Principal Investigator


At a Glance

The latest Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) found that “Limiting global temperature increase to a specific level would imply limiting cumulative CO2 emissions to within a carbon budget.” This budget is estimated to be 500 gigatonnes of CO2  from the beginning of 2020 to cap temperatures at 1.5 °C. To arrive at this number, scientists use climate models that include representations of terrestrial ecosystems, including processes that release carbon to the atmosphere like wildfires and forest diebacks due to droughts and heat. The Geophysical Fluid Dynamics Laboratory (GFDL) at the National Oceanic and Atmospheric Administration (NOAA) and CMI have developed one of the few existing models that accounts for the impacts of more frequent extreme weather in today’s warming world. This is important for bp because land models are significant tools in understanding the impact of extreme weather on land carbon uptake and are critical in designing standards to achieve net-zero global emissions.

 


Research Highlight

The IPCC AR6 bases estimates of their carbon budget on the relationship between cumulative CO2 emissions and global average temperature change predicted by climate models. Most of the Earth System Models (ESMs) in the AR6 predicted that about half of the cumulative emissions would continue to be removed by the land biosphere and oceans, with the land responsible for marginally more net uptake than the oceans. However, these models have a limited representation of terrestrial ecosystem complexity, including extreme fires and forest diebacks due to droughts and heat. There are only four ESMs, including NOAA/GFDL ESM4.1, that represent changes in vegetation distribution because of the impacts of climate change.

Last year, a team of CMI and NOAA/GFDL scientists, including researchers Sergey Malyshev, Isabel Martinez Cano, and Yujin Zeng, used ESM.1 to demonstrate that under the extreme greenhouse gasses emission scenario SSP5-8.5, Amazon forests may begin to convert to savanna before mid-century because of increased forest fires. To explore the robustness of this conclusion in the tropics and to investigate the possibility of abrupt changes in other regions, the team implemented several improvements to the land component of the ESM4.1 and developed a new land model, LM4.2. This new model included a new representation of nutrient limitation nitrogen (N) on carbon uptake and a refined representation of grass-tree competition for both seedlings to mature trees. It also included a suit of parameterizations accounting for effects of orography, or mountainous geography, on soil moisture (via hillslopes), surface radiation (via mountain shading), and orographic scaling of atmospheric forcing (surface temperature, precipitation, and specific humidity) (Martinez Cano et al., 2022).

Figure 11.1.
Diameter growth rates from the open N cycle simulation experiments. Panels a, b, and c show the results of Oak Ridge (OKR), Harvard Forest (HFR), and the Northern Old Black Spruce (NOBS) sites, respectively. The diameter growth rate is the mean of the cohorts of a PFT (deciduous or ‘evergreen’) in the canopy layer. At a low N mineralization rate, the diameter growth rates of ‘evergreen’ trees are greater than those of deciduous trees at the three sites. At a high N mineralization rate however, the ‘evergreen’ trees grow more slowly than the deciduous trees at OKR and HFR (Wang et al., 2017).

Previously, the Pacala lab demonstrated in a theoretical analysis that soil nitrogen availability plays a critical role in shaping the competition between long-lived leaves (i.e., evergreen) trees and short-lived leaves (i.e., deciduous) trees (Weng et al., 2017; figure 12.1). The new N scheme in LM4.2 will enable CMI scientists, including researcher Enrico Zorzetto, to explore how competition between evergreens and deciduous trees in high latitudes and high altitudes under a changing climate may accelerate the warming through biophysical feedbacks. As ESMs remain computationally expensive and typically simulate atmosphere and land at 50-100 km resolution, the ability to resolve sub-grid orographic heterogeneity allows LM4.2 to better characterize both wet (floods) and dry extremes (droughts and fire). Both extreme wet and dry conditions could accelerate tree mortality, which in turn will lead to shifts in the wildfire regimes. These processes could affect carbon uptake on land and, thus, the remaining carbon budgets.

The orography-aware new land model LM4.2 provides CMI and NOAA/GFDL researchers with a unique tool to understand the implications of dry and wet extremes for future carbon uptake at a higher resolution than typically afforded by the atmospheric components of the ESMs.

 


References

Martinez Cano, I.M., E. Shevliakova, S. Malyshev, J. John, Y. Yu, B. Smith, and S.W. Pacala, 2022. Abrupt loss and uncertain recovery from fires of Amazon forests under low climate mitigation scenarios. Proceedings of the National Academy of Sciences 119(52):e2203200119. (https://doi.org/10.1073/pnas.2203200119).

Weng, E., C.E. Farrior, R. Dybzinski, and S.W. Pacala, 2017. Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework. Global Change Biology 23(6):2482-2498. (https://doi.org/10.1111/gcb.13542).