A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Probabilistic assessments of the impacts of compound dry and hot events on global vegetation during growing seasons
The response of vegetation to climate extremes, including droughts and hot extremes, has been evaluated extensively in recent decades. However, quantitative assessments of individual and combined impacts of dry and hot conditions on vegetation are rather limited. In this study, we developed a multivariate approach for analyzing vegetation responses to dry, hot, and compound dry-hot conditions from a probabilistic perspective using precipitation, temperature, and the Normalized Difference Vegetation Index (NDVI) for the period from 1982 to 2015. The Standardized Precipitation Index (SPI) and Standardized Temperature Index (STI) were used to define individual and compound dry and hot conditions. Based on the diagnosis of the correlation between SPI/STI and NDVI during growing seasons, we investigated the conditional probability of vegetation decline under different climate conditions. The results showed that vegetation was affected by compound dry and hot conditions (defined as SPI ⩽ −1.3 and STI > 1.3) in arid and semi-arid regions. In these regions, the conditional probabilities of vegetation decline under compound dry and hot conditions increased by 7% and 28% compared with those under individual dry and hot conditions, respectively. The impact of compound dry and hot events on vegetation for different biomes was also assessed. Temperate grassland was found to be particularly vulnerable to compound dry and hot conditions. This study highlights the necessity of considering compound dry and hot extremes when assessing vegetation responses to climate extremes under global warming.
Probabilistic assessments of the impacts of compound dry and hot events on global vegetation during growing seasons
The response of vegetation to climate extremes, including droughts and hot extremes, has been evaluated extensively in recent decades. However, quantitative assessments of individual and combined impacts of dry and hot conditions on vegetation are rather limited. In this study, we developed a multivariate approach for analyzing vegetation responses to dry, hot, and compound dry-hot conditions from a probabilistic perspective using precipitation, temperature, and the Normalized Difference Vegetation Index (NDVI) for the period from 1982 to 2015. The Standardized Precipitation Index (SPI) and Standardized Temperature Index (STI) were used to define individual and compound dry and hot conditions. Based on the diagnosis of the correlation between SPI/STI and NDVI during growing seasons, we investigated the conditional probability of vegetation decline under different climate conditions. The results showed that vegetation was affected by compound dry and hot conditions (defined as SPI ⩽ −1.3 and STI > 1.3) in arid and semi-arid regions. In these regions, the conditional probabilities of vegetation decline under compound dry and hot conditions increased by 7% and 28% compared with those under individual dry and hot conditions, respectively. The impact of compound dry and hot events on vegetation for different biomes was also assessed. Temperate grassland was found to be particularly vulnerable to compound dry and hot conditions. This study highlights the necessity of considering compound dry and hot extremes when assessing vegetation responses to climate extremes under global warming.
Probabilistic assessments of the impacts of compound dry and hot events on global vegetation during growing seasons
Ying Hao (author) / Zengchao Hao (author) / Yongshuo Fu (author) / Sifang Feng (author) / Xuan Zhang (author) / Xinying Wu (author) / Fanghua Hao (author)
2021
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Probabilistic impacts of compound dry and hot events on global gross primary production
| DOAJ | 2022
Impacts of Compound Hot–Dry Events on Vegetation Productivity over Northern East Asia
| DOAJ | 2024