Abstract
Leaf area index (LAI) is increasing throughout the globe, implying Earth greening. Global modeling studies support this contention, yet satellite observations and model simulations have never been directly compared. Here, for the first time, a coupled land-climate model was used to quantify the potential impact of the satellite-observed Earth greening over the past 30 years on the terrestrial water cycle. The global LAI enhancement of 8% between the early 1980s and the early 2010s is modeled to have caused increases of 12.0 ± 2.4 mm yr-1 in evapotranspiration and 12.1 ± 2.7 mm yr-1 in precipitation-about 55% ± 25% and 28% ± 6% of the observed increases in land evapotranspiration and precipitation, respectively. In wet regions, the greening did not significantly decrease runoff and soil moisture because it intensified moisture recycling through a coincident increase of evapotranspiration and precipitation. But in dry regions, including the Sahel, west Asia, northern India, the western United States, and the Mediterranean coast, the greening was modeled to significantly decrease soil moisture through its coupling with the atmospheric water cycle. This modeled soil moisture response, however, might have biases resulting from the precipitation biases in the model. For example, the model dry bias might have underestimated the soil moisture response in the observed dry area (e.g., the Sahel and northern India) given that the modeled soil moisture is near the wilting point. Thus, an accurate representation of precipitation and its feedbacks in Earth system models is essential for simulations and predictions of how soil moisture responds to LAI changes, and therefore how the terrestrial water cycle responds to climate change.
| Original language | English |
|---|---|
| Pages (from-to) | 2633-2650 |
| Number of pages | 18 |
| Journal | Journal of Climate |
| Volume | 31 |
| Issue number | 7 |
| DOIs | |
| State | Published - Apr 1 2018 |
Funding
We wish to thank two anonymous reviewers for constructive comments that helped to strengthen this analysis. This study was supported by the National Natural Science Foundation of China (41125004), National Youth Top-notch Talent Support Program in China, the 111 Project (B14001), and the ANR China-Trend-Stream project. We thank the National Supercomputer Center in Tianjin (NSCC-TJ) and the National Computer Center IDRIS/CNRS in France for providing computing resources. J. Mao and X. Shi are partially supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA), which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the U.S.Department of Energy Office of Science. Oak Ridge National Laboratory is managed by UT-BATTELLE for DOE under Contract DE-AC05-00OR22725 Acknowledgments. We wish to thank two anonymous reviewers for constructive comments that helped to strengthen this analysis. This study was supported by the National Natural Science Foundation of China (41125004), National Youth Top-notch Talent Support Program in China, the 111 Project (B14001), and the ANR China-Trend-Stream project. We thank the National Supercomputer Center in Tianjin (NSCC-TJ) and the National Computer Center IDRIS/CNRS in France for providing computing resources. J. Mao and X. Shi are partially supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA), which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the U.S. Department of Energy Office of Science. Oak Ridge National Laboratory is managed by UT-BATTELLE for DOE under Contract DE-AC05-00OR22725.
Keywords
- Atmosphere-land interaction
- Evapotranspiration
- Feedback
- Vegetation
- Vegetation-atmosphere interactions
- Vegetation-atmosphere interactions