EGU23-11599
https://doi.org/10.5194/egusphere-egu23-11599
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Global trends of vegetation leaf moisture content and extreme weather since the 1980s

Luisa Schmidt1, Wantong Li2, and Matthias Forkel1
Luisa Schmidt et al.
  • 1Junior Professorship in Environmental Remote Sensing, Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Dresden, Germany (luisa.schmidt1@tu-dresden.de)
  • 2Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany

Climate change leads to a change of precipitation frequency and quantity as well as to increased temperature inducing extreme weather events like floods but also more intensive and longer drought periods.

The response of the vegetation to these trends is of high interest because vegetation regulates interception, transpiration and is a water storage which is important for plant productivity, agriculture, carbon cycling and the danger of wild fire occurrence. Reduced precipitation in combination with increased temperature lead to water stressed vegetation which might not only behave different in regards of evapotranspiration but are also prone to wildfires. However, currently we don’t know how the water status changes in the long-term. A long-term time series of the vegetation leaf moisture content can help to understand the consequences of changing environmental conditions on the vegetation layer as part of the water as well as the carbon cycle.

Measurements of vegetation leaf moisture are usually only available for single test-sites (missing spatial coverage), often measured for a short time span and might hold missing data. Estimations of vegetation leaf moisture are able to provide consistent time series but are mostly done on regional scale which are also missing spatial transferability. However, long-term data with a consistent time series and large spatial coverage are necessary to address a reliable time series analyses in the context of climate change.

Our trend analysis will focus on the live-fuel moisture content (LFMC) which is based on the vegetation optical depth (VOD) and Leaf Area Index (LAI). LFMC is defined as the water mass of living vegetation to the dry mass of the vegetation, usually expressed in percentage. LFMC is an important variable in the field of wild fire analyses as it is one of the key predictors for risk and development of a fire. LFMC can be estimated on ecosystem level due to its independence of plant type. Here we use VODCA VOD and GLOBMAP LAI data to create a longer time series of LFMC for the period 1988-2017 on global scale to analyse temporal changes in LFMC. Initial results indicate a heterogeneous pattern of LFMC trends which depend on land cover type, e.g., with a decreasing trend for shrublands but an increasing trend for needle-leaved forests. We compare the trends in LFMC with trends in heat and drought events as well as fire weather indices. Inter-annual changes in LFMC correspond to multi-year drought events.

How to cite: Schmidt, L., Li, W., and Forkel, M.: Global trends of vegetation leaf moisture content and extreme weather since the 1980s, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11599, https://doi.org/10.5194/egusphere-egu23-11599, 2023.