidentiary support for the development of science-informed climate resilience policies,ensuring that strategies to address climate challenges are rooted in robust empirical analysis.Situated within the ecologically significant eastern mid-subtropical Fujian-Zhejiang mountainous evergreen broad-leaved forest zone,the Fujian Sanming Forest Ecosystem National Observation and Research Station occupies a strategically important position for environmental scientific research.This area demonstrates exceptional carbon sequestration potential,positioning it as a critical asset in addressing national strategic objectives for ecological civilization development and carbon neutrality initiatives.Characterized by pronounced subtropical monsoon climatic conditions and enriched with abundant hydrothermal resources,the region provides an exemplary natural laboratory for investigating climate-ecosystem interactions and advancing ecosystem process studies.The dataset comprises atmospheric and soil variables observed at the station from 2017 to 2022,forming a continuous daily time series spanning six years.Recorded metrics encompass daily average air temperature,atmospheric precipitation,atmospheric pressure,photosynthetically active radiation,relative humidity,surface temperature,soil temperature,and soil volumetric moisture content.These parameters have undergone rigorous standardized quality control procedures,resulting in a continuous temporal sequence spanning the observation period.This repository significantly enhances the meteorological data repository for mid-subtropical China and exhibits substantial applicability and extensibility potential for multidisciplinary research domains such as localized ecological process modeling,regional ecosystem pattern analysis,and validation of global climate change models.