The complex interactions between climatic drivers

The gap

Evidence profile

Sourced from the future work and abstract of the source papers, classified as general, drawn from work published between 2013 and 2026, spanning 2 journals. Those papers have been cited 33 times in total.

Supporting evidence — 3 representative gaps

• Vegetation drag partition effects redistribute dust globally (2026) · Atmospheric Chemistry and Physics · doi

  This study points to the importance of the vegetation, in par- ticular grassland, on modulating the dust cycle. By incor- porating the vegetation data simulated by the ORCHIDEE land surface model into the LMDzORINCA dust emission scheme, we quantified the variations of emissions, DAOD, concentrations, and deposition due to the sheltering effects of vegetation. Building on our recent work (Xu et al., 2026), incorporating dynamic grassland densities provides an effec- tive and feasible way to explicitly represent bare soil gaps within grasslands – a key control on dust emission. This allows for consistent estimates of vegetation characteristics from the ORCHIDEE model rather than getting information from external datasets (Foroutan et al., 2017; Klose et al., 2021; Leung et al., 2023). This study opens the way to fully couple vegetation to the dust cycle within the IPSL Earth System Model (Boucher et al., 2020). The next studies will hence focus on the feedbacks occurring in semi-arid regions between vegetation and dust cycle. It also opens the way to explore the role played by these interactions under climate change, extreme weather events, and potential tipping points. The incorporation of vegetation reduces global dust emis- sions by 23 %, with higher reductions of 35 %–78 % in semi- arid regions, exhibiting the significant positive relationships between vegetation fraction and relative emission reduction across different regions. This modification alters the regional contribution of emissions to the global dust cycle: higher contributions take place from major dust source regions with sparse vegetation and lower contributions occur from regions where vegetation cover is more abundant. The suppressive effect of vegetation also reduces significantly global dust loads from the control simulation, both in source regions – such as the Thar Desert – and in remote downwind areas, in- cluding Antarctica, where total deposition is considerably re- duced. Overall, evaluations against DAOD, surface concen- tration, and deposition observations show model improve- ments that vary from modest to significant depending on the region. This study also investigates the impact of simulated dust particle size representations. The 4-mode representation pro- vides a more comprehensive description of the dust particle size distribution, whereas the 1-mode representation, which is more computationally efficient, treats mainly micrometre- sized particles below 7 µm. The 1-mode distribution appears to adequately represent optical properties but provides a sim- plified representation of concentrations and deposition distri- butions. Models still struggle in their current state to repre- sent coarse particles. This is manifest in the long-range trans- port, in overly rapid dry deposition, and in insufficient ver- tical lofting, which all contribute to the underestimation of surface concentrations and deposition fluxes in remote down- wind regions. Taken together, these results demonstrate that accounting for vegetation effects and adopting an appropri- ate size-distribution framework are crucial for improving the physical consistency of dust simulations. Building on these findings, we identify several priori- ties for future development: (1) Improving the representa- tion of dust source restriction (e.g., temperature and pre- cipitation thresholds) and surface roughness, including the distinct aerodynamic effects of different vegetation types, non-vegetative roughness elements (e.g., rocks and pebbles), and the seasonal variation of vegetation; (2) Moving toward higher spatial resolutions to better resolve sub-grid meteoro- logical variability and orographic heterogeneity, supporting both more accurate simulation of dust processes and more robust evaluations against point-scale observational sites; (3) Improving the treatment of coarse particle dynamics in trans- port and deposition schemes, particularly gravitational set- tling and scavenging processes, to more accurately represent atmospheric residence times and long-range transport; and (4) Advancing fully coupled Earth System Model (ESM) frameworks that integrate climate, aerosols, and dynamic vegetation, enabling a more consistent representation of the bidirectional feedbacks between land-surface changes and the global dust cycle.

  generalfuture workevidence 5/5
  Keywords: vegetation dust deposition regions cycle surface model global representation emission concentrations effects represent higher signi
• Potential dust emissions from the southern Kalahari's dunelands (2013) · Journal of Geophysical Research Earth Surface · cited 33× · doi

  The dependence of sediment fluxes and dust emissions on vegetation cover in the Kalahari dunelands remains poorly understood, which prevents a quantitative assessment of possible changes in aeolian activity in this region under different land use and land cover scenarios.

  generalabstractevidence 2/5
  Keywords: cover land dependence sediment fluxes dust emissions vegetation kalahari dunelands remains poorly understood prevents quantitative
• Surface Mineralogy and Hydrological Controls on “Hotspots” of Dust Emission at Etosha Pan, Namibia (2026) · Journal of Geophysical Research Earth Surface · doi

  The complex interactions between climatic drivers and surface properties that govern dust emissions remain poorly understood, contributing to uncertainties in model predictions of atmospheric dust concentrations and their global effects.

  generalabstractevidence 2/5
  Keywords: dust complex interactions climatic drivers surface properties govern emissions remain poorly understood contributing uncertainties model

Questions about this gap