Quantitative Assessment of Vegetation Feedback to Atmospheric Variability over East Asia
Received date: 2023-10-19
Revised date: 2024-02-04
Online published: 2024-09-19
This paper employs statistical methods to analyze the relationship between vegetation and climatology variables.Additionally, it quantitatively assesses vegetation feedback over East Asia using the equilibrium feedback assessment (EFA) method.The study reveals a significant correlation between vegetation and climate variables, including temperature and precipitation.In middle and high latitudes, positive feedback is observed between vegetation and temperature, while negative feedback is identified between vegetation and precipitation.In middle and low latitudes, positive feedback is observed between vegetation and precipitation, while negative feedback is identified between vegetation and temperature.In high latitudes, the positive vegetation anomaly tends to reduce the albedo by shading effect, leading to increased energy absorption and warming air during winter and spring.The analysis highlights that in low latitudes, the correlation between leading vegetation and precipitation is highly sensitive.It is mainly because the high year-round temperature in this area leads to the vegetation being dominated by precipitation signals.The study also finds a positive correlation between leading vegetation and precipitation in low latitudes.The increased vegetation stimulates moisture convergence and enhances evapotranspiration, resulting in more precipitation.The vegetation feedback parameter for temperature is positive in regions around the Da Hinggan Mountains and Baikal Lake, predominantly covered by evergreen needle-leaf forests.The feedback parameter in this area is approximately 1 to 2 .The positive feedback parameter is identified in the southern part of China, ranging from 0.2 to 1 .Regarding precipitation, the feedback parameter exhibits significant noise, making it challenging to distinguish signals except for the positive signal around the North China Plain.In the North China Plain, the feedback parameter for precipitation is approximately 1.5 .
Di MA , Shihua Lü , Xianhong MENG , Lin ZHAO , Zhaoguo LI , Yuanyuan MA , Meixia LI . Quantitative Assessment of Vegetation Feedback to Atmospheric Variability over East Asia[J]. Plateau Meteorology, 2024 , 43(5) : 1234 -1248 . DOI: 10.7522/j.issn.1000-0534.2024.00014
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | |
null | 鲍艳, 王玉琦, 南素兰, 等 |
null | 鲍艳, 王玉琦, 南素兰, 等 |
null | 刘宜纲, 吕世华, 马翠丽, 等, 2022.区域气候模式RegCM砾石参数化方案在青藏高原不同区域土壤水分输送的模拟分析[J].高原气象, 41(1): 79-92.DOI: 10.7522/j.issn.1000-0534.2020.00086.Liu Y G , |
null | |
null | 罗斯琼, 李红梅, 马迪, 等, 2022.三江源冻土-植被相互作用及气候效应研究现状及展望[J].高原气象, 41(2): 255-267.DOI: 10.7522/j.issn.1000-0534.2021.00098.Luo S Q , |
null | |
null | 田定方, 范闻捷, 任华忠, 2020.植被光合有效辐射吸收比率遥感研究进展[J].遥感学报, 24(11): 1307-1324.DOI: 10.11834/jrs.20208498.Tian D F , |
null | |
null | 杨耀先, 胡泽勇, 路富全, 等, 2022.青藏高原近60年来气候变化及其环境影响研究进展[J].高原气象, 41(1): 1-10.DOI: 10.7522/j.issn.1000-0534.2021.00117.Yang Y X , |
null | |
null | 张戈, 赖欣, 刘康, 2023.黄河源区玛曲土壤冻融过程中地表水热交换特征分析[J].高原气象, 42(3): 575-589.DOI: 10.7522/j.issn.1000-0534.2022.00083.Zhang G , |
null |
/
〈 |
|
〉 |